Substation-oriented anchor point timestamp calibration method and related device

Abstract

The application provides a substation-oriented anchor point timestamp calibration method and related device, which is applied to a collection terminal in a substation monitoring system, the substation monitoring system further comprises a master clock and a sensor in communication connection with the collection terminal, and the method comprises the following steps: determining a drift parameter of a local crystal oscillator of the collection terminal according to a clock offset sequence between the collection terminal and the master clock in a plurality of continuous synchronization periods; correcting a sampling counter in the collection terminal by using the drift parameter; if a transient partial discharge signal is detected according to a data frame sequence collected by the sensor on a target metal pipeline in the substation, a dynamic anchor point is established at a triggering moment of the transient partial discharge signal; and based on the dynamic anchor point, the generated sampling count sequence after correction and a time reference of the collection terminal, a data frame related to the transient partial discharge signal in the data frame sequence is timestamped. The accuracy of timestamping is improved.

Description

Technical Field

[0001] This application relates to the field of substation technology, and in particular to a method and related apparatus for anchor point timestamp calibration in substations. Background Technology

[0002] Traditional substations have high-voltage lines and switches exposed in the open, occupying a large area and easily affected by wind, rain, and bird activity. In order to save space and improve safety, modern substations pack high-voltage equipment such as circuit breakers, disconnecting switches, and grounding switches into an extremely robust, sealed aluminum alloy metal pipe (Gas Insulated Switchgear, GIS), and the pipe is filled with a gas with excellent insulating properties.

[0003] Because high-voltage equipment is completely enclosed in thick metal tubes, the insulation inside is not visible to the naked eye. If the insulation ages and a tiny lightning bolt (partial discharge) occurs, it will generate extremely weak high-frequency electromagnetic waves inside the metal tube. The current fault location method involves attaching sensors to the outside of the metal tube to collect these electromagnetic waves. Because electromagnetic waves propagate extremely fast, calculating their location requires extremely high precision in the timestamp.

[0004] However, in the current architecture of separating the timing and sampling domains of the acquisition terminal, the time stamp binding mechanism of periodic fixed anchor points is generally adopted. This has problems such as the inability to continuously suppress the accumulation of local sampling clock drift and large hardware timestamp matching errors of transient partial discharge signals, which ultimately leads to inaccurate positioning accuracy of partial discharge sources in substation GIS. Summary of the Invention

[0005] In view of this, this application provides an anchor point timestamp calibration method and related apparatus for substations. By using the clock offset sequence between the acquisition terminal and the master clock to determine the drift parameters of the local crystal oscillator in the acquisition terminal, the counter is corrected and a dynamic anchor point is established when a transient partial discharge signal is detected, so that the timestamps bound to the data frames related to the transient signal are more accurate.

[0006] This application provides an anchor point timestamp calibration method for substations, applied to a data acquisition terminal within a substation monitoring system. The substation monitoring system also includes a master clock and sensors communicatively connected to the data acquisition terminal. The method includes the following steps:

[0007] The drift parameters of the local crystal oscillator of the acquisition terminal are determined based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles.

[0008] The drift parameters are used to correct the sampling counter in the acquisition terminal;

[0009] If a transient partial discharge signal is detected based on the data frame sequence collected by the sensor from the target metal pipe in the substation, a dynamic anchor point is established at the triggering time of the transient partial discharge signal.

[0010] Based on the dynamic anchor point, the corrected sampling count sequence, and the time reference of the acquisition terminal, the data frames in the data frame sequence related to the transient partial discharge signal are timestamped.

[0011] In one possible embodiment, the drift parameters include frequency drift rate and time offset. Determining the drift parameters of the local crystal oscillator of the acquisition terminal based on the clock offset sequence between the acquisition terminal and the master clock over several consecutive synchronization cycles includes:

[0012] Construct the system state equation and observation equation with the frequency drift rate and the time deviation as state variables;

[0013] The clock offset sequence is preprocessed to obtain the observation samples;

[0014] Based on the system state equation, the observation equation, and the observation samples, the frequency drift rate and time deviation of the local crystal oscillator are obtained.

[0015] In one possible embodiment, obtaining the frequency drift rate and time deviation of the local crystal oscillator based on the system state equation, the observation equation, and the observation samples includes:

[0016] Initialize the system state vector, state covariance matrix, process noise covariance matrix, and observation noise covariance matrix;

[0017] Based on the unscented transformation rule, a corresponding number of state representation sampling points are selected from the initialized system state vector and state covariance matrix; and the propagation deduction of each of the state representation sampling points is performed through the system state equation.

[0018] Based on the sampling points of each state representation after transmission, the prior estimates and prior covariance matrix of the state variables are calculated.

[0019] Using the observed samples and the observed equation, the Kalman gain is calculated, and the prior estimates of the state variables and the prior covariance matrix are updated to obtain the posterior estimates of the state variables and the posterior covariance matrix, so as to obtain the values ​​of the frequency drift rate and the time deviation.

[0020] In one possible embodiment, the sampling counter in the acquisition terminal is calibrated using the drift parameter, including:

[0021] The frequency drift rate and the time deviation are used as correction parameters to correct the counting parameters of the sampling counter, so as to generate the sampling count sequence based on the corrected counting parameters.

[0022] In one possible embodiment, the counting parameters include a sampling offset and a sampling frequency. The counting parameters of the sampling counter are corrected using the frequency drift rate and the time deviation as correction parameters, including:

[0023] The product of the time deviation and the sampling frequency of the sampling counter is used as the corrected sampling offset.

[0024] The product of the difference between the preset value and the frequency drift rate and the sampling frequency is used as the corrected sampling frequency.

[0025] In one possible embodiment, the method further includes:

[0026] If a synchronization cycle trigger signal is detected, a fixed anchor point is established at the start of the next synchronization cycle. The fixed anchor point is used to represent the correspondence between the time base and the count value at the start time.

[0027] Based on the count value of the data frame corresponding to the fixed anchor point and the time base, the data frame of the fixed anchor point is timestamped.

[0028] In one possible embodiment, the number of data frames corresponding to the transient partial discharge signal is multiple. The step of timestamping the data frames related to the transient partial discharge signal in the data frame sequence based on the dynamic anchor point, the corrected sampling count sequence, and the time reference of the acquisition terminal includes:

[0029] For each of the data frames, perform the following steps:

[0030] Obtain the count difference between the count value of the data frame and the count value at the trigger time;

[0031] The target ratio between the count difference and the corrected sampling frequency in the counter;

[0032] The sum of the target ratio and the timestamp corresponding to the triggering time is used as the timestamp for the data frame.

