Accurate measurement method for large current

Abstract

The invention discloses a high-current accurate measurement method, which relates to the technical field of current measurement, and comprises the following steps: obtaining multi-dimensional measurement parameters, carrying out preprocessing, constructing an error model to obtain a comprehensive error, and carrying out calculation based on the comprehensive error to obtain a comprehensive feedback value; based on the comprehensive feedback value, utilizing a closed-loop feedback mechanism to dynamically optimize a compensation parameter, and further utilizing the compensation parameter and the comprehensive feedback value to carry out error correction on the measurement current; real-time measurement parameters are obtained through a built-in sensor and a factory calibration reference model, an error model is constructed, the dynamic closed-loop self-calibration function is achieved, dependence on external calibration equipment is not needed, the problems that a traditional measurement method is high in complexity and high in cost are solved, and the method is suitable for integrated application of a high-precision electric energy meter and industrial measurement equipment and has wide application prospects. And meanwhile, the real-time performance and the convenience of measurement are remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of current measurement, and in particular to a method for accurately measuring large currents. Background Art

[0002] With the rapid development of power systems and industrial measurement technology, high current measurement technology plays an important role in the fields of high-precision energy meters, industrial equipment monitoring and smart grids. In the existing technology, measurement methods based on current transformers, Hall effect sensors or shunts are mostly used, and single-dimensional error correction technologies such as temperature compensation and electromagnetic interference suppression are used to improve measurement accuracy. In addition, some devices implement basic error compensation functions through fixed parameter models or linear calibration algorithms, which provides a certain accuracy guarantee for high current measurement in a stable environment.

[0003] However, there are still some key issues that need to be addressed in the existing technology: First, the existing measurement technology cannot achieve real-time response and precise compensation when faced with dynamic interference from multi-dimensional data (such as current fluctuations, temperature drifts, and load changes), and the measurement results are easily affected by changes in the external environment; second, traditional error compensation algorithms rely on fixed compensation parameters or linear models, ignoring the nonlinear coupling relationship between multi-dimensional inputs, resulting in insufficient error correction accuracy in complex environments; in addition, the measurement equipment relies on external standard calibration devices (such as standard transformers) for error correction, which not only increases the size and cost of the equipment, but also limits its applicability in integrated and portable application scenarios. Therefore, it is urgent to use innovative algorithms and processing technologies to accurately measure large currents. Summary of the invention

[0004] In order to solve the problems that the measurement results of existing measurement technologies are easily affected by changes in the external environment, the error correction accuracy is insufficient in complex environments, the measurement equipment is costly and has poor applicability, and large currents cannot be accurately measured and processed, the purpose of the present invention is to provide a large current accurate measurement method, which can achieve high-precision measurement in a complex environment through error correction.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0006] A method for accurately measuring a large current comprises the following steps:

[0007] Step 1, obtain multi-dimensional measurement parameters for preprocessing, build an error model to obtain a comprehensive error, fuse real-time data based on the comprehensive error, and calculate a comprehensive feedback value;

[0008] The multi-dimensional measurement parameters include measurement values ​​and standard values; the measurement values ​​are the measurement current collected in real time, the ambient temperature collected by the embedded sensor, and the impedance value calculated in real time at the load end; the standard value is the standard current calculated by the embedded standard current model, the reference temperature set during equipment calibration, and the reference impedance calibrated at the factory;

[0009] Step 2, based on the comprehensive feedback value, using a closed-loop feedback mechanism to dynamically optimize the compensation parameters, and further using the compensation parameters and the comprehensive feedback value to perform error correction on the measured current;

[0010] The closed-loop feedback mechanism is a process of iteratively adjusting compensation parameters by acquiring error signals and comprehensive feedback values ​​in real time, which is used to dynamically respond to changes in multi-dimensional inputs and gradually reduce measurement errors;

[0011] The compensation parameters are dynamic variables used to correct measurement errors. The updating and optimization of the compensation parameters determine the accuracy and reliability of the final measurement results. The dynamic optimization of the compensation parameters is a process of adjusting the compensation parameters in real time by combining the comprehensive feedback value and the error change rate. By integrating the historical state, the comprehensive feedback value and the error change rate, the compensation parameters can be adaptively optimized in the closed-loop regulation to adapt to the complex changes of multi-dimensional inputs and ensure accurate error correction.

