Equipotential connection measurement method and system based on precise low resistance

Abstract

The invention relates to the technical field of electrical variable measurement, and discloses an equipotential connection measurement method and system based on precise low resistance. The method comprises the steps that according to high-precision ADC chip sampling parameters and temperature sensor arrangement, initial configuration of measurement channels is completed to obtain a dynamic compensation parameter database, and meanwhile, 20 channels are connected through an elastic crimping structure to obtain stress compensation data; a dynamic calibration compensation coefficient is obtained by using a standard resistance network through time division multiplexing calibration in combination with temperature-resistance and stress characteristic analysis; performing four-wire system measurement and 1kHz sampling based on the coefficient to obtain original data; a resistance value is obtained through compensation processing and interference identification; performing correlation analysis to obtain state parameters; and finally, evaluating the stability to obtain an optimized compensation parameter. The method is used for solving the problem of dynamic interference caused by temperature change and mechanical stress in the equipotential connection resistance measurement process, and high-precision multi-channel measurement is achieved.

Description

Technical Field

[0001] The present application relates to the field of electrical variable measurement, and in particular to a method and system for measuring equipotential connection based on precise low resistance. Background Art

[0002] In modern industrial production and power systems, equipotential bonding is a key technical measure to ensure safe operation of equipment and personal safety. Equipotential bonding prevents dangerous voltages caused by potential differences by connecting conductive parts such as equipment housings, metal components, and grounding devices to the same potential. At present, the resistance measurement of equipotential bonding mainly adopts the four-wire measurement method, which calculates the resistance value by injecting a constant current into the measured resistor and measuring the voltage at both ends. With the large-scale and complex industrial equipment, the number of equipotential bonding points continues to increase, which puts higher requirements on the accuracy, stability, and reliability of the measurement system.

[0003] However, the existing equipotential bonding resistance measurement technology has obvious shortcomings. First, the measurement results are easily affected by factors such as test line resistance and contact resistance, resulting in large measurement errors. Secondly, traditional measurement methods have difficulty coping with dynamic interference caused by temperature changes and mechanical stress, and lack effective compensation mechanisms. Thirdly, there is a lack of correlation analysis between channels during multi-channel measurement, and it is impossible to fully evaluate the overall status of the equipotential bonding network. In addition, the existing technology also has problems such as a single sampling strategy and limited data processing capabilities, which makes it difficult to meet the online monitoring needs of large-scale equipotential bonding systems. Summary of the invention

[0004] The present application provides an equipotential connection measurement method and system based on precise low resistance, which is used to solve the dynamic interference problem caused by temperature change and mechanical stress during the equipotential connection resistance measurement process, and realize high-precision multi-channel measurement.

[0005] In the first aspect, the present application provides an equipotential connection measurement method based on precise low resistance, and the equipotential connection measurement method based on precise low resistance includes: performing initial parameter configuration on the measurement channel according to the sampling parameters of the high-precision ADC chip and the layout position of the temperature sensor to obtain a dynamic compensation parameter database; at the same time, using an elastic crimping structure to physically connect 20 measurement channels to obtain mechanical stress compensation data; performing time-division multiplexing calibration on the parameters in the dynamic compensation parameter database through a standard resistor network, and combining the mechanical stress compensation data, after analyzing the temperature-resistance characteristics and stress-contact resistance characteristics, obtaining a multi-channel dynamic calibration compensation coefficient; according to the multi-channel dynamic calibration compensation coefficient, using independent The excitation source applies a compensation current to each measurement channel for four-wire measurement, and collects temperature data and stress data at a sampling rate of 1 kHz to obtain multiple channels of original measurement data; the dynamic compensation processing unit performs temperature compensation and stress compensation on the multiple channels of original measurement data, and the transient interference identification unit analyzes the adjacent channel data to obtain the equipotential connection resistance value; according to the equipotential connection resistance value, the data characteristics of the adjacent measurement channels are correlated and analyzed, and when an abnormal trend is detected, the sampling frequency is increased to obtain the equipotential connection network state parameters; according to the equipotential connection network state parameters, the stability of the measurement channel is evaluated, and based on the temperature change and stress change historical data, the optimized compensation model parameters are obtained.

[0006] In a second aspect, the present application provides an equipotential connection measurement system based on precise low resistance, and the equipotential connection measurement system based on precise low resistance includes: The acquisition module is used to configure the initial parameters of the measurement channels according to the sampling parameters of the high-precision ADC chip and the layout of the temperature sensor to obtain the dynamic compensation parameter database; at the same time, the elastic crimping structure is used to physically connect the 20 measurement channels to obtain mechanical stress compensation data; A calibration module, used to perform time-division multiplexing calibration on the parameters in the dynamic compensation parameter database through a standard resistor network, and obtain multi-channel dynamic calibration compensation coefficients after analyzing the temperature-resistance characteristics and stress-contact resistance characteristics in combination with the mechanical stress compensation data; A measurement module, used to apply compensation current to each measurement channel using an independent excitation source according to the multi-channel dynamic calibration compensation coefficients to perform four-wire measurement, and collect temperature data and stress data at a sampling rate of 1kHz to obtain multi-channel original measurement data; A compensation module, used for performing temperature compensation and stress compensation on the multiple channels of original measurement data through a dynamic compensation processing unit, and analyzing adjacent channel data through a transient interference identification unit to obtain an equipotential connection resistance value; A correlation module, used to perform correlation analysis on data features of adjacent measurement channels according to the equipotential bonding resistance value, increase the sampling frequency when an abnormal trend is detected, and obtain equipotential bonding network status parameters; The evaluation module is used to evaluate the stability of the measurement channel according to the equipotential connection network state parameters, and obtain optimized compensation model parameters based on temperature change and stress change historical data.

[0007] In the technical solution provided by the present application, a dynamic compensation parameter database is established by combining high-precision ADC chip sampling with temperature sensor arrangement, and an elastic crimping structure is used to realize the physical connection of 20 measurement channels. This design not only ensures the accuracy of data acquisition, but also solves the reliability problem of multi-channel connection. Secondly, a high-precision standard resistor network is used for time-division multiplexing calibration, and the multi-channel dynamic calibration compensation coefficient is obtained by combining the temperature-resistance characteristic and stress-contact resistance characteristic analysis, which significantly improves the measurement accuracy. Thirdly, through the design of an independent excitation source and a high-frequency sampling strategy of 1kHz, the synchronous acquisition of temperature data and stress data is realized, providing complete data support for subsequent compensation processing. In terms of data processing, the coordinated use of the dynamic compensation processing unit and the transient interference identification unit effectively eliminates the influence of various interference factors. In particular, the sampling frequency can be automatically increased when an abnormal trend is detected, reflecting the adaptive characteristics of the solution. Finally, the continuous optimization of the measurement system is achieved by evaluating the stability of the measurement channel and optimizing the compensation model parameters. At the algorithm level, this solution innovatively combines multiple data processing algorithms, including dynamic compensation algorithm, time division multiplexing algorithm, transient interference identification algorithm, etc. The synergy of these algorithms not only improves the measurement accuracy, but also enhances the anti-interference ability and adaptability of the system. Through the comprehensive application of these technical features, the present invention successfully solves the dynamic interference problem in the measurement of equipotential connection resistance and achieves the technical goal of high-precision, multi-channel, and real-time monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0009] Figure 1 This is a schematic diagram of an embodiment of an equipotential connection measurement method based on precise low resistance in an embodiment of the present application; Figure 2 A timing diagram of initial parameter configuration of a measurement channel in an embodiment of the present application; Figure 3This is a schematic diagram of an embodiment of an equipotential connection measurement system based on precise low resistance in an embodiment of the present application. DETAILED DESCRIPTION