[0033] In one possible embodiment, after using the sum of the target ratio and the timestamp corresponding to the triggering time as the timestamp for the data frame, the method further includes:

[0034] Obtain the preset transmission delay corresponding to the link between the sensor and the acquisition terminal;

[0035] The timestamps of each data frame are corrected according to the preset transmission delay.

[0036] In one possible embodiment, the number of sensors is at least two, and each sensor acquires at least one data frame corresponding to the transient partial discharge signal in its acquired data frame. The method further includes:

[0037] Select one data frame from the data frames collected by each of the sensors that correspond to the transient partial discharge signal as the target data frame;

[0038] The location of the fault in the target metal pipe is determined based on the time difference between the timestamps marked on the target data frames collected by each of the sensors.

[0039] This application provides an anchor timestamp calibration device for substations, applied to a data acquisition terminal within a substation monitoring system. The substation monitoring system also includes a master clock and sensors communicatively connected to the data acquisition terminal. The anchor timestamp calibration device for substations includes:

[0040] The drift parameter determination unit is used to determine the drift parameters of the local crystal oscillator of the acquisition terminal based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles.

[0041] A correction unit is used to correct the sampling counter in the acquisition terminal using the drift parameters;

[0042] The dynamic anchor point establishment unit is used to establish a dynamic anchor point at the triggering time of the transient partial discharge signal if a transient partial discharge signal is detected based on the data frame sequence collected by the sensor from the target metal pipe in the substation.

[0043] The timestamp calibration unit is used to calibrate the timestamps of the data frames in the data frame sequence that are related to the transient partial discharge signal, based on the dynamic anchor point, the calibrated sampling count sequence, and the time reference of the acquisition terminal.

[0044] This application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps in any of the above-described anchor point timestamp calibration methods for substations.

[0045] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the above-described anchor point timestamp calibration methods for substations.

[0046] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the above-described anchor point timestamp calibration methods for substations.

[0047] In the anchor point timestamp calibration method and related device for substations provided in this application, a high-precision anchor point is dynamically established when a transient partial discharge signal is detected, and the counter is corrected by combining the local crystal oscillator drift parameters. This solves the problems of sampling count drift accumulation and large transient signal timestamp matching error under the fixed anchor point mechanism, and provides a foundation for achieving high-precision partial discharge source positioning. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is one of the flowcharts illustrating a method for anchor point timestamp calibration in substations provided in this application embodiment;

[0050] Figure 2 This is a schematic diagram of the architecture of the substation monitoring system provided in the embodiments of this application;

[0051] Figure 3 This is a second schematic flowchart of an anchor point timestamp calibration method for substations provided in this application embodiment;

[0052] Figure 4 This is a schematic diagram showing the position of the electric shock location relative to the two sensors in an electric shock test provided in this application embodiment;

[0053] Figure 5 This is a schematic diagram showing the location result of the electric shock position provided in an embodiment of this application;

[0054] Figure 6 This is one of the functional unit block diagrams of an anchor point timestamp calibration device for substations provided in the embodiments of this application;

[0055] Figure 7 This is the second functional unit block diagram of an anchor point timestamp calibration device for substations provided in this application embodiment;

[0056] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0058] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0059] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0060] See also Figure 1 , Figure 1 This is one of the flowcharts illustrating an anchor point timestamp calibration method for substations provided in this application embodiment. The anchor point timestamp calibration method for substations is applied to the acquisition terminal 300 within the substation monitoring system. It aims to solve problems such as inaccurate timestamp calibration and drift accumulation in ultra-high-speed sampling of partial discharge (partial discharge) from target metal pipes such as gas-insulated switchgear (GIS) in transparent substation scenarios, under an architecture where the time domain and sampling domain are separated.

[0061] In a specific application scenario, the substation can be a transparent substation, with a precision time synchronization network compliant with the IEEE 1588V2 protocol deployed within it. Currently, intelligent inspection and edge IoT agent coverage of the substation have been completed. All existing online monitoring data of the substation are uniformly aggregated to the equipment channel environment and status perception system through the provincial company's channel. Among them, 10 types of monitoring, including oil chromatography, surge arresters, batteries, main transformer oil temperature / level, iron core grounding, SF6, low oil pressure, switchgear temperature, and switchgear comprehensive status, are included in the unified provincial supervision, laying the foundation for observable external conditions and imperceptible internal conditions of the substation.

[0062] The acquisition terminal 300 is an intelligent electronic device (IED), such as a GIS partial discharge acquisition IED terminal built on FPGA+ARM heterogeneous SoC chip. It is responsible for high-speed acquisition and processing of partial discharge signals, as well as dynamic anchor point timestamp calibration and multi-channel phase consistency correction, providing reliable data support for subsequent accurate positioning of partial discharge sources.

[0063] like Figure 2 As shown, the number of data acquisition terminals 300 in the substation monitoring system can be multiple. The substation monitoring system also includes a master clock 100 communicatively connected to each data acquisition terminal 300, and sensors 400 connected to each data acquisition terminal 300. Each data acquisition terminal 300 can be connected to multiple sensors 400, which can be deployed at different locations on the same metal pipe to locate the partial discharge source in the metal pipe based on the transient partial discharge signals acquired by different sensors 400. The master clock 100 can be a dedicated power master clock server, providing a unified nanosecond-level time reference for the entire station. The data acquisition terminal 300 is also connected to sensors 400, such as ultra-high frequency (UHF) sensors 400 or ultrasonic sensors 400, to monitor and acquire partial discharge signals generated by insulation defects in target metal pipes such as GIS (Gas Insulation System). The substation monitoring system includes an edge IoT agent 200, which enables transparent forwarding of the master clock 100 signal and link delay compensation. It also has a high-precision time synchronization function based on the IEEE 1588V2 protocol, providing a unified time reference for the acquisition terminals 300 in the substation, so that each acquisition terminal 300 can receive the accurate system time.