[0012] Preferably, the error model is as follows:

[0013]

[0014] Among them, E is the comprehensive error, which reflects the comprehensive influence of measurement current deviation, temperature drift and load impedance change on measurement accuracy; k1 is the current deviation weight coefficient, which indicates the influence weight of current deviation on comprehensive error; ΔI is the current deviation, which indicates the deviation between the measurement current and the standard current; k2 is the temperature deviation weight coefficient, which indicates the influence weight of temperature deviation on comprehensive error; ΔT is the temperature deviation, which indicates the deviation between the current temperature and the reference temperature, reflecting the influence of ambient temperature change on measurement error; k3 is the load impedance deviation weight coefficient, which indicates the influence weight of load impedance deviation on comprehensive error; ΔR is the load impedance deviation, which indicates the deviation between the current load impedance and the reference load impedance, reflecting the influence of actual load change on measurement error.

[0015] Further preferably, when compensating for the comprehensive error of multi-dimensional measurement parameters, it is achieved by determining the weight coefficient of each deviation in the error model; the weight coefficient determines the specific influence ratio of current deviation, temperature deviation and load impedance deviation on the comprehensive error.

[0016] Further preferably, when compensating for the comprehensive error of the multi-dimensional measurement parameters, the standard deviation of the deviation is used to characterize the fluctuation range of each parameter, and a weight calculation formula is designed through a nonlinear combination of a logarithmic function, a square root and an exponential term. The specific weight calculation formula is:

[0017]

[0018] Among them, k i is the weight coefficient of the i-th parameter, indicating the influence of the parameter on the comprehensive error; i and j are parameter index variables, indicating the current deviation, temperature deviation and load impedance deviation; η i is the weight balance factor of the i-th parameter, which is used to adjust the influence of the i-th parameter on the weight. It is set based on expert experience according to experimental calibration or simulation results, reflecting the actual importance of the parameter to the comprehensive error; σ i is the standard deviation of the ith parameter, which is calculated based on historical measurement data and reflects the fluctuation characteristics of the parameter, and n is the total number of parameters; η j is the weight balancing factor of the jth parameter; σ j is the standard deviation of the jth parameter.

[0019] Preferably, the calculation formula of the comprehensive feedback value is:

[0020]

[0021] Where X is the comprehensive feedback value after integrating multi-dimensional input variables and error information, which is used for subsequent closed-loop feedback control and adjustment of compensation parameters; I m is the measured current; E is the comprehensive error value; T is the ambient temperature, which is the real-time temperature value in the measured environment; R is the impedance value; R s is the reference impedance; and the multi-dimensional input variables are current, voltage, temperature and impedance.

[0022] Preferably, the updating formula of the compensation parameter is as follows:

[0023]

[0024] Among them, θ k+1 is the compensation parameter at the next moment, which is determined by the current compensation parameter θ k It is obtained after closed-loop feedback adjustment and is used to correct the current measurement error; θ k is the compensation parameter at the current moment, and its initial value is set to 1; k is the current iteration step number, and is the time step index variable; e is a natural constant; is an exponential scaling term used to dynamically adjust the compensation parameter θ k ; λ is the comprehensive adjustment coefficient, which is used to balance the influence of error gradient and feedback signal on compensation parameters and is obtained through experimental tuning; is the error gradient, which indicates the degree of influence of the compensation parameter change on the error; sin(λ·X) is the sinusoidal period adjustment term of the fusion feedback, which is used to increase the dynamic response capability to the feedback data; X is the comprehensive feedback value, which indicates the comprehensive state change of multi-dimensional data, and the multi-dimensional data is current, temperature or load; log(1+X 2 ) is a logarithmic enhancement term for high-order feedback, which is used to enhance the effect of larger feedback values ​​on the compensation parameters while smoothing small changes in feedback values.

