Tmr current acquisition self-calibration error compensation method, device, equipment and medium

Abstract

This invention relates to a method, apparatus, device, and medium for self-calibration error compensation in TMR current acquisition. The method dynamically injects a reference signal into the TMR current acquisition circuit through a built-in standard signal excitation source module; synchronously acquires the mixed response of the original signal and the reference signal; separates the original signal and the reference signal in the mixed response using digital signal processing technology to obtain the measured values ​​of the original signal and the reference signal; analyzes the difference between the measured values ​​of the reference signal and the reference signal in real time, establishes a multi-dimensional error vector, and obtains a dynamic error compensation matrix. The dynamic error compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term, with adaptive weight coefficients for each term determined based on the signal-to-noise ratio, phase difference, and frequency, respectively; and dynamically corrects the measured value of the original signal based on the dynamic error compensation matrix to achieve adaptive error compensation. Compared with existing technologies, this invention has advantages such as the ability to achieve adaptive calibration.

Description

Technical Field

[0001] This invention relates to the field of TMR current monitoring, and in particular to a method, apparatus, equipment and medium for compensating for TMR current acquisition self-calibration error. Background Technology

[0002] Against the backdrop of rapid development of smart grids and digital transformation of power systems, real-time and accurate monitoring of transmission line operating status has become a key link in ensuring the safe and stable operation of the power grid. This necessitates that current monitoring technology support refined energy efficiency management. However, traditional current monitoring technology faces severe reliability challenges. Existing sensors typically operate on a "fit and call" basis, lacking an effective self-calibration mechanism throughout their entire lifecycle from commissioning to decommissioning. In actual operation, due to time-varying material properties, environmental interference, and accumulated measurement errors, monitoring accuracy continuously deteriorates, directly affecting the reliability of monitoring data. Chinese patent CN120507702A designs a calibration and testing system for three-phase TMR current sensors, integrating calibration and testing mode switching devices. By controlling mode switching through the test host, combined with current chip calibration equipment, current generation and commutation devices, and data acquisition equipment, convenient calibration and testing of current sensors can be achieved. However, this method requires current commutation during testing, affecting normal measurement processes, and manual calibration is required, making adaptive calibration impossible. Therefore, there is currently a lack of a simple, adaptive self-calibration error compensation method for TMR current sensors that does not affect the measurement process. Summary of the Invention

[0003] The purpose of this invention is to overcome the defects of the prior art and provide a TMR current acquisition self-calibration error compensation method, device, equipment and medium.

[0004] The objective of this invention can be achieved through the following technical solutions:

[0005] According to a first aspect of the present invention, a method for self-calibration error compensation in TMR current acquisition is provided. This method dynamically injects a reference signal with known characteristics into the TMR current acquisition circuit through a built-in standard signal excitation source module; synchronously acquires the mixed response of the original signal and the reference signal using a high-precision sampling circuit; separates the original signal and the reference signal in the mixed response based on digital signal processing technology to obtain the measured values ​​of the original signal and the reference signal; analyzes the difference between the measured values ​​of the reference signal and the reference signal in real time to establish a multi-dimensional error vector, thereby obtaining a dynamic error compensation matrix. The dynamic error compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term. The adaptive weight coefficients of the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term are determined based on the signal-to-noise ratio, the phase difference, and the frequency, respectively; and dynamically corrects the measured value of the original signal based on the dynamic error compensation matrix to achieve adaptive error compensation.

[0006] The multidimensional error vector is represented as follows:

[0007] ;

[0008] in, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... Indicates the amplitude of the reference signal. This represents the amplitude of the reference signal measurement. Indicates the phase of the reference signal. Indicates the phase of the reference signal measurement. Indicates the harmonic order. Indicates the reference signal number The amplitude of the second harmonic. Indicates the reference signal measurement value of the first The amplitude of the subharmonic.

