A tool for measuring and inspecting the opening and closing operating force of disconnecting switches

Abstract

This invention discloses a tool for measuring and maintaining the operating force of a disconnecting switch, used to achieve intelligent control and fault diagnosis of the disconnecting switch's opening and closing. The tool includes a hardware unit, a control unit, and a service unit. The hardware unit drives the disconnecting switch to complete opening or closing actions according to instructions from the control unit, collects torque and angle data during the opening and closing process in real time, and feeds it back to the control unit. The control unit controls the working status of the hardware unit in real time, records and displays torque-angle curve data, and judges and outputs the expected fault mode obtained from the current diagnosis. The service unit judges and outputs the best expected fault mode obtained from the current diagnosis, predicts and manages the mechanical life of the disconnecting switch, allowing a digital twin to simulate the motion state and stress conditions of the physical disconnecting switch in real time and synchronously, and feeds the results back to the control unit for display.

Description

Technical Field

[0001] This invention relates to the field of fault detection and diagnosis of disconnecting switch transmission components, and specifically to a tool for measuring and repairing the opening and closing operating force of a disconnecting switch. Background Technology

[0002] The safe and stable operation of the power grid places extremely high demands on the reliability of key equipment. However, two recent incidents of the same type of failure have exposed a significant weakness in the existing operation and maintenance system. Both failures involved disconnecting switches operating with excessive force, exceeding the design load capacity of their operating mechanism motors, ultimately leading to motor overload and burnout, posing a direct threat to the power grid.

[0003] In-depth analysis revealed that the root cause of the fault could be traced back to changes in the state of the mechanical transmission system of the disconnecting switch. Specific reasons included: first, mechanical jamming caused by wear, corrosion, or improper assembly of transmission components; second, the weakening or improperly adjusted parameter of the balance spring, a key component for balancing the operating force; and third, changes in the assembly state of the conductive transmission parts after the equipment underwent a Class A on-site overhaul, leading to a loss of dynamic harmony between the transmission and the operating mechanism, resulting in the actual opening operation power exceeding the mechanism's design output power. The existing fault cases clearly pointed to the third scenario: changes in the mechanical characteristics of the transmission parts after maintenance created a potential overload hazard.

[0004] Currently, the biggest bottleneck in on-site maintenance work lies in the lack of effective quantitative testing methods. For the critical mechanical parameter of opening and closing operating force, maintenance personnel still generally rely on subjective judgment based on manual operation. This qualitative method, lacking data support, is highly subjective and uncertain, unable to accurately determine whether the operating force is within the safe threshold, and even less able to warn of potential overload risks caused by minor changes in mechanical coordination. This makes it difficult to guarantee maintenance quality, allowing equipment with potential faults to be put into operation, thus constituting a hidden weakness in power grid safety. Summary of the Invention

[0005] The purpose of this invention is to provide a tool for measuring and inspecting the opening and closing operating force of disconnecting switches. This tool can collect, record, and display torque-angle curve data of the entire opening and closing process of disconnecting switches in real time and with high precision. It transforms the abstract opening and closing operating force into intuitive and comparable basic data, providing accurate and effective scientific basis for judging the mechanical matching status between the mechanism and the conductive circuit, identifying spring performance degradation, and identifying potential jamming faults.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A tool for measuring and repairing the operating force of a disconnecting switch is used to realize intelligent control and fault diagnosis of the disconnecting switch. The tool includes a hardware unit and a control unit. The hardware unit is used to establish a communication connection with the control unit and drive the disconnecting switch to complete the opening or closing action according to the received control command. At the same time, it collects torque data and angle data during the opening or closing process and transmits the torque data and angle data to the control unit. The control unit includes: An external communication module is used to establish a communication connection with the hardware unit and to enable real-time interaction between the hardware unit and the control unit. The core processing module is used to receive torque data and rotation angle data in real time, convert them into torque-rotation angle curve data, and draw torque-rotation angle curve images based on the obtained torque-rotation angle curve data; The fault diagnosis model processing module is used to extract features and recognize patterns from torque-angle curve data through the fault diagnosis model, and output the expected fault mode of the initial diagnosis and its corresponding confidence information. The touchscreen interaction module is used to input control commands and control the working state of the hardware unit according to the input control commands, and to display the detection results, wherein the detection results include torque data, rotation angle data, torque-rotation angle curve image, expected fault mode of initial diagnosis and its corresponding confidence information.

[0007] Furthermore, the control unit also includes: The basic storage module is used to store torque data, angle data, and torque-angle curve data converted by the core processing module; The stop processing module is used to control the hardware unit to stop operating when it is determined that the currently received torque data exceeds the preset torque threshold.

[0008] Furthermore, it also includes service units, which include: The edge communication module is used to establish a communication connection with the external communication module, acquire the currently collected torque-angle curve data in real time, distribute it to each module in the service unit for analysis, and transmit the output results obtained from the analysis to the touch screen interaction module for display. The machine learning classification model processing module is used to build and pre-train a machine learning classification model. The pre-trained machine learning classification model uses a convolutional neural network to extract features and recognize patterns from the currently collected torque-angle curve data, and outputs the expected fault mode that best matches the currently collected torque-angle curve data and its corresponding confidence information. The regression analysis processing module is used to fit the pre-stored torque-angle curve data of the disconnector switch throughout its entire life cycle into a degradation trajectory sequence using a regression analysis algorithm model. It then compares this sequence with the currently collected torque-angle curve data to determine whether the current opening and closing action will exceed the safety threshold at a future time point or after a certain number of operations, and outputs the expected evaluation results. The motion state synchronization module is used to map the currently collected torque-angle curve data to the digital twin model in real time, synchronously drive the operation of the digital twin model, simulate the motion state of the disconnector switch in the real environment, and output the corresponding motion state data.