[0025] Preferably, the error correction formula is:

[0026]

[0027] Among them, I c is the correction current value, indicating the final measurement result after error correction; I m is the measured current value; θ k+ is the compensation parameter, which is the latest updated compensation parameter in the closed-loop feedback control, indicating the current correction strength of the error; ζ is the nonlinear scaling factor, which is a scaling factor used to control the influence of the feedback value on the correction formula; a larger nonlinear scaling factor will enhance the response to the feedback value, and vice versa. The nonlinear scaling factor is based on the measured current, temperature, impedance and comprehensive error data, and the error response model is established through COMSOL multi-physics field simulation, and the genetic algorithm is used to optimize the minimization of the correction error. The calculation of the nonlinear scaling factor adopts the existing technology, which will not be elaborated here; X is the comprehensive feedback value.

[0028] Preferably, step 3 is also included, verifying the accuracy of the correction current value, comparing the correction current value with the reference standard current value, calculating the error and confirming whether it is within the design requirement range; if the correction current value does not meet the requirement, the compensation parameters are optimized again through a closed-loop feedback mechanism until the correction result meets the accuracy requirement.

[0029] Further preferably, the method further includes step 4, wherein after the measurement result output is completed, the measurement process is summarized, and when the correction current value meets the accuracy requirement, the final compensation parameter, correction current value and comprehensive feedback value are recorded.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] The present invention obtains real-time measurement parameters through built-in sensors and factory-calibrated reference models, and constructs an error model, thereby realizing a dynamic closed-loop self-calibration function without relying on external calibration equipment. This solves the problems of high complexity and high cost of traditional measurement methods, and is suitable for the integrated application of high-precision electric energy meters and industrial measurement equipment, while significantly improving the real-time and convenience of measurement.

[0032] The present invention is based on the fluctuation characteristics of multi-dimensional measurement parameters (current, temperature, load impedance) and a nonlinear weight calculation method, dynamically adjusts the comprehensive feedback value, optimizes the compensation parameters through a closed-loop feedback mechanism, and can adapt to the interference of complex dynamic environments such as temperature drift and load changes in real time, ensuring high measurement accuracy within the full range.

[0033] By designing a nonlinear error compensation formula based on logarithmic functions, square roots and exponential terms, the present invention achieves higher flexibility and accuracy in weight allocation, feedback optimization and error correction. The correction formula introduces comprehensive feedback values ​​and dynamic compensation parameters, which can balance large and small errors, effectively improve measurement accuracy and stability, and adapt to complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of a method for accurately measuring large currents according to the present invention;

[0035] Figure 2 The line graph of relative error measured by this method when the current is 10A to 1000A. DETAILED DESCRIPTION

[0036] The purpose of the present invention is to provide a method for accurately measuring large currents. The present invention is further described below in conjunction with specific embodiments.

[0037] Example 1

[0038] A method for accurate measurement of large currents, such as Figure 1 As shown, the following steps are included:

[0039] Step 1, obtain multi-dimensional measurement parameters for preprocessing, construct an error model to obtain a comprehensive error, and calculate a comprehensive feedback value based on the comprehensive error;

[0040] First, through built-in sensors (such as Hall current sensors, temperature sensors), built-in circuit modules (impedance detection modules) and factory-calibrated reference models, multi-dimensional measurement parameters are obtained in real time, and the parameters are divided into measured values ​​and standard values. The factory-calibrated reference model is a reference data model built into the measuring device after precise calibration at the factory, including a standard current model, a reference temperature and a reference impedance, etc., which is used to provide accurate reference values ​​in actual measurements and realize a dynamic closed-loop self-calibration function. The measured value includes the measured current collected in real time, the ambient temperature collected by the embedded sensor, and the impedance value calculated in real time at the load end; the standard value includes the standard current calculated by the embedded standard current model, the reference temperature set during equipment calibration, and the reference impedance calibrated at the factory. The above-mentioned measured values ​​and standard values ​​are preprocessed to construct an error model. The preprocessing is a technique well known to those skilled in the art, including filtering and denoising, data normalization and outlier removal to ensure the stability and consistency of the data.

