A mutual inductor on-site calibration method and system based on an intelligent detection vehicle

Abstract

The application discloses a mutual inductor on-site calibration method and system based on an intelligent detection vehicle, and relates to the field of mutual inductor calibration. The method comprises the following steps: obtaining transformer substation information and detection vehicle information; when the intelligent detection vehicle enters a mutual inductor calibration area of a target transformer substation, a target working pose is planned for the intelligent detection vehicle; when the intelligent detection vehicle is parked at the target working pose, a grounding loop calibration of the mutual inductor calibration area is completed; if the grounding loop calibration of the mutual inductor calibration area is passed, terminal electric field signals and mechanical arm pose data are collected; the plug-in control parameters of the intelligent detection vehicle are calculated, the plug-in control parameters and the mechanical arm pose data are combined, and a second mechanical arm is used to complete a docking and insertion step of a to-be-detected mutual inductor; after the docking and insertion step is completed, a pressure discharge calibration of the to-be-detected mutual inductor is completed, and a mutual inductor calibration report of the to-be-detected mutual inductor is generated. The application can effectively improve the accuracy of mutual inductor on-site calibration.

Description

Technical Field

[0001] This application relates to the field of instrument transformer verification, and in particular to a method and system for on-site verification of instrument transformers based on an intelligent testing vehicle. Background Technology

[0002] With the large-scale construction of ultra-high voltage power transmission projects and the continuous advancement of power grid upgrading and transformation in my country, 750kV / 765kV voltage level power voltage transformers have become core equipment for power grid metering, relay protection and condition monitoring. Their on-site AC withstand voltage test and periodic verification are key operational links to ensure the safe and stable operation of the power grid and meet the requirements of metering traceability compliance.

[0003] Currently, the on-site verification of ultra-high voltage / super-high voltage instrument transformers generally adopts a traditional operation mode that combines split-type equipment with manual climbing. This operation mode requires personnel to work continuously at heights, facing long-term risks of falls, electric shock from high-voltage induced current and residual voltage, thus posing a high safety risk. Furthermore, the traditional operation mode requires the coordinated operation of multiple vehicles and multiple on-site transfers of equipment, relying entirely on manual high-altitude operations and on-site coordination, resulting in low operational efficiency and failing to meet the intelligent, efficient, and safe operation and maintenance requirements of the power grid. Summary of the Invention

[0004] This application provides a method and system for on-site verification of instrument transformers based on an intelligent testing vehicle, which is used to improve the accuracy of on-site verification of instrument transformers.

[0005] To achieve the above objectives, the embodiments of this application adopt the following technical solutions: Firstly, a method for on-site verification of instrument transformers based on an intelligent inspection vehicle is provided. This method is applied to the intelligent inspection vehicle, which is equipped with a first robotic arm and a second robotic arm. The method includes: When the intelligent testing vehicle enters the mutual inductance verification area of ​​the target substation according to the preset on-site verification path, the target working posture is planned for the intelligent testing vehicle based on the substation information. When the intelligent inspection vehicle stops at the target working position, the grounding circuit verification of the mutual inductance verification area is completed by the first robotic arm. If the grounding loop of the mutual inductance verification area passes the verification, the terminal electric field signal in the vicinity of the high voltage terminal of the mutual inductor under test and the robotic arm posture data of the second robotic arm are collected in real time by multiple types of sensors preset in the intelligent inspection vehicle. The insertion control parameters of the intelligent inspection vehicle are calculated based on the terminal electric field signal and the inspection vehicle information. The insertion control parameters and the position data of the robotic arm are combined and the second robotic arm is used to complete the docking and insertion steps of the current transformer under test. After the docking and insertion steps are completed, the intelligent testing vehicle performs the pressure discharge verification of the instrument transformer under test, and generates an instrument transformer verification report based on the pressure discharge verification results.

[0006] Optionally, the substation information includes substation map information and substation equipment information. The step of planning the target working posture for the intelligent inspection vehicle based on the substation information includes the following steps: Multi-angle magnetic field signals in the mutual inductance verification area are collected by multiple sensors pre-installed in the chassis of the intelligent inspection vehicle. Complete the gradient vector calculation of the multi-angle magnetic field signal in the region, and determine the relative positional relationship between the intelligent detection vehicle and the grounding down conductor in the mutual inductance verification area based on the gradient vector calculation results; The intelligent inspection vehicle's pose calibration is completed based on the relative positional relationship, and the inspection base point of the intelligent inspection vehicle is output based on the pose calibration result; Centered on the detection base point, several candidate working positions are planned for the intelligent detection vehicle based on the substation map information; By combining substation map information and substation equipment information, determine the electrical information of all live equipment and the obstacle range parameters of all obstacle areas within the mutual inductance verification area; Based on the electrical information of the equipment, an obstacle avoidance envelope area is planned for all energized equipment, and the target working pose is selected from all candidate working poses using the obstacle avoidance envelope area and obstacle range parameters as constraints.

[0007] Optionally, the grounding loop verification of the mutual inductance verification area by the first robotic arm includes the following steps: The first robotic arm injects a current conduction test signal into the grounding terminal of the mutual inductance verification area, and the primary circuit verification of the grounding terminal is completed using the current conduction test signal. If the primary circuit of the grounding terminal passes the test, the grounding resistance value of the grounding terminal is measured using the constant current method. Calculate the average resistance and resistance fluctuation of the grounding terminal based on the grounding resistance value; If the average resistance is less than or equal to the preset average threshold and the resistance fluctuation is less than or equal to the preset fluctuation threshold, then the mutual inductance verification area is determined to have passed the grounding loop verification. If the average resistance value is greater than the preset average threshold, or the resistance fluctuation value is greater than the preset fluctuation threshold, then the mutual inductance verification area is determined to have failed the grounding loop verification.

[0008] Optionally, calculating the insertion control parameters of the intelligent testing vehicle based on the terminal electric field signal and the testing vehicle information includes the following steps: Acquire terminal image information of the high-voltage terminal to be inspected; Based on the terminal image information and using a feature matching algorithm, the insertion position parameters are located. Combining the insertion position parameters and the detection vehicle information, a terminal insertion path is planned for the second robotic arm. Based on the terminal insertion path, motion control parameters for the second robotic arm are generated. The frequency domain conversion of the terminal electric field signal is completed using the fast Fourier function to obtain the electric field frequency domain signal; The terminal signal features of the electric field frequency domain signal are extracted, and a terminal signal feature sequence is constructed based on the terminal signal features. The terminal signal features include signal frequency features, signal phase features, and signal amplitude features. The threshold method is used to verify the volatility of the terminal signal feature sequence, and the stable terminal feature sequence is extracted from the terminal signal feature sequence based on the volatility verification result. The feedforward control parameters of the second robotic arm are calculated based on the terminal stability characteristic sequence. The feedforward control parameters include the end effector motion period, end effector initial phase, and end effector motion vector of the second robotic arm. The motion control parameters and feedforward control parameters are spatiotemporally fused to obtain the plug-in control parameters of the intelligent inspection vehicle.

[0009] Optionally, the docking and insertion steps of the current transformer under test, which combine the insertion control parameters and the robot arm pose data and utilize the second robot arm, include the following steps: The six-dimensional force sensor pre-installed on the second robotic arm is calibrated at its no-load zero point to obtain the no-load zero point reference value of the six-dimensional force sensor. When the second robotic arm grips the high-voltage experimental equipment of the target substation, it collects six-dimensional force data through a six-dimensional force sensor, and combines the six-dimensional force data with the no-load zero-point reference value to complete the load zero-point correction of the six-dimensional force sensor and obtain the load zero-point reference value. The initial load parameters of the second robotic arm are collected in real time by a six-dimensional force sensor, and the initial load parameters are corrected in real time using the zero-point reference value under load, so as to obtain the real-time load parameters of the second robotic arm. By combining the pose data of the robotic arm and the real-time load parameters and using the rigid body dynamics model, the self-weight load parameters of the high-pressure experimental equipment are calculated, and the gravity feedforward compensation parameters of the second robotic arm are calculated based on the self-weight load parameters. The plug-in control parameters are corrected in real time based on the gravity feedforward compensation parameters; The second robotic arm completes the docking and insertion between the high-voltage test equipment and the transformer under test according to the real-time corrected insertion control parameters, and outputs a docking completion signal.

[0010] Optionally, after completing the docking insertion step, the method further includes the following steps: When the insertion completion signal of the docking step is received, the mechanical load data between the high voltage test equipment and the transformer under test is collected by the six-dimensional force sensor. The constant load component in the mechanical load data is extracted using a preset sliding window; The environmental interference frequency band is determined based on the wind speed and direction parameters of the target substation obtained in advance. Perform Fourier transform on the mechanical load data, and extract the fluctuating load component from the mechanical load data after Fourier transform based on the environmental interference frequency band. By combining constant load components and fluctuating load components, the reaction load component in the mechanical load data is selected. The contact interface between the high-voltage test equipment and the transformer under test is defined as a virtual support point, and a three-dimensional equivalent coordinate system is constructed with the virtual support point as the origin. The constant load component and the fluctuating load component are mapped to a three-dimensional equivalent coordinate system to calculate the three-dimensional load cancellation value; Using the reaction load component as a constraint, the interference compensation parameters of the second robotic arm are calculated based on the three-dimensional load cancellation value.

[0011] Optionally, the pressurized discharge verification of the instrument transformer under test is completed using an intelligent testing vehicle, and an instrument transformer verification report is generated based on the pressurized discharge verification results, including the following steps: The intelligent testing vehicle performs a step-by-step voltage boost on the transformer under test and collects the transformer voltage boosting parameters in real time until the transformer voltage reaches the preset voltage threshold, at which point the transformer under test is determined to have entered the transformer withstand voltage stage. When the current transformer under test enters the current transformer withstand voltage stage, the current transformer withstand voltage parameters of the current transformer under test are collected in real time. When the withstand voltage stage of the current transformer lasts longer than the preset time threshold, the current transformer under test is stepped down in a stepwise manner through the intelligent testing vehicle, and the current transformer voltage reduction parameters of the current transformer under test are collected in real time. The transformer step-up parameters, transformer withstand voltage parameters, and transformer step-down parameters are compared and verified against the corresponding preset thresholds for compliance. Based on the compliance comparison and verification results, a transformer verification report for the transformer under test is generated.

[0012] Optionally, the method may also include the following steps: The intelligent testing vehicle completes the zero-return verification of the high-voltage source of the high-voltage experimental equipment in the mutual inductance verification area. If the high-voltage source returns to zero and passes the verification, the residual potential data of the high-voltage test equipment and the high-voltage terminal under test are collected in real time by the second robotic arm. Real-time potential verification of residual potential data is performed using a pre-acquired residual voltage safety threshold. If the residual potential data passes the real-time potential verification, the second robotic arm and the first robotic arm will sequentially complete the robotic arm reset and locking steps, and output the current transformer verification completion signal.

[0013] Secondly, this application provides a machine-readable storage medium storing instructions for causing a machine to perform the on-site verification method for current transformers based on an intelligent inspection vehicle as described in the first aspect.

[0014] Thirdly, this application provides a field calibration system for instrument transformers based on an intelligent testing vehicle, comprising: The memory is configured to store instructions; and The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the on-site verification method for current transformers based on an intelligent inspection vehicle as described in the first aspect.

[0015] The above technical solution pre-collects substation information to plan the target operating posture for the intelligent inspection vehicle. It selects postures that meet the requirements of full-stroke coverage by both robotic arms, comply with high-voltage electrical safety regulations, and avoid all on-site obstacles. This step replaces the inefficient traditional method of manually directing the vehicle to move multiple times, manually judging safety distances, and manually checking for obstacles. This significantly improves overall operational efficiency and provides a stable, interference-free spatial reference for subsequent sensor data acquisition and robotic arm insertion, fundamentally ensuring the measurement and motion accuracy of subsequent verification processes. Next, the first robotic arm completes the grounding circuit verification of the mutual inductance verification area. This is a crucial step in ensuring the compliance and safety of subsequent high-voltage pressurization tests, fundamentally avoiding potential drift and data fluctuations caused by poor grounding circuits during high-voltage verification. This ensures the accuracy of data acquisition during subsequent pressurization and discharge verification, guaranteeing the authenticity and validity of the final verification results. Next, by collecting the terminal electric field signal within the vicinity of the high-voltage terminal in the transformer under test, the insertion control parameters of the intelligent testing vehicle are calculated. This provides data support for the docking insertion step during the on-site verification of the transformer, fundamentally overturning the inefficient traditional manual high-altitude wiring method. It achieves an order-of-magnitude improvement in the efficiency of the terminal docking process. Simultaneously, the calculation of the insertion control parameters avoids control drift under strong electromagnetic environments, eliminates the influence of the high-voltage test equipment's own weight on the positioning accuracy of the second robotic arm's end effector, and offsets load fluctuations caused by environmental factors such as wind, preventing loose connections. This further ensures the stability of electrical connections during subsequent verification and guarantees the continuity and accuracy of voltage and current parameter acquisition during pressurization verification. After completing the docking insertion step, the intelligent testing vehicle performs pressurization and discharge verification of the transformer under test, generating a transformer verification report based on the results. This ensures the accuracy, compliance, and traceability of the verification results and effectively improves the efficiency and accuracy of on-site transformer verification, providing a technical foundation for ensuring the safe and stable operation of the power grid.

[0016] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a method for on-site verification of instrument transformers based on an intelligent testing vehicle, provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an intelligent inspection vehicle provided in an embodiment of this application; Figure 3 This is a flowchart illustrating a target operation pose planning method provided in an embodiment of this application.