[0064] In some application scenarios, the data acquisition terminal 300 can achieve automatic discovery, automatic registration, and automatic authentication with the smart gateway via a bus, and then the smart gateway will uniformly authenticate the data with the edge IoT agent 200. The functions of the smart gateway can include: deploying a data acquisition application to transmit monitoring data sent by the data acquisition terminal 300 to the edge IoT agent 200 according to the protocol, and providing a real-time data recording interface for near-field data recording; obtaining data acquisition configuration information from the edge IoT agent 200, including data point tables, device information, and communication parameters; monitoring link status, resource usage, and the running status of the data acquisition application and reporting this information to the edge IoT agent 200; receiving operation and maintenance management from the edge IoT agent 200, including upgrades to the data acquisition application; implementing transparent clock forwarding functionality based on the 1588 protocol and supporting high-precision time synchronization of the data acquisition terminal 300 using IRIG-B code; and achieving automatic discovery, automatic networking, and automatic authentication of the data acquisition terminal based on the bus.

[0065] Furthermore, the Edge IoT Agent 200's functions also include receiving data pushed by smart gateways, performing model conversion according to configuration files, and pushing the converted data to the data reporting API interface or to third-party applications, such as pushing monitoring data to third-party partial discharge analysis programs. It also supports automatic registration and authentication of smart gateways, and operational monitoring of smart gateways, including the running status and resource usage of data acquisition applications on the smart gateway, resource usage monitoring, and basic service running status. It also supports the upgrade and maintenance of data acquisition applications within the smart gateway, and monitoring of the smart gateway sensor link status. Additionally, it provides authentication services for the acquisition terminal 300.

[0066] In some application scenarios, the transmission path of monitoring data can be as follows: the acquisition terminal 300 can send monitoring data (such as data frames collected by sensors) to the edge IoT agent through the smart gateway. The edge IoT agent can then connect the monitoring data to the provincial company's IoT private network through the substation's integrated data network switch, and then enter the provincial company's internal information network through the provincial company's security access gateway and network isolation device, before uploading it to the equipment channel environment and status awareness system. Maintenance personnel and others can monitor the data within the equipment channel environment and status awareness system online.

[0067] The anchor point timestamp calibration method for substations includes the following steps:

[0068] S101, based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles, determine the drift parameters of the local crystal oscillator of the acquisition terminal.

[0069] Specifically, the acquisition terminal and the master clock communicate periodically via time synchronization protocols such as PTP (Precision Time Protocol). Within each synchronization cycle (e.g., 1 second), the acquisition terminal calculates the clock offset between the two by exchanging time synchronization messages (such as Sync messages, Delay_Req messages, etc.) with the master clock.

[0070] Because the frequency of the local crystal oscillator (such as a temperature-compensated crystal oscillator or a conventional crystal oscillator) inside the acquisition terminal can drift due to factors such as temperature and voltage, its local time gradually deviates from the reference time of the master clock. By continuously acquiring the clock offset over several synchronization cycles (e.g., N cycles), a sequence reflecting the drift trend of the local crystal oscillator can be formed. Based on this sequence, drift parameters characterizing the drift characteristics of the local crystal oscillator can be estimated using a specific algorithm model (e.g., a predictive filtering algorithm).

[0071] S102 uses drift parameters to calibrate the sampling counter in the acquisition terminal.

[0072] The sampling counter can be implemented in the FPGA (Field-Programmable Gate Array) of the acquisition terminal. It is driven by the clock after the local crystal oscillator is divided, and counts each sampling action of the ADC (Analog-to-Digital Converter). This count value is the "local time coordinate" of the sampling domain.

[0073] Because of drift in the local crystal oscillator, the counting rate of the sampling counter will deviate from the ideal value. Therefore, it is necessary to use the determined drift parameters to continuously and smoothly adjust the counting behavior of the sampling counter dynamically, making it as consistent as possible with the drift-free ideal counter. This correction method differs from the traditional jump-type correction at each synchronization cycle boundary, and can suppress the accumulation of sampling count drift, ensuring the continuity of the sampling time axis. The corrected sampling counter will generate a more accurate sampling count sequence.

[0074] S103, if a transient partial discharge signal is detected based on the data frame sequence collected by the sensor from the target metal pipe in the substation, a dynamic anchor point is established at the triggering moment of the transient partial discharge signal.

[0075] A data frame is a sequence of digital signals generated by an ADC after ultra-high-speed sampling (e.g., 5 GS / s) of the analog signals acquired by a sensor. Under normal circumstances, this sequence mainly reflects background noise. However, when partial discharge occurs inside the target metal pipe, a pulse signal with an extremely short duration (nanosecond level) and an amplitude much higher than the background noise is generated, i.e., a transient partial discharge signal. The detection logic in the acquisition terminal (e.g., a threshold comparator implemented in an FPGA) monitors the amplitude of the data frame sequence in real time. When a sampling point with an amplitude exceeding a preset threshold (e.g., the background noise threshold calculated according to the 3σ criterion) is detected, it is determined that a transient partial discharge signal has been detected, and the time point corresponding to that sampling point is recorded as the trigger time.

[0076] At the trigger moment, a dynamic anchor point can be established. The core of this dynamic anchor point is to instantaneously bind the count value of the sampling counter at the current trigger moment with the absolute time of the system (i.e., the time base) of the acquisition terminal synchronized with the master clock. This breaks through the limitation of traditional methods that rely on a fixed period (such as 1PPS pulse per second) to establish the anchor point.

[0077] S104 timestamps the data frames related to transient partial discharge signals in the data frame sequence based on dynamic anchor points, the calibrated sampling count sequence, and the time reference of the acquisition terminal.

[0078] Data frames associated with transient partial discharge signals can be data frames acquired within a period before and after the trigger moment. The combination of these data frames can contain relatively complete partial discharge pulse waveform data. The purpose of timestamp calibration is to calculate a high-precision absolute timestamp for each data frame (i.e., each sampling point) within this period. The calculation is based on: using the dynamic anchor point (i.e., the absolute time and sampling count value at the trigger moment) as a reference, combined with a more linear and accurate sampling count sequence generated after correction, the time offset of each relevant data frame relative to the dynamic anchor point is calculated through interpolation, and then added to the absolute time of the dynamic anchor point to finally obtain the high-precision absolute timestamp for each data frame.

[0079] In the above scheme, by dynamically establishing a high-precision anchor point when a transient partial discharge signal is detected, and by combining the local crystal oscillator drift parameter to correct the counter, the problems of sampling count drift accumulation and large transient signal timestamp matching error under the fixed anchor point mechanism can be solved, providing a foundation for achieving high-precision partial discharge source positioning.