[0041] Next, the preprocessed data is subjected to error analysis, and an error model is established to achieve quantitative calculation and compensation of the comprehensive error. The error model is used to quantify the comprehensive influence of multi-dimensional measurement parameters on measurement accuracy, and to provide a theoretical basis for the optimization of compensation parameters and the correction of measurement errors by establishing a mathematical relationship between actual deviation and comprehensive error.

[0042] The error model is as follows:

[0043]

[0044] Where E is the comprehensive error, which reflects the comprehensive influence of measurement current deviation, temperature drift and load impedance change on measurement accuracy; k1 is the current deviation weight coefficient, which indicates the influence weight of current deviation on comprehensive error; ΔI m is the current deviation, which is the deviation between the measured current and the standard current; k2 is the temperature deviation weight coefficient, which indicates the weight of the temperature deviation on the comprehensive error; ΔT is the temperature deviation, which is the deviation between the current temperature and the reference temperature, reflecting the influence of the ambient temperature change on the measurement error; k3 is the load impedance deviation weight coefficient, which indicates the weight of the load impedance deviation on the comprehensive error; ΔR is the load impedance deviation, which is the deviation between the current load impedance and the reference load impedance, reflecting the influence of the actual load change on the measurement error;

[0045] Table 1 shows the value range of each parameter in the actual error model

[0046] Parameter name Value range Current deviation weight coefficient k 0.1-1.0 Current deviation ΔI ±0.1％-±5％ Temperature deviation weight coefficient k 0.01-0.1 Temperature deviation ΔT ±0.1℃-±10℃ Load impedance deviation weight coefficient k 0.1-1.0 Load impedance deviation ΔR ±0.5％-±10％ Comprehensive error E ±0.01％-±5％

[0047] In order to achieve comprehensive error compensation for multi-dimensional measurement parameters, it is necessary to determine the weight coefficients k1, k2, and k3 of each deviation in the error model. The weight coefficients determine the specific impact ratio of current deviation, temperature deviation, and load impedance deviation on the comprehensive error. Since multi-dimensional parameters have different fluctuation characteristics and environmental dependence, the determination of weight coefficients needs to be combined with historical data, simulation analysis, and the statistical characteristics of real-time parameters to achieve dynamic adaptation and precise quantification.

[0048] To this end, the standard deviation of the deviation is used to characterize the fluctuation range of each parameter, and the weight calculation formula is designed through the nonlinear combination of logarithmic function, square root and exponential term. The weight calculation formula can not only reflect the nonlinear characteristics of the fluctuation of each parameter, but also enhance the control ability of high fluctuation parameters through normalization processing and exponential decay, thereby ensuring the rationality of weight distribution. The specific weight calculation formula is as follows:

[0049]

[0050] Among them, k i is the weight coefficient of the i-th parameter, indicating the influence of the parameter on the comprehensive error; i and j are parameter index variables, indicating the current deviation, temperature deviation and load impedance deviation; η i is the weight balance factor of the i-th parameter, which is used to adjust the influence of the i-th parameter on the weight. It is set based on expert experience according to experimental calibration or simulation results, reflecting the actual importance of the parameter to the comprehensive error; σ i is the standard deviation of the deviation of the i-th parameter, which is calculated based on the statistics of historical measurement data and reflects the fluctuation characteristics of the parameter. The historical measurement data is the measurement value within the time range selected by expert experience, combined with the sampling frequency of the measurement equipment and the actual application scenario, to reflect the typical characteristics and change laws of parameter fluctuations; n is the total number of parameters; η j is the weight balancing factor of the jth parameter; σ j is the standard deviation of the jth parameter.

[0051] Table 2 shows the parameter value ranges in the specific weight calculation formula

[0052]

[0053]

[0054] The weight calculation calculates the weight coefficients of current deviation, temperature deviation and load impedance deviation to ensure that the contribution ratio of each parameter in the comprehensive error calculation is consistent with the actual fluctuation characteristics, providing a reliable basis for subsequent error compensation and feedback control.