[0018] Explanation of reference numerals in the attached figures: 1. Intelligent inspection vehicle; 2. Inspection robot. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0021] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0022] Figure 1 The illustration shows a schematic flowchart of a method for on-site verification of instrument transformers based on an intelligent testing vehicle, according to an embodiment of this application. Figure 1As shown in the figure, this application provides a method for on-site verification of current transformers based on an intelligent inspection vehicle. The method is applied to an intelligent inspection vehicle, which is equipped with a first robotic arm and a second robotic arm. The method includes the following steps: S101. Obtain substation information of the target substation and inspection vehicle information of the intelligent inspection vehicle.

[0023] In this embodiment, the substation information includes two categories: substation map information and substation equipment information. The substation map information includes spatial data such as drivable roads within the target substation, boundaries of the transformer verification area, equipment layout coordinates, grounding down conductor locations, restricted areas, outlines of fixed facilities, and three-dimensional spatial coordinates of energized equipment. The substation equipment information includes nameplate parameters of the transformer under inspection, such as model, rated voltage level, transformation ratio, and accuracy class; rated parameters, operating status, and legally mandated safety distance standards for corresponding voltage levels of energized equipment within the substation; and compliance data such as boundary parameters and obstacle avoidance rules for obstruction areas within the substation. (Refer to...) Figure 2 The intelligent inspection vehicle is equipped with an inspection robot, which has a first robotic arm and a second robotic arm. The vehicle's information includes the vehicle's dimensions, chassis leveling parameters, and preset driving control parameters; the DH kinematic calibration parameters of the first and second robotic arms, the rated range of motion of each joint, rated speed and torque parameters, and end effector installation parameters; the calibration parameters, sampling frequency, and synchronization rules of various onboard sensors; the rated parameters and compliance thresholds of the onboard high-voltage generator and calibration measuring equipment; and the baseline calibration parameters of the global operating coordinate system. This step provides a complete and accurate foundational data for subsequent pose planning, safety verification, robotic arm control, parameter calculation, and compliance determination throughout the entire process, serving as a prerequisite for achieving fully automated and high-precision operations.

[0024] S102. When the intelligent inspection vehicle enters the mutual inductance verification area of ​​the target substation according to the preset on-site verification path, the target working position is planned for the intelligent inspection vehicle based on the substation information.

[0025] In this embodiment, the intelligent inspection vehicle automatically drives into the mutual inductance verification area designated by the target substation, following a pre-planned on-site verification path based on substation map information. Using a multi-channel magnetic sensor array pre-installed at the four corners of the intelligent inspection vehicle's chassis, it collects multi-angle power frequency magnetic field signals within the mutual inductance verification area in real time. The vehicle performs gradient vector calculations in both longitudinal and lateral dimensions on the magnetic field signals to accurately determine the relative positional relationship between the intelligent inspection vehicle and the grounding down conductor within the verification area. Based on the relative positional relationship, the intelligent inspection vehicle completes longitudinal approach and lateral alignment pose calibration, ultimately locking the vehicle's detection base point. Using the detection base point as the center, and considering the robotic arm's rated operating range and vehicle mobility performance, a feasible region for pose fine-tuning is defined. After discretization with a preset minimum step size, several candidate operating poses are generated. Combining substation map information and equipment information, the electrical information of all energized equipment within the verification area and the obstacle range parameters of all obstacle areas are determined, and an obstacle avoidance envelope area conforming to safety distance standards is planned for each energized device. Using obstacle avoidance envelope area and obstacle range parameters as dual constraints, candidate poses with high voltage risk are first eliminated through electrical safety distance verification, and candidate poses with collision risk are eliminated through obstacle avoidance verification. Finally, the comprehensive cost value of the remaining compliant poses is calculated, and the optimal pose with the minimum comprehensive cost value is selected as the target working pose, and the intelligent inspection vehicle is controlled to accurately stop at that pose.

[0026] This step completely replaces the inefficient traditional operation mode of manually directing vehicles to move multiple times, manually judging safe distances, and manually checking for obstacles, greatly improving the efficiency of operation and positioning. At the same time, the selected target operation posture not only fully meets the coverage requirements of the entire working stroke of the dual robotic arms, but also strictly complies with high-voltage electrical safety specifications, while avoiding all on-site obstacles. This provides a stable and interference-free spatial reference for subsequent sensor data acquisition and high-precision robotic arm movements, fundamentally ensuring the measurement accuracy and motion accuracy of subsequent verification stages.

[0027] S103. When the intelligent inspection vehicle stops at the target working position, the grounding circuit verification of the mutual inductance verification area is completed by the first robotic arm.

[0028] In this embodiment, the first robotic arm is raised to a preset working height. A depth camera integrated at its end effector visually identifies and spatially positions the grounding terminal within the mutual inductance verification area. The first robotic arm then grasps a dedicated grounding wire, precisely connecting one end of the wire to the grounding terminal and the other end to the grounding terminal of the intelligent testing vehicle, thus constructing a complete grounding verification electrical circuit. A low-amplitude, highly stable power frequency small current conduction test signal is injected into the grounding circuit through the current injection unit at the end of the first robotic arm. Signal transmission data and voltage feedback signals are collected in real time to complete the primary circuit verification of the grounding terminal. If the verification fails, an on-site alarm is immediately triggered, and the first robotic arm is controlled to readjust its connection posture and retry until the maximum number of retries is reached, at which point subsequent high-voltage operation permissions are locked. If the primary circuit verification passes, a constant DC test current conforming to power industry standards is injected into the grounding circuit. A constant current method is used to continuously sample multiple times within a preset measurement period to calculate multiple instantaneous grounding resistance values. Based on multiple sets of instantaneous grounding resistance values, the average resistance of the grounding terminal and the resistance fluctuation value reflecting the stability of the grounding connection are calculated. The average resistance value is compared with the preset average threshold and the resistance fluctuation value is compared with the preset fluctuation threshold. If both indicators meet the threshold requirements, the grounding circuit is deemed to have passed the verification. If either one exceeds the standard, the verification is deemed to have failed, and the subsequent high-voltage operation authority is blocked.

[0029] This procedure strictly adheres to the mandatory safety principle of grounding before connecting to high voltage during high-voltage operations, eliminating safety risks such as electric shock from induced current and discharge due to poor grounding from the very beginning of the process. Simultaneously, two-stage verification ensures the mechanical reliability and electrical conductivity stability of the grounding circuit, fundamentally avoiding potential drift and data fluctuations during subsequent high-voltage verification caused by poor grounding circuits. This guarantees the accuracy of data acquisition during subsequent pressurized discharge verification, ensuring the authenticity and validity of the final verification results.

[0030] S104. If the grounding loop verification of the mutual inductance verification area passes, the terminal electric field signal in the vicinity of the high voltage terminal in the mutual inductor under test and the robotic arm posture data of the second robotic arm are collected in real time by multiple types of sensors preset in the intelligent inspection vehicle.

[0031] In this embodiment, after confirming that the grounding loop verification is successful, the multi-type synchronous acquisition sensors mounted on the intelligent inspection vehicle are activated. Among them, the miniature inductive electric field sensor integrated at the end of the second robotic arm collects the power frequency electric field time-domain signal, i.e., the terminal electric field signal, within the vicinity of the high-voltage terminal of the transformer under test in real time. Simultaneously, the joint encoders and attitude sensors of the second robotic arm collect the real-time rotation angles of each joint of the second robotic arm, the three-dimensional spatial coordinates of the end effector in the global working coordinate system, and the pitch / roll / yaw attitude angles, i.e., the robotic arm pose data. The terminal electric field signal and the robotic arm pose data are globally clock synchronized to match a unified timestamp for the two sets of data, ensuring that the timing of the two sets of data is completely aligned and there is no timing misalignment problem. This step uses non-contact electric field sensing to accurately acquire the micron- to millimeter-level high-frequency micro-amplitude oscillation characteristics of the high-voltage terminal under test caused by bus electrodynamics, power frequency vibration, and on-site wind load. At the same time, it simultaneously acquires the real-time spatial pose of the second robotic arm, providing dual-dimensional core input data for the subsequent calculation of insertion control parameters. This effectively solves the core pain points of hard docking collision and insertion offset of the robotic arm caused by the micro-amplitude vibration of the high-voltage terminal, while ensuring the spatiotemporal synchronization of subsequent robotic arm control.

[0032] S105. Calculate the insertion control parameters of the intelligent inspection vehicle based on the terminal electric field signal and the inspection vehicle information. Combine the insertion control parameters and the robotic arm posture data, and use the second robotic arm to complete the docking and insertion steps of the current transformer under test.

[0033] In this embodiment, the terminal image information of the high-voltage terminal to be inspected is acquired by the depth camera at the end of the second robotic arm. The insertion position parameters are located by feature matching algorithm. Combined with the information of the inspection vehicle, a three-segment terminal insertion path is planned for the second robotic arm, and motion control parameters are generated. At the same time, the frequency domain conversion of the terminal electric field signal is completed by using the fast Fourier function, and the signal frequency, phase and amplitude features are extracted to construct the terminal signal feature sequence. The stable feature sequence is extracted by fluctuation verification, and the feedforward control parameters of the second robotic arm are calculated. The motion control parameters and the feedforward control parameters are spatiotemporally fused with timestamp and coordinate alignment to finally obtain the insertion control parameters of the intelligent inspection vehicle. The docking and insertion steps include: first, calibrating the six-dimensional force sensor pre-installed at the end of the second robotic arm under no-load conditions to obtain the no-load zero-point reference value; after the second robotic arm clamps the high-voltage experimental equipment, collecting six-dimensional force data under load to complete the zero-point correction under load, obtaining the zero-point reference value under load; collecting the initial load parameters of the second robotic arm in real time, and obtaining the real-time load parameters after correction by the zero-point reference value under load; combining the synchronously collected robotic arm pose data and real-time load parameters, calculating the self-weight load parameters of the high-voltage experimental equipment through a rigid body dynamics model, and then calculating the gravity feedforward compensation parameters of the second robotic arm; using the gravity feedforward compensation parameters to correct the insertion control parameters in real time, and finally driving the second robotic arm to complete the precise docking and insertion of the high-voltage experimental equipment and the transformer under test according to the real-time corrected insertion control parameters, and outputting a docking completion signal after the action is completed.

[0034] This step utilizes phase-locked synchronous feedforward control to achieve a relatively static steady-state synchronization between the end of the second robotic arm and the high-voltage terminal of the high-frequency micro-oscillating device. This transforms the traditional dynamic hard connection into a steady-state soft connection, effectively avoiding the risks of collision offset, spark discharge, and transformer winding damage during the insertion process. Simultaneously, gravity feedforward compensation eliminates the end-position offset and uneven stress at the terminal contact interface caused by the self-weight of the high-voltage test lead. This achieves zero-impact, high-precision, fully automated insertion, completely overturning the inefficient and high-risk traditional manual high-altitude wiring method. It also provides a stable and reliable electrical connection for subsequent verification processes, avoiding the degradation of verification accuracy caused by nonlinear drift in contact resistance.

[0035] S106. After completing the docking and insertion steps, the intelligent testing vehicle performs the pressure discharge verification of the instrument transformer under test, and generates an instrument transformer verification report based on the pressure discharge verification results.

[0036] In this embodiment, upon receiving the connection completion signal, the intelligent testing vehicle, through its onboard voltage regulator drive unit, high-voltage generator, and reactor, performs a stepped voltage increase on the transformer under test at a rate not exceeding 2% per second of the transformer's rated voltage, while simultaneously collecting the transformer's voltage increase parameters. Upon entering the withstand voltage stage, the transformer's withstand voltage parameters are collected. Once the withstand voltage stage lasts for the preset required duration, the transformer under test is steppedly de-voltaged at a rate symmetrical to the voltage increase process, with the transformer's voltage decrease parameters collected in real-time throughout the process, until the primary side voltage drops below the safety threshold, at which point high-voltage output ceases. The collected transformer voltage increase, withstand voltage, and voltage decrease parameters are compared with corresponding preset thresholds set according to national power industry verification regulations for compliance verification item by item and throughout the entire time period. Based on the verification results, the transformer under test is determined to be qualified, and non-compliant items and deviation data are accurately marked. The equipment information, parameters collected throughout the entire process, and compliance determination results of this verification are integrated to generate a standardized transformer verification report that conforms to industry standards.

[0037] Through the above steps, automatic data collection and analysis can be effectively achieved, avoiding human error caused by manual operation. At the same time, measurement errors caused by contact resistance drift and environmental interference are eliminated, ensuring the accuracy, compliance and traceability of the verification results. Ultimately, the entire process of on-site verification of instrument transformers, from operation execution to data archiving, is fully automated and closed-loop, which greatly improves the operation efficiency and detection accuracy of on-site verification of UHV / UHV instrument transformers.

[0038] In one embodiment, reference is made to Figure 3 The substation information includes substation map information and substation equipment information. The step of planning the target working posture for the intelligent inspection vehicle based on the substation information includes the following steps: S201. Multi-angle magnetic field signals of the mutual inductance verification area are collected by multiple sensors preset in the chassis of the intelligent detection vehicle. S202. Complete the gradient vector calculation of the multi-angle magnetic field signal in the region, and determine the relative positional relationship between the intelligent detection vehicle and the grounding lead in the mutual inductance verification area based on the gradient vector calculation results. S203. Perform position and pose calibration of the intelligent inspection vehicle based on the relative positional relationship, and output the detection base point of the intelligent inspection vehicle based on the position and pose calibration result; S204. Based on the detection base point and the substation map information, several candidate working positions are planned for the intelligent detection vehicle. S205. Combine the substation map information and substation equipment information to determine the electrical information of all live equipment and the obstacle range parameters of all obstacle areas within the mutual inductance verification area; S206. Based on the electrical information of the equipment, plan the obstacle avoidance envelope area for all live equipment, and select the target working pose from all candidate working poses using the obstacle avoidance envelope area and obstacle range parameters as constraints.