[0009] Furthermore, the service unit also includes: The first sample database is used to store torque-angle curve data of disconnect switches under known fault modes. The torque-angle curve data of disconnect switches under known fault modes is used as pre-training data for machine learning classification models. The torque-angle curve data of disconnect switches under known fault modes includes data obtained from laboratory simulations and data collected on-site. The second sample database is used to store torque-angle curve data of disconnecting switches throughout their entire life cycle; The third sample database is used to store the motion state data obtained by the digital twin model when synchronously simulating disconnecting switches.

[0010] Furthermore, the hardware unit includes: An electric drive mechanism, the output end of which is connected to a disconnecting switch and is used to drive the disconnecting switch to complete the opening or closing action; A measuring mechanism used to collect torque and angle data at the output of the electric drive mechanism; The edge control module is connected to the electric drive mechanism and the measuring mechanism, and establishes a communication connection with the control unit. It is used to collect the corresponding torque data and angle data, and transmit the torque data and angle data to the control unit. At the same time, it controls the electric drive mechanism according to the received control commands.

[0011] Furthermore, the electric drive mechanism includes a high-torque motor, an output connector, and a wireless motor drive module. The output end of the high-torque motor is connected to an isolating switch via the output connector. The wireless motor drive module is communicatively connected to the edge control module and is used to control the working state of the high-torque motor.

[0012] Furthermore, the measuring mechanism includes a gearbox and a torque sensor and an angle sensor that are communicatively connected to the edge control module. The gearbox includes a power input shaft and a first power output shaft and a second power output shaft that rotate synchronously with the power input shaft via a gear set. The power input shaft is connected to the output end of a high-torque motor. The first power output shaft is connected to an output connector via a torque sensor. The angle sensor is connected to the second power output shaft.

[0013] Furthermore, a quick-release connector is provided between the output connector and the torque sensor to allow for detachable connection between the two. The quick-release connector includes a drive shaft, a flange, a limiting ball, a sleeve, and a spring. One end of the drive shaft is connected to the torque sensor via the flange, and the other end of the drive shaft has a slot for inserting the output connector. The inner side of the slot has at least two radially symmetrical positioning holes, which are configured as a trumpet-shaped structure that gradually narrows from the outside to the inside. At least two limiting balls are provided and are correspondingly arranged in the positioning holes. The outer circumferential surface of the drive shaft has a first retaining ring. The sleeve is fitted over the outside of the drive shaft, and the inner circumferential surface of the sleeve has a second retaining ring. The spring is fitted over the drive shaft and springs between the first and second retaining rings. The side of the output connector has at least two slots. Under normal conditions, the second retaining ring abuts against one side of the limiting ball, and the other side of the limiting ball passes through the positioning hole and engages with the slot.

[0014] Furthermore, the hardware unit also includes a protective housing, in which the power drive mechanism and the measuring mechanism are encapsulated, and the outer surface of the protective housing has an opening that allows the output connector to extend outward.

[0015] Furthermore, the hardware unit also includes a battery pack mechanism, which is encapsulated in a protective housing and used to power the electric drive mechanism and the measuring mechanism. The outer surface of the protective housing is provided with a charging interface electrically connected to the battery pack mechanism, and the outer surface of the protective housing is provided with a switch assembly for controlling the power supply or power cut-off of the battery pack mechanism.

[0016] Furthermore, the hardware unit also includes multiple fixing fixtures, which include a fixed gripper, a movable gripper, a screw, a handle, and a bolt. The fixed gripper is mounted on the outer surface of the protective housing by bolts. The fixed gripper and the movable gripper are threaded together by the screw. The handle is threaded to the end of the screw.

[0017] Furthermore, the control unit is a handheld terminal, and the tool also includes a storage box. The upper surface of the storage box is provided with a first groove for placing a protective shell, a second groove for placing a handheld terminal, a third groove for placing an output connector, and a fourth groove for placing a fixing fixture.

[0018] The beneficial effects of this invention are: 1. The control unit of this tool can realize intelligent control of the hardware unit, enabling it to automatically complete the opening or closing action of the disconnecting switch. At the same time, the operator can obtain the torque and angle data of the current opening and closing action through the control unit. The relevant data is displayed in the form of torque-angle curve graph, which allows for quick understanding of the current health status of the disconnecting switch, timely maintenance and handling, and effectively prevents the potential overload risk caused by excessive manual opening and closing force leading to slight changes in mechanical coordination. This ensures the quality of disconnecting switch opening and closing operations and maintenance.

[0019] 2. During the opening and closing of the disconnecting switch, if the torque is too large and exceeds the preset torque threshold due to mechanical jamming of the disconnecting switch, improper adjustment of the balance spring, or mismatch of dynamic coordination with the operating mechanism, the control unit will directly stop the opening and closing operation of the electric drive mechanism to ensure that the components of the disconnecting switch are not damaged, and to avoid changes in the mechanical characteristics of the transmission parts and the creation of potential faults.