[0010] The embodiment of the present application provides an equipotential connection measurement method and system based on precise low resistance. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0011] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of the equipotential connection measurement method based on precise low resistance in the embodiment of the present application includes: Step S101: Perform initial parameter configuration on the measurement channels according to the sampling parameters of the high-precision ADC chip and the layout position of the temperature sensor to obtain a dynamic compensation parameter database; at the same time, use an elastic crimping structure to physically connect the 20 measurement channels to obtain mechanical stress compensation data; Step S102, performing time-division multiplexing calibration on the parameters in the dynamic compensation parameter database through a standard resistor network, and combining the mechanical stress compensation data, and obtaining multi-channel dynamic calibration compensation coefficients after temperature-resistance characteristics and stress-contact resistance characteristics analysis; Step S103, according to the multi-channel dynamic calibration compensation coefficient, use an independent excitation source to apply compensation current to each measurement channel to perform four-wire measurement, and collect temperature data and stress data at a sampling rate of 1kHz to obtain multi-channel original measurement data; Step S104, performing temperature compensation and stress compensation on the multiple channels of original measurement data by the dynamic compensation processing unit, and analyzing the adjacent channel data by the transient interference identification unit to obtain the equipotential connection resistance value; Step S105, performing correlation analysis on the data features of adjacent measurement channels according to the equipotential bonding resistance value, increasing the sampling frequency when an abnormal trend is detected, and obtaining the equipotential bonding network state parameter; Step S106: Evaluate the stability of the measurement channel according to the equipotential connection network state parameters, and obtain optimized compensation model parameters based on the temperature change and stress change history data.

[0012] It is understandable that the execution subject of the present application can be an equipotential connection measurement system based on precise low resistance, or a terminal or a server, which is not limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0013] Specifically, in the initial parameter configuration stage, the high-precision ADC chip uses 24-bit resolution, the range is set to ±10V, and the sampling rate is initially configured to 1kHz. The temperature sensor uses a PT100 platinum resistor, which is arranged at the input, middle and output ends of each measurement channel to form a temperature gradient monitoring network. The dynamic compensation parameter database stores sampling parameter configuration information, temperature sensor position coordinate data and initial compensation coefficients. The elastic crimping structure uses a special spring contact array to physically connect the 20 measurement channels. Each contact integrates a strain stress sensor to collect contact pressure data in real time and generate mechanical stress compensation data.

[0014] In the time-division multiplexing calibration stage, a 0.01-level standard resistor network is used as the benchmark, and 20 measurement channels are polled and switched through a multi-way switch array. The calibration time for each channel is 1ms. During the calibration process, temperature data and stress data are collected synchronously to establish temperature-resistance characteristic curves and stress-contact resistance characteristic curves. The temperature characteristic analysis uses a piecewise linear fitting method to divide the temperature coefficient change in the range of -20℃ to 60℃ into multiple intervals. The stress characteristic analysis is based on the inverse relationship between contact pressure and contact resistance, and the dynamic calibration compensation coefficient is obtained through data fitting. In the four-wire measurement stage, an independent excitation source provides 100mA constant current excitation for each measurement channel, and the influence of thermoelectric potential is eliminated by reverse excitation. The amplitude of the compensation current is modulated by the dynamic calibration compensation coefficient to achieve dynamic compensation of measurement errors. The sampling system synchronously collects voltage signals, temperature data, and stress data at a frequency of 1kHz to form multiple original measurement data streams.

[0015] In the compensation processing stage, the dynamic compensation processing unit performs temperature compensation and stress compensation on the original measurement data. Temperature compensation calculates the influence of thermoelectric potential based on temperature gradient data, while stress compensation considers the dynamic change of contact resistance. Transient interference identification uses correlation analysis of adjacent channel data to identify common mode interference components by setting correlation coefficient thresholds, and obtains equipotential connection resistance values ​​after compensation processing.

[0016] During the correlation analysis phase, the equipotential bonding resistance value is trend analyzed, and the abnormal change trend is identified by calculating the resistance difference and change rate between adjacent channels. When the resistance value change rate exceeds the set threshold, the system automatically increases the sampling frequency to 2kHz, encrypts the sampling to capture transient characteristics, and generates equipotential bonding network status parameters.

[0017] During the optimization phase, the stability of the measurement channel is evaluated, and a correlation model between measurement error and environmental factors is established by analyzing historical data of temperature and stress changes. The compensation model parameters are optimized using the recursive least squares method, and the compensation coefficients are continuously updated based on historical data to improve measurement accuracy.

[0018] Taking the equipotential connection measurement of a lightning protection system as an example, the measurement system monitors the grounding grid nodes through 20 measurement channels. In the initial configuration stage, temperature sensors are arranged at three characteristic positions of each node to monitor the temperature gradient changes in real time. In the calibration stage, a 10mΩ standard resistor is used for time-division multiplexing calibration, and a compensation model is established in combination with the stress data of the crimping point. During the measurement process, the system detected a rapid increase of 20% in the resistance value of a certain node, automatically triggered an increase in the sampling frequency, and revealed the loose contact problem of the node through high-density sampling data, and generated an alarm signal. After the compensation model parameters are continuously optimized, the measurement system can still maintain stable measurement accuracy under large temperature fluctuations.

[0019] In the embodiment of the present application, a dynamic compensation parameter database is established by combining high-precision ADC chip sampling with temperature sensor arrangement, and an elastic crimping structure is used to realize the physical connection of 20 measurement channels. This design not only ensures the accuracy of data acquisition, but also solves the reliability problem of multi-channel connection. Secondly, a high-precision standard resistor network is used for time-division multiplexing calibration, and the multi-channel dynamic calibration compensation coefficient is obtained by combining the temperature-resistance characteristic and stress-contact resistance characteristic analysis, which significantly improves the measurement accuracy. Again, through the design of an independent excitation source and a high-frequency sampling strategy of 1kHz, the synchronous acquisition of temperature data and stress data is achieved, providing complete data support for subsequent compensation processing. In terms of data processing, the coordinated use of the dynamic compensation processing unit and the transient interference identification unit effectively eliminates the influence of various interference factors. In particular, the sampling frequency can be automatically increased when an abnormal trend is detected, reflecting the adaptive characteristics of the scheme. Finally, the continuous optimization of the measurement system is achieved by evaluating the stability of the measurement channel and optimizing the compensation model parameters. At the algorithm level, this solution innovatively combines multiple data processing algorithms, including dynamic compensation algorithm, time division multiplexing algorithm, transient interference identification algorithm, etc. The synergy of these algorithms not only improves the measurement accuracy, but also enhances the anti-interference ability and adaptability of the system. Through the comprehensive application of these technical features, the present invention successfully solves the dynamic interference problem in the measurement of equipotential connection resistance and achieves the technical goal of high-precision, multi-channel, and real-time monitoring.