[0039] In this embodiment, the multi-channel sensors pre-installed on the intelligent inspection vehicle chassis are multi-channel magnetic sensor arrays installed at the four corners of the chassis. These arrays can collect multi-angle magnetic field signals from the mutual inductance verification area in real time during the vehicle's operation. These multi-angle magnetic field signals refer to the power frequency magnetic field signals at four different spatial angles within the target substation. Next, based on the fixed installation spacing of the multi-channel sensors on the intelligent inspection vehicle chassis, gradient vector calculations are performed on the multi-angle magnetic field signals in two dimensions: longitudinal gradient vector calculation and lateral gradient vector calculation. First, based on the longitudinal fixed installation spacing of the two magnetic sensors at the front and rear of the intelligent inspection vehicle chassis, the rate of change of magnetic field strength at the two spatial positions at the front and rear of the vehicle is calculated to obtain the longitudinal gradient vector. The positive or negative attribute of the longitudinal gradient vector reflects the front-rear orientation of the grounding lead relative to the intelligent inspection vehicle, and the magnitude of this vector reflects the longitudinal distance between the intelligent inspection vehicle and the grounding lead. Next, based on the lateral fixed installation spacing of the two magnetic sensors on the left and right sides of the intelligent inspection vehicle chassis, the rate of change of magnetic field strength at the two spatial positions on the left and right sides of the vehicle is calculated to obtain the lateral gradient vector. The positive or negative attribute of this vector reflects the left and right orientation of the grounding down conductor relative to the intelligent inspection vehicle, and the magnitude of the vector reflects the lateral distance between the intelligent inspection vehicle and the grounding down conductor. By combining the gradient vector and the lateral gradient vector, the spatial parameters such as the front-back distance and left-right distance of the intelligent inspection vehicle relative to the grounding down conductor within the mutual inductance verification area are updated in real time. This accurately determines the relative positional relationship between the intelligent inspection vehicle and the grounding down conductor, that is, the front-back distance and left-right distance of the grounding down conductor relative to the intelligent inspection vehicle.

[0040] The intelligent inspection vehicle is controlled to move forward or reverse at low speed based on the relative position relationship. Specifically, if the longitudinal gradient vector is positive and exceeds the preset first gradient threshold, it indicates that the target grounding down conductor is in front of the intelligent inspection vehicle, and the vehicle continues to move forward. If the longitudinal gradient vector is negative and exceeds the preset first gradient threshold, it indicates that the intelligent inspection vehicle has passed the target position, and the vehicle is immediately stopped and reversed for adjustment. When the absolute value of the longitudinal gradient vector drops below the preset first gradient threshold, it is determined that the longitudinal approach pose calibration is complete, meaning the intelligent inspection vehicle has reached the longitudinal corresponding position of the grounding down conductor. Next, based on the left-right relative position relationship calculated by the lateral gradient vector, specifically, if the lateral gradient vector is positive and exceeds the preset threshold, the vehicle is controlled to adjust to the right; if the lateral gradient vector is negative and exceeds the preset second gradient threshold, the vehicle is controlled to adjust to the left. When the absolute value of the lateral gradient vector stabilizes within a smaller preset second gradient threshold, and this stable state lasts for more than a preset time, it is determined that the lateral alignment pose calibration is complete, meaning that the centerline of the intelligent inspection vehicle completely coincides with the ground projection of the grounding down conductor. The first gradient threshold can be set to 0.8 meters, and the second gradient threshold can be set to 1.2 meters. After completing the longitudinal and lateral pose calibrations, the average magnetic field strength changes collected by multiple magnetic sensors are continuously monitored. The intelligent inspection vehicle is controlled to move back and forth slightly at an extremely low speed. When the average magnetic field strength reaches its maximum value, and the magnetic field strength no longer increases when the intelligent inspection vehicle moves within a 0.1-meter range, it is determined that the center position of the intelligent inspection vehicle is directly above the target grounding lead, thus completing the final pose calibration. After all pose calibrations are completed, the center point of the current location of the intelligent inspection vehicle is used as the detection base point, and the vehicle heading angle, chassis level parameters, and other parameters corresponding to this detection base point are recorded simultaneously.

[0041] Centered on the detection base point, and combining the actual spatial range of the mutual inductance verification area in the substation map information, the rated operating range of the robotic arm, and the mobility performance of the intelligent inspection vehicle, a feasible region for pose fine-tuning of the intelligent inspection vehicle is defined. This feasible region includes the longitudinal movement range, the lateral movement range, and the heading angle fine-tuning range relative to the detection base point, ensuring that all positions within the feasible region are within the drivable and operational range marked on the substation map. Next, the intelligent inspection vehicle is discretized within the pose fine-tuning feasible region using a preset minimum step size. Each discretized vehicle spatial position, i.e., the coordinate position of the intelligent inspection vehicle, combined with its corresponding heading angle, forms a candidate operating pose, thereby generating several candidate operating poses covering the entire pose fine-tuning feasible region.

[0042] The substation equipment information includes basic information such as equipment attributes, rated parameters, operating status, and spatial outline of all primary electrical equipment, secondary electrical equipment, live-lined equipment, fixed facilities, and restricted areas within the mutual inductance verification area. This information corresponds one-to-one with the spatial coordinate information in the substation map information. Combining the three-dimensional spatial coordinates and outline information of live equipment in the substation map information with the rated voltage level, operating status, and distribution information of live parts in the substation equipment information, the electrical information of each live piece of equipment is extracted and determined. Specifically, this includes the rated voltage level, three-dimensional spatial outline, precise spatial coordinates of live parts, equipment operating status, and the legal safety distance standard for the corresponding voltage level. Simultaneously, based on the area boundary information in the substation map information, it is matched with the facility attributes and restricted access rules in the substation equipment information to extract and determine the obstacle range parameters for all obstacle areas. Obstacle areas include static fixed obstacles within the substation, fire lanes, maintenance restricted areas, and safety protection facility areas. The obstacle range parameters specifically include the three-dimensional spatial outline, occupied area, restricted access boundary, and legal minimum avoidance distance of the obstacle area.

[0043] Based on the electrical information of each piece of live equipment, a corresponding obstacle avoidance envelope area is planned. That is, taking the three-dimensional spatial outline of each piece of live equipment as the core, and combining the legal minimum safety distance standard corresponding to the rated voltage level of the equipment, the obstacle avoidance envelope area is generated by extending outward at equal distances along the outline of the equipment to generate an obstacle avoidance envelope area that covers the entire live equipment. This obstacle avoidance envelope area is a three-dimensional obstacle avoidance envelope area, which is an absolute no-entry area for live work. No part of the intelligent inspection vehicle and its robotic arm may enter this area during the entire operation process.

[0044] The target operational pose is selected from all candidate operational poses using obstacle avoidance envelope region and obstacle range parameters as constraints. Specifically, for any candidate operational pose, the robot arm's inverse kinematics algorithm is used to pre-simulate all typical operational configurations of the robot arm in the entire process of subsequent grounding circuit verification, high-voltage terminal insertion, pressurization and discharge verification, and disconnection and reset. The minimum distances between each joint of the robot arm, the end effector, the high-voltage test line, and the intelligent inspection vehicle body and the obstacle avoidance envelope region of all energized equipment are calculated. Only candidate operational poses whose minimum distance fully meets the safety requirements of the corresponding voltage level are retained, while all candidate operational poses with insufficient electrical safety distance risks are eliminated. Next, a secondary screening is performed on the candidate operational poses that have passed the above screening. Specifically, the minimum avoidance distances between the intelligent inspection vehicle body, including the ground projection contour after the hydraulic outriggers are fully extended and the robot arm's full operating stroke, and all obstacle areas are verified. Only candidate operational poses that do not interfere with all obstacle areas and fully meet the minimum avoidance distance requirements are retained, while all candidate operational poses with obstacle collision risks or violations of on-site operation management regulations are eliminated. After completing the above two-level screening, the remaining candidate job poses are marked as primary job poses.

[0045] If the number of primary working poses is 1, it is directly used as the target working pose. If it is greater than 1, the comprehensive cost of the primary working poses is calculated, and the target working pose is selected based on the comprehensive cost. Specifically, for any primary working pose, first calculate the straight-line spatial distance between the center point of the intelligent inspection vehicle and the detection base point when in the initial working pose. After normalizing this distance, it is used as the position offset. The center point can be the center of gravity of the intelligent inspection vehicle's planar projection. Next, calculate the difference between the heading angle of the intelligent inspection vehicle and the heading angle of the detection base point when in the initial working pose. After normalizing this, it is used as the heading angle offset. Then, calculate the ratio of the maximum joint output torque to the rated maximum torque during the entire operation process of the robotic arm under the current initial working pose. After normalizing this ratio, it is used as the joint torque utilization rate. The smaller the joint torque utilization rate, the lighter the load on the robotic arm and the more stable the operation. The weighted sum of the heading angle offset, position offset, and joint torque utilization rate is used to obtain the comprehensive cost of the primary working pose. The weights can be determined using the entropy weighting method or the expert scoring method. The primary job pose with the lowest overall cost is selected as the target job pose.

[0046] The target working postures selected through the above steps not only fully meet the rigid compliance requirements of electrical safety and obstacle avoidance at the substation site, but also provide the best posture basis for the subsequent high-precision and high-stability operation of the robotic arm.

[0047] In one embodiment, the grounding loop verification of the mutual inductance verification area by the first robotic arm includes the following steps: The first robotic arm injects a current conduction test signal into the grounding terminal of the mutual inductance verification area, and the primary circuit verification of the grounding terminal is completed using the current conduction test signal. If the primary circuit of the grounding terminal passes the test, the grounding resistance value of the grounding terminal is measured using the constant current method. Calculate the average resistance and resistance fluctuation of the grounding terminal based on the grounding resistance value; If the average resistance is less than or equal to the preset average threshold and the resistance fluctuation is less than or equal to the preset fluctuation threshold, then the mutual inductance verification area is determined to have passed the grounding loop verification. If the average resistance value is greater than the preset average threshold, or the resistance fluctuation value is greater than the preset fluctuation threshold, then the mutual inductance verification area is determined to have failed the grounding loop verification.

[0048] In this embodiment, the first robotic arm is first raised to a preset working height. A depth camera integrated at the end of the first robotic arm performs precise visual recognition and three-dimensional spatial positioning of the grounding terminal within the mutual inductance verification area. Then, the first robotic arm is controlled to grasp a dedicated grounding wire, accurately connecting one end of the grounding wire to the grounding terminal while ensuring a reliable electrical connection between the other end of the grounding wire and the intelligent testing vehicle, thus constructing a complete primary verification electrical circuit. Next, a current conduction test signal with preset parameters is injected into the connected grounding terminal and grounding circuit within the mutual inductance verification area through a current injection unit integrated at the end of the first robotic arm. This current conduction test signal is a low-amplitude, highly stable power frequency small current signal, which can effectively verify the circuit's continuity without causing electrical interference to the substation's operating equipment or grounding grid, and also possesses amplitude limiting and impact-resistant safety protection characteristics. Throughout the entire process of injecting the current conduction test signal, the intelligent testing vehicle collects the transmission data of the current conduction test signal in the grounding circuit in real time and simultaneously monitors the voltage feedback signal in the grounding circuit to determine the continuity status of the grounding circuit. If, during the monitoring process, the current conduction test signal in the grounding circuit is transmitted continuously and stably without signal interruption, amplitude drop, or abnormal change, the primary circuit verification of the grounding terminal can be determined to be passed. If signal interruption, no effective feedback signal, or amplitude fluctuation exceeding the preset range is detected (the amplitude fluctuation is determined based on industry experience), the primary circuit verification is determined to be failed, and an on-site audible and visual alarm is immediately triggered. At the same time, the first robotic arm is controlled to readjust the hanging posture and perform the grounding wire hanging and primary circuit verification actions again until the primary circuit verification is passed, or after reaching the preset maximum number of retries, all subsequent high-voltage operation permissions are locked, and the operator is prompted to conduct on-site manual inspection.

[0049] If the primary circuit verification of the grounding terminal passes, a constant DC test current conforming to the power industry's on-site grounding resistance measurement standards is injected into the completed grounding circuit. This constant current value has the characteristics of fixed amplitude and continuous stability, and is equipped with multiple safety current limiting protections to prevent electrical impact and damage to the substation grounding grid, the transformer under test, and other on-site equipment. During the continuous and stable injection of the constant test current into the grounding circuit, the effective values ​​of the constant current and voltage drop between the grounding terminal and the reference grounding terminal of the intelligent testing vehicle are simultaneously collected. Ohm's law is used to calculate the instantaneous grounding resistance value at each sampling moment in real time. Within the preset standard measurement duration, multiple consecutive cyclic sampling and calculations are completed to obtain multiple sets of instantaneous grounding resistance values, also known as grounding resistance values. Then, the grounding resistance values ​​are arithmetically averaged, and the final arithmetic mean is the average resistance value of the grounding terminal. At the same time, the deviation between the grounding resistance value and the average resistance value is calculated, and then the dispersion of all effective measured values ​​is calculated using mathematical statistics methods. This dispersion value is the resistance fluctuation value. Resistance fluctuation value can intuitively reflect the long-term stability of the grounding loop contact state, as well as whether there are problems such as poor contact, loose connection, or loose connection during the measurement process. It is the core indicator for judging the mechanical reliability and electrical contact stability of the grounding connection. If the average resistance value is less than or equal to the preset average value threshold and the resistance fluctuation value is less than or equal to the preset fluctuation value threshold, then the mutual inductance verification area is judged to have passed the grounding loop verification.

[0050] If the average resistance value is greater than the preset average threshold, or the resistance fluctuation value is greater than the preset fluctuation threshold, the mutual inductance verification area is deemed to have failed the grounding loop verification. Both the preset average threshold and the preset fluctuation threshold are determined according to the National Power Safety Work Regulations. The preset average threshold is the maximum permissible resistance value of the temporary grounding loop during extra-high voltage / ultra-high voltage field testing, and the preset fluctuation threshold is the maximum permissible discrete value of the grounding connection stability. Both thresholds can be adjusted for compliance based on the voltage level of the equipment under test and the safety requirements of the field operation, ensuring that the judgment criteria fully match the safety requirements of the field operation.