[0009] The dynamic compensation matrix is ​​expressed as follows:

[0010] ;

[0011] in, For dynamic compensation matrix, To compensate for the amplitude term, To compensate for the phase term, To compensate for harmonic distortion, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... , , These are the adaptive weighting coefficients for the compensation amplitude term, compensation phase term, and compensation harmonic distortion term, respectively.

[0012] The method for calculating the adaptive weight coefficients is as follows:

[0013] ;

[0014] ;

[0015] ;

[0016] in, , , These are the adaptive weighting coefficients for the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term, respectively. For signal-to-noise ratio, The phase error between the reference signal and the measured value of the reference signal. For frequency, , , , , , The coefficients are all greater than 0, and , , , , , .

[0017] According to a second aspect of the present invention, a TMR current acquisition self-calibration error compensation device is provided, the device comprising:

[0018] The TMR sensing module is used for TMR current acquisition.

[0019] A standard signal excitation source module is used to dynamically inject a reference signal with known characteristics into the TMR current acquisition circuit.

[0020] A high-precision sampling circuit is used to synchronously acquire the mixed response of the original signal and the reference signal;

[0021] The signal processing module is used to perform preliminary processing on the acquired mixed responses;

[0022] The main control MCU is used to separate the original signal and reference signal in the pre-processed mixed response based on digital signal processing technology, obtaining the original signal measurement value and the reference signal measurement value; it analyzes the difference between the reference signal and the reference signal measurement value in real time, establishes a multi-dimensional error vector, and obtains an error dynamic compensation matrix. The error dynamic compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term. The adaptive weight coefficients of the compensation amplitude term, compensation phase term, and compensation harmonic distortion term are determined based on the signal-to-noise ratio, phase difference, and frequency, respectively; it is used to dynamically correct the original signal measurement value based on the error dynamic compensation matrix to achieve adaptive error compensation.

[0023] According to a third aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method described thereon.

[0024] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described thereon.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] This invention achieves self-correction through innovations in both hardware and algorithm applications, eliminating the influence of errors caused by time-varying materials and limitations imposed by equipment installation methods and operating environments. Specifically, it possesses the following advantages and effects:

[0027] (1) By using a built-in reference signal source and dynamic compensation algorithm, a complete closed-loop system from signal acquisition and error analysis to real-time correction is constructed, breaking through the technical limitations of traditional measurement equipment that relies on external calibration. The system performs periodic closed-loop calibration to ensure that the measurement accuracy is maintained at ±0.1% throughout its entire life cycle.

[0028] (2) Multidimensional dynamic compensation technology innovatively integrates the three-dimensional error vector of amplitude-phase-harmonic and adopts an adaptive weighting algorithm to simultaneously compensate for: sensor nonlinearity, temperature drift, frequency fluctuation and harmonic interference.

[0029] (3) Performance improvement effect: Long-term stability breakthrough. The error of traditional equipment increases by 1.2%, while the present invention controls the error within 0.05% through adaptive error compensation; environmental adaptability is enhanced, supporting installation at any angle, eliminating the strict requirements of traditional CT on installation posture, and still maintaining 0.1 level accuracy under 100V / m electromagnetic interference.

[0030] (4) Long-term maintenance-free capability: Eliminates the need for on-site calibration twice a year, extending the maintenance cycle from 2 years to 10 years. Attached Figure Description

[0031] Figure 1 This is a flowchart of the method of the present invention;

[0032] Figure 2 This is a structural diagram of the device of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0035] Example 1

[0036] This embodiment provides a method for compensating for TMR current acquisition self-calibration error, such as... Figure 1 As shown, the method includes the following steps:

[0037] S1 dynamically injects a reference signal with known characteristics into the TMR current acquisition circuit through a built-in standard signal excitation source module.

[0038] S2 utilizes a high-precision sampling circuit to synchronously acquire the mixed response of the original signal and the reference signal.

[0039] S3 uses digital signal processing technology to separate the original signal and reference signal in the mixed response, and obtains the original signal measurement value and the reference signal measurement value.

[0040] This embodiment uses Discrete Fourier Transform to extract features of different frequencies, thereby obtaining data information of the reference signal and the original signal.