[0020] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) The sampling control unit of the high-precision ADC chip sets a sampling frequency of 1 kHz, alternately samples standard resistor groups with different resistance values, and combines a 4th-order Butterworth filter to suppress noise in the sampled data to establish benchmark compensation data; (2) The temperature sensors are arranged at the three key nodes of the lead-in end, middle end and lead-out end of each measurement channel, and the temperature data sequence is collected by the three-point temperature difference method. After thermodynamic equilibrium calculation, the temperature gradient distribution data is established; (3) The stress sensing unit integrated in the elastic crimping structure collects three-dimensional stress data on the X-axis, Y-axis, and Z-axis, and generates stress-temperature correlation data through thermal stress coupling calculation based on the temperature gradient distribution data; (4) Writing the reference compensation data, temperature gradient distribution data, and stress-temperature correlation data into the dynamic compensation parameter database according to a hierarchical storage structure through a data fusion processor; (5) An elastic crimping structure with automatic compensation function is used to crimp and fix the 20 measurement channels at a fixed pressure value. The crimping stress value is collected in real time through the built-in strain stress sensor, and the mechanical stress compensation data is generated in combination with the stress threshold judgment.

[0021] Specifically, Figure 2 As shown, it is a timing diagram of the initial parameter configuration of the measurement channel in the embodiment of the present application. The high-precision ADC chip first sets the sampling frequency of 1kHz and alternately samples the standard resistor group. The sampled data is filtered by Butterworth to establish the benchmark compensation data; the temperature sensor collects temperature data at three key nodes, and obtains the temperature gradient distribution data after the three-point temperature difference method and thermodynamic equilibrium calculation; the stress sensing unit collects three-dimensional stress data and combines the temperature data to perform thermal stress coupling calculation; the data processor writes various types of data into the dynamic compensation parameter database according to the hierarchical structure; finally, the elastic crimping structure crimps and fixes the 20 measurement channels, and generates mechanical stress compensation data through stress threshold judgment.

[0022] The sampling frequency is set and fixed at 1kHz, and a set of standard resistors including 10mΩ, 100mΩ and 1Ω are sampled alternately. During the sampling process, a 4th-order Butterworth filter is used for data processing, and the cutoff frequency of the filter is set to 1 / 10 of the sampling frequency, that is, 100Hz. The high-frequency noise components in the sampled data are suppressed by recursive calculation to form stable benchmark compensation data.

[0023] The temperature monitoring layout adopts the three-point temperature difference method, and PT100 platinum resistance temperature sensors are installed at the input, middle and output ends of each measurement channel. The core of the three-point temperature difference method is to establish a temperature gradient field through multi-point temperature measurement, and the temperature gradient distribution calculation adopts the following formula:

[0024] in, is the temperature gradient distribution value; is the weight coefficient of the i-th measuring point; is the temperature value of the i-th measuring point; is the reference temperature value; is the heat transfer coefficient matrix; is the heat flux density; is the space coordinate.

[0025] This formula describes the distribution calculation process of temperature gradient. Weight coefficient It reflects the importance of different measuring points. Its value range is between 0-1. The weight of the leading end is 0.4, the middle end is 0.3, and the leading end is 0.3. Temperature difference ( ) reflects the degree of deviation between the temperature at the measuring point and the reference temperature. Thermal conductivity matrix It characterizes the heat conduction characteristics in all directions of space. The diagonal elements represent the conduction coefficient in the main direction, and the non-diagonal elements represent the coupled conduction effect. The second-order partial derivative of the heat flux reflects the curvature change of the temperature field and is used to capture the nonlinear characteristics of the temperature distribution.

[0026] The elastic crimping structure integrates a three-axis stress sensing unit to collect stress data in the X-axis, Y-axis and Z-axis directions. The thermal stress coupling calculation uses the following formula:

[0027] is the thermal stress coupling value; is the thermal stress compensation coefficient; is the elastic modulus; is the stress weight in the kth direction; is the triaxial stress component; is the temperature sensitivity coefficient; is the temperature gradient distribution value.

[0028] This formula establishes the coupling relationship between stress and temperature. The thermal stress compensation coefficient β reflects the thermal mechanical properties of the material, and its typical value is / ℃. The elastic modulus E represents the stiffness characteristics of the material, which is about 110GPa for copper. Directional weight It reflects the contribution of different axial stresses. Usually, the weights of the X-axis and Y-axis are 0.3, and the weight of the Z-axis is 0.4. The square root of the sum of the squares of the three-axis stress components represents the comprehensive stress intensity. The temperature sensitivity coefficient η in the exponential term describes the sensitivity of the stress response to temperature changes, and its value is usually between 0.01-0.1.

[0029] The data fusion processor uses a hierarchical storage structure to manage various types of data. The bottom layer stores benchmark compensation data, the middle layer stores temperature gradient distribution data, and the top layer stores stress-temperature correlation data. A timestamp synchronization mechanism is used during data writing to ensure the timing consistency of the data. For the 20 measurement channels, the elastic crimping structure adopts a fixed pressure value design, and the stress state of the crimping point is monitored in real time through the built-in strain stress sensor. When the measured stress value exceeds the preset threshold range, the compensation mechanism is automatically triggered to generate mechanical stress compensation data.

[0030] Taking the equipotential connection system of a 220kV substation as an example, the grounding points of the main equipment are monitored through 20 measurement channels. During the benchmark compensation data acquisition process, the 10mΩ standard resistor is sampled. After the sampled data is processed by a 4th-order Butterworth filter, the noise is effectively suppressed. Temperature monitoring shows that the temperature values ​​of the three measuring points are 28.5℃, 29.2℃ and 30.1℃, respectively. The temperature gradient distribution is calculated by the three-point temperature difference method. The stress monitoring data shows that the stress values ​​of the X-axis, Y-axis and Z-axis are 15N, 12N and 20N, respectively. The thermal stress coupling calculation is combined with the temperature gradient data to generate stress-temperature correlation data. The data fusion processor writes these data into the database according to the hierarchical structure. During the monitoring process, the elastic crimping structure detects that the crimping stress value of a certain grounding point drops to 8N, which is lower than the preset threshold of 10N, and immediately generates compensation data for correction.