[0051] If the mutual inductance verification area passes the grounding loop verification, then proceed to the subsequent on-site verification steps for the mutual inductors. If the mutual inductance verification area fails the grounding loop verification, the above method further includes the following steps: If the mutual inductance verification area fails the grounding loop verification, a dual-frequency detection carrier signal is injected into the grounding loop through the first robotic arm, and the loop feedback signal of the grounding loop is collected simultaneously. Full-band spectrum analysis is performed on the return signal to extract the loop spectrum component of the loop return signal; Determine whether there are third-order intermodulation components in the loop return signal based on the loop spectral components. If the loop feedback signal contains a third-order intermodulation component, a narrow current pulse is injected into the grounding loop through the first robotic arm, and the acoustic response signal of the grounding loop is collected simultaneously. The acoustic response signal is subjected to kurtosis analysis, and the presence of ultrasonic pulse signals is determined based on the kurtosis analysis results. If the acoustic response signal contains an ultrasonic pulse signal, it is determined that there is a false contact fault in the grounding terminal. If the loop return signal does not contain a third-order intermodulation component or the acoustic response signal does not contain a steep ultrasonic pulse signal, the instantaneous phase characteristics of the loop return signal can be extracted using a phase-sensitive detector. The initial phase characteristics of the dual-frequency probe carrier signal are extracted, and the phase offset sequence is calculated by combining the initial phase characteristics and the instantaneous phase characteristics. A grounding resistance sequence is constructed by integrating all grounding resistance values. The cross-correlation between the grounding resistance sequence and the phase offset sequence is performed to obtain the sequence correlation coefficient. The loop fault type of the grounding loop is determined based on the sequence correlation coefficient. If the fault type of the grounding loop is a phase lag fault, the stray current waveform of the grounding loop can be inverted based on the phase offset sequence. Extract the current waveform characteristics of the stray current waveform and construct the reverse current parameters based on the current waveform characteristics; The first robotic arm injects a reverse balancing current into the grounding loop according to the reverse current parameters to complete the destructive interference of the stray current waveform until the mutual inductance verification area is verified by the grounding loop.

[0052] Specifically, when the mutual inductance verification area fails the grounding loop verification, the first robotic arm is controlled to maintain a stable clamping contact with the grounding terminal, without performing grounding wire disconnection or robotic arm retraction actions, locking the clamping pressure and spatial posture of the end gripper to provide a stable physical contact reference for signal injection and acquisition. Subsequently, through the signal generation unit built into the intelligent testing vehicle, a dual-frequency detection carrier signal is continuously injected into the grounding loop via the current injection unit at the end of the first robotic arm. Throughout the dual-frequency detection carrier signal injection process, the loop feedback signal of the grounding loop is acquired in real time at a sampling frequency that is completely synchronized with the signal injection frequency. The dual-frequency detection carrier signal is a set of two low-power, high-stability, fixed-frequency, and closely spaced sinusoidal high-frequency current signals generated by the built-in signal generation unit of the intelligent detection vehicle. Generally, a high-frequency band far away from the 50Hz power frequency and its integer multiples of the substation is selected to completely avoid strong power frequency electromagnetic interference on site and avoid interference from the power frequency and its harmonics to subsequent spectrum analysis. The frequency difference between the two signals is controlled within a small range to ensure that the third-order intermodulation components generated subsequently fall within the effective measurement range of the spectrum analysis module. At the same time, the signal power is strictly controlled at the milliwatt level, which is far below the safety threshold for on-site operations in the power industry. It will not cause any electrical impact on the grounding terminal or the equipment operating in the station, nor will it interfere with the normal operation of the relay protection device in the station.

[0053] Next, the acquired loop feedback signal undergoes bandpass filtering preprocessing to remove power frequency interference, high-frequency electromagnetic spurious interference, and instantaneous sampling noise. Then, a Fast Fourier Transform (FFT) is performed on the preprocessed loop feedback signal to convert the continuously varying time-domain loop feedback signal into frequency-domain spectral data, obtaining the feedback frequency domain signal. Subsequently, the signal amplitude and phase characteristics corresponding to all effective frequencies in the feedback frequency domain signal are extracted point-by-point and integrated to form the loop spectral component of the loop feedback signal. This component fully includes the injected dual-frequency probe carrier signal and all harmonics and intermodulation products generated by the electrical characteristics of the grounding loop.

[0054] Third-order intermodulation (TMI) component analysis is performed on the loop spectrum components to determine whether TMI components exist in the loop return signal. TMI components refer to signal components with frequencies of 2f1-f2 and 2f2-f1, where f1 and f2 are the signal frequencies of the dual-frequency probe carrier signal. TMI components only occur in nonlinear electrical systems. Pure metal contacts with good contact are linear ohmic contacts and do not produce this component, while metal-semiconductor junctions formed by oxide layers exhibit strong nonlinear characteristics and will produce significant TMI components. If TMI components are present in the loop spectrum components, it indicates that the grounding terminal contact interface may have a "false contact" fault due to oxidation, corrosion, or foreign matter adhesion, requiring maintenance personnel at the target substation to maintain the grounding terminal. To further determine whether a false contact fault exists in the grounding terminal, a narrow current pulse is injected into the grounding loop, and the acoustic response signal of the grounding loop is simultaneously acquired. The narrow current pulse is a set of rectangular current pulses with microsecond-level pulse width, low amplitude, and steep leading edge, generated by the pulse generation unit built into the intelligent inspection vehicle. Its pulse width is controlled between 1 and 10 microseconds to avoid overheating damage to the grounding terminal substrate caused by prolonged energization. The pulse amplitude is strictly controlled within a safe range, generating localized Joule heating only at the high-resistance point of the oxide layer, without melting the metal substrate or causing any permanent damage to the grounding terminal. Simultaneously, the pulse rise edge is less than 1 microsecond, ensuring instantaneous localized thermal expansion at the high-resistance point, exciting a precisely captured ultrasonic signal. At the same time, a high-sensitivity piezo-acoustic sensor integrated into the end effector of the first robotic arm, rigidly connected to the fixture, collects the acoustic response signal generated at the grounding terminal contact interface in real time at a sampling frequency of no less than 1 MHz, completely recording the time-domain waveform data of the acoustic signal to ensure the capture of the steep ultrasonic pulse at the microsecond level.

[0055] The acquired acoustic response signal undergoes kurtosis analysis. The steps include: extracting the signal rise time (the time it takes for the signal to rise from 10% to 90% of its peak value), calculating the waveform leading-edge slope (the rate of change of signal amplitude during the rise phase), and verifying the time synchronization between the signal peak value and the narrow current pulse injection moment. Then, noise signals such as environmental vibration and mechanical friction that are out of sync with the pulse injection moment are removed, and only the acoustic signal within 10 microseconds after pulse injection is analyzed. If the signal rise time within this period is less than a preset kurtosis threshold, the waveform leading-edge slope is greater than a preset slope threshold, and it is strictly synchronized with the pulse injection moment, the system determines that the acoustic response signal contains a compliant steep ultrasonic pulse signal; otherwise, it is determined that it does not. If the acoustic response signal contains a compliant steep ultrasonic pulse signal, it can be determined that there is a false contact fault at the grounding terminal. Otherwise, there is no false contact fault.

[0056] If the loop return signal does not contain a third-order intermodulation component or the acoustic response signal does not contain a steep ultrasonic pulse signal, it indicates that there is no false contact fault at the grounding terminal. Further verification is needed to determine if other faults caused the mutual inductance verification area to fail the grounding loop verification, such as checking for phase lag faults. Phase lag faults refer to non-stationary random stray potentials induced by adjacent large nonlinear loads, such as UHV converter stations or large industrial rectifier equipment, i.e., "phase lag" stray current interference in the grounding grid. Specific identification methods include: extracting the initial phase characteristics of the injected dual-frequency probe carrier signal, i.e., the standard fixed phase of the signal under ideal conditions without any interference. This phase is the original reference phase when the signal generation unit generates the signal, remaining fixed throughout, and is used as the reference zero point for this phase calculation. Then, for each sampling moment, the instantaneous phase characteristics of the loop return signal extracted at that moment are subtracted from the initial phase characteristics to obtain the instantaneous phase offset at that sampling moment; the sign of this offset represents phase lead or lag, and the absolute value represents the magnitude of the phase offset. Arrange the instantaneous phase offsets at all sampling times in chronological order to form a phase offset sequence.

[0057] During the grounding loop verification process, all instantaneous grounding resistance values, continuously acquired using the constant current method, are arranged in chronological order of sampling time to form a grounding resistance sequence. The time axes of the grounding resistance sequence and the phase shift sequence are aligned. A cross-correlation operation is performed on the perfectly aligned grounding resistance and phase shift sequences to calculate the sequence correlation coefficient, which can be calculated using the Pearson correlation coefficient formula. The closer the absolute value of the sequence correlation coefficient is to 1, the higher the matching degree of the fluctuation characteristics of the two sequences; the closer the absolute value is to 0, the lower the matching degree. If the sequence correlation coefficient is greater than or equal to a preset threshold, such as 0.9, it indicates that the fluctuation pattern of the grounding resistance highly overlaps with the change pattern of the phase shift, meaning that the fluctuation of the grounding resistance is entirely caused by the dynamic modulation of the phase-lag stray current in the grounding grid, rather than a physical continuity fault in the grounding loop itself. Therefore, the loop fault type of the grounding loop is ultimately determined to be a phase-lag fault. If the sequence correlation coefficient is less than the preset coefficient threshold, it means that the fluctuation of the grounding resistance is not significantly correlated with the phase shift. That is, the excessive resistance is not caused by stray current interference, but by structural defects in the grounding grid itself, such as corrosion or breakage of the grounding electrode, or poor connection with the main grounding grid. Finally, the fault type of the grounding loop is determined to be a structural defect fault in the grounding grid itself.

[0058] For phase-lag type faults, the recursive least squares method is used to invert and calculate the real-time dynamic waveform of the native stray current causing phase modulation in the grounding grid by using the dynamic change characteristics of the phase offset sequence. This includes the real-time amplitude of the stray current, fundamental frequency, higher harmonic components, phase evolution law, and dynamic change rate, resulting in a complete and continuous stray current waveform. All current waveform characteristics of the inverted stray current waveform are extracted, including the real-time amplitude of the stray current, fundamental frequency, amplitude and phase of each harmonic, phase evolution law, dynamic change rate, and rising and falling edge characteristics of the waveform. With the core objective of "completely offsetting the native stray current of the grounding grid and constructing a dynamic zero-potential quiescent zone at the grounding point," reverse current parameters are constructed. The core rules are: the fundamental frequency and harmonic frequencies of the reverse current are completely consistent with the stray current; the phase of the reverse current is completely opposite to the phase of the corresponding frequency component of the stray current; the amplitude of the reverse current is dynamically matched with the amplitude of the corresponding frequency component of the stray current to ensure optimal offsetting effect at each moment; the update frequency of the reverse current is completely synchronized with the sampling frequency of the stray current to ensure that the reverse current can follow the dynamic changes of the stray current throughout the process without timing misalignment. In addition, the amplitude of the reverse current is strictly controlled within a safe range and will not cause any interference to the grounding grid or the operating equipment within the station. The first robotic arm continuously injects a reverse balancing current into the grounding loop in real time according to the reverse current parameters. The reverse balancing current, determined by these parameters, interacts with the stray current in the grounding grid at the local measurement area of ​​the grounding point, causing destructive interference. The two currents, with opposite phases and matched amplitudes, superimpose in the same area, resulting in a combined current amplitude approaching zero. This forcibly constructs a dynamic zero-potential quiescent zone with near-zero potential fluctuation at the grounding resistance measurement node, maximizing the cancellation of stray current interference with the grounding resistance measurement process. During the injection of the reverse balancing current, the grounding loop verification of the mutual inductance verification area is simultaneously completed according to the entire grounding loop verification process. Once the mutual inductance verification area passes the grounding loop verification, the injection of the reverse balancing current is immediately stopped, completing the entire fault handling process. If the loop fault type is a structural defect in the grounding grid itself, fault repair information is generated, reminding the equipment maintenance personnel of the target substation to inspect the grounding grid structure.

[0059] In one embodiment, calculating the insertion control parameters of the intelligent testing vehicle based on the terminal electric field signal and the testing vehicle information includes the following steps: Acquire terminal image information of the high-voltage terminal to be inspected; Based on the terminal image information and using a feature matching algorithm, the insertion position parameters are located. Combining the insertion position parameters and the detection vehicle information, a terminal insertion path is planned for the second robotic arm. Based on the terminal insertion path, motion control parameters for the second robotic arm are generated. The frequency domain conversion of the terminal electric field signal is completed using the fast Fourier function to obtain the electric field frequency domain signal; The terminal signal features of the electric field frequency domain signal are extracted, and a terminal signal feature sequence is constructed based on the terminal signal features. The terminal signal features include signal frequency features, signal phase features, and signal amplitude features. The threshold method is used to verify the volatility of the terminal signal feature sequence, and the stable terminal feature sequence is extracted from the terminal signal feature sequence based on the volatility verification result. The feedforward control parameters of the second robotic arm are calculated based on the terminal stability characteristic sequence. The feedforward control parameters include the end effector motion period, end effector initial phase, and end effector motion vector of the second robotic arm. The motion control parameters and feedforward control parameters are spatiotemporally fused to obtain the plug-in control parameters of the intelligent inspection vehicle.