[0080] In one possible embodiment, the drift parameters include frequency drift rate and time skew. The frequency drift rate characterizes the degree of deviation of the local crystal oscillator frequency from its nominal frequency and is a dimensionless relative value; the time skew (physically corresponding to phase offset) characterizes the accumulated time error of the local crystal oscillator at a given moment. Accordingly, based on the clock offset sequence between the acquisition terminal and the master clock over several consecutive synchronization cycles, the drift parameters of the local crystal oscillator of the acquisition terminal are determined, including:

[0081] First, the system state equation and observation equation are constructed with frequency drift rate and time deviation as state variables. The drift process of the local crystal oscillator is modeled as a linear stochastic system. The system state equation describes the evolution of frequency drift rate and time deviation over time. For example, it can be assumed that the frequency drift rate is approximately constant within a synchronization period, while the time deviation is the sum of the time deviation at the previous moment, the product of the frequency drift rate, and the synchronization period. The observation equation establishes the relationship between the system state variables (frequency drift rate and time deviation) and observable physical quantities (i.e., the clock offset measured in each synchronization period).

[0082] Secondly, the clock offset sequence is preprocessed to obtain the observation samples. Considering that the obtained raw clock offset sequence may contain noise or outliers, the preprocessing steps may include filtering, outlier removal, and other operations to improve the accuracy of subsequent estimations.

[0083] Then, based on the system state equation, the observation equation, and the observation samples, the frequency drift rate and time deviation of the local crystal oscillator are obtained. For example, using a state estimation algorithm, such as Kalman filtering and its variants (e.g., unscented Kalman filtering), the observation samples are substituted into the established system model, and the optimal estimation of the system state variables (i.e., frequency drift rate and time deviation) is performed through iterative calculation.

[0084] In one possible embodiment, the method for obtaining the frequency drift rate and time deviation of the local crystal oscillator based on the system state equation, observation equation, and observation samples may include, for example: Figure 3 The following steps are shown:

[0085] S201, initialize the system state vector, state covariance matrix, process noise covariance matrix, and observation noise covariance matrix.

[0086] The initial values ​​of the system state vector can be set empirically; for example, if no drift is initially assumed, then the frequency drift rate and time deviation are both 0. The state covariance matrix characterizes the degree of uncertainty in the initial state estimation. The process noise covariance matrix and the observation noise covariance matrix characterize the inaccuracy of the system model itself and the measurement noise level during the observation process, respectively.

[0087] S202, based on the unscented transformation rule, selects a corresponding number of state representation sampling points from the initialized system state vector and state covariance matrix; and performs the propagation deduction of each state representation sampling point through the system state equation.

[0088] The Unscented Transform (UT) approximates the probability distribution of a state using a set of weighted state representation sampling points (Sigma points). Substituting the selected Sigma points into the system state equations yields their predicted positions at the next time step.

[0089] S203, based on the sampling points of each state representation after transmission, calculate the prior estimate and prior covariance matrix of the state variables.

[0090] By summing the weighted values ​​of the transferred Sigma points, we can obtain the prior estimate (i.e., the predicted value) of the state variable. By calculating the weighted variance of the transferred Sigma points, we can obtain the prior covariance matrix, which represents the uncertainty of the predicted state.

[0091] S204. Using the observed samples and combined with the observation equation, the Kalman gain is calculated and the prior estimates and prior covariance matrix of the state variables are updated to obtain the posterior estimates and posterior covariance matrix of the state variables, so as to obtain the values ​​of frequency drift rate and time deviation.

[0092] S204 is the UKF update stage. First, the predicted Sigma point is substituted into the observation equation to obtain the predicted observation value. Then, the difference between the predicted observation value and the actual observed sample (i.e., the innovation) is calculated, and the Kalman gain is calculated accordingly. The Kalman gain determines the extent to which the new observation sample is trusted. Finally, the Kalman gain is used to correct the prior estimate and the prior covariance matrix to obtain the optimal estimate of the state variable at the current time, i.e., the posterior estimate and the posterior covariance matrix. This posterior estimated state vector contains the frequency drift rate and time bias of the optimal estimate at the current time.

[0093] In this embodiment, the crystal oscillator drift problem is transformed into a mathematical model that can be solved by a state estimation algorithm. The drift parameters to be determined are identified as frequency drift rate and time deviation, providing specific and quantifiable parameter basis for subsequent accurate correction, making the determination process of drift parameters more scientific and rigorous.

[0094] In this process, by accurately tracking and predicting the drift state of the local crystal oscillator, high-precision parameter input is provided for subsequent sampling counter calibration.

[0095] In one possible embodiment, the sampling counter in the acquisition terminal is calibrated using drift parameters, including:

[0096] The frequency drift rate and time deviation are used as correction parameters to correct the counting parameters of the sampling counter, and a sampling counting sequence is generated based on the corrected counting parameters.

[0097] After obtaining the estimated high-precision frequency drift rate and time deviation, these correction parameters are used to adjust the counting logic inside the counter in real time. This adjustment is not a direct addition or subtraction of the count value (jump-type correction), but rather a fine-tuning of the sampling counter's cycle time (i.e., the counting parameters), thereby achieving a continuous and smooth correction effect. After correction, the sequence of count values ​​generated by the sampling counter in each ADC sampling clock cycle is the sampling count sequence, and the long-term stability and linearity of this sequence are significantly improved.

[0098] In this embodiment, smooth correction is achieved by adjusting the intrinsic counting parameters of the sampling counter. This method solves the problems of time jumps and data discontinuities that may be introduced by traditional correction methods, and ensures the integrity of ultra-high-speed sampling data and the smoothness of the time axis.

[0099] In one possible embodiment, the counting parameters include the sampling offset and the sampling frequency. Correcting the counting parameters of the sampling counter using frequency drift rate and time deviation as correction parameters may include the following steps:

[0100] First, the product of the time deviation and the sampling frequency of the sampling counter is used as the corrected sampling offset. Multiplying the estimated time deviation (in seconds or nanoseconds) by the ADC sampling frequency (e.g., 5GS / s, in Hz) yields the number of sampling points that need compensation. This value is used as the corrected sampling offset to compensate for the accumulated error in the count values ​​caused by phase shift, thus converting the time dimension deviation into a sampling count dimension deviation.