[0031] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) The standard resistor network is divided into 20 independent compensation units, and the parameters in the dynamic compensation parameter database are polled and switched using a phase-interleaved sampling method to generate multi-channel interleaved compensation benchmark data; (2) The piezoelectric stress sensor performs three-dimensional component decomposition of the mechanical stress compensation data and generates stress-resistance coupling data by combining the nonlinear deformation characteristics of the elastic crimping structure; (3) Gradient temperature compensation is performed on the multi-channel interleaved compensation benchmark data through a thermocouple array, and dynamic correction is performed on the temperature change rate to obtain temperature coefficient compensation data; (4) Contact resistance characteristics are identified based on stress-resistance coupling data, and micro deformation compensation of the crimping surface is introduced to obtain contact impedance compensation data; (5) Perform nonlinear weighted processing on the temperature coefficient compensation data and the contact impedance compensation data to generate a dynamic joint compensation coefficient; (6) Perform piecewise linear fitting and interpolation calculation on the dynamic joint compensation coefficients to obtain multi-channel dynamic calibration compensation coefficients.

[0032] Specifically, the 0.01-level standard resistor network is divided into 20 independent compensation units, each of which contains three standard resistance values: 10mΩ, 100mΩ, and 1Ω. Phase interleaved sampling is used for data acquisition, and the sampling time between adjacent channels is staggered by 50μs to form a time-interleaved sampling sequence. The parameters in the dynamic compensation parameter database are polled and switched through a multi-way switch matrix, and the switching cycle of each channel is 1ms, generating multi-channel interleaved compensation benchmark data with time stamps.

[0033] The piezoelectric stress sensor is made of piezoelectric crystal material and performs three-dimensional component decomposition of the mechanical stress compensation data. The stress signals in the X, Y, and Z directions are sampled simultaneously, with a sampling rate of 1kHz. The elastic crimping structure uses a special beryllium copper alloy spring, which has nonlinear force-deformation characteristics. Based on the stress component data and the deformation characteristic curve, the stress-resistance coupling data of the crimping point is calculated. In the thermocouple array, T-type thermocouples are used for temperature monitoring, and the temperature measurement range is -20℃ to 60℃. When performing temperature gradient compensation on the multi-channel interleaved compensation benchmark data, a temperature change rate curve is established, the temperature change rate and acceleration characteristics are calculated, and the temperature coefficient compensation data is obtained after dynamic correction.

[0034] The contact resistance characteristic identification is calculated based on the following formula:

[0035] is the contact resistance value; Surface roughness coefficient; is the shape factor of the mth contact point; is the resistivity of the contact material; is the effective area of ​​the contact point; is the pressure coefficient; is the deformation of the contact point; is the contact point pressure; is the total number of contact points.

[0036] The surface roughness coefficient μ reflects the microscopic state of the contact surface, and its value range is usually between 0.8 and 1.2. Describes the geometric characteristics of the contact point, which is approximately 1 for a circular contact point and less than 1 for an elliptical contact point. and effective contact area The pressure coefficient ω represents the influence of pressure on contact resistance, and its value is generally in the range of 0.01-0.1. Reflects the deformation state of the contact point and the pressure at the contact point It is a nonlinear relationship. This formula takes into account the combined effect of M independent contact points.

[0037] The nonlinear weighted processing of temperature coefficient compensation data and contact impedance compensation data adopts the following formula:

[0038] in: is the dynamic joint compensation coefficient; is the weight factor of the nth compensation item; is the temperature compensation weight; is the temperature coefficient compensation value; is the contact impedance compensation weight; is the time attenuation coefficient; To compensate for the time interval; The number of compensation items.

[0039] Weight Factor Reflects the importance of different compensation items, with values ​​between 0 and 1. Temperature compensation weight and contact impedance compensation weight The sum of the two compensation mechanisms is 1, reflecting the relative contributions of the two compensation mechanisms. and contact resistance After the n-th power operation, the nonlinear characteristics are reflected. The time attenuation coefficient θ describes the attenuation law of the compensation effect over time. The compensation time interval It reflects the temporal characteristics of the data.

[0040] The piecewise linear fitting and interpolation calculations use the following formula:

[0041] is the multi-channel dynamic calibration compensation coefficient; is the global calibration coefficient; is the piecewise fitting coefficient matrix; is the temperature segmentation coefficient; is the temperature deviation; is the pressure segmentation coefficient; is the pressure deviation.

[0042] Global calibration coefficients Used for overall calibration, usually close to 1. Piecewise fitting coefficient matrix The fitting coefficients of each segment interval are stored. Temperature segment coefficient and pressure segmentation coefficient Respectively reflects the impact of temperature and pressure changes on compensation. Temperature deviation and pressure deviation It indicates the difference between the measured value and the reference value. I and J indicate the number of temperature and pressure segments, respectively, with a typical value of 3-5.

[0043] Taking the equipotential connection measurement of a lightning protection system as an example, 20 measurement channels monitor the ground connection points of different devices respectively. The independent compensation units of the standard resistance network are switched in turn, and the sampling data shows good time interleaving characteristics. The three-axis stress data measured by the piezoelectric stress sensor reflects the stress distribution state of the crimping point after processing. The thermocouple array monitors the temperature change process, and the temperature compensation coefficient is calculated based on this. At the microscopic scale, the contact resistance shows nonlinear characteristics with pressure changes, and the influence of surface roughness and actual contact area needs to be considered. Through nonlinear weighted processing and segmented fitting, an accurate multi-channel dynamic calibration compensation coefficient is established.

[0044] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Through a high-stability current source array, an excitation current with adjustable amplitude is injected into each of the 20 measurement channels. The multi-channel dynamic calibration compensation coefficient is used as the modulation signal to generate a compensated excitation current sequence. (2) Under the action of the compensated excitation current sequence, the voltage sampling points of each measurement channel are differentially collected, and the thermal potential interference is eliminated according to the current reversal method to obtain the original voltage data; (3) Perform synchronous demodulation and digital integration on the raw voltage data, and combine it with the current amplitude information to generate the initial resistance measurement value; (4) The temperature sensor array is used to perform partitioned temperature sampling on the measurement channel, and stress sensing data is synchronously collected at a frequency of 1 kHz to form temperature-stress joint sampling data; (5) Perform time stamp alignment and data synchronization processing on the initial resistance measurement value and the temperature-stress joint sampling data to generate a multi-channel measurement data stream; (6) Perform real-time error compensation and data reconstruction on multi-channel measurement data streams to obtain multiple channels of original measurement data.

[0045] Specifically, a high-stability current source array is used to excite 20 measurement channels. The high-stability current source uses a reference source circuit with a temperature coefficient of less than 1ppm / ℃, an output current range of 10mA-1A, and a resolution of 1μA. The multi-channel dynamic calibration compensation coefficient is used as a modulation signal to adjust the amplitude of the excitation current in real time to compensate for the influence of various error factors, thereby generating a compensated excitation current sequence.

[0046] When performing differential acquisition of the voltage sampling points of each measurement channel, an instrumentation amplifier circuit is used, and the common mode rejection ratio is greater than 120dB. The current reversal method is to periodically change the direction of the excitation current, collect the forward and reverse voltage values, and eliminate the influence of the thermoelectric potential by calculating half of the difference. The sampling frequency is set to 1kHz to ensure sufficient data points for subsequent processing.