[0020] 3. This tool has an intelligent fault diagnosis function for disconnecting switches. It combines the torque-angle curve data collected in real time during the opening and closing of the disconnecting switch with the fault diagnosis model and machine learning classification model built based on machine learning. It can automatically identify and locate specific fault modes, such as mechanical jamming, weak balance spring, and wear of transmission components, and provide corresponding confidence information. This provides accurate and effective scientific basis for fault diagnosis of disconnecting switches, so that operators can quickly develop targeted on-site maintenance plans.

[0021] 4. This tool can predict and manage the mechanical life of disconnect switches. Based on the stored full life cycle data of disconnect switches, it can construct a degradation trajectory sequence of the mechanical performance of disconnect switches, realize the prediction of the remaining service life of disconnect switches and the trend assessment of their health status, thereby promoting the transformation of operation and maintenance strategies from preventive maintenance to predictive maintenance.

[0022] 5. This tool features a digital twin model for disconnector operation and maintenance. During the opening and closing of the disconnector, the real-time collected torque-angle curve data stream is mapped to the digital twin model, synchronously driving the digital twin model to run. This allows the digital twin to simulate the motion state and stress conditions of the physical disconnector in real time and synchronously, and provides real-time feedback to the operator through the control unit. When a fault occurs in the disconnector, the tool can replay the complete operation process so that the operator can formulate the optimal on-site maintenance plan.

[0023] 6. When faced with different types of disconnect switches in the same substation, this tool can be freely disassembled and replaced with suitable output connectors, effectively improving the operation efficiency and maintenance efficiency of disconnect switch opening and closing.

[0024] 7. The maintenance tool provided by this invention has a small and lightweight structure, which can be uniformly stored in a storage box and placed in an isolated and safe manner. It is convenient for operators to carry and transport, and can quickly perform the operation of opening and closing the disconnecting switch and maintenance work after arriving at the site, which significantly improves work efficiency and reduces labor intensity. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the physical structure of an embodiment of the present invention.

[0026] Figure 2 This is a three-dimensional exploded view of the hardware unit in an embodiment of the present invention.

[0027] Figure 3 This is a structural block diagram showing the communication connection between the hardware unit, control unit, and service unit in this embodiment of the invention.

[0028] Figure 4 yes Figure 1 Enlarged diagram of point A in the middle.

[0029] Figure 5 This is a schematic diagram illustrating the application of the storage box in an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0031] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0032] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized. Example 1

[0033] like Figure 1 , Figure 2 , Figure 3 As shown, a tool for measuring and repairing the operating force of a disconnecting switch is used to realize intelligent control and fault diagnosis of the disconnecting switch. The tool includes a hardware unit 11 and a control unit 3. The hardware unit 11 includes: Electric drive mechanism 1, the output end of which is connected to the disconnecting switch and is used to drive the disconnecting switch to complete the opening or closing action; Measuring mechanism 2 is used to collect torque and rotation data at the output end of the electric drive mechanism; The edge control module 12 is connected to the electric drive mechanism 1 and the measuring mechanism 2, and establishes a communication connection with the control unit 3. It is used to collect the corresponding torque data and rotation angle data, and transmit the torque data and rotation angle data to the control unit 3. At the same time, it controls the electric drive mechanism 1 according to the received control commands. The control unit 3 includes: The external communication module 301 is used to establish a communication connection with the edge control module 12 and realize real-time interaction between the hardware unit 11 and the control unit 3. The core processing module 302 is used to receive torque data and rotation angle data in real time, convert them into torque-rotation angle curve data, and draw torque-rotation angle curve images based on the obtained torque-rotation angle curve data; The fault diagnosis model processing module 303 is used to perform feature extraction and pattern recognition on the torque-angle curve data through the fault diagnosis model, and output the expected fault mode of the initial diagnosis and its corresponding confidence information. The basic data storage module 304 is used to store torque data, rotation angle data, and torque-rotation angle curve data converted by the core processing module 302; The braking processing module 305 is used to control the hardware unit to stop operating when it is determined that the currently received torque data exceeds a preset torque threshold. The touchscreen interaction module 306 is used to input control commands and control the working state of the hardware unit according to the input control commands, and to display the detection results, wherein the detection results include torque data, rotation angle data, torque-rotation angle curve image, expected fault mode of initial diagnosis and its corresponding confidence information.

[0034] The electric drive mechanism 1 includes a high-torque motor 101, an output connector 102, and a wireless motor drive module 103. The output end of the high-torque motor 101 is connected to a disconnect switch through the output connector 102. The wireless motor drive module 103 is communicatively connected to the edge control module 12 and is used to control the working state of the high-torque motor 101.

[0035] The measuring mechanism 2 includes a gearbox 201 and a torque sensor 202 and an angle sensor 203 that are communicatively connected to the edge control module 12. The gearbox 201 includes a power input shaft 201a and a first power output shaft 201b and a second power output shaft 201c that rotate synchronously with the power input shaft 201a via a gear set. The power input shaft 201a is connected to the output end of the high-torque motor 101. The first power output shaft 201b is connected to the output connector 102 via the torque sensor 202. The angle sensor 203 is connected to the second power output shaft 201c.