[0041] For the Fourier transform, given a time-domain signal Its frequency domain representation is:

[0042] ;

[0043] in, For frequency The complex spectrum (including amplitude and phase) at the location. These are orthogonal basis functions used to decompose frequency components.

[0044] In this embodiment, the mixed signal is first processed according to the sampling rate. Sampling is performed to obtain the sampled signal. ,in, The length of the sampling sequence.

[0045] Then, signal preprocessing is performed: windowing (such as Hamming window) is applied to the sampled signal after discrete processing to suppress spectral leakage, and zero-filling is performed to improve frequency resolution.

[0046] For the preprocessed discrete signal Perform a Discrete Fourier Transform (DFT) to obtain the discrete spectrum. :

[0047] ;

[0048] The discrete spectrum contains all frequency components of the mixed signal. Subsequently, a frequency mask is created to extract the characteristic frequencies.

[0049] Based on the known target frequency of the reference signal Generate frequency mask :

[0050] ;

[0051] in, , indicating frequency resolution. When the frequency... Falling Within the nearby narrow band (width equal to frequency resolution) If the mask value is 1, the frequency component is retained; if the mask value is 0 at other frequencies, the corresponding component is filtered out.

[0052] The reference signal is extracted by multiplying the frequency mask by the discrete spectrum, and then the time-domain signal is recovered by inverse FFT to obtain the measured value of the reference signal.

[0053] ;

[0054] in, Indicates the inverse FFT. This is the measured value of the reference signal.

[0055] The frequency domain form of the original signal measurement is then expressed as:

[0056] .

[0057] S4. Analyze the difference between the reference signal and the measured value of the reference signal in real time, establish a multi-dimensional error vector, and thus obtain the error dynamic compensation matrix. The error dynamic compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term. The adaptive weight coefficients of the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term are determined based on the signal-to-noise ratio, the phase difference, and the frequency, respectively.

[0058] The multidimensional error vector is represented as:

[0059] ;

[0060] in, This represents the normalized amplitude error (±0.1% accuracy) between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal (0.01° resolution). The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... Indicates the amplitude of the reference signal. This represents the amplitude of the reference signal measurement. Indicates the phase of the reference signal. Indicates the phase of the reference signal measurement. Indicates the harmonic order. Indicates the reference signal number The amplitude of the second harmonic. Indicates the reference signal measurement value of the first The amplitude of the subharmonic.

[0061] The dynamic compensation matrix is ​​then expressed as:

[0062] ;

[0063] in, For dynamic compensation matrix, To compensate for the amplitude term, To compensate for the phase term, To compensate for harmonic distortion, , , These are the adaptive weighting coefficients for the compensation amplitude term, compensation phase term, and compensation harmonic distortion term, respectively.

[0064] In this embodiment, the adaptive weighting coefficient is calculated as follows:

[0065] ;

[0066] ;

[0067] ;

[0068] in, , , These are the adaptive weighting coefficients for the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term, respectively. For signal-to-noise ratio, The phase error between the reference signal and the measured value of the reference signal. For frequency, , , , , , The coefficients are all greater than 0, and , , , , , .

[0069] In one preferred embodiment, , , , , , ,Right now:

[0070] ;

[0071] ;

[0072] .

[0073] S5. Based on the error dynamic compensation matrix, the original signal measurement value is dynamically corrected to achieve adaptive error compensation.

[0074] First, the error dynamic compensation matrix is ​​used. Measurement of the original signal Perform real-time signal correction:

[0075] ;

[0076] Then, the corrected signal Perform inverse FFT to reconstruct the time domain:

[0077] .

[0078] This method, through internal closed-loop calibration, eliminates errors caused by prolonged operation, ensuring the equipment system maintains high measurement accuracy over long periods and extending its service life. Using a built-in high-precision reference signal source, combined with a compensation algorithm, the original signal amplitude, phase, and harmonics are compensated, significantly enhancing the equipment's anti-interference capabilities and substantially improving its measurement accuracy compared to traditional CT scanners.