[0047] The following formula is used for synchronous demodulation and digital integration of raw voltage data:

[0048] In this formula: is the initial resistance measurement value; is the instrumentation amplifier gain; is the sampling voltage time series; is the synchronous demodulation function; is the weight coefficient of the kth current component; is the amplitude of the kth current component; is the frequency of the kth component; is the integration time constant; T is the integration period; K is the number of current components.

[0049] G reflects the amplification characteristics of the signal conditioning circuit. U(t) is the voltage time series acquired by differential sampling. Synchronous demodulation function Used to extract specific frequency components. The current information part takes into account the superposition effect of multiple components, and each component has its weight The exponential term introduces the effect of the integration time constant.

[0050] The temperature sensor array performs partitioned temperature sampling on the measurement channels, and three temperature measurement points are arranged in each channel to form a temperature gradient monitoring network. The stress sensing data acquisition uses a strain sensor with a sensitivity of 2mV / V. The temperature data and stress data are collected synchronously with a sampling rate of 1kHz to form time-aligned temperature-stress joint sampling data. The timestamp alignment uses a 64-bit timestamp with a resolution of 1μs. The initial resistance measurement value and the temperature-stress joint sampling data are matched according to the timestamp to generate a multi-channel measurement data stream containing complete information. When performing real-time error compensation on the measurement data stream, multiple factors such as temperature gradient effect and mechanical stress influence are considered to obtain multiple channels of original measurement data.

[0051] Taking the equipotential connection system of a 500kV substation as an example, 20 measurement channels monitor the ground connection points of key equipment respectively. A high-stability current source injects 100mA of excitation current into each channel, and the current value is adjusted in real time according to the dynamic calibration compensation coefficient. The voltage sampling adopts a differential method, and the thermoelectric potential interference of about 5μV is eliminated by the current reversal method. The initial resistance value is obtained after synchronous demodulation and integral operation. Temperature monitoring shows the temperature gradient changes of each measuring point, which are synchronously collected together with the stress data. After timestamp alignment and data synchronization processing, a multi-channel measurement data stream is formed, and accurate equipotential connection resistance measurement results are obtained through compensation processing.

[0052] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Divide the multi-channel original measurement data into multiple compensation unit groups according to the spatial position relationship of the measurement channels, and segment the data in each group into time series using a sliding window to obtain a segmented compensation data stream; (2) Calculate the temperature gradient of the segmented compensation data stream, combine the temperature difference coefficient between adjacent channels, generate the temperature distribution feature vector, and perform graded compensation processing according to the temperature change rate to obtain the temperature compensation sequence; (3) Cross-validate the temperature compensation sequence with the stress data to eliminate transient fluctuations caused by mechanical vibration and obtain steady-state compensation data; (4) The common-mode interference components in the steady-state compensation data are separated by the dual-frequency excitation method, and the interference characteristic signals are screened out by combining the data correlation of adjacent channels; (5) Perform amplitude tracking and phase comparison on the interference characteristic signal, identify the abnormal fluctuation component, and generate the interference suppression compensation factor; (6) The interference suppression compensation factor and the steady-state compensation data are adaptively compensated to obtain the equipotential connection resistance value.

[0053] Specifically, according to the physical layout relationship of 20 measurement channels, the multi-channel original measurement data are divided into 4 compensation unit groups, each group contains 5 spatially adjacent measurement channels. A sliding window with a length of 1s and a window overlap rate of 50% is used to segment the data in each group into time series to generate a segmented compensation data stream with time correlation. The temperature gradient calculation is based on the temperature data in the segmented compensation data stream, calculates the temperature difference between adjacent measuring points, and combines the physical distance between the measuring points to obtain the temperature gradient value. The temperature difference coefficient between adjacent channels is obtained by normalization processing, which reflects the spatial distribution characteristics of the temperature field. The temperature distribution feature vector contains information in two dimensions: temperature gradient value and temperature difference coefficient. According to the size of the temperature change rate, the temperature compensation is divided into two levels: fast change compensation and slow change compensation. Different compensation strategies are used to generate a temperature compensation sequence.

[0054] During the cross-validation process, the temperature compensation sequence is compared with the stress data in the time domain. By setting the stress change threshold, the transient stress fluctuation caused by mechanical vibration is identified. When the stress value changes rapidly beyond the threshold, the data of the corresponding time period is marked as a transient fluctuation. After eliminating these transient fluctuations, steady-state compensation data reflecting the stable state is obtained. The dual-frequency excitation method uses two excitation signals with different frequencies, 1kHz and 2kHz respectively. The steady-state compensation data is subjected to spectral analysis to extract the amplitude and phase information of the two frequency components. Since the common-mode interference is consistent in each channel, while the effective signal is different in each channel, the common-mode interference component can be separated by comparing the response characteristics of different channels at two frequencies. Combined with the correlation analysis of the adjacent channel data, the interference characteristic signal is further screened and confirmed.

[0055] The identified interference characteristic signals are processed, and the signal strength changes are tracked through amplitude envelope detection, while phase contrast analysis focuses on the timing characteristics of the signal. The amplitude and phase characteristics of the interference signal are compared with the preset normal range, and the part beyond the range is identified as an abnormal fluctuation component. Based on these abnormal characteristics, the corresponding interference suppression compensation factor is calculated. The adaptive compensation operation adopts a weighted iteration method to apply the interference suppression compensation factor to the steady-state compensation data. During the compensation process, the weight coefficient will be automatically adjusted according to the dynamic characteristics of the data to ensure the accuracy of the compensation. After compensation processing, the equipotential connection resistance value is obtained.

[0056] Taking the equipotential connection measurement of a large industrial equipment as an example, it involves the monitoring of 20 measurement points. These measurement points are divided into 4 groups according to their spatial positions, and each group contains 5 adjacent measurement points. A sliding window with a length of 1s is used to segment the data and generate a time series data stream. Temperature monitoring shows that there is a temperature gradient between adjacent channels, based on which the temperature compensation sequence is calculated. Stress monitoring finds transient fluctuations caused by equipment vibration, which are eliminated through cross-validation. 1kHz and 2kHz dual-frequency excitations are used to separate common mode components such as power frequency interference. Analysis of the interference signal finds abnormal fluctuations, and adaptive compensation is performed after the compensation factor is generated to obtain accurate equipotential connection resistance measurement results.

[0057] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) The equipotential bonding resistance values ​​are grouped by time domain segmentation, and a channel correlation matrix is ​​constructed according to the spatial adjacent relationship of the measurement channels to generate a multidimensional feature data group; (2) Performing difference calculation on the resistance values ​​of adjacent channels in the multidimensional feature data set and combining the measurement timestamp information to obtain a series of resistance change rates between channels; (3) Track the slope of the resistance change rate sequence between channels. When the slope exceeds the preset threshold, trigger the secondary sampling control signal to increase the sampling frequency to 2kHz to obtain a high-frequency sampling data stream. (4) Segment the high-frequency sampling data stream through a sliding time window, extract statistical features from the data in each time window, and generate a feature parameter sequence; (5) Compare the characteristic parameter sequence with historical data, screen out abnormal change intervals, and establish a characteristic map of change trends; (6) State identification and parameter reconstruction are performed based on the characteristic graph of the changing trend to obtain the state parameters of the equipotential connection network.

