Micro current measurement method, device and equipment based on fuzzy clustering and medium

Abstract

The invention relates to a micro current measurement method, device and equipment based on fuzzy clustering and a medium, and belongs to the field of current measurement. The method comprises the following steps: capturing a micro current signal through an improved fuzzy clustering method; removing the variation amplitude of the micro current signal to obtain an amplitude-limited micro current signal; and performing denoising processing on the amplitude-limited micro current signal through a continuous wavelet basis function to obtain a final-state micro current signal. According to the method, capturing and measuring of the micro current are achieved through the improved fuzzy clustering method, the measuring precision is high, and the denoising effect is good.

Description

Technical Field

[0001] The present invention belongs to the technical field of current measurement, and in particular relates to a method, device, equipment and medium for measuring tiny current based on fuzzy clustering. Background Art

[0002] In power systems, although the focus is usually on large current measurement, micro current measurement is equally important. For example, detecting leakage current and evaluating insulation performance require accurate micro current measurement to ensure the safe operation of power equipment. Since the micro current signal is very weak, it may be affected by various noises and interferences during the measurement process. Therefore, the development of reliable micro current measurement methods has always been a challenge. Various micro current measurement methods, such as electrochemical method, differential amplifier method, field effect tube method and superconducting quantum interference device (SQUID) method, each have their own advantages and disadvantages, and it is necessary to select a suitable measurement method according to the specific application scenario. Most of the above measurement methods have defects such as difficulty in suppressing noise and difficulty in capturing micro current signals. Therefore, a micro current measurement method with strong capture capability and high recognition accuracy is urgently needed. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a method, device, equipment and medium for measuring tiny current based on fuzzy clustering.

[0004] The purpose of the present invention can be achieved by the following technical solutions: A method for measuring a small current based on fuzzy clustering, the implementation of which comprises the following steps: Capturing tiny current signals by improving fuzzy clustering method; Removing the variation amplitude of the tiny current signal to obtain a limited tiny current signal; The amplitude-limited tiny current signal is processed by continuous wavelet basis function denoising to obtain a final-state tiny current signal.

[0005] Preferably, the method of capturing tiny current signals by improving the fuzzy clustering method comprises: Preset a sampling number within a wavelength, obtain an original tiny current signal according to the sampling number, collect the original tiny current signals to obtain an original tiny current signal sequence, and process the original tiny current signal sequence through a fuzzy clustering algorithm to obtain a first current signal component and a second current signal component; The first current signal component and the second current signal component are clustered again to obtain a secondary clustering result, and the mathematical description of the secondary clustering result is: , where AB i is the i-th secondary clustering result, A 2i is the 2ith first current signal component, A 2i-1is the 2i-1th first current signal component, N is the number of samples, B 2i is the 2ith second current signal component, B 2i-1 is the 2i-1th second current signal component; A peak value threshold is preset, and whether the original tiny current signal sequence is successfully captured is judged according to the peak value threshold. When the maximum peak value of the secondary clustering result is greater than the peak value threshold, tiny current signal capture information is output; when the maximum peak value of the secondary clustering result is less than or equal to the peak value threshold, tiny current signal failure information is output, and the sampling step of the original tiny current signal is returned; When the tiny current signal capture information is output, a tiny current signal quadratic curve model is constructed. The mathematical description of the tiny current signal quadratic curve model is: ,in, l i is the quadratic curve model of the ith tiny current signal, a is the first clustering coefficient, c is the third clustering coefficient, and d is the fourth clustering coefficient; The frequency shift of the tiny current signal is calculated according to the characteristics of the quadratic curve model of the tiny current signal. The calculation formula is: , where AB min It is the frequency shift of tiny current signal; The tiny current signal is obtained according to the tiny current signal frequency shift and the secondary clustering result, and the expression is: , where y(n) is a small current signal.

[0006] Preferably, the processing of the original tiny current signal sequence by a fuzzy clustering algorithm comprises: Obtain the current signal disturbance factor and sampling time point, and obtain the mathematical description of the first current signal component, which is: , where A i is the i-th first current signal component, S i is the output value of the ith fuzzy clustering algorithm, φ is the current signal disturbance factor, th is the channel noise generated by the current signal, t * is the sampling time point; Obtain a clustering result of the original tiny current signal sequence, and obtain a mathematical description of the second current signal component according to the clustering result, which is: , where B i is the i-th second current signal component, y is the original small current signal sequence, is the clustering result, and b is the second clustering coefficient.