[0055] The real-time data (including the measured current, ambient temperature and load impedance) and the comprehensive error information are integrated to generate a comprehensive feedback value. The comprehensive feedback value is an indicator after the multi-dimensional measurement parameters and the comprehensive error are integrated, which is used to reflect the measurement status in real time, guide error compensation and measurement correction, and improve accuracy and stability.

[0056] The comprehensive feedback value calculation formula is as follows:

[0057]

[0058] Where X is the comprehensive feedback value after integrating multi-dimensional input variables (current, voltage, temperature, impedance) and error information, which is used for subsequent closed-loop feedback control and adjustment of compensation parameters; I m is the measured current; E is the comprehensive error value; T is the ambient temperature, which is the real-time temperature value in the measured environment; R is the impedance value; R s is the reference impedance.

[0059] Table 3 shows the parameter value range in the comprehensive feedback value calculation formula

[0060] Parameter name Value range Measuring current I 0.1A-1000A Comprehensive error value E ±0.01％-±5％ Ambient temperature T -40℃-85℃ Impedance R 0.1Ω-1000Ω Reference impedance R 1Ω-1000Ω Comprehensive feedback value X 0-1000

[0061] The comprehensive feedback value calculation formula generates a single comprehensive feedback value by fusing multiple real-time data sources and error feedback, thereby improving the responsiveness to multi-dimensional input changes.

[0062] Step 2: Based on the comprehensive feedback value, the closed-loop feedback mechanism is used to dynamically optimize the compensation parameters, and the compensation parameters and the comprehensive feedback value are further used to perform error correction on the measured current.

[0063] Based on the comprehensive feedback value, the compensation parameters are dynamically optimized through a closed-loop feedback mechanism to achieve real-time response to changes in multi-dimensional inputs, thereby effectively improving measurement accuracy. The closed-loop feedback mechanism is a process of iteratively adjusting the compensation parameters by acquiring error signals and comprehensive feedback values ​​in real time, which is used to dynamically respond to changes in multi-dimensional inputs and gradually reduce measurement errors; the compensation parameters are dynamic variables used to correct measurement errors, and the updating and optimization of the compensation parameters determine the accuracy and reliability of the final measurement results; the dynamic optimization of the compensation parameters is a process of adjusting the compensation parameters in real time by combining the comprehensive feedback value and the error change rate. By integrating the historical state, the comprehensive feedback value and the error change rate, the compensation parameters can be adaptively optimized in the closed-loop adjustment to adapt to the complex changes in the multi-dimensional inputs and ensure accurate error correction.

[0064] The compensation parameter update formula is as follows:

[0065]

[0066] Among them, θ k+1is the compensation parameter at the next moment, which is determined by the current compensation parameter θ k It is obtained after closed-loop feedback adjustment and is used to correct the current measurement error; θ k is the compensation parameter at the current moment, and its initial value is set to 1:; k is the current iteration step number, is the time step index variable; e is a natural constant; is an exponential scaling term used to dynamically adjust the compensation parameter θ k ; λ is the comprehensive adjustment coefficient, which is used to balance the influence of error gradient and feedback signal on compensation parameters and is obtained through experimental tuning; is the error gradient, which indicates the influence of compensation parameter change on the error; sin(λ·X) is the sinusoidal period adjustment item of fusion feedback, which is used to increase the dynamic response capability of feedback data; X is the comprehensive feedback value, which indicates the comprehensive state change of multi-dimensional data (current, temperature, load); log(1+X 2 ) is a logarithmic enhancement term for high-order feedback, which is used to enhance the effect of larger feedback values ​​on the compensation parameters while smoothing small changes in feedback values.

[0067] Table 4 Parameter value ranges in compensation parameter update formula

[0068]

[0069] The compensation parameter update formula introduces an exponential scaling mechanism, which can respond sensitively to changes in errors. The sinusoidal period adjustment method enhances the adaptability to environmental fluctuations. The high-order logarithmic enhancement design effectively balances the influence of large-amplitude and small-amplitude feedback signals, making the compensation adjustment smoother and more stable, and improving the response speed and measurement accuracy in complex dynamic environments.