[0101] Then, the product of the difference between the preset value and the frequency drift rate and the sampling frequency is used as the corrected sampling frequency. This step corresponds to frequency correction. The preset value can be an initial reference value, such as 1. Subtracting the estimated frequency drift rate (dimensionless) from 1 yields a frequency correction coefficient. Multiplying this coefficient by the ADC's nominal sampling frequency gives a real-time corrected, equivalent sampling frequency.

[0102] For example, after correction Local sample count at time It can be calculated using the following formula:

[0103]

[0104] in, It is the sampling frequency before correction. express The initial sample count value at time 10:00. Indicates frequency drift rate, This represents the time deviation, i.e. This indicates the corrected sampling frequency. Indicates the corrected sampling offset. Subscript Used to indicate drift, subscript Indicates sampling.

[0105] In this embodiment, by adjusting the sampling offset and sampling frequency respectively, compensation for the phase and frequency drift of the crystal oscillator is achieved, making the correction process more accurate and feasible.

[0106] In one possible embodiment, in addition to the dynamic anchoring mechanism for transient partial discharge signals, the method may also include a basic, periodic timestamp calibration mechanism to handle non-transient, regular background data. The method further includes:

[0107] First, if a synchronization cycle trigger signal is detected, a fixed anchor point is established at the start of the next synchronization cycle. The fixed anchor point is used to represent the correspondence between the time base at the start time and the count value.

[0108] The synchronization cycle trigger signal can come from the master clock or a 1PPS (Pulse Per Second) pulse signal recovered locally via the PTP protocol. This signal has extremely high edge accuracy. When the FPGA of the acquisition terminal detects the rising edge of the 1PPS signal, a fixed anchor point is established. This fixed anchor point is similar to the dynamic anchor point, binding the absolute system time (time base) at that moment (i.e., the beginning of each synchronization cycle, such as the beginning of each second) to the current sampling count value.

[0109] Then, based on the count value of the data frame corresponding to the fixed anchor point and the time base, the data frame of the fixed anchor point is timestamped.

[0110] If no transient partial discharge signal is detected between two fixed anchor points, the data frames between the two fixed anchor points can be calibrated based on the most recent fixed anchor point. The calculation method is similar to that based on dynamic anchor points, that is, the time offset is calculated by the difference between the sample count values ​​and the corrected sampling frequency, thereby binding a timestamp to each data frame.

[0111] For example, the timestamp marking method for each sampled data frame between two fixed anchor points can be:

[0112]

[0113] in, Indicates the first The timestamps corresponding to each data frame Indicates the first The timestamp corresponding to each fixed anchor point Indicates the first The sampling count value corresponding to each data frame Indicates the first The sampling count value corresponding to each fixed anchor point.

[0114] This embodiment introduces a fixed anchor point mechanism, providing a basic timestamp framework for all sampled data, which complements the dynamic anchor point mechanism. The fixed anchor point ensures the time stamp continuity and traceability of regular data, while the dynamic anchor point focuses on improving the timing accuracy of key transient signals.

[0115] In one possible embodiment, there are multiple data frames corresponding to the transient partial discharge signal, and each data frame can constitute a complete waveform. S104 described above may include the following steps performed for each data frame associated with the transient partial discharge signal:

[0116] Obtain the count difference between the count value of the data frame and the count value at the trigger time. Assume the current frame to be calibrated is... The sampling count value corresponding to each data frame is The sampling count value corresponding to the dynamic anchor point (i.e., the trigger time) is... The difference in counts is .

[0117] The target ratio between the count difference and the corrected sampling frequency in the counter. As mentioned above, the corrected sampling frequency is... .

[0118] The sum of the target ratio and the timestamp corresponding to the trigger time is used as the timestamp for data frame labeling.

[0119] For example, the method for timestamping the current data frame to be calibrated can refer to the following formula:

[0120]

[0121] in, Indicates the number of the currently uncalibrated [number]. The timestamp after each data frame is calibrated This indicates the timestamp corresponding to the triggering time.

[0122] By repeating the above steps for each data frame associated with the transient partial discharge signal, absolute timestamps with nanosecond precision can be calibrated for all sampling points on the entire partial discharge pulse waveform.

[0123] In this embodiment, the accurate reference provided by the dynamic anchor point and the sampling frequency after drift correction are used to ensure the accuracy of the calibration results and reduce the timestamp matching error of the transient partial discharge signal.

[0124] In one possible embodiment, to further improve the final accuracy of the timestamp, this embodiment introduces a correction for the inherent latency of the hardware link. After using the sum of the target ratio and the timestamp corresponding to the trigger time as the timestamp for data frame labeling, the method further includes:

[0125] First, obtain the preset transmission delay corresponding to the link between the sensor and the acquisition terminal.

[0126] In multi-channel sampling scenarios, each sensor is connected to the ADC channel of the acquisition terminal via a physical cable. Due to factors such as cable length and component differences, each channel's hardware link has an inherent, essentially fixed signal transmission delay. This delay can be pre-measured through offline calibration and stored in the acquisition terminal, forming a list of preset transmission delays that corresponds one-to-one with each channel.

[0127] Then, the timestamps of each data frame are corrected according to the preset transmission delays.

[0128] The correction process can be achieved by subtracting the preset transmission delay corresponding to that channel from the timestamp already marked on the data frame of each channel. For example, for the first... The first channel The final timestamp of a data frame can be determined using the following formula:

[0129]

[0130] in, Indicates the first The first channel Each data frame has a timestamp. Indicates the first The preset transmission delay of the channel. Indicates the first The first channel The corrected timestamp of each data frame.

[0131] This embodiment compensates for the inherent time delay difference of the multi-channel hardware link, eliminating the time error introduced by the difference in physical links, and realizing the alignment of the sampling data of each channel in terms of timestamps. This removes a key interference factor for subsequent analysis that requires multi-channel data fusion (such as partial discharge source location).

[0132] In one possible embodiment, the number of sensors is at least two, for example, M sensors are installed at different locations on the GIS equipment to form a sensor array. Each sensor collects data frames corresponding to the transient partial discharge signal, including at least one data frame. The method further includes:

[0133] First, select one data frame from the data frames collected by each sensor that correspond to the transient partial discharge signal as the target data frame.