[0007] Preferably, the step of removing the variation amplitude of the tiny current signal comprises: Normalizing the tiny current signal to obtain a normalized tiny current signal; Processing the normalized tiny current signal through a filtering circuit to obtain a filtered tiny current signal; The amplitude-limited tiny current signal is obtained by dividing the filtered tiny current signal.

[0008] Preferably, the processing of the normalized tiny current signal by a filtering circuit comprises: The topological structure of the filtering circuit is composed of an operational amplifier, a resistor and a power supply, the resistor includes a feedback resistor, a grounding resistor and a second-order resistor, the second-order resistor includes a second-order resistor 1 and a second-order resistor 2, the power supply includes a power supply 1 and a power supply 2, and the second-order resistor, the power supply 1 and the grounding resistor constitute a filtering network; The filter circuit parameters are determined according to the filter circuit, and the normalized tiny current signal is input into the filter circuit for determining the filter circuit parameters to obtain the filtered tiny current signal.

[0009] Preferably, the step of dividing the filtered tiny current signal comprises: The filtered tiny current signal is divided into overlapping blocks and overlapping blocks are obtained. The number of zero crossings is calculated based on the overlapping blocks. The calculation formula is: ,in, is the number of zero crossings, K is the size of the overlapping blocking window, For overlapping blocking, is the preset overlapping blocking threshold; When the filtered tiny current signal is not disturbed, the signal noise of the filtered tiny current signal is all contributed to the zero crossing number, and the expression for obtaining the limited tiny current signal is: , where S(n) is the limited small current signal, Q is the number of overlapping blocks, and h(n) q To filter the signal characteristics of the tiny current signal at the qth overlapping block, To filter the small current signal The signal characteristics at the overlapping blocks are is the autocorrelation lag coefficient.

[0010] Preferably, the denoising process of the amplitude-limited tiny current signal by continuous wavelet basis function comprises: Performing continuous wavelet transform on the amplitude-limited tiny current signal based on the continuous wavelet basis function; The limited small current signal is decomposed into a small current signal to be reconstructed after continuous wavelet transformation, and the expression is: , where I is the small current signal to be reconstructed, I1 is the high-frequency information of the signal obtained by the first-layer decomposition, I2 is the high-frequency information of the signal obtained by the second-layer decomposition, and ID is the high-frequency information of the signal decomposed at the Dth layer, and E is the low-frequency information of the signal; The to-be-reconstructed tiny current signal is reconstructed based on the signal high-frequency information and the signal low-frequency information to obtain the final-state tiny current signal.

[0011] A micro-current measuring device based on fuzzy clustering, used to execute the micro-current measuring method based on fuzzy clustering, comprising a signal capturing module, a signal limiting module, and a signal denoising module; The signal capture module is used to capture tiny current signals by improving the fuzzy clustering method; The signal limiting module is used to remove the variation amplitude of the small current signal to obtain a limited small current signal; The signal denoising module is used to perform denoising processing on the amplitude-limited tiny current signal through a continuous wavelet basis function to obtain a final-state tiny current signal.

[0012] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned method for measuring minute current based on fuzzy clustering is implemented.

[0013] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute the above-mentioned fuzzy clustering-based minute current measurement method when executed by a computer processor.

[0014] The beneficial effects of the present invention are: (1) By improving the fuzzy clustering method and continuous wavelet basis function to capture and process small current signals, a small current measurement method with strong capture capability and high recognition accuracy is realized; (2) The original tiny current signal sequence is processed by a fuzzy clustering algorithm to obtain the first current signal component and the second current signal component, and the first current signal component and the second current signal component are clustered again to achieve accurate processing of fuzzy and uncertain data. When facing noise, interference or data missing in the signal data, it has good robustness and can stably cluster the signal, reducing analysis errors caused by data quality problems; (3) The normalized small current signal is processed by the filtering circuit to obtain the filtered small current signal, ensuring that the extracted signal is clean and stable, which helps to improve the quality and reliability of the signal and makes the subsequent signal processing steps more accurate. The filtering circuit can remove high-frequency noise and retain low-frequency signal components, which is crucial for accurately capturing and analyzing signals. At the same time, the filtering circuit can also ensure the integrity of the signal during transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0016] Figure 1 The present invention is a flowchart of the steps of a method for measuring tiny current based on fuzzy clustering. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0018] The working principle and use process of the present invention: See also Figure 1 , a method for measuring tiny current based on fuzzy clustering, comprising: S1: Capturing tiny current signals by improving fuzzy clustering method; S2: removing the variation amplitude of the small current signal to obtain a limited small current signal; S3: De-noising the amplitude-limited tiny current signal by continuous wavelet basis function to obtain a final-state tiny current signal.