[0070] The compensation parameters and comprehensive feedback values ​​are used to correct the error of the measured current to obtain the final correction result. The introduction of the comprehensive feedback value enables the measurement process to quickly respond to multi-dimensional environmental changes and effectively reduce error accumulation through dynamic iteration. The adjusted compensation parameters further improve the correction accuracy. By substituting the adjusted compensation parameters into the correction formula, the deviation of the actual measured value can be accurately corrected. In a complex dynamic environment, high stability and accuracy are ensured, providing reliable guarantee for the final measurement result.

[0071] The correction formula is as follows:

[0072]

[0073] Among them, I c is the correction current value, indicating the final measurement result after error correction; I m is the measured current value; θ k+1is the compensation parameter, which is the latest updated compensation parameter in the closed-loop feedback control, indicating the current correction strength of the error; ζ is the nonlinear scaling factor, which is used to control the scaling factor of the feedback value's influence on the correction formula. A larger nonlinear scaling factor will enhance the response to the feedback value, and vice versa. The nonlinear scaling factor is based on the measured current, temperature, impedance and comprehensive error data, and the error response model is established through COMSOL multi-physics field simulation. The nonlinear scaling factor is optimized by using a genetic algorithm with the goal of minimizing the correction error. The calculation of the nonlinear scaling factor adopts the existing technology, which will not be described here; X is the comprehensive feedback value.

[0074] Table 5 Parameter value ranges in the correction formula

[0075] Parameter name Value range Measured current value I 0.1A-1000A Compensation parameter θ 0-10 Nonlinear scaling factor ζ 0.01-1.0 Comprehensive feedback value X 0–1000 Correction current value I 0.1A-1000A

[0076] The correction formula closely combines the dynamically changing feedback information with the error correction through a nonlinear adjustment mechanism, achieving rapid response to environmental changes and continuous optimization of measurement accuracy. It can effectively improve the flexibility and accuracy of error correction and adapt to complex working conditions.

[0077] Example 2

[0078] A high current precision measurement method, based on the steps of embodiment 1, further includes the following steps:

[0079] Step 3, verify the accuracy of the corrected current value, compare the corrected current value with the reference standard current value, calculate the error and confirm whether it is within the design requirement range (such as 0.05%). If the corrected current value does not meet the requirements, the compensation parameters are optimized again through a closed-loop feedback mechanism. Specifically, the above method is used to recalculate the comprehensive feedback value and error gradient, dynamically adjust the compensation parameters, and recalibrate the measured current according to the updated compensation parameters. The error is gradually reduced through multiple iterations until the correction result meets the accuracy requirements. The corrected measurement result is applied to the actual scenario as the final output.

[0080] like Figure 2 The relative error line graph of the method for measuring 10A to 1000A shows that the relative error of the method is within ±0.25‰ in the measurement of large currents of 10 to 1000A.

[0081] Step 4: After the measurement results are output, summarize the measurement process. When the correction current value meets the accuracy requirements, record the final compensation parameters, correction current value and comprehensive feedback value. By recording and analyzing the compensation parameters and correction data, a reference basis can be provided for subsequent optimization and expansion of applications.

[0082] Example 3

[0083] The high current accurate measurement method of Example 1 was used to accurately measure the high current output, and the results are shown in Tables 6 to 10.

[0084] Table 6 shows the values ​​of various parameters in the actual error model

[0085] Parameter name Actual value Current deviation weight coefficient k 0.5 Current deviation ΔI ±1％ Temperature deviation weight coefficient k 0.05 Temperature deviation ΔT ±5℃ Load impedance deviation weight coefficient k 0.5 Load impedance deviation ΔR ±1％ Comprehensive error E ±0.45％

[0086] Table 7 shows the parameter values ​​in the specific weight calculation formula. In Table 6, k1, k2, and k3 are the initially set weight coefficient values. In Table 7, k1, k2, and k3 are the values ​​dynamically adjusted through the closed-loop feedback mechanism. The two sets of values ​​can be the same.