[0036] It should be noted that during on-site operations, operators can input control commands based on torque values ​​through the touchscreen interaction module 306, causing the output of the electric drive mechanism 1 to drive the disconnector switch to open or close using that torque value. Operators can obtain torque and angle data of the current opening and closing actions or historical records through the touchscreen interaction module 306, and display them through the torque-angle curve image. This facilitates understanding the health status of the disconnector switch, timely maintenance, and effectively prevents potential overload risks caused by excessive manual opening and closing force leading to slight changes in mechanical coordination, thus ensuring the quality of disconnector switch opening and closing operations and maintenance.

[0037] It is important to understand that the fault diagnosis model processing module 303 has an intelligent fault diagnosis function for disconnecting switches. Based on the torque-angle curve data collected in real time during the opening and closing of the disconnecting switch, it combines the data with a fault diagnosis model built on machine learning. This allows it to automatically identify and locate specific fault modes, such as mechanical jamming, weakened balance springs, and wear of transmission components, and provide corresponding confidence information. This provides accurate and effective scientific basis for fault diagnosis of disconnecting switches, enabling operators to quickly develop targeted on-site maintenance solutions.

[0038] Specifically, the fault diagnosis model is a mathematical model pre-trained based on original fault sample data, and the specific structure of the fault diagnosis model includes: (1) Input layer: It is used to receive the torque-rotation curve data after standardization. If N points are sampled in one complete operation, the input shape is represented as (N,1). (2) Feature extraction layer: It is divided into a first convolutional layer, a first pooling layer, a second convolutional layer, a second pooling layer, a third convolutional layer, and a third pooling layer, wherein: The first convolutional layer uses multiple one-dimensional convolutional kernels to perform sequential scanning on the data obtained from the input layer and extract primary local features. The first pooling layer performs max pooling on primary local features, reducing data dimensionality, enhancing feature invariance, and preserving key features. The configurations of the second convolutional layer and the second pooling layer, as well as the configurations of the third convolutional layer and the third pooling layer, are all functional stacking structures, serving the same purpose as the configurations of the first convolutional layer and the first pooling layer, thereby forming a deep network to gradually extract higher-level and more global features. (3) Classification Decision Layer: It is divided into a flattening layer, a fully connected layer, and a recognition output layer, wherein: The flattening layer flattens the final feature map extracted by the convolutional layer into a one-dimensional vector. The fully connected layer, which can be configured to be one or more, each fully connected layer contains at least 64 neurons, is used to prevent overfitting and to perform nonlinear combination and mapping of high-level features; The identification output layer is used to activate neuron functions related to fault modes. The number of neurons is equal to the number of preset fault mode categories, and the output value of each neuron represents the probability that the input data belongs to the corresponding fault mode.

[0039] Specifically, the pre-training process and input / output application of the fault diagnosis model include the following steps: 1. Training data preparation: The input features come from a database used to store the original fault sample data. Each original fault sample data is a standardized torque value sequence. To ensure that the model focuses on the waveform shape rather than the absolute value, the torque values ​​of each sequence need to be normalized first, and each original fault sample data is labeled with the corresponding fault mode label. 2. Model training process: 2-1. Data partitioning: Divide the labeled dataset into training set, validation set, and test set according to the specified proportions; 2-2 Loss Function and Optimization: The classification cross-entropy loss function is used to measure the difference between the model's predicted probability distribution and the true label. The Adam optimizer is used to minimize the loss function and automatically adjust the model parameters. 2-3. Training loop: Perform batch forward and backward propagation iterations on the training set. After each training round, evaluate the performance using the validation set, monitor the loss and accuracy, and prevent overfitting. 2-3. Model Stabilization: After training is completed, a final evaluation is performed on the test set. Once the performance requirements are met, the final model structure and parameters are stabilized into a model file for deployment in control unit 3. 3. Diagnostic logic in practical application: The real-time torque data and angle data collected in one operation are preprocessed and input into the trained fault diagnosis model. After forward propagation calculation, a probability distribution vector is obtained in the recognition output layer. One or more fault modes with higher probabilities are judged as the diagnosis results of this operation, and the corresponding fault mode and its confidence level (i.e. probability value) are output to the user.

[0040] It should be noted that during the process of the electric drive mechanism 1 driving the disconnector to open and close, if the torque is too large and exceeds the preset torque threshold due to mechanical jamming of the disconnector, improper adjustment of the balance spring, or dynamic mismatch with the operating mechanism, the stop processing module 305 will intervene in the continuous control of the electric drive mechanism 1 based on the currently collected torque data, and stop the opening and closing operation of the electric drive mechanism 1 in time to ensure that the components of the disconnector are not damaged, and also to avoid changes in the mechanical characteristics of the transmission part and the potential for failure.

[0041] The hardware unit 11 also includes a protective housing 6, in which the electric drive mechanism 1 and the measuring mechanism 2 are encapsulated. The outer surface of the protective housing 6 is provided with an opening 601 that allows the output connector 102 to extend outward.

[0042] The hardware unit 11 also includes a battery pack mechanism 7, which is encapsulated in a protective housing 6 and is used to supply power to the electric drive mechanism 1 and the measuring mechanism 2. The outer surface of the protective housing 6 is provided with a charging interface 602 that is electrically connected to the battery pack mechanism 7, and the outer surface of the protective housing 6 is provided with a switch assembly 8 for controlling the power supply or power cut-off of the battery pack mechanism 7.