[0058] Specifically, the equipotential connection resistance value is segmented in the time domain, and a fixed time window of 500ms is used for data grouping. A 5×4-dimensional channel association matrix is ​​constructed according to the spatial layout relationship of the 20 measurement channels, and each element in the matrix represents the spatial distance weight between adjacent channels. The grouped data is transformed through the association matrix to obtain a multidimensional feature data group containing resistance value, spatial position and time information.

[0059] The resistance difference calculation between adjacent channels is based on relative position, and the resistance difference between adjacent channels in the horizontal and vertical directions is calculated. Each set of difference data is accompanied by microsecond-level precision timestamp information to ensure the timing of the data. By calculating the difference within a continuous time window, a resistance change rate sequence reflecting the resistance change trend is obtained.

[0060] The slope tracking of the resistance change rate series uses the following formula:

[0061] in: is the resistance change slope; is the channel position weight coefficient; is the resistance difference between adjacent channels; is the time decay factor; is the reference time; is the spatial distance influence factor; P, Q are the matrix dimensions.

[0062] This formula describes the calculation process of the resistance change slope. The channel position weight coefficient y_p,q reflects the importance of channels at different positions, and its value is between 0 and 1. The time derivative of the resistance difference represents the rate of change. The exponential term introduces the time decay effect, so that the farther the data is from the current moment, the less the impact. The spatial distance impact factor takes into account the influence of the physical distance between channels. When the calculated slope exceeds the preset threshold, the sampling frequency increase mechanism is triggered, and the original 1kHz sampling is increased to 2kHz to obtain more detailed change information.

[0063] The high-frequency sampling data stream is segmented using a sliding time window of 200ms in length, with a window overlap rate of 50%. Statistical features are extracted in each time window, including parameters such as mean, standard deviation, kurtosis and skewness, to form a characteristic parameter sequence. These characteristic parameters reflect the statistical characteristics of the change in resistance value. The characteristic parameter sequence is compared with the stored historical data in time series, and the abnormal change interval is screened out by the set judgment criteria. Cluster analysis is performed on the data in these abnormal intervals to establish a trend characteristic map reflecting the law of change. According to the data distribution characteristics in the trend characteristic map, state identification and parameter reconstruction are performed to obtain the state parameters of the equipotential connection network.

[0064] Taking the equipotential connection system in a certain industrial area as an example, 20 measurement channels are arranged in a 5×4 matrix to monitor the key nodes of the grounding network. The data after time domain segmentation shows spatial correlation, and the resistance value change trend of adjacent channels is consistent. When the contact state of a connection point changes, the resistance change rate exceeds the preset threshold, triggering the high-frequency sampling mode for in-depth analysis. Through feature extraction and historical data comparison, it is found that abnormal changes are mainly concentrated in a specific time period. The trend feature map generated based on this intuitively reflects the evolution of the connection state, providing a basis for maintenance decisions.

[0065] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) Perform multi-window segmentation processing on the equipotential connection network state parameters, establish stability evaluation indicators through inter-window data deviation calculation, and generate channel stability characteristic data; (2) Perform time series correlation analysis on the channel stability characteristic data and the temperature change history data, and obtain the temperature influence characteristic sequence through temperature mutation point detection and temperature drift tracking; (3) Cross-validate the temperature influence feature sequence and stress change historical data, establish a temperature-stress coupling relationship table, and generate multi-dimensional compensation feature quantities; (4) Dynamically weight the multi-dimensional compensation feature quantities and combine them with the spatial position relationship of the measurement channels to form a compensation parameter optimization sequence; (5) Perform error analysis on the compensation parameter optimization sequence through the bidirectional recursive method, and generate compensation parameter correction values ​​by combining the steady-state and transient response characteristics; (6) Iteratively update the compensation parameter correction value and the original compensation parameter to obtain the optimized compensation model parameters.

[0066] Specifically, the state parameters of the equipotential connection network are segmented using three time windows of different lengths, namely 100ms, 200ms and 500ms, and the window overlap rate is set to 50%. The standard deviation and deviation values ​​of the data between adjacent windows are calculated to construct a stability evaluation index matrix. Each element of the index matrix contains information in three dimensions: mean deviation, fluctuation range and trend characteristics, and characteristic data reflecting the stability of each measurement channel is generated based on this. When the channel stability characteristic data is analyzed in time series with the temperature change history data, the sliding window method is used to detect the temperature mutation point. The determination of the temperature mutation point is based on the two parameters of temperature change rate and acceleration. When these two parameters exceed the threshold at the same time, it is marked as a temperature mutation point. Temperature drift tracking focuses on the slow change trend of temperature. By calculating the first-order and second-order derivatives of the temperature curve, the key characteristic points of temperature change are identified, and a characteristic sequence describing the law of temperature influence is obtained.

[0067] The cross-validation of the temperature effect feature sequence and the historical data of stress change adopts data alignment and correlation analysis methods. The two sets of data are aligned by timestamp, and then the correlation coefficients at different time scales are calculated to establish a temperature-stress coupling relationship table. This relationship table reflects the mapping relationship between temperature change and stress change. The temperature-stress coupling model is obtained by polynomial fitting, and then a multidimensional compensation feature quantity containing temperature coefficient, stress coefficient and coupling coefficient is generated. The dynamic weighted fusion of the multidimensional compensation feature quantity takes into account the spatial layout characteristics of the measurement channel. According to the physical distance and connection relationship between the channels, a spatial weight matrix is ​​constructed. The compensation feature quantities are weighted and combined through the weight matrix, and the time attenuation factor is introduced at the same time, so that the recent data has a greater weight, forming an optimization sequence of compensation parameters.

[0068] The bidirectional recursive method performs error analysis on the compensation parameter optimization sequence, including two calculation processes, forward and backward. The forward recursive method calculates the cumulative error, and the backward recursive method finds the error source. The steady-state error is calculated by comparing the steady-state response characteristics at different time points; the transient error is obtained by analyzing the overshoot and adjustment time of the transient response. The correction value of the compensation parameter is generated by combining these two parts of error information. The iterative update process adopts a progressive method to weightedly superimpose the correction value of the compensation parameter with the original compensation parameter. The effect of the parameter update is evaluated after each iteration. When the improvement of multiple consecutive updates is less than the set threshold, the iteration is stopped and the optimized compensation model parameters are output.

[0069] Taking the equipotential connection monitoring of a substation as an example, 20 measurement channels monitor the grounding connection points of main transformers, switch cabinets and other equipment. Through multi-window segmentation processing, it was found that some measurement channels were unstable when the temperature changed drastically. Temperature mutation point detection showed that when the outdoor temperature rose rapidly, the temperature of the equipment casing changed with lag. Stress data analysis showed that temperature changes caused deformation of the metal structure, resulting in changes in contact resistance. Based on these data, a temperature-stress coupling model was constructed. Through dynamic weighted fusion and bidirectional recursive calculation, accurate compensation parameters were obtained, which effectively suppressed the influence of temperature and stress changes on measurement accuracy.