[0134] When a partial discharge event occurs, all sensors will acquire the signal, but the arrival time will differ due to different propagation paths. In order to perform localization calculations, it is necessary to select a point with consistent characteristics from the partial discharge pulse waveform acquired by each channel as the target data frame, such as the start point or peak point of the waveform.

[0135] Secondly, the location of the fault in the target metal pipe is determined based on the time difference between the timestamps marked on the target data frames collected by each sensor.

[0136] By using the final timestamps of the target data frames obtained after correction for each channel, the time difference between any two channels can be calculated. Based on these time differences, combined with the precise spatial coordinates of the sensors in the GIS equipment, a set of hyperbolic equations can be established. Solving this set of equations yields the three-dimensional spatial coordinates of the partial discharge source, thereby enabling precise location of the fault in the target metal pipe.

[0137] Alternatively, in other embodiments, the fault location can be accurately located through an edge IoT agent. That is, the acquisition terminal sends data frames related to the transient partial discharge signal with timestamps to the edge IoT agent, and the edge IoT agent selects one data frame from the data frames corresponding to the transient partial discharge signal collected by each sensor as the target data frame; and determines the fault location in the target metal pipe based on the time difference between the timestamps of the target data frames collected by each sensor.

[0138] This embodiment provides multi-channel, high-precision, and phase-consistent timestamps, resulting in a qualitative leap in the accuracy of partial discharge source localization based on the TDOA algorithm, which greatly improves the accuracy of substation equipment status monitoring and operation and maintenance efficiency.

[0139] In one possible embodiment, the substation monitoring system may also include an edge IoT agent. Specifically, the master clock is a dedicated power master clock server, providing a nanosecond-level time reference source for the entire station. The edge IoT agent enables transparent forwarding of the master clock signal and link latency compensation.

[0140] The system's acquisition terminal is a GIS partial discharge acquisition IED terminal. This acquisition terminal has two independent direct-connect channels: a timing channel for hardware-level timestamp capture; and a sampling channel that connects to multiple UHF or ultrasonic sensors for synchronous sampling of partial discharge signals from GIS and other target metal pipes.

[0141] The method may include the following steps:

[0142] First, initialize the reference timing link parameters. For example, the acquisition terminal captures the transmission time of the Sync message. (Carried by the master clock in its message) and the receiving time and the sending time of the Delay_Req message. and the time received by the master clock (Returned from the master clock). The one-way delay of the link can then be calculated using the following formula. relative to the initial clock offset :

[0143]

[0144] in, All are timestamps, in seconds (s); This represents the one-way link transmission delay, measured in seconds (s). The clock offset of the acquisition terminal relative to the initial master clock is expressed in seconds (s).

[0145] Based on the initial clock offset The acquisition terminal completes its initial alignment with the master clock, establishing a unified time reference in the time domain.

[0146] Then, local sampling clock drift prediction and smoothing correction are performed.

[0147] For example, a sliding window of length N is constructed to store the historical clock offset sequence O= Then, the sequence is fitted using the unscented Kalman filter (UKF) algorithm to predict the drift parameter of the local crystal oscillator, i.e., the frequency drift rate. and time deviation Its state equation is as follows:

[0148]

[0149] in, for The system state vector at time t. ; for The crystal frequency drift rate (dimensionless) fitted at time. for The time deviation of the fitting at any given moment (in seconds); Here is the state transition matrix. ; The PTP synchronization period is, for example, 1 second. Let be the process noise vector, and let its covariance matrix be the process noise covariance matrix.

[0150] The observation equation can be , Indicates the first The clock offset obtained from the next cycle synchronization, i.e. , Represents the observation matrix. Let represent the observation noise vector, whose covariance matrix is ​​the observation noise covariance matrix.

[0151] Based on frequency drift rate and time deviation The sampling counter is then subjected to continuous and smooth frequency modulation correction. After correction... Local sample count at time It can be calculated using the following formula:

[0152]

[0153] in, It is the sampling frequency before correction. express The initial sample count value at time 10:00. Indicates frequency drift rate, This represents the time deviation, i.e. This indicates the corrected sampling frequency. Indicates the corrected sampling offset. Subscript Used to indicate drift, subscript Indicates sampling.

[0154] Then, the anchor point mapping can be periodically fixed and bound to the base timestamp.

[0155] As mentioned above, the timestamp of each sampled data frame between two fixed anchor points can be determined as follows:

[0156]

[0157] in, Indicates the first The timestamps corresponding to each data frame Indicates the first The timestamp corresponding to each fixed anchor point Indicates the first The sampling count value corresponding to each data frame Indicates the first The sampling count value corresponding to each fixed anchor point.

[0158] If a transient partial discharge signal is detected, dynamic anchor insertion is triggered.

[0159] For example, the mean of the background noise is calculated within a sliding window according to the 3σ criterion. and standard deviation Thus, the detection threshold for partial discharge transient signals is constructed. .

[0160] When the module detects the amplitude of the current sampling point When the signal is determined to be a transient partial discharge signal, it is immediately triggered at the current trigger time. Insert dynamic anchor points to complete the sampling and counting at that moment in real time. With system absolute time Bind the anchor point and update the anchor mapping table.

[0161] Then, based on the dynamic anchor point, the calibrated sampling count sequence, and the time reference of the acquisition terminal, the data frames related to the transient partial discharge signal in the data frame sequence are timestamped.

[0162] Next, the preset transmission delay corresponding to the link between the sensor and the acquisition terminal is obtained; based on each preset transmission delay, the timestamp of each data frame is calculated. Perform corrections. The same method can also be used to correct the timestamps of data frames between fixed anchor points. Perform corrections.

[0163] One data frame corresponding to the transient partial discharge signal acquired by each sensor is selected as the target data frame. The fault location in the target metal pipe is determined based on the time difference between the timestamps marked on the target data frames acquired by each sensor.

[0164] Please see Figure 4 The data acquisition terminal 300 is connected to a first sensor 401 and a second sensor 402. An electric shock test is performed at a preset position away from the first sensor 401, and the positioning result output by the data acquisition terminal 300 is as follows: Figure 5 As shown.

[0165] Figure 5In the figure, the horizontal axis represents the distance from the first sensor 401 (in meters), with the side closer to the second sensor 402 being the positive direction and the side farther from the second sensor 402 being the negative direction; the vertical axis represents the location confidence (or normalized location probability).