[0019] In this embodiment, the small current signal is captured by improving the fuzzy clustering method, which can be implemented by the following steps: S101: Preset a sampling number within a wavelength, obtain an original tiny current signal according to the sampling number, collect the original tiny current signals to obtain an original tiny current signal sequence, and process the original tiny current signal sequence through a fuzzy clustering algorithm to obtain a first current signal component and a second current signal component; S102: clustering the first current signal component and the second current signal component again to obtain a secondary clustering result, the mathematical description of the secondary clustering result is: , where AB i is the i-th secondary clustering result; S103: Preset a peak value threshold, and judge whether the original tiny current signal sequence is captured successfully according to the peak value threshold. When the maximum peak value of the secondary clustering result is greater than the peak value threshold, output tiny current signal capture information; when the maximum peak value of the secondary clustering result is less than or equal to the peak value threshold, output tiny current signal uncapture information, and return to the sampling step of the original tiny current signal; S104: When the tiny current signal capture information is output, a tiny current signal quadratic curve model is constructed. The mathematical description of the tiny current signal quadratic curve model is: ,in, l iis the quadratic curve model of the ith tiny current signal, c is the third clustering coefficient, and d is the fourth clustering coefficient; S105: Calculate the frequency shift of the tiny current signal according to the characteristics of the quadratic curve model of the tiny current signal. The calculation formula is: , where AB min It is the frequency shift of tiny current signal; S106: Obtain the tiny current signal according to the tiny current signal frequency shift and the secondary clustering result, expressed as: , where y(n) is a small current signal.

[0020] In this embodiment, the original tiny current signal sequence is processed by a fuzzy clustering algorithm, which can be specifically implemented by the following steps: S101-1: Obtain the current signal disturbance factor and sampling time point, and obtain the mathematical description of the first current signal component, which is: , where A i is the i-th first current signal component, N is the number of samples, S i is the output value of the ith fuzzy clustering algorithm, a is the first clustering coefficient, φ is the current signal disturbance factor, th is the channel noise generated by the current signal, t * is the sampling time point; S101-2: Obtain a clustering result of the original tiny current signal sequence, and obtain a mathematical description of the second current signal component according to the clustering result, which is: , where B i is the i-th second current signal component, y is the original small current signal sequence, is the clustering result, and b is the second clustering coefficient.

[0021] In this embodiment, removing the variation amplitude of the small current signal to obtain a limited small current signal can be implemented by the following steps: S201: normalize the small current signal to obtain a normalized small current signal, which is mathematically described as , where h(n) is the normalized small current signal and W is the variation amplitude; S202: Processing the normalized small current signal through a filtering circuit to obtain a filtered small current signal; S203: Obtain the amplitude-limited tiny current signal by dividing the filtered tiny current signal.

[0022] In this embodiment, the normalization process of the small current signal to obtain a normalized small current signal can be implemented by the following steps: S202-1: The topological structure of the filtering circuit is composed of an operational amplifier, a resistor and a power supply, the resistor includes a feedback resistor, a grounding resistor and a second-order resistor, the second-order resistor includes a second-order resistor 1 and a second-order resistor 2, the power supply includes a power supply 1 and a power supply 2, and the second-order resistor, the power supply 1 and the grounding resistor constitute a filtering network; S202-2: Determine filter circuit parameters according to the filter circuit, and input the normalized tiny current signal into the filter circuit for determining the filter circuit parameters, to obtain the filtered tiny current signal.

[0023] The expression of the circuit gain in the filter circuit is: , where Q is the circuit gain, R f is the resistance of the feedback resistor, R j is the resistance value of the grounding resistor; The expression of the cut-off frequency in the filter circuit is: , where w is the cutoff frequency, R1 is the resistance of the second-order resistor 1, R2 is the resistance of the second-order resistor 2, C1 is the capacitance of the power supply 1, and C2 is the capacitance of the power supply 2. f is the frequency of the normalized tiny current signal; The expression of the filter network voltage in the filter circuit is: , where V is the filter network voltage and Vc is the output voltage of the filter circuit; When some filter circuit parameters of the filter circuit are determined according to requirements, the remaining filter circuit parameters can be determined according to the above expressions.