[0060] In this embodiment, the inspection vehicle information includes the current pose parameters of the intelligent inspection vehicle, the reference parameters of the global working coordinate system, the DH kinematic calibration parameters of the second robotic arm, the rated motion range of each joint, the rated speed and torque parameters, and the response characteristic parameters of the hydraulic and electric coordinated control system. Terminal image information of the high-voltage terminal to be inspected is acquired through a depth camera integrated at the end of the second robotic arm. The terminal image information is then preprocessed, including filtering using Gaussian filtering or median filtering algorithms, and histogram equalization to stretch its grayscale dynamic range and improve overall contrast. Next, the preprocessed terminal image information is matched against a pre-acquired standard feature template of the high-voltage terminal to be inspected. Through feature matching algorithms, core geometric features such as the slot outline, insertion center point, insertion axis, slot inner diameter, and effective insertion depth of the high-voltage terminal to be inspected are extracted. Combined with the reference parameters of the global working coordinate system, the three-dimensional spatial coordinates and pitch / roll / yaw attitude angles of the high-voltage terminal to be inspected in the global working coordinate system are accurately calculated, thereby forming complete insertion position parameters. Next, taking the current position of the second robotic arm's end effector as the starting point of the path, and the insertion start position and final insertion position determined by the insertion position parameters as the ending points of the path, where the insertion start position is the safe positioning position at a preset distance from the end face of the high-voltage terminal to be inspected, and the final insertion position is the target position where the connector is fully inserted into the terminal slot. The obstacle avoidance envelope area and obstacle area of ​​the live equipment are marked as no-entry areas. Then, based on the fixed contours of the intelligent inspection vehicle body, hydraulic outriggers, and work bucket, the effective working space of the robotic arm is divided within the mutual inductance verification area.

[0061] Next, based on the DH kinematic calibration parameters of the second robotic arm, forward and inverse kinematics calculations are performed on all possible poses within the effective working space of the robotic arm. Singular poses with singularities, joint over-limits, or precision failures are identified and eliminated, retaining continuous non-singular working intervals where all joint movements are within the effective working space of the robotic arm. This ensures that subsequent planned paths are free from the risk of motion loss of control. The DH kinematic calibration parameters of the second robotic arm include core kinematic parameters such as the length of each joint, torsion angle, range of motion, and end effector installation deviation. Then, within the non-singular working intervals, the insertion path is divided into three continuous segments according to the operational logic: a pre-synchronization positioning segment, a precision feed segment, and a final insertion segment. The start point, end point, and transition nodes of each segment are precisely calibrated. The start point of the pre-synchronization positioning segment is the current pose of the second robotic arm, and the end point is the insertion start safety position 100 mm from the end face of the high-voltage terminal to be inspected. This segment is used to complete the initial alignment and phase-locking synchronization preparation between the robotic arm and the terminal. The precision feed segment starts at a 100mm safety margin and ends at a 5mm safety redundancy margin from the end face of the high-voltage terminal to be inspected. This segment is used for high-precision coaxial alignment and attitude fine-tuning. The final insertion segment starts at a 5mm safety redundancy margin and ends at the rated depth of the connector fully inserted into the terminal slot. This segment is used to achieve zero-impact precision insertion. Then, a smooth curve interpolation algorithm is used to seamlessly connect the three trajectories, forming a complete, continuous, and uninterrupted terminal insertion path. This ensures that the second robotic arm moves smoothly and without impact, without sudden speed changes or joint over-limit issues, providing a compliant and feasible trajectory reference for subsequent motion control parameter generation. Next, the terminal insertion path is calculated into a continuous control sequence of the rotation angle, rotation speed, acceleration, and jerk of each joint of the second robotic arm. Simultaneously, a timestamp synchronized with the global clock is matched to each control sequence, forming complete motion control parameters for the second robotic arm.

[0062] The terminal electric field signal is generated by the 50Hz power frequency electric field of the high-voltage terminal under test. It can accurately and non-contactly reflect the periodic, phase, and amplitude characteristics of the micro-oscillation of the high-voltage terminal under test caused by bus electrodynamics, power frequency vibration, and on-site wind load, without measurement interference caused by mechanical contact. The continuously acquired terminal electric field signal is transformed into a full-range frequency domain signal using a fast Fourier transform function, converting the time-varying electric field intensity signal in the time domain into frequency-varying electric field component signals in the frequency domain, thus obtaining a complete electric field frequency domain signal. During the frequency domain transformation, the generated electric field frequency domain signal is simultaneously bandpass filtered to remove invalid frequency domain components caused by stray electric fields, high-frequency electromagnetic interference, and equipment operating noise from the substation. Only the effective frequency domain components related to the 50Hz power frequency and its harmonics of the substation are retained, ensuring that the final electric field frequency domain signal can truly and accurately reflect the real-time micro-oscillation law of the high-voltage terminal under test, providing a high-quality frequency domain data source for subsequent feature extraction.

[0063] Next, a full-dimensional feature analysis is performed on the filtered electric field frequency domain signal. Effective feature components are extracted from the electric field frequency domain signal point by point, and a complete terminal signal feature sequence is constructed in chronological order. The terminal signal feature sequence consists of multiple sets of continuous terminal signal features with uniform timestamps. Each set of terminal signal features includes signal frequency features, signal phase features, and signal amplitude features. The core of the signal frequency feature is the measured frequency value corresponding to the 50Hz power frequency and its harmonics at the substation, which can accurately reflect the period and frequency of the micro-amplitude oscillation of the high-voltage terminal under test. The signal phase feature can accurately reflect the real-time phase angle during the oscillation process of the high-voltage terminal under test. The signal amplitude feature can accurately reflect the three-dimensional spatial displacement amplitude of the oscillation of the high-voltage terminal under test.

[0064] The specific steps include: using the frequency axis of the electric field frequency domain signal as the horizontal axis and the electric field intensity amplitude as the vertical axis, traversing all spectral lines within the entire effective analysis frequency band, identifying all local peak points, i.e., spectral peaks, and selecting the fundamental spectral peak corresponding to the power frequency as the core characteristic peak. Simultaneously, selecting harmonic spectral peaks that are strictly integer multiples of the fundamental frequency as auxiliary characteristic peaks, and eliminating random interference spectral peaks that are not integer multiples of the power frequency, resulting in a set of effective characteristic peaks that accurately reflect the swing pattern of the high-voltage terminal under test. Next, for the core fundamental characteristic peak, a spectral line interpolation fitting algorithm is used to correct the inherent frequency fence effect of the fast Fourier transform, accurately calculating the actual frequency value corresponding to the fundamental characteristic peak. This value is the core signal frequency characteristic, which can directly reflect the period and frequency of the micro-amplitude swing of the high-voltage terminal under test. Simultaneously, for the selected auxiliary harmonic characteristic peaks, the frequency values ​​corresponding to each harmonic are extracted as supplementary frequency characteristics to correct the nonlinear distortion of terminal swing caused by on-site electrodynamics and wind load. The core signal frequency characteristics and supplementary frequency characteristics are integrated as the signal frequency characteristics. Similarly, the electric field intensity amplitude corresponding to the core fundamental characteristic peak on the frequency domain's vertical axis is read as the core amplitude feature, while the amplitudes corresponding to each harmonic characteristic peak are extracted as supplementary amplitude features. The core and supplementary amplitude features are then integrated to form the signal amplitude feature. Furthermore, the phase corresponding to the fundamental characteristic peak is extracted as the core phase feature, and the phases corresponding to the harmonic characteristic peaks are extracted as supplementary phase features, forming the signal phase feature. First, a characteristic fluctuation threshold is preset that perfectly matches the voltage level of the high-voltage terminal to be inspected, the substation site conditions, and the accuracy requirements of the connection operation. This threshold is divided into three categories: frequency fluctuation threshold, phase fluctuation threshold, and amplitude fluctuation threshold, corresponding to the three core dimensions of the terminal signal characteristics. All thresholds are strictly set according to the power industry's on-site operation standards and the connection accuracy requirements of UHV equipment, and can be adjusted for compliance according to on-site conditions. For each group of terminal signal characteristics in the terminal signal characteristic sequence, a dimensional fluctuation verification is performed. First, the statistical average value of the frequency, phase, and amplitude of multiple consecutive groups of terminal signal characteristics in the terminal signal characteristic sequence is calculated. Then, the absolute value of the difference between each characteristic value within each terminal signal characteristic (i.e., the core characteristic and corresponding supplementary characteristic within the signal frequency characteristic, signal phase characteristic, and signal amplitude characteristic) and the statistical average value is calculated. Then, this absolute value of the difference is divided by the statistical average value to obtain the core frequency fluctuation amplitude, core phase fluctuation amplitude, core amplitude fluctuation amplitude, supplementary frequency fluctuation amplitude, supplementary phase fluctuation amplitude, and supplementary amplitude fluctuation amplitude, respectively. Next, the corresponding frequency fluctuation threshold, phase fluctuation threshold, and amplitude fluctuation threshold are used to verify each fluctuation. If all the fluctuation amplitudes are less than their corresponding thresholds, the fluctuation verification is considered successful. If any fluctuation amplitude exceeds its corresponding threshold, the fluctuation verification fails. Specifically, the thresholds for core frequency fluctuation amplitude, core phase fluctuation amplitude, and core amplitude fluctuation amplitude are all less than the thresholds for supplementary frequency fluctuation amplitude, supplementary phase fluctuation amplitude, and supplementary amplitude fluctuation amplitude. For example, the frequency fluctuation thresholds, phase fluctuation thresholds, and amplitude fluctuation thresholds for core frequency fluctuation amplitude, core phase fluctuation amplitude, and core amplitude fluctuation amplitude are 0.01, 0.05, and 0.08, respectively, while the corresponding values ​​for supplementary frequency fluctuation amplitude, supplementary phase fluctuation amplitude, and supplementary amplitude fluctuation amplitude are 0.03, 0.15, and 0.2, respectively. The terminal stability features that pass the stability verification are retained and organized into a terminal stability feature sequence.

[0065] Based on the terminal stability feature sequence, the feedforward control parameters of the second robotic arm are accurately calculated using a rigid body kinematic mapping model. These feedforward control parameters are the core control quantities for achieving synchronized phase-locked following of the second robotic arm's end effector with the swinging high-voltage terminal under test. The end effector motion period is obtained by calculating the average frequency characteristic of the core signal in the terminal stability feature sequence to ensure that the frequency of the robotic arm's end effector motion is completely consistent with the terminal's swinging frequency, achieving precise synchronous following. The initial phase of the second robotic arm's end effector is also set based on the average core phase characteristic in the terminal stability feature sequence to ensure that the phase of the second robotic arm's end effector is completely synchronized with the swinging high-voltage terminal under test, achieving precise synchronous following and avoiding relative displacement during insertion. The average core amplitude characteristic is calculated as the magnitude of the end effector motion vector. The vector direction of the end effector motion vector is determined based on the spatial position of the high-voltage terminal under test and the insertion axis in the global operating coordinate system, ensuring that the second robotic arm's end effector can accurately follow the spatial swinging trajectory of the terminal, maintaining ideal coaxiality between the connector and the terminal slot throughout the entire process.

[0066] The motion control parameters and feedforward control parameters are timestamped and aligned with coordinates. The motion control parameters and feedforward control parameters at the same time dimension and coordinate position are fused to obtain the insertion control parameters of the intelligent inspection vehicle. This ensures that the basic insertion path movement of the second robotic arm is fully integrated with the phase-locked synchronous following movement of the terminal swing. This not only ensures that the robotic arm completes a smooth feeding action along the planned path, but also ensures that the connector keeps synchronously following the high voltage terminal under inspection at the same frequency and phase throughout the entire process, and always maintains the ideal coaxiality between the connector and the terminal slot.

[0067] In one embodiment, the docking and insertion step of the current transformer under test, which combines the insertion control parameters and the robot arm pose data and utilizes the second robot arm, includes the following steps: The six-dimensional force sensor pre-installed on the second robotic arm is calibrated at its no-load zero point to obtain the no-load zero point reference value of the six-dimensional force sensor. When the second robotic arm grips the high-voltage experimental equipment of the target substation, it collects six-dimensional force data through a six-dimensional force sensor, and combines the six-dimensional force data with the no-load zero-point reference value to complete the load zero-point correction of the six-dimensional force sensor and obtain the load zero-point reference value. The initial load parameters of the second robotic arm are collected in real time by a six-dimensional force sensor, and the initial load parameters are corrected in real time using the zero-point reference value under load, so as to obtain the real-time load parameters of the second robotic arm. By combining the pose data of the robotic arm and the real-time load parameters and using the rigid body dynamics model, the self-weight load parameters of the high-pressure experimental equipment are calculated, and the gravity feedforward compensation parameters of the second robotic arm are calculated based on the self-weight load parameters. The plug-in control parameters are corrected in real time based on the gravity feedforward compensation parameters; The second robotic arm completes the docking and insertion between the high-voltage test equipment and the transformer under test according to the real-time corrected insertion control parameters, and outputs a docking completion signal.

[0068] In this embodiment, the second robotic arm is first controlled to adjust to a preset no-load calibration posture, ensuring that the end effector and connector are in a completely no-load state, not clamping the high-voltage test line of the high-voltage experimental equipment, and without any external force contact or additional load application. Subsequently, the forces and moments around the three axes (X, Y, and Z) are continuously collected in multiple complete sampling periods using a six-dimensional force sensor, and their average values ​​are calculated to obtain the zero-point offset values ​​of the forces and moments in the three orthogonal directions of the six-dimensional force sensor under no-load conditions. These two sets of offset values ​​together constitute the no-load zero-point reference value of the six-dimensional force sensor. When the second robotic arm clamps the high-voltage experimental equipment of the target substation, the six-dimensional force sensor continuously collects six-dimensional force data under load conditions in multiple complete sampling periods at the same sampling frequency as the no-load calibration. The six-dimensional force data refers to the forces and moments around the three axes (X, Y, and Z) under load conditions. The no-load zero-point reference value is subtracted from the six-dimensional force data under load conditions to obtain the load zero-point reference value. The zero-point reference value under load is a dynamic reference for subsequent real-time load parameter correction. It can completely eliminate the load offset caused by the static self-weight of the high-voltage test equipment, ensuring that the load data collected later only reflects the contact force changes during the insertion process, rather than the static load.