[0166] Depend on Figure 5 As can be seen, the positioning result calculated based on the time difference of the signals collected by the two sensors reaches its peak reliability at a distance of 0.3m from the first sensor 401, indicating that the electric shock location (fault location) is located at this position. Therefore, it is evident that the fault location obtained from the data frame after timestamp calibration according to this application is accurate.

[0167] This embodiment solves the drift accumulation and time jump problems caused by the periodic fixed anchor point mechanism in transparent substations. Specifically, the timestamp matching error of transient partial discharge signals is reduced, thereby improving the positioning accuracy of GIS partial discharge sources and ensuring the continuity and stability of ultra-high-speed sampling.

[0168] The following describes an anchor timestamp calibration device for substations provided in this application. The anchor timestamp calibration device for substations described below corresponds to the method of the anchor timestamp calibration device for substations described above.

[0169] This application also provides an anchor point timestamp calibration device 500 for an ultrasonic endoscope facing a substation, applied to a data acquisition terminal within a substation monitoring system. The substation monitoring system also includes a master clock and sensors that are communicatively connected to the data acquisition terminal, such as... Figure 6 The anchor point timestamp calibration device 500 for substations includes:

[0170] The drift parameter determination unit 501 is used to determine the drift parameters of the local crystal oscillator of the acquisition terminal based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles.

[0171] The correction unit 502 is used to correct the sampling counter in the acquisition terminal using drift parameters;

[0172] The dynamic anchor point establishment unit 503 is used to establish a dynamic anchor point at the triggering moment of the transient partial discharge signal if a transient partial discharge signal is detected based on the data frame sequence collected by the sensor from the target metal pipe in the substation.

[0173] The timestamp calibration unit 504 is used to calibrate the timestamps of data frames related to transient partial discharge signals in the data frame sequence based on dynamic anchor points, the calibrated sampling count sequence, and the time reference of the acquisition terminal.

[0174] In one possible embodiment, the drift parameters include frequency drift rate and time offset. The drift parameter determination unit 501 determines the drift parameters of the local crystal oscillator of the acquisition terminal based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles, including:

[0175] Construct the system state equation and observation equation with the frequency drift rate and the time deviation as state variables;

[0176] The clock offset sequence is preprocessed to obtain the observation samples;

[0177] Based on the system state equation, the observation equation, and the observation samples, the frequency drift rate and time deviation of the local crystal oscillator are obtained.

[0178] In one possible embodiment, the drift parameter determination unit 501 obtains the frequency drift rate and time deviation of the local crystal oscillator based on the system state equation, the observation equation, and the observation samples, including:

[0179] Initialize the system state vector, state covariance matrix, process noise covariance matrix, and observation noise covariance matrix;

[0180] Based on the unscented transformation rule, a corresponding number of state representation sampling points are selected from the initialized system state vector and state covariance matrix; and the propagation deduction of each of the state representation sampling points is performed through the system state equation.

[0181] Based on the sampling points of each state representation after transmission, the prior estimates and prior covariance matrix of the state variables are calculated.

[0182] Using the observed samples and the observed equation, the Kalman gain is calculated, and the prior estimates of the state variables and the prior covariance matrix are updated to obtain the posterior estimates of the state variables and the posterior covariance matrix, so as to obtain the values ​​of the frequency drift rate and the time deviation.

[0183] In one possible embodiment, the drift parameter determination unit 501 uses the drift parameter to correct the sampling counter in the acquisition terminal, including:

[0184] The frequency drift rate and the time deviation are used as correction parameters to correct the counting parameters of the sampling counter, so as to generate the sampling count sequence based on the corrected counting parameters.

[0185] In one possible embodiment, the counting parameters include a sampling offset and a sampling frequency. The counting parameters of the sampling counter are corrected using the frequency drift rate and the time deviation as correction parameters, including:

[0186] The product of the time deviation and the sampling frequency of the sampling counter is used as the corrected sampling offset.

[0187] The product of the difference between the preset value and the frequency drift rate and the sampling frequency is used as the corrected sampling frequency.

[0188] In one possible embodiment, the timestamp calibration unit 504 is further configured to:

[0189] If a synchronization cycle trigger signal is detected, a fixed anchor point is established at the start of the next synchronization cycle. The fixed anchor point is used to represent the correspondence between the time base and the count value at the start time.

[0190] Based on the count value of the data frame corresponding to the fixed anchor point and the time base, the data frame of the fixed anchor point is timestamped.

[0191] In one possible embodiment, there are multiple data frames corresponding to the transient partial discharge signal. The timestamp calibration unit 504 timestamps the data frames related to the transient partial discharge signal in the data frame sequence based on the dynamic anchor point, the corrected sampling count sequence, and the time reference of the acquisition terminal, including:

[0192] For each of the data frames, perform the following steps:

[0193] Obtain the count difference between the count value of the data frame and the count value at the trigger time;

[0194] The target ratio between the count difference and the corrected sampling frequency in the counter;

[0195] The sum of the target ratio and the timestamp corresponding to the triggering time is used as the timestamp for the data frame.

[0196] In one possible embodiment, after using the sum of the target ratio and the timestamp corresponding to the triggering time as the timestamp for data frame calibration, the timestamp calibration unit 504 is further configured to:

[0197] Obtain the preset transmission delay corresponding to the link between the sensor and the acquisition terminal;

[0198] The timestamps of each data frame are corrected according to the preset transmission delay.

[0199] In one possible embodiment, the number of sensors is at least two, and each sensor collects at least one data frame corresponding to the transient partial discharge signal. The anchor point timestamp calibration device for the substation further includes a positioning unit, which is used for:

[0200] Select one data frame from the data frames collected by each of the sensors that correspond to the transient partial discharge signal as the target data frame;

[0201] The location of the fault in the target metal pipe is determined based on the time difference between the timestamps marked on the target data frames collected by each of the sensors.

[0202] It is understood that since the method embodiments and the device embodiments are different presentations of the same technical concept, the content of the method embodiment section in this application should be adapted to the device embodiment section in a synchronous manner, and will not be repeated here.