[0043] The hardware unit 11 also includes multiple fixing fixtures 9, each of which includes a fixed gripper 901, a movable gripper 902, a screw 903, a handle 904, and a bolt 905. The fixed gripper 901 is mounted on the outer surface of the protective housing 6 by the bolt 905. The fixed gripper 901 and the movable gripper 902 are threaded together by the screw 903. The handle 904 is threaded to the end of the screw 903.

[0044] It is important to understand that multiple fixed fixtures 9 can be freely attached and detached from the protective housing 6 via bolts 905. By gripping the handle 904 and rotating the screw 903 through the handle 904, the fixed gripper 901 and the movable gripper 902 can form a clamping or releasing effect, so that the electric drive mechanism 1 and the measuring mechanism 2 can be stably clamped to the bracket of the disconnecting switch through the fixed fixtures 9, thereby enabling the tool to stably drive the disconnecting switch to perform opening and closing actions. Example 2

[0045] like Figure 1 , Figure 5 As shown, the control unit 3 is a handheld terminal, and the tool also includes a storage box 10. The upper surface of the storage box 10 is provided with a first groove 1001 for placing the protective shell 6, a second groove 1002 for placing the handheld terminal, a third groove 1003 for placing the output connector 102, and a fourth groove 1004 for placing the fixing fixture 9.

[0046] It is understandable that the control unit 3 can be a stand-alone handheld terminal or an operating system installed on existing devices such as mobile phones and computers, so that the control unit 3 can remotely communicate and control the hardware unit 11 without the need for operators to be near the work site, thereby improving the safety and stability of the operation.

[0047] It should be noted that the maintenance tool provided by the present invention has a compact and lightweight overall structure, and can be uniformly stored and safely isolated by the storage box 10, making it convenient for operators to carry and transport. After the operators arrive at the site, they can quickly perform the operation of opening and closing the disconnecting switch and maintenance work, effectively improving work efficiency and reducing labor intensity. Example 3

[0048] like Figure 3As shown, the present invention also includes a service unit 4, which includes: Edge communication module 401 is used to establish a communication connection with external communication module 301, acquire the currently collected torque-angle curve data in real time, distribute it to each module in service unit 4 for analysis, and transmit the output results obtained from the analysis to touch screen interaction module 306 for display. The machine learning classification model processing module 402 is used to construct and pre-train a machine learning classification model. The pre-trained machine learning classification model uses a convolutional neural network to extract features and recognize patterns from the currently collected torque-angle curve data, and outputs the expected fault mode that best matches the currently collected torque-angle curve data and its corresponding confidence information. The regression analysis processing module 403 is used to fit the pre-stored torque-angle curve data of the disconnector switch throughout its entire life cycle into a degradation trajectory sequence using a regression analysis algorithm model, and compare it with the currently collected torque-angle curve data to determine whether the current opening and closing action will exceed the safety threshold at a certain time point or after a certain number of operations, and output the expected evaluation result. The motion state synchronization module 404 is used to map the currently collected torque-angle curve data to the digital twin model in real time, synchronously drive the digital twin model to run, simulate the motion state of the disconnector switch in the real environment, and output the corresponding motion state data.

[0049] Furthermore, the service unit also includes: The first sample database 405 is used to store torque-angle curve data of disconnect switches under known fault modes. The torque-angle curve data of disconnect switches under known fault modes is used as pre-training data for machine learning classification models. The torque-angle curve data of disconnect switches under known fault modes includes data obtained from laboratory simulations and data collected on-site. The second sample database 406 is used to store torque-angle curve data of disconnecting switches throughout their entire life cycle; The third sample database 407 is used to store motion state data obtained by the digital twin model when synchronously simulating disconnecting switches.

[0050] It is important to understand that, compared to the fault diagnosis model processing module 303, the machine learning classification model processing module 402 can output relatively better diagnostic results. The pre-trained machine learning classification model uses a convolutional neural network to extract features and recognize patterns from the currently collected torque-angle curve data, thereby predicting the expected fault mode that best matches the current opening and closing operation of the disconnecting switch, so that operators can perform timely maintenance and handling before the disconnecting switch fails.

[0051] Specifically, the machine learning classification model is a mathematical model generated and trained online in service unit 4, and the specific structure of the machine learning classification model includes: (1) Bootstrap sampling layer: Random sampling with replacement is performed on the original training dataset to generate multiple different sub-training sets for training different decision trees, ensuring the diversity of decision trees; (2) Random feature selection layer: When splitting nodes in each decision tree, a feature subset is randomly selected first, and then the optimal split point is selected from the feature subset, which further enhances the difference between decision trees and the generalization ability of random forest. (3) Integrated decision logic layer: When a new collection of data is input and fault diagnosis is required, each decision tree in the random forest will independently give an output result related to the fault mode; (4) Final output layer: Random forest adopts the majority voting rule and takes the fault mode with the most votes as the final diagnosis result of the model. At the same time, the proportion of the number of votes for the fault mode to the total number of trees can be calculated as the confidence level of this fault diagnosis.