[0069] The initial load parameters of the second robotic arm's end effector are acquired in real time using a six-dimensional force sensor at a high sampling frequency fully synchronized with the motion control cycle of the second robotic arm. These initial load parameters refer to the forces and moments at the end effector of the second robotic arm in the X, Y, and Z axes. They originate from the dynamic load components generated by the self-weight of the high-voltage experimental equipment changing with the robotic arm's posture, the contact reaction force between the connector and the terminal under test during the insertion process, the fluctuating load components caused by environmental interference such as wind load, and the residual zero drift component of the sensor. The initial load parameters are subtracted from the zero-point reference value under load to eliminate the basic offset of the static load. Then, a preset real-time sliding filter window is used to eliminate invalid fluctuation data caused by instantaneous electromagnetic interference and environmental vibration, ultimately obtaining the real-time load parameters of the second robotic arm that accurately reflect the contact state of the insertion interface. These real-time load parameters include three-dimensional real-time contact force and three-dimensional real-time contact moment, maintaining strict time synchronization with the real-time posture data of the second robotic arm throughout the process, without any timing misalignment.

[0070] The robotic arm pose data refers to the real-time rotation angles of each joint of the second robotic arm, and the three-dimensional spatial coordinates and attitude angles of the end effector in the global working coordinate system. The real-time load parameters are decomposed into four independent components: the self-weight load component generated by the change of the high-voltage test equipment's self-weight with the pose of the second robotic arm; the contact reaction force component between the connector and the high-voltage terminal of the transformer under test during the insertion process; the dynamic interference load component caused by environmental wind load and vibration of the working platform; and the residual zero drift component of the six-dimensional force sensor. By using a preset bandpass filtering algorithm, high-frequency interference components corresponding to the 50Hz power frequency vibration of the substation and the high-frequency jitter of the second robotic arm servo system are removed from the real-time load parameters, eliminating dynamic interference load components caused by environmental vibration. Then, the threshold method is used to identify and remove the abrupt contact reaction force components caused by the contact between the connector and external objects in the real-time load parameters, retaining only the stable load data in the state of no contact before the insertion action or in the stage of no rigid contact during the insertion process. Then, the stable load data is corrected by the load zero-point reference value, and the residual zero drift component of the six-dimensional force sensor is removed, resulting in pure load data to be calculated that only includes the self-weight effect of the high-voltage experimental equipment.

[0071] The robot arm's pose data is imported into a pre-defined rigid body dynamics model. This model treats each link and end-effector of the robot arm as an ideal rigid body that does not deform. Using classical mechanics laws, it establishes a mathematical model that quantitatively describes the relationship between the robot arm's motion and all forces / torques acting on it. The rigid body dynamics model includes terms for the total driving torque, inertia, Coriolis force, centrifugal force, gravity, and friction compensation required for each joint of the robot arm. The inertia term describes the mass of each link and end-effector load. The inertial effect caused by moment of inertia and rotational inertia is a matrix constructed based on the real-time joint angles of the robotic arm. The Coriolis force and centrifugal force terms are related to the real-time joint angles and angular velocities of the robotic arm, describing the inertial forces caused by the kinematic coupling between different links during joint movement. The gravity term describes the static torque exerted on each joint by the weight of the robotic arm's own links and the high-voltage experimental equipment held at the end effector. The friction compensation term describes the frictional torque of the robotic arm's joint reducer, bearings, and transmission mechanism, used to compensate for control errors caused by transmission losses and further improve the motion accuracy of the robotic arm. The rigid body dynamics model has been pre-calibrated with the DH kinematic parameters of the second robotic arm, joint transmission characteristics, and physical property parameters of the high-voltage experimental equipment. Using forward kinematics algorithm, the full linkage pose mapping of the second robotic arm from the base to the end effector is completed. This accurately calculates the three-dimensional spatial position of the center of mass of the high-voltage experimental equipment held by the end effector in the global working coordinate system, as well as the vector distance of the center of mass relative to the six-dimensional force sensor measurement coordinate system at the end effector. The forward kinematics algorithm is a forward pose calculation algorithm for multi-joint robotic arms. Given the real-time motion parameters of each joint of the robotic arm, such as the rotation angle of rotary joints and the translation distance of translational joints, a complete algorithm is used through standardized geometric modeling and matrix operations to solve for the three-dimensional spatial position and orientation of the end effector, such as the gripper holding the high-voltage test line and the six-dimensional force sensor, in the global reference coordinate system. Next, using the constant gravitational acceleration and the total mass of the high-voltage experimental equipment, the theoretical resultant force of the high-voltage experimental equipment in the vertical direction is calculated. The formula is: G = mg, where G is the theoretical resultant force, m is the total mass of the high-voltage experimental equipment, and g is the constant gravitational acceleration. By combining the vector distance of the center of mass relative to the six-dimensional force sensor measurement coordinate system, and through the rigid body static torque balance logic (that is, torque equals the cross product of the lever arm vector and the force vector), the theoretical self-weight components of the high-pressure experimental equipment acting on the X, Y, and Z axes in the six-dimensional force sensor measurement coordinate system under the current pose, as well as the theoretical self-weight overturning torque around the three axes, are calculated. The formula for calculating the theoretical self-weight overturning torque is as follows: ,in, It refers to the vector distance of the center of mass relative to the coordinate system of the six-dimensional force sensor measurement. This represents the coordinate system for the six-dimensional force sensor measurement, with the origin at the measurement center of the six-dimensional force sensor. This represents the weight force vectors decomposed from the theoretical resultant force of self-weight into the three axes of the sensor's measurement coordinate system. This represents the three-dimensional vector cross product operator. It integrates the theoretical self-weight components and theoretical self-weight overturning moment described above into the initial value of the theoretical self-weight load.

[0072] The initial value of the theoretical self-weight load is matched and compared dimension by dimension with the pure load data to be calculated in the same measurement coordinate system. The component force deviation value in each axis and the torque deviation value in each rotation direction are calculated. The least squares fitting algorithm is used to fit the component force deviation value and the torque deviation value. The fitted component force deviation value and torque deviation value are added to the initial value of the theoretical self-weight load to obtain the self-weight load parameters of the high-pressure experimental equipment. The self-weight load parameters include the three-dimensional self-weight component force generated by the high-pressure experimental equipment in the current pose and the self-weight overturning torque around the three axes. Based on the principle of inverse dynamics, with the goal of counteracting the self-weight load of the high-pressure experimental equipment and eliminating the influence of self-weight on the positioning accuracy of the end effector of the second robotic arm, the self-weight load parameters are imported into the servo control model of the second robotic arm. The additional compensation torque and joint angle correction amount required by each joint of the second robotic arm to counteract the corresponding self-weight load are calculated. The compensation torque and joint angle correction amount are integrated to obtain the gravity feedforward compensation parameters of the second robotic arm. The gravity feedforward compensation parameters are spatiotemporally fused with the insertion control parameters of the second robotic arm in the current cycle. This means that the gravity feedforward compensation parameters at the same time dimension and coordinate position are superimposed on the insertion control parameters joint by joint and dimension by dimension. The rotation angle, rotation speed, and acceleration control sequence of each joint in the insertion control parameters are corrected in real time. This eliminates the end-position offset and attitude deviation caused by the self-weight of the high-pressure experimental equipment. It ensures that the corrected insertion control parameters can accurately control the end of the second robotic arm to follow the preset terminal insertion path and complete a smooth feeding action without offset or attitude deviation.

[0073] The servo control system of the second robotic arm, based on the insertion control parameters after real-time correction of gravity feedforward compensation, drives the coordinated movement of each joint of the second robotic arm. This moves the high-voltage test line connector of the high-voltage experimental equipment held at the end effector along the preset terminal insertion path, sequentially completing the three stages of pre-synchronous positioning, precise feeding, and final insertion. Throughout the entire docking and insertion process, the system continuously executes a closed-loop control process, including real-time data acquisition from the six-dimensional force sensor, load parameter correction, gravity feedforward compensation parameter calculation, and real-time correction of insertion control parameters. This ensures the coaxiality of the connector and the high-voltage terminal of the transformer under test throughout the process, preventing collisions, jamming, and terminal damage during insertion. When the connector at the end of the second robotic arm is fully inserted into the slot of the high-voltage terminal under test, reaching the preset rated insertion depth, and the contact force data collected by the end six-dimensional force sensor meets the preset insertion in place judgment threshold, the judgment threshold can be determined by measuring the mechanical data when the connector is fully inserted into the slot of the high-voltage terminal under test. This determines that the docking insertion action between the high-voltage test equipment and the transformer under test is completed, and then outputs a docking completion signal to provide a trigger benchmark for the completion of the action in the subsequent pressurization and discharge verification stage.

[0074] The above steps ensure zero-impact and high-precision insertion, and provide solid technical support for the stability of electrical connections and the accuracy of measurement data during subsequent transformer pressurization and discharge verification.

[0075] In one embodiment, after completing the docking insertion step, the method further includes the following steps: When the insertion completion signal of the docking step is received, the mechanical load data between the high voltage test equipment and the transformer under test is collected by the six-dimensional force sensor. The constant load component in the mechanical load data is extracted using a preset sliding window; The environmental interference frequency band is determined based on the wind speed and direction parameters of the target substation obtained in advance. Perform Fourier transform on the mechanical load data, and extract the fluctuating load component from the mechanical load data after Fourier transform based on the environmental interference frequency band. By combining constant load components and fluctuating load components, the reaction load component in the mechanical load data is selected. The contact interface between the high-voltage test equipment and the transformer under test is defined as a virtual support point, and a three-dimensional equivalent coordinate system is constructed with the virtual support point as the origin. The constant load component and the fluctuating load component are mapped to a three-dimensional equivalent coordinate system to calculate the three-dimensional load cancellation value; Using the reaction load component as a constraint, the interference compensation parameters of the second robotic arm are calculated based on the three-dimensional load cancellation value.

[0076] In this embodiment, upon receiving the docking completion signal (i.e., after the docking insertion step is completed), a six-dimensional force sensor is used to collect mechanical load data between the high-voltage test equipment and the transformer under test. The six-dimensional force sensor is integrated between the end effector of the second robotic arm and the high-voltage test line gripper of the high-voltage test equipment. It can simultaneously collect force data in the X, Y, and Z axes in three-dimensional space, as well as torque data around these three axes. Then, a bandpass filtering algorithm is used to filter the collected force data in the three axes and the torque data around these three axes to shield against invalid noise interference caused by power grid frequency vibration and high-frequency jitter of the second robotic arm servo system, and to eliminate values ​​generated by instantaneous sampling jitter, thus obtaining the mechanical load data. Next, a preset sliding time window is invoked. The width of this sliding window is fixed to an integer multiple of the preset power frequency period to ensure that the window can completely cover the complete cycle of power grid frequency vibration, avoiding the influence of power frequency interference on the extraction of constant load. Mechanical load data is imported into a sliding window in chronological order. Within the window, multiple sets of synchronously acquired six-dimensional force and torque data are subjected to statistical analysis. The statistical average of each axial force and torque within the window is calculated using an arithmetic mean algorithm. This statistical average does not fluctuate significantly over time and represents a constant load generated by the self-weight of the high-voltage test lead of the high-voltage experimental equipment; this is the constant load component. As the sliding window continues to slide, the calculation results of the constant load component are continuously updated to ensure that the extracted constant load component perfectly matches the self-weight load of the high-voltage test lead. Simultaneously, all dynamically fluctuating loads that change over time are eliminated, retaining only the stable and continuous constant load component. This component is one of the core loads that needs to be actively offset by the second robotic arm later.

[0077] Wind speed and direction parameters in the mutual inductance verification area are collected in real time by wind speed and direction sensors pre-installed at the target substation. These parameters include real-time wind speed, wind direction, and turbulence intensity. Based on the angle between the real-time wind direction and the axial direction of the high-voltage test lead, the effective wind speed perpendicular to the lead's axis is calculated. The formula for calculating the effective wind speed is: ,in, This refers to real-time wind speed. Since the axial angle is [value missing], only the vertical component will cause lateral wind vibration of the lead wire; the parallel component does not generate effective alternating load and is therefore discarded. Next, the dominant frequency of vortex-induced vibration of the lead wire is calculated using the industry-standard Storoha formula. ,in, The Storoja number is typically taken as a standard engineering value of 0.2. The outer diameter of the high-voltage test lead can be obtained from the lead's manufacturer specifications. The effective wind speed is represented by the formula for the natural frequency of the suspension structure. The first three natural frequency ranges are calculated, and the broadband range of turbulent buffeting is simultaneously determined. These are then combined to obtain the full frequency range of the wind-loaded vibration of the lead wire. Specifically, the first three natural frequency ranges of the robotic arm in the current pose are calculated using the natural frequency formula for the cantilever beam. The natural frequency formula for the cantilever beam is as follows:

[0078] in, =1, 2, 3, corresponding to the first 3 orders respectively. The straight-line distance from the end gripping point of the second robotic arm to the high-voltage terminal connection point of the current transformer is calculated in real time using the robotic arm's pose data. The horizontal tension of the high-voltage test lead can be acquired in real time by a six-dimensional force sensor at the end of the second robotic arm. The linear density per unit length of the high-voltage test lead is obtained from the lead's manufacturer specifications. This represents the sag correction factor, used in engineering. =1, 2, 3, with values ​​of 0.95, 1, 0.98 respectively. The broadband range of turbulent buffeting is calculated simultaneously, where the lower limit of the broadband range is 0.1 times the dominant frequency of the lead-wire vortex-induced vibration, and the upper limit is... ,in, This is the dominant frequency of vortex-induced vibration of the lead wire. The turbulence intensity is represented, and the frequency range of wind-loaded vibration of the robotic arm is obtained by merging these values. The wind vibration frequency ranges of the two types of structures are merged, and their upper and lower limits are taken as the initial interference frequency band. A 10% safety redundancy is added to complete the frequency band expansion, and finally the environmental interference frequency band is obtained.