[0087] Table 7 shows the parameter values ​​in the specific weight calculation formula

[0088] Parameter name Actual value Weight balance factor η of current deviation 1.0 Weight balance factor η of temperature deviation 0.5 Weight balancing factor η of load impedance deviation 1.0 The standard deviation of the current deviation σ 0.1A Standard deviation of temperature deviation σ 1.0℃ Standard deviation of load impedance deviation σ 1.0Ω <![CDATA[Weight coefficient k1 of current deviation]]> 0.5 <![CDATA[Weight coefficient k2 of temperature deviation]]> 0.05 <![CDATA[Weight coefficient k3 for load impedance deviation]]> 0.5

[0089] Table 8 shows the parameter values ​​in the comprehensive feedback value calculation formula

[0090] Parameter name Actual value Measuring current I 600A Comprehensive error value E ±0.45％ Ambient temperature T 35℃ Impedance R 500Ω Reference impedance R 300Ω Comprehensive feedback value X 358.36

[0091] Table 9 Parameter values ​​in compensation parameter update formula

[0092]

[0093]

[0094] Table 10 Parameter values ​​in the correction formula

[0095] Parameter name Actual value Measured current value I 600A Compensation parameter θ 0.05 Nonlinear scaling factor ζ 0.05 Comprehensive feedback value X 358.36 Correction current value I 599.0A

[0096] It can be seen from the results of Tables 6 to 10 that the present invention has higher flexibility and accuracy in weight allocation, feedback optimization and error correction. The correction formula introduces comprehensive feedback values ​​and dynamic compensation parameters to achieve balanced correction of large current measurement errors, effectively improve measurement accuracy and stability, and adapt to complex working conditions.

Claims

1. A method for accurate measurement of large current, characterized by: The following steps are involved: Step 1, obtain multi-dimensional measurement parameters for preprocessing, build an error model to obtain a comprehensive error, fuse real-time data based on the comprehensive error, and calculate a comprehensive feedback value; The multi-dimensional measurement parameters include measurement values ​​and standard values; the measurement values ​​are the measurement current collected in real time, the ambient temperature collected by the embedded sensor, and the impedance value calculated in real time at the load end; the standard value is the standard current calculated by the embedded standard current model, the reference temperature set during equipment calibration, and the reference impedance calibrated at the factory; Step 2, based on the comprehensive feedback value, using a closed-loop feedback mechanism to dynamically optimize the compensation parameters, and further using the compensation parameters and the comprehensive feedback value to perform error correction on the measured current; The closed-loop feedback mechanism is a process of iteratively adjusting compensation parameters by acquiring error signals and comprehensive feedback values ​​in real time, which is used to dynamically respond to changes in multi-dimensional inputs and gradually reduce measurement errors; The compensation parameters are dynamic variables used to correct measurement errors. The updating and optimization of the compensation parameters determine the accuracy and reliability of the final measurement results. The dynamic optimization of the compensation parameters is a process of adjusting the compensation parameters in real time by combining the comprehensive feedback value and the error change rate. By integrating the historical state, the comprehensive feedback value and the error change rate, the compensation parameters can be adaptively optimized in the closed-loop regulation to adapt to the complex changes of multi-dimensional inputs and ensure accurate error correction.

2. A high current precision measurement method according to claim 1, characterized in that: The error model is as follows: Among them, E is the comprehensive error, which reflects the comprehensive influence of measurement current deviation, temperature drift and load impedance change on measurement accuracy; k1 is the current deviation weight coefficient, which indicates the influence weight of current deviation on comprehensive error; ΔI is the current deviation, which indicates the deviation between the measurement current and the standard current; k2 is the temperature deviation weight coefficient, which indicates the influence weight of temperature deviation on comprehensive error; ΔT is the temperature deviation, which indicates the deviation between the current temperature and the reference temperature, reflecting the influence of ambient temperature change on measurement error; k3 is the load impedance deviation weight coefficient, which indicates the influence weight of load impedance deviation on comprehensive error; ΔR is the load impedance deviation, which indicates the deviation between the current load impedance and the reference load impedance, reflecting the influence of actual load change on measurement error.