[0052] Specifically, the pre-training process and input / output application of machine learning classification models include the following steps: 1. Training Data Preparation: Unlike the original fault sample data used by the fault diagnosis model, the input features of the machine learning classification model are multi-dimensional feature vectors extracted manually or automatically based on torque-angle curve data, including: (1) Statistical characteristics: maximum torque, minimum torque, average torque, torque variance, skewness, kurtosis; (2) Process characteristics: the curve integral of the work done throughout the closing and opening process, the angle position when the maximum torque is reached, and the average torque in a specific angle range; (3) Morphological characteristics: The complexity is measured by the waveform energy characteristics extracted by wavelet transform and the curve. (4) Label features: Fault mode label corresponding to each torque-angle curve feature vector sample; 2. Model training process: 2-1. Feature Standardization: Standardize all extracted features to make their mean 0 and variance 1, in order to eliminate the influence of different units of measurement. 2-2. Parameter Setting and Training: Determine the key hyperparameters of the random forest, including the number of decision trees in the forest, the maximum depth of the trees, and the maximum number of features considered when splitting nodes. Use the prepared labeled feature vector dataset to train the model. The training process is the process of building a large number of decision trees. 2-3. Model Evaluation and Consolidation: Cross-validation is used to evaluate model performance. After training, the entire trained machine learning classification model is serialized into a model file and embedded into service unit 4. The trained machine learning classification model contains the basic structure and split point information of all decision trees. 3. Diagnostic logic in practical application: The real-time torque data and angle data collected in one operation are preprocessed and input into the trained machine learning classification model. After being processed by each decision tree in the random forest, the fault mode with the most votes is taken as the final diagnosis result of the model. At the same time, the proportion of the number of votes for the fault mode to the total number of trees can be calculated as the confidence level of this fault diagnosis.

[0053] Furthermore, the first sample database 405 will actively collect torque-angle curve data related to fault modes obtained through on-site operation of this tool, update and train the machine learning classification model in real time, so that the machine learning classification model can quickly respond to different disconnector switch fault conditions and provide corresponding expected fault modes, providing accurate and effective scientific basis for fault diagnosis of disconnectors. Among them, the real-time updated machine learning classification model classifies the structured feature vectors extracted from the currently collected torque-angle curve data, selects the random forest ensemble learning algorithm to construct multiple decision trees and votes to obtain the best matching expected fault mode, thereby improving the accuracy and stability of prediction.

[0054] It is important to understand that this tool can predict and manage the mechanical lifespan of disconnecting switches. The regression analysis processing module 403 analyzes the pre-stored torque-angle curve data of the disconnecting switch throughout its entire lifespan using a regression analysis algorithm model. It fits the degradation trajectory sequence of this data over time or after a certain number of operations, and compares it with the currently collected torque-angle curve data to determine whether the current opening and closing action will exceed the safety threshold at a future point in time or after a certain number of operations. It outputs the expected assessment results, realizing the prediction of the remaining service life of the disconnecting switch and the trend assessment of its health status, thereby promoting the transformation of operation and maintenance strategies from preventive maintenance to predictive maintenance.

[0055] Specifically, the regression analysis algorithm model has a structure including an autoregressive part, a differencing part, and a moving average part, denoted as ARIMA(p,d,q), where: The autoregressive part describes the relationship between the current value and historical values, that is, it means using the values ​​of the past p time points to regress the current value; The difference part is the difference order d performed to stabilize the non-stationary sequence; The moving average portion describes the relationship between the current error and the historical error, which is expressed as the prediction error of the model considering the past q time points.

[0056] Specifically, the pre-training process and input / output application of regression analysis algorithm models include the following steps: 1. Parameter order determination: By analyzing the autocorrelation and partial autocorrelation plots of the differencing sequence, the range of values ​​for p and q is initially determined. The information criterion is commonly used to perform a grid search in the candidate parameter combination, and the (p,d,q) that minimizes the criterion is selected as the optimal model order. 2. Parameter estimation: For a given (p,d,q), use the maximum likelihood estimation method or the least squares method to calculate all coefficients of the AR and MA parts based on historical data; 3. Model Validation: Backtest the trained model with historical data to check whether the prediction error is a white noise sequence, in order to determine whether the model can extract information sufficiently. If it is determined that the model can extract information sufficiently, the pre-training process of the regression analysis algorithm model is completed, and it is solidified into a model file for deployment in service unit 4. 4. Diagnostic logic in practical applications: The trained regression analysis algorithm model becomes a prediction function. The latest historical data is input, namely the torque-angle curve data of the disconnect switch throughout its entire life cycle. It is fitted into a degradation trajectory sequence. Then, newly collected data is continuously added to the degradation trajectory sequence to establish data comparison and continuously update the model. The model outputs the maximum torque prediction value for multiple future operations or a future point in time, realizing dynamic prediction and evaluation.