[0070] The above describes the equipotential connection measurement method based on precise low resistance in the embodiment of the present application. The following describes the equipotential connection measurement system based on precise low resistance in the embodiment of the present application. Figure 3 In the embodiment of the present application, an embodiment of an equipotential connection measurement system based on precise low resistance includes: The acquisition module is used to configure the initial parameters of the measurement channels according to the sampling parameters of the high-precision ADC chip and the layout of the temperature sensor to obtain the dynamic compensation parameter database; at the same time, the elastic crimping structure is used to physically connect the 20 measurement channels to obtain mechanical stress compensation data; A calibration module, used to perform time-division multiplexing calibration on the parameters in the dynamic compensation parameter database through a standard resistor network, and obtain multi-channel dynamic calibration compensation coefficients after analyzing the temperature-resistance characteristics and stress-contact resistance characteristics in combination with the mechanical stress compensation data; A measurement module, used to apply compensation current to each measurement channel using an independent excitation source according to the multi-channel dynamic calibration compensation coefficients to perform four-wire measurement, and collect temperature data and stress data at a sampling rate of 1kHz to obtain multi-channel original measurement data; A compensation module, used for performing temperature compensation and stress compensation on the multiple channels of original measurement data through a dynamic compensation processing unit, and analyzing adjacent channel data through a transient interference identification unit to obtain an equipotential connection resistance value; A correlation module, used to perform correlation analysis on data features of adjacent measurement channels according to the equipotential bonding resistance value, increase the sampling frequency when an abnormal trend is detected, and obtain equipotential bonding network status parameters; The evaluation module is used to evaluate the stability of the measurement channel according to the equipotential connection network state parameters, and obtain optimized compensation model parameters based on temperature change and stress change historical data.

[0071] Through the cooperation of the above components, a dynamic compensation parameter database was established by combining high-precision ADC chip sampling with temperature sensor layout. At the same time, an elastic crimping structure was used to realize the physical connection of 20 measurement channels. This design not only ensures the accuracy of data acquisition, but also solves the reliability problem of multi-channel connection. Secondly, a high-precision standard resistor network was used for time-division multiplexing calibration, and combined with the analysis of temperature-resistance characteristics and stress-contact resistance characteristics, the multi-channel dynamic calibration compensation coefficient was obtained, which significantly improved the measurement accuracy. Thirdly, through the design of independent excitation source and 1kHz high-frequency sampling strategy, the synchronous acquisition of temperature data and stress data was realized, providing complete data support for subsequent compensation processing. In terms of data processing, the coordinated use of dynamic compensation processing unit and transient interference identification unit effectively eliminated the influence of various interference factors. In particular, the sampling frequency can be automatically increased when an abnormal trend is detected, which reflects the adaptive characteristics of the scheme. Finally, the continuous optimization of the measurement system was achieved by evaluating the stability of the measurement channel and optimizing the compensation model parameters. At the algorithm level, this solution innovatively combines multiple data processing algorithms, including dynamic compensation algorithm, time division multiplexing algorithm, transient interference identification algorithm, etc. The synergy of these algorithms not only improves the measurement accuracy, but also enhances the anti-interference ability and adaptability of the system. Through the comprehensive application of these technical features, the present invention successfully solves the dynamic interference problem in the measurement of equipotential connection resistance and achieves the technical goal of high-precision, multi-channel, and real-time monitoring.

[0072] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0073] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for measuring equipotential connection based on precise low resistance, characterized in that: The equipotential connection measurement method based on precise low resistance includes: According to the sampling parameters of the high-precision ADC chip and the layout of the temperature sensor, the initial parameter configuration of the measurement channel is performed to obtain the dynamic compensation parameter database; at the same time, the elastic crimping structure is used to physically connect the 20 measurement channels to obtain mechanical stress compensation data; The parameters in the dynamic compensation parameter database are calibrated in time division multiplexing through a standard resistor network, and combined with the mechanical stress compensation data, after temperature-resistance characteristics and stress-contact resistance characteristics analysis, a multi-channel dynamic calibration compensation coefficient is obtained; According to the multi-channel dynamic calibration compensation coefficient, a compensation current is applied to each measurement channel using an independent excitation source to perform four-wire measurement, and temperature data and stress data are collected at a sampling rate of 1 kHz to obtain multi-channel original measurement data; The dynamic compensation processing unit performs temperature compensation and stress compensation on the multiple channels of original measurement data, and the transient interference identification unit analyzes the adjacent channel data to obtain the equipotential connection resistance value; According to the equipotential bonding resistance value, correlation analysis is performed on the data features of adjacent measurement channels, and when an abnormal trend is detected, the sampling frequency is increased to obtain the equipotential bonding network status parameter; According to the equipotential connection network state parameters, the stability of the measurement channel is evaluated, and based on the temperature change and stress change historical data, the optimized compensation model parameters are obtained.

2. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: According to the sampling parameters of the high-precision ADC chip and the layout position of the temperature sensor, the measurement channel is initially configured with parameters to obtain a dynamic compensation parameter database; at the same time, the 20 measurement channels are physically connected using an elastic crimping structure to obtain mechanical stress compensation data, including: The sampling control unit of the high-precision ADC chip sets a sampling frequency of 1kHz, alternately samples standard resistor groups with different resistance values, and combines a 4th-order Butterworth filter to suppress noise in the sampled data to establish benchmark compensation data. The temperature sensors are respectively arranged at the three key nodes of the lead-in end, the middle end and the lead-out end of each measurement channel, and the temperature data sequence is collected by using the three-point temperature difference method, and the temperature gradient distribution data is established after thermodynamic equilibrium calculation; The stress sensing unit integrated in the elastic crimping structure collects three-dimensional stress data of the X-axis, Y-axis and Z-axis, and generates stress-temperature correlation data through thermal stress coupling calculation based on the temperature gradient distribution data; Writing the reference compensation data, the temperature gradient distribution data and the stress-temperature correlation data into the dynamic compensation parameter database according to a hierarchical storage structure through a data fusion processor; An elastic crimping structure with an automatic compensation function is used to crimp and fix 20 measurement channels at a fixed pressure value. The crimping stress value is collected in real time through a built-in strain stress sensor, and the mechanical stress compensation data is generated in combination with stress threshold judgment.

3. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: The parameters in the dynamic compensation parameter database are calibrated in time division multiplexing through a standard resistor network, and combined with the mechanical stress compensation data, after temperature-resistance characteristics and stress-contact resistance characteristics analysis, a multi-channel dynamic calibration compensation coefficient is obtained, including: The standard resistor network is divided into 20 independent compensation units, and the parameters in the dynamic compensation parameter database are polled and switched by adopting a phase interleaved sampling method to generate multi-channel interleaved compensation benchmark data; The piezoelectric stress sensor performs three-dimensional component decomposition on the mechanical stress compensation data, and generates stress-resistance coupling data in combination with the nonlinear deformation characteristics of the elastic crimping structure; Performing gradient temperature compensation on the multi-channel staggered compensation reference data through a thermocouple array, and performing dynamic correction on the temperature change rate to obtain temperature coefficient compensation data; Based on the stress-resistance coupling data, contact resistance characteristics are identified, and micro deformation compensation of the crimping surface is introduced to obtain contact impedance compensation data; Performing nonlinear weighted processing on the temperature coefficient compensation data and the contact impedance compensation data to generate a dynamic joint compensation coefficient; The dynamic joint compensation coefficients are subjected to piecewise linear fitting and interpolation calculation to obtain the multi-channel dynamic calibration compensation coefficients.

4. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: According to the multi-channel dynamic calibration compensation coefficient, a compensation current is applied to each measurement channel using an independent excitation source to perform four-wire measurement, and temperature data and stress data are collected at a sampling rate of 1kHz to obtain multi-channel original measurement data, including: Injecting excitation currents with adjustable amplitudes into 20 measurement channels respectively through a high-stability current source array, using the multi-channel dynamic calibration compensation coefficients as modulation signals, and generating a compensated excitation current sequence; Under the action of the compensated excitation current sequence, differential acquisition is performed on the voltage sampling points of each measurement channel, and the thermal potential interference is eliminated according to the current reversal method to obtain the original voltage data; Performing synchronous demodulation and digital integration operations on the raw voltage data, and combining the current amplitude information to generate an initial resistance measurement value; The temperature sensor array is used to perform partitioned temperature sampling on the measurement channel, and stress sensing data is synchronously collected at a frequency of 1kHz to form temperature-stress joint sampling data; Performing time stamp alignment and data synchronization processing on the initial resistance measurement value and the temperature-stress joint sampling data to generate a multi-channel measurement data stream; Real-time error compensation and data reconstruction are performed on the multi-channel measurement data stream to obtain the multi-channel original measurement data.

5. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: The method of performing temperature compensation and stress compensation on the multiple channels of original measurement data by the dynamic compensation processing unit and analyzing the adjacent channel data by the transient interference identification unit to obtain the equipotential connection resistance value includes: Dividing the multiple channels of original measurement data into a plurality of compensation unit groups according to the spatial position relationship of the measurement channels, and performing time series segmentation on the data in each group through a sliding window to obtain a segmented compensation data stream; Calculating the temperature gradient of the segmented compensation data stream, combining the temperature difference coefficients between adjacent channels to generate a temperature distribution feature vector, and performing hierarchical compensation processing according to the temperature change rate to obtain a temperature compensation sequence; Cross-validating the temperature compensation sequence with stress data to eliminate transient fluctuations caused by mechanical vibration and obtain steady-state compensation data; The common-mode interference components in the steady-state compensation data are separated by a dual-frequency excitation method, and the interference characteristic signals are screened out by combining the data correlation of adjacent channels; Performing amplitude tracking and phase comparison on the interference characteristic signal, identifying abnormal fluctuation components, and generating interference suppression compensation factors; The interference suppression compensation factor and the steady-state compensation data are subjected to an adaptive compensation operation to obtain the equipotential connection resistance value.

6. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: The method of performing correlation analysis on the data features of adjacent measurement channels according to the equipotential connection resistance value, increasing the sampling frequency when an abnormal trend is detected, and obtaining the equipotential connection network state parameters includes: Data grouping of the equipotential connection resistance values ​​is performed by time domain segmentation, a channel correlation matrix is ​​constructed according to the spatial adjacent relationship of the measurement channels, and a multi-dimensional feature data group is generated; Performing difference calculation on the resistance values ​​of adjacent channels in the multi-dimensional feature data group, and combining with the measurement timestamp information, obtaining a resistance change rate sequence between channels; Tracking the slope of the resistance value change rate sequence between the channels, triggering a secondary sampling control signal when the slope exceeds a preset threshold, increasing the sampling frequency to 2kHz, and obtaining a high-frequency sampling data stream; Segmenting the high-frequency sampling data stream through a sliding time window, extracting statistical features from the data in each time window, and generating a feature parameter sequence; Compare the characteristic parameter sequence with historical data, screen out abnormal change intervals, and establish a characteristic map of change trends; State identification and parameter reconstruction are performed according to the change trend characteristic graph to obtain the equipotential connection network state parameters.

7. The equipotential connection measurement method based on precise low resistance according to claim 1 is characterized in that: The stability of the measurement channel is evaluated according to the equipotential connection network state parameters, and the optimized compensation model parameters are obtained based on the temperature change and stress change historical data, including: Performing multi-window segmentation processing on the equipotential connection network state parameters, establishing a stability evaluation index by calculating the data deviation between windows, and generating channel stability characteristic data; Performing time series correlation analysis on the channel stability characteristic data and the temperature change history data, and obtaining the temperature influence characteristic sequence through temperature mutation point detection and temperature drift tracking; Cross-validating the temperature influence characteristic sequence and stress change historical data, establishing a temperature-stress coupling relationship table, and generating a multi-dimensional compensation characteristic quantity; Dynamically weighting and fusing the multi-dimensional compensation feature quantities, and combining the spatial position relationship of the measurement channels to form a compensation parameter optimization sequence; Performing error analysis on the compensation parameter optimization sequence by a bidirectional recursive method, and generating compensation parameter correction values ​​by combining steady-state and transient response characteristics; The compensation parameter correction value and the original compensation parameter are iteratively updated to obtain the optimized compensation model parameter.

8. An equipotential connection measurement system based on precise low resistance, used to implement the equipotential connection measurement method based on precise low resistance as described in any one of claims 1 to 7, characterized in that: The equipotential connection measurement system based on precise low resistance includes: The acquisition module is used to configure the initial parameters of the measurement channels according to the sampling parameters of the high-precision ADC chip and the layout of the temperature sensor to obtain the dynamic compensation parameter database; at the same time, the elastic crimping structure is used to physically connect the 20 measurement channels to obtain mechanical stress compensation data; A calibration module, used to perform time-division multiplexing calibration on the parameters in the dynamic compensation parameter database through a standard resistor network, and obtain multi-channel dynamic calibration compensation coefficients after analyzing the temperature-resistance characteristics and stress-contact resistance characteristics in combination with the mechanical stress compensation data; A measurement module, used to apply compensation current to each measurement channel using an independent excitation source according to the multi-channel dynamic calibration compensation coefficients to perform four-wire measurement, and collect temperature data and stress data at a sampling rate of 1kHz to obtain multi-channel original measurement data; A compensation module, used for performing temperature compensation and stress compensation on the multiple channels of original measurement data through a dynamic compensation processing unit, and analyzing adjacent channel data through a transient interference identification unit to obtain an equipotential connection resistance value; A correlation module, used to perform correlation analysis on data features of adjacent measurement channels according to the equipotential bonding resistance value, increase the sampling frequency when an abnormal trend is detected, and obtain equipotential bonding network status parameters; The evaluation module is used to evaluate the stability of the measurement channel according to the equipotential connection network state parameters, and obtain optimized compensation model parameters based on temperature change and stress change historical data.

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