[0079] Example 2

[0080] The above is an introduction to the method embodiments. The following describes the solution of the present invention further through device embodiments.

[0081] like Figure 2 As shown, this embodiment provides a TMR current acquisition self-calibration error compensation device, which includes:

[0082] The TMR sensing module is used for TMR current acquisition.

[0083] A standard signal excitation source module is used to dynamically inject a reference signal with known characteristics into the TMR current acquisition circuit.

[0084] A high-precision sampling circuit is used to synchronously acquire the mixed response of the original signal and the reference signal;

[0085] The signal processing module is used to perform preliminary processing on the acquired mixed responses;

[0086] The main control MCU is used to separate the original signal and reference signal in the pre-processed mixed response based on digital signal processing technology, obtaining the original signal measurement value and the reference signal measurement value; it analyzes the difference between the reference signal and the reference signal measurement value in real time, establishes a multi-dimensional error vector, and obtains an error dynamic compensation matrix. The error dynamic compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term. The adaptive weight coefficients of the compensation amplitude term, compensation phase term, and compensation harmonic distortion term are determined based on the signal-to-noise ratio, phase difference, and frequency, respectively; it is used to dynamically correct the original signal measurement value based on the error dynamic compensation matrix to achieve adaptive error compensation.

[0087] In this embodiment, the TMR sensing module uses a tunneling magneto-resistance (TMR) sensor chip as the core detection element. Through its high-sensitivity magnetoelectric conversion characteristics, it senses changes in the magnetic field around the current-carrying conductor in real time and linearly converts them into a differential voltage signal output (typical sensitivity value 5mV / V / Oe). The module has a built-in temperature compensation circuit, maintaining a measurement accuracy of ±0.5% within the range of -40℃ to 85℃.

[0088] The signal processing circuit consists of an instrumentation amplifier with a high common-mode rejection ratio (CMRR > 120dB) and a programmable filter, amplifying the weak μV-level signal output from the TMR module to the standard range of 0-3.3V. A multi-stage filtering design effectively suppresses power frequency interference and harmonic noise, ensuring a signal-to-noise ratio (SNR) > 70dB.

[0089] The standard signal excitation source module is based on direct digital frequency synthesis (DDS) technology to generate a sinusoidal current signal with an adjustable frequency of 0.1Hz-1kHz and an adjustable amplitude of 0.1-5A. It adopts closed-loop feedback control, with a load regulation rate of <0.1% and an output distortion (THD) of <0.5%, meeting the stable excitation requirements under various operating conditions.

[0090] Main control MCU: Equipped with a 32-bit ARM Cortex-M4 core MCU, integrating a high-speed ADC (16-bit / 1MSPS) and digital signal processing algorithms to achieve adaptive calibration of the measurement system. Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the main control MCU can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0091] Example 3

[0092] The electronic device of this invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0093] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0094] The processing unit executes the various methods and processes described above, such as methods S1 to S5. For example, in some embodiments, methods S1 to S5 may be implemented as computer software programs tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of methods S1 to S5 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute methods S1 to S5 by any other suitable means (e.g., by means of firmware).

[0095] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0096] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0097] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0098] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A TMR current acquisition self-calibration error compensation method, characterized in that, This method dynamically injects a reference signal with known characteristics into the TMR current acquisition circuit through a built-in standard signal excitation source module; it synchronously acquires the mixed response of the original signal and the reference signal using a high-precision sampling circuit; and it separates the original signal and the reference signal in the mixed response based on digital signal processing technology to obtain the measured values ​​of the original signal and the reference signal. The difference between the measured values ​​of the reference signal and the actual reference signal is analyzed in real time to establish a multi-dimensional error vector, thereby obtaining a dynamic error compensation matrix. This dynamic error compensation matrix includes compensation amplitude, compensation phase, and compensation harmonic distortion terms. The adaptive weighting coefficients of these terms are determined based on the signal-to-noise ratio, phase difference, and frequency, respectively. Based on this dynamic error compensation matrix, the original signal measurement values ​​are dynamically corrected to achieve adaptive error compensation. The method for calculating the adaptive weight coefficients is as follows: ； ； ； in, , , These are the adaptive weighting coefficients for the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term, respectively. For signal-to-noise ratio, The phase error between the reference signal and the measured value of the reference signal. For frequency, , , , , , The coefficients are all greater than 0, and , , , , , .