[0057] It is important to understand that the motion state synchronization module 404 has a digital twin model for the operation and maintenance of disconnecting switches. During the process of driving the disconnecting switch to open or close, the real-time collected torque-angle curve data stream is mapped to the digital twin model, and the digital twin model is driven to run synchronously. This allows the digital twin to simulate the motion state and force conditions of the physical disconnecting switch in real time and synchronously, and provide real-time feedback to the operator through the touch screen interaction module 306. The third sample database 407 synchronously stores the corresponding simulated motion state data. When a fault occurs in the disconnecting switch, the complete operation process of this tool can be replayed so that the operator can formulate the optimal on-site maintenance plan. Example 4

[0058] like Figure 2 , Figure 4As shown, a quick-release connector 5 is provided between the output connector 102 and the torque sensor 202 to allow for detachable connection between the two. The quick-release connector 5 includes a drive shaft 501, a flange 502, a limiting ball 503, a sleeve 504, and a spring 505. One end of the drive shaft 501 is connected to the torque sensor 202 via the flange 502, and the other end of the drive shaft 501 has a slot 506 for the output connector 102 to be inserted. The inner surface of the slot 506 has at least two radially symmetrical positioning holes 507. The positioning holes 507 are configured as a trumpet-shaped structure that gradually narrows from the outside to the inside. The limiting ball 504... At least two beads 503 are provided and are arranged in a one-to-one correspondence within the positioning hole 507. The outer circumferential surface of the drive shaft 501 is provided with a first retaining ring 508. The sleeve 504 is sleeved on the outside of the drive shaft 501. The inner circumferential surface of the sleeve 504 is provided with a second retaining ring 509. The spring 505 is sleeved on the drive shaft 501 and springs between the first retaining ring 508 and the second retaining ring 509. The side of the output connector 102 is provided with at least two slots 510. Under normal conditions, the second retaining ring 509 abuts against one side of the limiting ball 503. The other side of the limiting ball 503 passes through the positioning hole 507 and engages with the slot 510.

[0059] It should be noted that, when dealing with different types of disconnecting switches within the same substation, this tool can freely disassemble and replace the appropriate output connector 102 using the quick-release connector 5, effectively improving the operational and maintenance efficiency of the disconnecting switch opening and closing. When it is necessary to disassemble the output connector 102, simply move the sleeve 504 away from the output connector 102. The second retaining ring 509 will no longer abut against the limiting ball 503, and the limiting ball 503 will be movable in the positioning hole 507. At this time, pull the output connector 102 outward, and the limiting ball 503 will be pushed open by the output connector 102 and exit from the slot 510 of the output connector 102. The disassembly of the output connector 102 is completed. When the output connector 102 needs to be installed, simply move the sleeve 504 away from the output connector 102, insert the output connector 102 into the slot 506, and align the slot 510 with the positioning hole 507. Then release the sleeve 504. Under the elastic action of the spring 505, the sleeve 504 returns to its original position. The second retaining ring 509 abuts against one side of the limiting ball 503. The other side of the limiting ball 503 passes through the locking hole and engages with the slot 510, thus completing the installation of the output connector 102. The disassembly, assembly, and replacement of the output connector 102 are simple, convenient, and quick.

[0060] It should be noted that, since the positioning hole 507 is a funnel-shaped structure that gradually narrows from the outside to the inside, when the limiting ball 503 moves towards the slot 506, it will be restricted by the positioning hole 507. When the limiting ball 503 moves towards the sleeve 504, it will be blocked by the sleeve wall of the sleeve 504, ensuring that the limiting ball 503 will not disengage from the positioning hole 507. Under the elastic action of the spring 505, the second retaining ring 509 and the limiting ball 503 will abut against each other, and the two will cooperate to form a snap-fit, ensuring that the sleeve 504 will not disengage from the drive shaft 501.

[0061] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0062] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0063] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented 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.

[0064] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and 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 terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0065] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate 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 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal 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.

[0067] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0068] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A tool for measuring and inspecting the opening and closing operating force of a disconnecting switch, characterized in that, The tool used to achieve intelligent control and fault diagnosis of the opening and closing of disconnecting switches includes a hardware unit and a control unit. The hardware unit is used to establish a communication connection with the control unit and drive the disconnecting switch to complete the opening or closing action according to the received control command. At the same time, it collects torque data and angle data during the opening or closing process and transmits the torque data and angle data to the control unit. The control unit includes: An external communication module is used to establish a communication connection with the hardware unit and to enable real-time interaction between the hardware unit and the control unit. The core processing module is used to receive torque data and rotation angle data in real time, convert them into torque-rotation angle curve data, and draw torque-rotation angle curve images based on the obtained torque-rotation angle curve data; The fault diagnosis model processing module is used to extract features and recognize patterns from torque-angle curve data through the fault diagnosis model, and output the expected fault mode of the initial diagnosis and its corresponding confidence information. The touchscreen interaction module is used to input control commands and control the working state of the hardware unit according to the input control commands, and to display the detection results, wherein the detection results include torque data, rotation angle data, torque-rotation angle curve image, expected fault mode of initial diagnosis and its corresponding confidence information.

2. The disconnecting switch opening and closing operation force measuring and maintenance tool according to claim 1, characterized in that, The control unit also includes: The basic storage module is used to store torque data, angle data, and torque-angle curve data converted by the core processing module; The stop processing module is used to control the hardware unit to stop operating when it is determined that the currently received torque data exceeds the preset torque threshold.