[0079] A Fast Fourier Transform (FFT) is performed on the mechanical load data to convert the time-domain data into frequency-domain spectral data, fully revealing the amplitude and phase characteristics corresponding to different frequencies. After the FFT, using the environmental interference frequency band as the extraction interval, all spectral components within the environmental interference frequency band are extracted from the full-frequency-domain spectral data, eliminating invalid spectral data such as power frequency components, inherent equipment vibration components, and high-frequency noise components outside the frequency band. Next, an Inverse Fourier Transform is performed on the extracted spectral data within the environmental interference frequency band to convert the frequency-domain data back into dynamic load data in the time domain, obtaining the fluctuating load component. The fluctuating load component is entirely caused by environmental wind loads and the micro-swaying of the work platform, continuously fluctuating dynamically over time. This is the core dynamic interference load that needs to be offset in real-time by a second robotic arm.

[0080] The constant load component and the fluctuating load component are superimposed in the time domain to obtain the composite data of the total external disturbance load. Then, the mechanical load data and the composite external disturbance load data are differentially calculated time-stamped. After removing the total external disturbance load corresponding to the constant load component and the fluctuating load component, the contact reaction force and overturning torque generated between the connector of the high-voltage test equipment and the terminal of the transformer under test are obtained, i.e., the reaction load component. The reaction load component directly reflects the direct force exerted on the terminal of the transformer under test at the contact interface and is a core control target quantity that needs to be strictly controlled within the rated threshold in zero-stress adaptive control.

[0081] The complete contact interface between the connector of the high-voltage test equipment and the terminal slot of the transformer under test is defined as a virtual support point. This virtual support point is the only force fulcrum on which all loads act on the terminals of the transformer under test, and it is also the core control object of zero-stress adaptive control. Using this virtual support point as the origin, the connector feed axis as the Z-axis, the horizontal direction perpendicular to the connector axis as the X-axis, and the vertical direction perpendicular to the connector axis as the Y-axis, a three-dimensional equivalent coordinate system under the right-hand rule is constructed. This coordinate system achieves precise coordinate transformation and spatiotemporal alignment with the global operation coordinate system, ensuring that all load data and pose data within the coordinate system can be directly mapped to the kinematic model of the second robotic arm. Using the homogeneous transformation formula, the constant load component and the fluctuating load component are transformed from the six-dimensional force sensor measurement coordinate system to the three-dimensional equivalent coordinate system. The homogeneous transformation formula refers to a 4×4 matrix used to describe the pose relationship between the six-dimensional force sensor measurement coordinate system and the three-dimensional equivalent coordinate system. The homogeneous transformation formula is as follows:

[0082] Where R is a 3x3 rotation matrix, describing the three-axis relative rotation angles between the six-dimensional force sensor measurement coordinate system and the three-dimensional equivalent coordinate system; P is a 3x1 position vector, describing the phase distance between the origin of the six-dimensional force sensor measurement coordinate system and the origin of the three-dimensional equivalent coordinate system. This precisely quantifies the magnitudes of the force components of the two types of loads along the X / Y / Z axes of the coordinate system, as well as the magnitudes of the overturning moments around these axes, determining the total target load value that needs to be completely canceled in each axis and direction. With the core objective of completely canceling external disturbance loads and achieving zero net external force at the virtual support point, the corresponding reverse cancellation amount is calculated for the force component and the moment around the axis in each axis. The integration of all the reverse cancellation amounts along the axes yields the three-dimensional load cancellation value. This three-dimensional load cancellation value can completely cancel all external disturbance loads caused by the self-weight of the high-voltage test lead and environmental disturbances, making the net external force and net external moment at the virtual support point approach zero, achieving an ideal zero-stress state at the contact interface.

[0083] To ensure that the reaction load component at the contact interface remains continuously controlled within a preset zero-stress control threshold, the three-dimensional load cancellation value is used as the core input and imported into the inverse dynamics model of the second robotic arm. The core essence of the inverse dynamics model is, given the motion state of the robotic arm's end effector or joints, including the joint's rotation angle, angular velocity, and angular acceleration, to inversely solve, using the laws of rigid body mechanics, the required driving torque output of the drive motor for each joint of the robotic arm to enable the robotic arm to accurately and stably achieve the aforementioned motion state. The construction principle of the inverse dynamics model is consistent with that of the rigid body dynamics model. It includes inertial terms, Coriolis force terms, centrifugal force terms, gravity terms, external load terms, and friction compensation terms. The external load term corresponds to the aforementioned three-dimensional load cancellation value and the Jacobian transpose matrix constructed based on the robotic arm's pose parameters. The inertial and Coriolis force terms are extremely small and can be ignored. By combining the current real-time pose of the second robotic arm, DH kinematic calibration parameters, joint transmission characteristics, and servo system response characteristics, the virtual displacement adjustment amount in three-dimensional space required by the end effector of the second robotic arm to completely offset the external disturbance load corresponding to the three-dimensional load compensation value is calculated. This virtual displacement adjustment amount is only used to offset the load torque and does not change the insertion depth. The calculated virtual displacement compensation amount is decomposed into multiple continuous and smooth micro-adjustment commands with a minimum step size of 10μm to avoid mechanical jitter caused by a single large adjustment. At the same time, the end effector virtual displacement adjustment amount is decomposed and mapped to each motion joint of the second robotic arm, and the micro-angle and compensation torque required by the servo motor of each joint are calculated. The micro-angle and compensation torque corresponding to each motion joint of the second robotic arm are integrated to obtain the interference compensation parameters of the second robotic arm. Through the above steps, the self-weight of the high-voltage test lead and the force of environmental disturbance on the terminals of the transformer under test are eliminated to the greatest extent, avoiding contact impedance drift and measurement data distortion caused by contact stress changes.

[0084] In one embodiment, the process of performing pressurized discharge verification of the current transformer under test using an intelligent testing vehicle, and generating a current transformer verification report based on the pressurized discharge verification results, includes the following steps: The intelligent testing vehicle performs a step-by-step voltage boost on the transformer under test and collects the transformer voltage boosting parameters in real time until the transformer voltage reaches the preset voltage threshold, at which point the transformer under test is determined to have entered the transformer withstand voltage stage. When the current transformer under test enters the current transformer withstand voltage stage, the current transformer withstand voltage parameters of the current transformer under test are collected in real time. When the withstand voltage stage of the current transformer lasts longer than the preset time threshold, the current transformer under test is stepped down in a stepwise manner through the intelligent testing vehicle, and the current transformer voltage reduction parameters of the current transformer under test are collected in real time. The threshold compares and verifies the compliance of the transformer's boost parameters, withstand voltage parameters, and step-down parameters with the corresponding preset thresholds, and generates a transformer verification report for the transformer under test based on the compliance comparison and verification results.

[0085] In this embodiment, the voltage regulator drive unit, high-voltage generator, and reactor inside the intelligent testing vehicle first perform a stepped voltage boost on the transformer under test. The boost rate is controlled to not exceed 2% of the rated voltage of the transformer under test per second. A uniform stepped voltage boost mode is adopted to avoid voltage overshoot and voltage sudden changes that could cause insulation shock to the transformer under test and the vehicle-mounted high-voltage equipment, while also avoiding the risks of insulation breakdown and flashover during the voltage boost process. During the stepped voltage boost process, the transformer boost parameters of the transformer under test are collected in real time. These parameters include the primary voltage value of the transformer under test measured in real time by the voltage divider, the output current value of the high-voltage generator, and the amplitude and phase data of the secondary voltage of the transformer under test. When the primary voltage of the transformer under test is detected to have reached a preset voltage threshold, which is the short-time power frequency withstand voltage value automatically calculated based on the rated parameters of the transformer under test and the JJG1189.4-2022 specification, the voltage boosting operation is immediately stopped, the current high voltage output voltage is locked, and the transformer under test is officially determined to have entered the transformer withstand voltage stage.

[0086] Once the transformer under test enters the withstand voltage stage, its withstand voltage parameters are collected in real time. These parameters include the instantaneous waveform data of the secondary voltage, the ratio and phase difference of the transformer, the harmonic spectrum data of the secondary side, the triaxial vibration acceleration data of the working arm and dual robotic arms, and the real-time readings of the force sensor at the end of the robotic arm. When the withstand voltage stage lasts longer than a preset time threshold (typically 1 minute), the high-voltage generator is controlled to reduce the output voltage in a uniform, stepwise manner at a rate symmetrical to the voltage increase process. This avoids safety risks such as voltage surges, induced current anomalies, and equipment insulation damage caused by rapid voltage reduction. Simultaneously, the transformer's voltage reduction parameters are collected in real time. These parameters include the real-time value of the primary voltage, real-time monitoring data of the voltage reduction rate, residual voltage data on the primary and secondary sides of the transformer, and the output current data of the high-voltage generator. When the primary voltage of the transformer under test drops below 100V, the high voltage generator is immediately controlled to stop high voltage output, in preparation for subsequent multi-channel redundant discharge and complete release of residual charge.

[0087] Next, the threshold value will conduct a compliance comparison and verification on the voltage boosting parameters, withstand voltage parameters, and voltage reduction parameters of the mutual inductor with the corresponding preset threshold values, and generate a mutual inductor calibration report for the to-be-tested mutual inductor according to the results of the compliance comparison and verification. Specifically, first retrieve the corresponding preset threshold values set in advance according to the nameplate parameters, accuracy grade of the to-be-tested mutual inductor, and the JJG1189.4-2022 verification regulation. The preset threshold value is the compliance judgment benchmark for the entire process of this calibration, specifically including the allowable deviation threshold of the voltage boosting rate, the voltage overshoot limit threshold, and the abnormal current protection threshold during the voltage boosting process; the allowable limit of ratio error, the allowable limit of angular error, the harmonic distortion rate limit, the rated withstand voltage duration threshold, the allowable limit of leakage current, and the no-breakdown and no-flashover judgment standard during the withstand voltage process; the allowable deviation threshold of the voltage reduction rate, the residual voltage safety threshold, and the allowable limit of voltage fluctuation during the voltage reduction process. Conduct an item-by-item and full-time compliance comparison and verification on the voltage boosting parameters, withstand voltage parameters, and voltage reduction parameters of the mutual inductor with the corresponding preset threshold values. For the voltage boosting parameters of the mutual inductor, focus on verifying whether the voltage boosting rate is within the allowable range of the regulation, whether the output voltage reaches the preset voltage threshold smoothly, and whether there are situations such as abnormal current mutation and insulation abnormality during the voltage boosting process that do not meet the threshold requirements; for the withstand voltage parameters of the mutual inductor, focus on verifying whether the withstand voltage duration meets the preset time threshold, whether the ratio error and angular error at each test voltage point are within the corresponding limits, whether the total harmonic distortion rate and the content of each harmonic meet the requirements of the regulation, and whether there are problems such as breakdown, flashover, and excessive leakage current during the withstand voltage process. During the verification process, the platform uses an error separation model to finally decompose the ratio error and angular error data in the withstand voltage parameters, eliminate the environmental drift error and mechanical coupling error, and extract the inherent error of the to-be-tested mutual inductor as the final verification result, and then compare it with the corresponding threshold value; for the voltage reduction parameters of the mutual inductor, focus on verifying whether the voltage reduction rate meets the symmetric control requirements, whether the residual voltage drops below the safety threshold, and whether there are situations such as abnormal voltage fluctuation during the voltage reduction process that do not meet the threshold requirements. If all verification items meet the requirements of the corresponding preset threshold values, it is determined that the mutual inductor calibration is qualified this time; if any verification item exceeds the requirements of the corresponding preset threshold value, it is determined that the mutual inductor calibration is unqualified this time, and the unqualified items, the measured values, and the deviation from the threshold value are accurately marked, and the original data corresponding to the corresponding time period is synchronously associated to provide a basis for subsequent equipment analysis. Integrate whether the mutual inductor calibration is qualified this time, and the voltage boosting parameters, withstand voltage parameters, and voltage reduction parameters of the mutual inductor collected during the calibration process to generate a mutual inductor calibration report. The mutual inductor calibration report includes the detection results of the to-be-tested mutual inductor, that is, whether it is qualified, the equipment model, rated voltage, transformation ratio, accuracy grade, factory number, installation location, etc. of the to-be-tested mutual inductor, and parameters such as the voltage boosting parameters, withstand voltage parameters, and voltage reduction parameters of the mutual inductor.

[0088] In one of the embodiments, the method further includes the following steps: The intelligent testing vehicle completes the zero-return verification of the high-voltage source of the high-voltage experimental equipment in the mutual inductance verification area. If the high-voltage source returns to zero and passes the verification, the residual potential data of the high-voltage test equipment and the high-voltage terminal under test are collected in real time by the second robotic arm. Real-time potential verification of residual potential data is performed using a pre-acquired residual voltage safety threshold. If the residual potential data passes the real-time potential verification, the second robotic arm and the first robotic arm will sequentially complete the robotic arm reset and locking steps, and output the current transformer verification completion signal.