2. The TMR current acquisition self-calibration error compensation method according to claim 1, characterized in that, The multidimensional error vector is represented as follows: ； in, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... Indicates the amplitude of the reference signal. This represents the amplitude of the reference signal measurement. Indicates the phase of the reference signal. Indicates the phase of the reference signal measurement. Indicates the harmonic order. Indicates the reference signal number The amplitude of the second harmonic. Indicates the reference signal measurement value of the first The amplitude of the subharmonic.

3. The TMR current acquisition self-calibration error compensation method of claim 1, wherein, The aforementioned error dynamic compensation matrix is ​​expressed as: ； in, This is the error dynamic compensation matrix. To compensate for the amplitude term, To compensate for the phase term, To compensate for harmonic distortion, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... , , These are the adaptive weighting coefficients for the compensation amplitude term, compensation phase term, and compensation harmonic distortion term, respectively.

4. A TMR current harvesting self-calibration error compensation device, characterized in that, The device includes: The TMR sensing module is used for TMR current acquisition. A standard signal excitation source module is used to dynamically inject a reference signal with known characteristics into the TMR current acquisition circuit. A high-precision sampling circuit is used to synchronously acquire the mixed response of the original signal and the reference signal; The signal processing module is used to perform preliminary processing on the acquired mixed responses; The main control MCU is used to separate the original signal and reference signal in the pre-processed mixed response based on digital signal processing technology, obtaining the measured values ​​of the original signal and the reference signal; it analyzes the difference between the measured values ​​of the reference signal and the reference signal in real time, establishes a multi-dimensional error vector, and obtains an error dynamic compensation matrix. The error dynamic compensation matrix includes a compensation amplitude term, a compensation phase term, and a compensation harmonic distortion term. The adaptive weight coefficients of the compensation amplitude term, compensation phase term, and compensation harmonic distortion term are determined based on the signal-to-noise ratio, phase difference, and frequency, respectively; it is used to dynamically correct the measured values ​​of the original signal based on the error dynamic compensation matrix to achieve adaptive error compensation. The method for calculating the adaptive weight coefficients is as follows: ； ； ； in, , , These are the adaptive weighting coefficients for the compensation amplitude term, the compensation phase term, and the compensation harmonic distortion term, respectively. For signal-to-noise ratio, The phase error between the reference signal and the measured value of the reference signal. For frequency, , , , , , The coefficients are all greater than 0, and , , , , , .

5. The TMR current sensing self-calibration error compensation device of claim 4, wherein, The multidimensional error vector is represented as follows: ； in, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... Indicates the amplitude of the reference signal. This represents the amplitude of the reference signal measurement. Indicates the phase of the reference signal. Indicates the phase of the reference signal measurement. Indicates the harmonic order. Indicates the reference signal number The amplitude of the second harmonic. Indicates the reference signal measurement value of the first The amplitude of the subharmonic.

6. The TMR current sensing self-calibration error compensation device of claim 4, wherein, The aforementioned error dynamic compensation matrix is ​​expressed as: ； in, This is the error dynamic compensation matrix. To compensate for the amplitude term, To compensate for the phase term, To compensate for harmonic distortion, The normalized amplitude error between the reference signal and the measured value of the reference signal. The phase error between the reference signal and the measured value of the reference signal. The harmonic spectrum Euclidean distance between the reference signal and the measured value of the reference signal is... , , These are the adaptive weighting coefficients for the compensation amplitude term, compensation phase term, and compensation harmonic distortion term, respectively. 7.An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 3.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 3.

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