3. The disconnecting switch opening and closing operating force measuring and maintenance tool according to claim 1 or 2, characterized in that, It also includes service units, which include: The edge communication module is used to establish a communication connection with the external communication module, acquire the currently collected torque-angle curve data in real time, distribute it to each module in the service unit for analysis, and transmit the output results obtained from the analysis to the touch screen interaction module for display. The machine learning classification model processing module is used to build and pre-train a machine learning classification model. The pre-trained machine learning classification model uses a convolutional neural network to extract features and recognize patterns from the currently collected torque-angle curve data, and outputs the expected fault mode that best matches the currently collected torque-angle curve data and its corresponding confidence information. The regression analysis processing module is used to fit the pre-stored torque-angle curve data of the disconnector switch throughout its entire life cycle into a degradation trajectory sequence using a regression analysis algorithm model. It then compares this sequence with the currently collected torque-angle curve data to determine whether the current opening and closing action will exceed the safety threshold at a future time point or after a certain number of operations, and outputs the expected evaluation results. The motion state synchronization module is used to map the currently collected torque-angle curve data to the digital twin model in real time, synchronously drive the operation of the digital twin model, simulate the motion state of the disconnector switch in the real environment, and output the corresponding motion state data.

4. The tool for measuring and repairing the opening and closing operating force of a disconnecting switch according to claim 3, characterized in that, The service unit also includes: The first sample database is used to store torque-angle curve data of disconnect switches under known fault modes. The torque-angle curve data of disconnect switches under known fault modes is used as pre-training data for machine learning classification models. The torque-angle curve data of disconnect switches under known fault modes includes data obtained from laboratory simulations and data collected on-site. The second sample database is used to store torque-angle curve data of disconnecting switches throughout their entire life cycle; The third sample database is used to store the motion state data obtained by the digital twin model when synchronously simulating disconnecting switches.

5. The tool for measuring and repairing the opening and closing operating force of a disconnecting switch according to claim 1, characterized in that, The hardware unit includes: An electric drive mechanism, the output end of which is connected to a disconnecting switch and is used to drive the disconnecting switch to complete the opening or closing action; A measuring mechanism used to collect torque and rotation data at the output of the electric drive mechanism; The edge control module is connected to the electric drive mechanism and the measuring mechanism, and establishes a communication connection with the control unit. It is used to collect the corresponding torque data and angle data, and transmit the torque data and angle data to the control unit. At the same time, it controls the electric drive mechanism according to the received control commands.

6. The tool for measuring and repairing the opening and closing operating force of a disconnecting switch according to claim 5, characterized in that, The electric drive mechanism includes a high-torque motor, an output connector, and a wireless motor drive module. The output end of the high-torque motor is connected to a disconnect switch through the output connector. The wireless motor drive module is communicatively connected to the edge control module and is used to control the working state of the high-torque motor.

7. The tool for measuring and inspecting the opening and closing operating force of a disconnecting switch according to claim 6, characterized in that, The measuring mechanism includes a gearbox and a torque sensor and an angle sensor that are communicatively connected to the edge control module. The gearbox includes a power input shaft and a first power output shaft and a second power output shaft that rotate synchronously with the power input shaft via a gear set. The power input shaft is connected to the output end of a high-torque motor. The first power output shaft is connected to an output connector via a torque sensor. The angle sensor is connected to the second power output shaft.

8. The disconnecting switch opening and closing operation force measuring and maintenance tool according to claim 6, characterized in that, The output connector and the torque sensor are provided with a quick-release connector for detachable connection. The quick-release connector includes a drive shaft, a flange, a limiting ball, a sleeve, and a spring. One end of the drive shaft is connected to the torque sensor via the flange, and the other end of the drive shaft has a slot for the output connector to be inserted. The inner side of the slot has at least two radially symmetrical positioning holes, which are flared structures that gradually narrow from the outside to the inside. At least two limiting balls are provided and are correspondingly arranged in the positioning holes. The outer circumferential surface of the drive shaft has a first retaining ring. The sleeve is fitted over the outside of the drive shaft, and the inner circumferential surface of the sleeve has a second retaining ring. The spring is fitted over the drive shaft and springs between the first and second retaining rings. The side of the output connector has at least two slots. Under normal conditions, the second retaining ring abuts against one side of the limiting ball, and the other side of the limiting ball passes through the positioning hole and engages with the slot.

9. The disconnecting switch opening and closing operating force measuring and maintenance tool according to claim 6, 7 or 8, characterized in that, The hardware unit also includes a protective housing, in which the electric drive mechanism and the measuring mechanism are encapsulated. The outer surface of the protective housing has an opening that allows the output connector to extend outward.

10. The disconnecting switch opening and closing operating force measuring and maintenance tool according to claim 9, characterized in that, The hardware unit also includes a battery pack mechanism, which is encapsulated in a protective housing and is used to power the electric drive mechanism and the measuring mechanism. The outer surface of the protective housing is provided with a charging interface that is electrically connected to the battery pack mechanism, and the outer surface of the protective housing is provided with a switch assembly for controlling the power supply or power off of the battery pack mechanism.

11. The disconnecting switch opening and closing operation force measuring and maintenance tool according to claim 9, characterized in that, The hardware unit also includes multiple fixtures, which include a fixed gripper, a movable gripper, a screw, a handle, and a bolt. The fixed gripper is bolted to the outer surface of the protective housing. The fixed gripper and the movable gripper are threaded together by the screw. The handle is threaded to the end of the screw.

12. The disconnecting switch opening and closing operation force measuring and maintenance tool according to claim 11, characterized in that, The control unit is a handheld terminal, and the tool also includes a storage box. The upper surface of the storage box is provided with a first groove for placing a protective shell, a second groove for placing a handheld terminal, a third groove for placing an output connector, and a fourth groove for placing a fixing fixture.

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