[0203] In the case of using integrated units, please refer to Figure 7 , Figure 7 This is the second functional unit block diagram of an anchor time stamp calibration device for substations provided in this application embodiment. The anchor time stamp calibration device for substations is applied to a data acquisition terminal within a substation monitoring system. The substation monitoring system also includes a master clock and sensors communicatively connected to the data acquisition terminal. Figure 7 The substation-oriented anchor point timestamp calibration device 500 includes a processing module 512 and a communication module 511. The processing module 512 controls and manages the operation of the substation-oriented anchor point timestamp calibration device 500, for example, executing steps of the drift parameter determination unit, correction unit, dynamic anchor point establishment unit, timestamp calibration unit, and positioning unit, and / or other processes of the technology described herein. The communication module 511 is used for interaction between the substation-oriented anchor point timestamp calibration device 500 and other devices. Figure 7 As shown, the anchor point timestamp calibration device 500 for substations may further include a storage module 513, which is used to store the program code and data of the anchor point timestamp calibration device 500 for substations.

[0204] The processing module 512 can be a processor or controller, such as a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The communication module 511 can be a transceiver, RF circuitry, or a communication interface, etc. The storage module 513 can be a memory.

[0205] All relevant content for each scenario involved in the above method embodiments can be referenced from the functional descriptions of the corresponding functional modules, and will not be repeated here. The above-mentioned anchor point timestamp calibration device 500 for substations can execute the above-mentioned anchor point timestamp calibration method for substations.

[0206] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 8 As shown, the electronic device may include a processor 610, a communications interface 620, a memory 630, and a communication bus 640. The processor 610, communications interface 620, and memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute the aforementioned anchor point timestamp calibration method for substations. The electronic device may be the aforementioned data acquisition terminal.

[0207] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0208] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the anchor point timestamp calibration method for substations provided in the above embodiments.

[0209] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the above-described anchor point timestamp calibration methods for substations.

[0210] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0211] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0212] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0213] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0214] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0215] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0216] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0217] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0218] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0219] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for anchor point timestamp calibration in substations, characterized in that, A data acquisition terminal is used in a substation monitoring system, the substation monitoring system also includes a master clock and sensors that are communicatively connected to the data acquisition terminal, and the method includes the following steps: The drift parameters of the local crystal oscillator of the acquisition terminal are determined based on the clock offset sequence between the acquisition terminal and the master clock within a series of consecutive synchronization cycles. The drift parameters are used to correct the sampling counter in the acquisition terminal; If a transient partial discharge signal is detected based on the data frame sequence collected by the sensor from the target metal pipe in the substation, a dynamic anchor point is established at the triggering time of the transient partial discharge signal. Based on the dynamic anchor point, the corrected sampling count sequence, and the time reference of the acquisition terminal, the data frames in the data frame sequence related to the transient partial discharge signal are timestamped.

2. The method according to claim 1, characterized in that, The drift parameters include frequency drift rate and time offset. Determining the drift parameters of the local crystal oscillator of the acquisition terminal based on the clock offset sequence between the acquisition terminal and the master clock over several consecutive synchronization cycles includes: Construct the system state equation and observation equation with the frequency drift rate and the time deviation as state variables; The clock offset sequence is preprocessed to obtain the observation samples; Based on the system state equation, the observation equation, and the observation samples, the frequency drift rate and time deviation of the local crystal oscillator are obtained.

3. The method according to claim 2, characterized in that, The process of obtaining the frequency drift rate and time deviation of the local crystal oscillator based on the system state equation, the observation equation, and the observation samples includes: Initialize the system state vector, state covariance matrix, process noise covariance matrix, and observation noise covariance matrix; Based on the unscented transformation rule, a corresponding number of state representation sampling points are selected from the initialized system state vector and state covariance matrix; and the propagation deduction of each of the state representation sampling points is performed through the system state equation. Based on the sampling points of each state representation after transmission, the prior estimates and prior covariance matrix of the state variables are calculated. Using the observed samples and the observed equation, the Kalman gain is calculated, and the prior estimates of the state variables and the prior covariance matrix are updated to obtain the posterior estimates of the state variables and the posterior covariance matrix, so as to obtain the values ​​of the frequency drift rate and the time deviation.

4. The method according to claim 2, characterized in that, The sampling counter in the acquisition terminal is calibrated using the drift parameter, including: The frequency drift rate and the time deviation are used as correction parameters to correct the counting parameters of the sampling counter, so as to generate the sampling count sequence based on the corrected counting parameters.

5. The method according to claim 4, characterized in that, The counting parameters include the sampling offset and the sampling frequency. The frequency drift rate and the time deviation are used as correction parameters to correct the counting parameters of the sampling counter, including: The product of the time deviation and the sampling frequency of the sampling counter is used as the corrected sampling offset. The product of the difference between the preset value and the frequency drift rate and the sampling frequency is used as the corrected sampling frequency.

6. The method according to any one of claims 2 to 5, characterized in that, The method further includes: If a synchronization cycle trigger signal is detected, a fixed anchor point is established at the start of the next synchronization cycle. The fixed anchor point is used to represent the correspondence between the time base and the count value at the start time. Based on the count value of the data frame corresponding to the fixed anchor point and the time base, the data frame of the fixed anchor point is timestamped.

7. The method according to any one of claims 2 to 5, characterized in that, There are multiple data frames corresponding to the transient partial discharge signal. The step of timestamping the data frames related to the transient partial discharge signal in the data frame sequence based on the dynamic anchor point, the corrected sampling count sequence, and the time reference of the acquisition terminal includes: For each of the data frames, perform the following steps: Obtain the count difference between the count value of the data frame and the count value at the trigger time; The target ratio between the count difference and the corrected sampling frequency in the counter; The sum of the target ratio and the timestamp corresponding to the triggering time is used as the timestamp for the data frame.

8. The method according to claim 7, characterized in that, After using the sum of the target ratio and the timestamp corresponding to the triggering time as the timestamp for the data frame, the method further includes: Obtain the preset transmission delay corresponding to the link between the sensor and the acquisition terminal; The timestamps of each data frame are corrected according to the preset transmission delay.

9. The method according to claim 8, characterized in that, The number of sensors is at least two, and each sensor acquires at least one data frame corresponding to the transient partial discharge signal. The method further includes: Select one data frame from the data frames collected by each of the sensors that correspond to the transient partial discharge signal as the target data frame; The location of the fault in the target metal pipe is determined based on the time difference between the timestamps marked on the target data frames collected by each of the sensors.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the anchor point timestamp calibration method for substations as described in any one of claims 1-9.

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