[0089] In this embodiment, upon receiving the signal indicating completion of the test transformer verification, the high-voltage source zero-return verification of the high-voltage test equipment within the transformer verification area is completed via an intelligent testing vehicle. Specifically, a final verification of the output voltage returning to zero is performed first. Multiple vehicle-mounted voltage sensors installed at the output end of the high-voltage generator, the high-voltage side terminals of the reactor, and the output terminals of the high-voltage test leads are used to collect voltage values ​​at key nodes of the entire high-voltage circuit in real time and synchronously. This confirms that the high-voltage test equipment has completely stopped high-voltage output, and the voltage values ​​at all nodes of the entire circuit have stabilized and dropped to zero potential, with no voltage overshoot, residual high-voltage output, or abnormal voltage fluctuations. Next, a high-voltage circuit interlocking status verification is performed. The operating status of the high-voltage circuit interlocking device of the high-voltage test equipment is checked to confirm that the high-voltage output main circuit has been completely physically interlocked, with no risk of high-voltage reverse output or false triggering. Simultaneously, the overall operating status of the high-voltage test equipment is verified to confirm that there are no fault codes, no insulation abnormality alarm signals, and no component overheating abnormalities. After both verifications pass, the high-voltage source zero-return verification is deemed successful, and a high-voltage source zero-return verification qualified signal is generated. If either verification fails, the platform immediately triggers an on-site audible and visual alarm, permanently blocking all subsequent disconnection and reset operations. At the same time, it automatically triggers the high-voltage circuit redundant discharge device to continuously and forcibly discharge the entire high-voltage circuit until the high-voltage source zero-return dual verification is completed again and deemed successful, thus eliminating the safety risks of high-voltage operation from the source of the process.

[0090] After the high-voltage source returns to zero and passes the verification, the second robotic arm collects the residual potential data of the high-voltage test equipment and the high-voltage terminal under test in real time. The residual potential data is then continuously and frame-by-frame compared and verified using a pre-acquired residual voltage safety threshold. During the verification process, it is necessary to verify whether the instantaneous value in the residual potential data is lower than the safety threshold, and whether the duration of the instantaneous value being lower than the safety threshold is within the preset safety confirmation time. Simultaneously, there must be no potential rise, no abnormal discharge pulse signal, and no potential abrupt change throughout the process. Only when the safety threshold of the instantaneous value in the residual potential data being lower than the safety threshold is greater than or equal to the preset safety confirmation time can the residual potential data be considered to have passed the real-time potential verification. Then, the second and first robotic arms are controlled to sequentially complete the robotic arm reset and locking steps, and an instrument transformer verification completion signal is output. The robotic arm reset and locking steps include driving the second robotic arm to perform the high-voltage test line removal and reset operation. Specifically, the second robotic arm is first controlled to exit the zero-stress adaptive control mode and restore phase-locked synchronous control. The system employs a control mode based on locked global coordinate system parameters. It precisely matches the micro-oscillation frequency and phase of the high-voltage terminal under test, using synchronized micro-amplitude following movements to drive the high-voltage test line of the high-voltage testing equipment to complete a smooth, impact-free withdrawal operation. Throughout the process, the force sensor at the end of the second robotic arm monitors the pulling force in real time, preventing mechanical damage to the high-voltage terminal and related equipment caused by forceful pulling. After the high-voltage test line is completely withdrawn, a non-contact potential sensing device confirms the absence of arc risk. The second robotic arm is then controlled to smoothly retract along a preset collision-free safety path to its safe stopping position inside the work bucket, completing the automatic locking of each joint of the second robotic arm. Simultaneously, the cable return device is controlled to retract the high-voltage test line, ultimately generating a second robotic arm reset and locking completion signal. Upon receiving the reset and lock completion signal from the second robotic arm, the platform drives the first robotic arm to perform the grounding wire removal and reset operation. The first robotic arm is controlled to smoothly and slowly release the grounding clamp, completing a non-pulling and non-damaging separation from the grounding terminal within the transformer verification area. The clamping force and separation status are monitored throughout the process. After confirming complete removal of the grounding wire, the first robotic arm is controlled to retract along a preset collision-free safety path to its safe stopping position inside the work bucket. Automatic locking of all joints of the first robotic arm is completed, and the grounding wire is simultaneously retracted. Finally, a first robotic arm reset and lock completion signal is generated. Subsequently, a final verification of the four core safety states—high-voltage source zero-return state, residual charge discharge state, dual robotic arm reset and lock state, and hydraulic outrigger retraction state—is conducted. Once all states meet the standards, the platform integrates the operational data, safety monitoring data, and verification result data from the entire verification process, and officially outputs a transformer verification completion signal, marking the complete safety closed-loop completion of this on-site verification operation for ultra-high voltage and extra-high voltage transformers.

[0091] This application also provides a machine-readable storage medium storing instructions for causing a machine to execute a field verification method for current transformers based on an intelligent inspection vehicle, according to any one of the above embodiments.

[0092] This application also provides an embodiment of a field calibration system for instrument transformers based on an intelligent testing vehicle, including: The memory is configured to store instructions; and The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the on-site verification method for current transformers based on an intelligent inspection vehicle, according to any of the above.

[0093] The processor can be a central processing unit (CPU). Of course, depending on the actual use, it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it.

[0094] The memory can be an internal storage unit of a computer device, such as a hard disk or RAM, or an external storage device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) provided on the computer device. Furthermore, the memory can be a combination of internal storage units and external storage devices of a computer device. The memory is used to store computer programs and other programs and data required by the computer device. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0095] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0100] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0101] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0102] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0103] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for on-site verification of instrument transformers based on an intelligent inspection vehicle, characterized in that, Applied to an intelligent inspection vehicle, the intelligent inspection vehicle is equipped with a first robotic arm and a second robotic arm, the method includes the following steps: Obtain substation information for the target substation and vehicle information for the intelligent inspection vehicle; When the intelligent testing vehicle enters the mutual inductance verification area of ​​the target substation according to the preset on-site verification path, the target working posture is planned for the intelligent testing vehicle based on the substation information. When the intelligent inspection vehicle stops at the target working position, the grounding circuit verification of the mutual inductance verification area is completed by the first robotic arm. If the grounding loop of the mutual inductance verification area passes the verification, the terminal electric field signal in the vicinity of the high voltage terminal of the mutual inductor under test and the robotic arm posture data of the second robotic arm are collected in real time by multiple types of sensors preset in the intelligent inspection vehicle. The insertion control parameters of the intelligent inspection vehicle are calculated based on the terminal electric field signal and the inspection vehicle information. The insertion control parameters and the position data of the robotic arm are combined and the second robotic arm is used to complete the docking and insertion steps of the current transformer under test. After the docking and insertion steps are completed, the intelligent testing vehicle performs the pressure discharge verification of the instrument transformer under test, and generates an instrument transformer verification report based on the pressure discharge verification results.

2. The method according to claim 1, characterized in that, The substation information includes substation map information and substation equipment information. The step of planning the target operating position for the intelligent inspection vehicle based on the substation information includes the following steps: Multi-angle magnetic field signals in the mutual inductance verification area are collected by multiple sensors pre-installed in the chassis of the intelligent inspection vehicle. Complete the gradient vector calculation of the multi-angle magnetic field signal in the region, and determine the relative positional relationship between the intelligent detection vehicle and the grounding down conductor in the mutual inductance verification area based on the gradient vector calculation results; The intelligent inspection vehicle's pose calibration is completed based on the relative positional relationship, and the inspection base point of the intelligent inspection vehicle is output based on the pose calibration result; Centered on the detection base point, several candidate working positions are planned for the intelligent detection vehicle based on the substation map information; By combining substation map information and substation equipment information, determine the electrical information of all live equipment and the obstacle range parameters of all obstacle areas within the mutual inductance verification area; Based on the electrical information of the equipment, an obstacle avoidance envelope area is planned for all energized equipment, and the target working pose is selected from all candidate working poses using the obstacle avoidance envelope area and obstacle range parameters as constraints.

3. The method according to claim 1, characterized in that, The grounding loop verification of the mutual inductance verification area via the first robotic arm includes the following steps: The first robotic arm injects a current conduction test signal into the grounding terminal of the mutual inductance verification area, and the primary circuit verification of the grounding terminal is completed using the current conduction test signal. If the primary circuit of the grounding terminal passes the test, the grounding resistance value of the grounding terminal is measured using the constant current method. Calculate the average resistance and resistance fluctuation of the grounding terminal based on the grounding resistance value; If the average resistance is less than or equal to the preset average threshold and the resistance fluctuation is less than or equal to the preset fluctuation threshold, then the mutual inductance verification area is determined to have passed the grounding loop verification. If the average resistance value is greater than the preset average threshold, or the resistance fluctuation value is greater than the preset fluctuation threshold, then the mutual inductance verification area is determined to have failed the grounding loop verification.

4. The method according to claim 1, characterized in that, The calculation of the intelligent testing vehicle's insertion control parameters based on the terminal electric field signal and testing vehicle information includes the following steps: Acquire terminal image information of the high-voltage terminal to be inspected; Based on the terminal image information and using a feature matching algorithm, the insertion position parameters are located. Combining the insertion position parameters and the detection vehicle information, a terminal insertion path is planned for the second robotic arm. Based on the terminal insertion path, motion control parameters for the second robotic arm are generated. The frequency domain conversion of the terminal electric field signal is completed using the fast Fourier function to obtain the electric field frequency domain signal; The terminal signal features of the electric field frequency domain signal are extracted, and a terminal signal feature sequence is constructed based on the terminal signal features. The terminal signal features include signal frequency features, signal phase features, and signal amplitude features. The threshold method is used to verify the volatility of the terminal signal feature sequence, and the stable terminal feature sequence is extracted from the terminal signal feature sequence based on the volatility verification result. The feedforward control parameters of the second robotic arm are calculated based on the terminal stability characteristic sequence. The feedforward control parameters include the end effector motion period, end effector initial phase, and end effector motion vector of the second robotic arm. The motion control parameters and feedforward control parameters are spatiotemporally fused to obtain the plug-in control parameters of the intelligent inspection vehicle.

5. The method according to claim 4, characterized in that, The step of combining the insertion control parameters and the robotic arm pose data, and using the second robotic arm to complete the docking and insertion of the current transformer under test, includes the following steps: The six-dimensional force sensor pre-installed on the second robotic arm is calibrated at its no-load zero point to obtain the no-load zero point reference value of the six-dimensional force sensor. When the second robotic arm grips the high-voltage experimental equipment of the target substation, it collects six-dimensional force data through a six-dimensional force sensor, and combines the six-dimensional force data with the no-load zero-point reference value to complete the load zero-point correction of the six-dimensional force sensor and obtain the load zero-point reference value. The initial load parameters of the second robotic arm are collected in real time by a six-dimensional force sensor, and the initial load parameters are corrected in real time using the zero-point reference value under load, so as to obtain the real-time load parameters of the second robotic arm. By combining the pose data of the robotic arm and the real-time load parameters, and using the rigid body dynamics model, the self-weight load parameters of the high-pressure experimental equipment are calculated, and the gravity feedforward compensation parameters of the second robotic arm are calculated based on the self-weight load parameters. The plug-in control parameters are corrected in real time based on the gravity feedforward compensation parameters; The second robotic arm completes the docking and insertion between the high-voltage test equipment and the transformer under test according to the real-time corrected insertion control parameters, and outputs a docking completion signal.

6. The method according to claim 5, characterized in that, After completing the docking insertion step, the method further includes the following steps: When the insertion completion signal of the docking step is received, the mechanical load data between the high voltage test equipment and the transformer under test is collected by the six-dimensional force sensor. The constant load component in the mechanical load data is extracted using a preset sliding window; The environmental interference frequency band is determined based on the wind speed and direction parameters of the target substation obtained in advance. Perform Fourier transform on the mechanical load data, and extract the fluctuating load component from the mechanical load data after Fourier transform based on the environmental interference frequency band. By combining constant load components and fluctuating load components, the reaction load component in the mechanical load data is selected. The contact interface between the high-voltage test equipment and the transformer under test is defined as a virtual support point, and a three-dimensional equivalent coordinate system is constructed with the virtual support point as the origin. The constant load component and the fluctuating load component are mapped to a three-dimensional equivalent coordinate system to calculate the three-dimensional load cancellation value; Using the reaction load component as a constraint, the interference compensation parameters of the second robotic arm are calculated based on the three-dimensional load cancellation value.

7. The method according to claim 1, characterized in that, The process of performing pressurized discharge verification of the instrument transformer under test using an intelligent testing vehicle, and generating an instrument transformer verification report based on the pressurized discharge verification results, includes the following steps: The intelligent testing vehicle performs a step-by-step voltage boost on the transformer under test and collects the transformer voltage boosting parameters in real time until the transformer voltage reaches the preset voltage threshold, at which point the transformer under test is determined to have entered the transformer withstand voltage stage. When the current transformer under test enters the current transformer withstand voltage stage, the current transformer withstand voltage parameters of the current transformer under test are collected in real time. When the withstand voltage stage of the current transformer lasts longer than the preset time threshold, the current transformer under test is stepped down in a stepwise manner through the intelligent testing vehicle, and the current transformer voltage reduction parameters of the current transformer under test are collected in real time. The transformer step-up parameters, transformer withstand voltage parameters, and transformer step-down parameters are compared and verified against the corresponding preset thresholds for compliance. Based on the compliance comparison and verification results, a transformer verification report for the transformer under test is generated.

8. The method according to claim 1, characterized in that, The method further includes the following steps: The intelligent testing vehicle completes the zero-return verification of the high-voltage source of the high-voltage experimental equipment in the mutual inductance verification area. If the high-voltage source returns to zero and passes the verification, the residual potential data of the high-voltage test equipment and the high-voltage terminal under test are collected in real time by the second robotic arm. Real-time potential verification of residual potential data is performed using a pre-acquired residual voltage safety threshold. If the residual potential data passes the real-time potential verification, the second robotic arm and the first robotic arm will sequentially complete the robotic arm reset and locking steps, and output the current transformer verification completion signal.

9. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the on-site verification method for current transformers based on an intelligent inspection vehicle according to any one of claims 1 to 8.

10. A field verification system for instrument transformers based on an intelligent testing vehicle, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the on-site verification method for current transformers based on any one of claims 1 to 8.

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