3. A high current precision measurement method according to claim 2, characterized in that: When compensating for the comprehensive error of multi-dimensional measurement parameters, it is achieved by determining the weight coefficient of each deviation in the error model; the weight coefficient determines the specific influence ratio of current deviation, temperature deviation and load impedance deviation on the comprehensive error.

4. A high current precision measurement method according to claim 2, characterized in that: When compensating for the comprehensive errors of multi-dimensional measurement parameters, the standard deviation of the deviation is used to characterize the fluctuation range of each parameter, and a weight calculation formula is designed through a nonlinear combination of logarithmic function, square root and exponential term. The specific weight calculation formula is: Among them, k i is the weight coefficient of the i-th parameter, indicating the influence of the parameter on the comprehensive error; i and j are parameter index variables, indicating current deviation, temperature deviation and load impedance deviation; η i is the weight balancing factor of the i-th parameter, which is used to adjust the influence of the i-th parameter on the weight; σ i is the standard deviation of the ith parameter, which is calculated based on historical measurement data and reflects the fluctuation characteristics of the parameter, and n is the total number of parameters; η j is the weight balancing factor of the jth parameter; σ j is the standard deviation of the jth parameter.

5. A high current precision measurement method according to claim 1, characterized in that: The calculation formula of the comprehensive feedback value is: Where X is the comprehensive feedback value after integrating multi-dimensional input variables and error information, which is used for subsequent closed-loop feedback control and adjustment of compensation parameters; I m is the measured current; E is the comprehensive error value; T is the ambient temperature, which is the real-time temperature value in the measured environment; R is the impedance value; R s is the reference impedance; and the multi-dimensional input variables are current, voltage, temperature and impedance.

6. A high current precision measurement method according to claim 1, characterized in that: The update formula of the compensation parameters is as follows: Among them, θ k+1 is the compensation parameter at the next moment, which is determined by the current compensation parameter θ k It is obtained after closed-loop feedback adjustment and is used to correct the current measurement error; θ k is the compensation parameter at the current moment, and its initial value is set to 1; k is the current iteration step number, and is the time step index variable; e is a natural constant; is an exponential scaling term used to dynamically adjust the compensation parameter θ k ; λ is the comprehensive adjustment coefficient, which is used to balance the influence of error gradient and feedback signal on compensation parameters and is obtained through experimental tuning; is the error gradient, which indicates the degree of influence of the compensation parameter change on the error; sin(λ·X) is the sinusoidal period adjustment term of the fusion feedback, which is used to increase the dynamic response capability to the feedback data; X is the comprehensive feedback value, which indicates the comprehensive state change of multi-dimensional data, and the multi-dimensional data is current, temperature or load; log(1+X 2 ) is a logarithmic enhancement term for high-order feedback, which is used to enhance the effect of larger feedback values ​​on the compensation parameters while smoothing small changes in feedback values.

7. A high current precision measurement method according to claim 1, characterized in that: The error correction formula is: Among them, I c is the correction current value, indicating the final measurement result after error correction; I m is the measured current value; θ k+1 is the compensation parameter, which is the latest updated compensation parameter in the closed-loop feedback control and represents the current correction strength of the error; ζ is the nonlinear scaling factor, which is used to control the scaling factor of the influence of the feedback value on the correction formula; X is the comprehensive feedback value.

8. A high current precision measurement method according to claim 1, characterized in that: It also includes step 3, verifying the accuracy of the correction current value, comparing the correction current value with the reference standard current value, calculating the error and confirming whether it is within the design requirement range; if the correction current value does not meet the requirement, the compensation parameters are optimized again through a closed-loop feedback mechanism until the correction result meets the accuracy requirement.

9. A high current precision measurement method according to claim 8, characterized in that: The method also includes step 4, in which the measurement process is summarized after the measurement result output is completed, and when the correction current value meets the accuracy requirement, the final compensation parameter, correction current value and comprehensive feedback value are recorded.

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