[0024] In this embodiment, the amplitude-limited tiny current signal is obtained by dividing the filtered tiny current signal, which can be specifically implemented by the following steps: S203-1: Divide the filtered tiny current signal into overlapping blocks and obtain overlapping blocks, and calculate the number of zero crossings based on the overlapping blocks. The calculation formula is: ,in, is the number of zero crossings, K is the size of the overlapping blocking window, For overlapping blocking, is the preset overlapping blocking threshold; S203-2: When the filtered tiny current signal is not disturbed, the signal noise of the filtered tiny current signal is all contributed to the zero crossing number, then the expression for obtaining the limited tiny current signal is: , where S(n) is the limited small current signal, Q is the number of overlapping blocks, and h(n) q To filter the signal characteristics of the tiny current signal at the qth overlapping block, To filter the small current signal The signal characteristics at the overlapping blocks are is the autocorrelation lag coefficient.

[0025] In this embodiment, the amplitude-limited tiny current signal is processed by continuous wavelet basis function denoising, which can be implemented by the following steps: S301: Based on the continuous wavelet basis function, a continuous wavelet transform is performed on the amplitude-limited micro-current signal. The expression of the wavelet coefficient of the continuous wavelet transform is: , where P(e,u) is the wavelet coefficient, e is the scale factor of the continuous wavelet basis function, f (t) is the continuous wavelet feature, u is the translation factor, (·) is the continuous wavelet basis function, t is the time; S302: The amplitude-limited small current signal is decomposed into a small current signal to be reconstructed after continuous wavelet transformation, and the expression is: , where I is the small current signal to be reconstructed, I1 is the high-frequency information of the signal obtained by the first-layer decomposition, I2 is the high-frequency information of the signal obtained by the second-layer decomposition, and I D is the high-frequency information of the signal decomposed at the Dth layer, and E is the low-frequency information of the signal; S303: Reconstruct the to-be-reconstructed tiny current signal based on the signal high-frequency information and the signal low-frequency information to obtain the final-state tiny current signal.

[0026] A micro current measuring device based on fuzzy clustering, comprising a signal capturing module, a signal limiting module, and a signal denoising module; The signal capture module is used to capture tiny current signals by improving the fuzzy clustering method; The signal limiting module is used to remove the variation amplitude of the small current signal to obtain a limited small current signal; The signal denoising module is used to perform denoising processing on the amplitude-limited tiny current signal through a continuous wavelet basis function to obtain a final-state tiny current signal.

[0027] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0028] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0029] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0030] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for measuring small current based on fuzzy clustering, characterized in that: The implementation of the tiny current measurement method comprises the following steps: Capturing tiny current signals by improving fuzzy clustering method; Removing the variation amplitude of the tiny current signal to obtain a limited tiny current signal; The amplitude-limited tiny current signal is processed by continuous wavelet basis function denoising to obtain a final-state tiny current signal; The method of capturing tiny current signals by improving the fuzzy clustering method comprises: Preset a sampling number within a wavelength, obtain an original tiny current signal according to the sampling number, collect the original tiny current signals to obtain an original tiny current signal sequence, and process the original tiny current signal sequence through a fuzzy clustering algorithm to obtain a first current signal component and a second current signal component; The first current signal component and the second current signal component are clustered again to obtain a secondary clustering result, and the mathematical description of the secondary clustering result is: , where AB i is the i-th secondary clustering result, A 2i is the 2ith first current signal component, A 2i-1 is the 2i-1th first current signal component, N is the number of samples, B 2i is the 2ith second current signal component, B 2i-1 is the 2i-1th second current signal component; A peak value threshold is preset, and whether the original tiny current signal sequence is successfully captured is judged according to the peak value threshold. When the maximum peak value of the secondary clustering result is greater than the peak value threshold, tiny current signal capture information is output; when the maximum peak value of the secondary clustering result is less than or equal to the peak value threshold, tiny current signal failure information is output, and the sampling step of the original tiny current signal is returned; When the tiny current signal capture information is output, a tiny current signal quadratic curve model is constructed. The mathematical description of the tiny current signal quadratic curve model is: ,in, l i is the quadratic curve model of the ith tiny current signal, a is the first clustering coefficient, c is the third clustering coefficient, and d is the fourth clustering coefficient; The frequency shift of the tiny current signal is calculated according to the characteristics of the quadratic curve model of the tiny current signal. The calculation formula is: , where AB min It is the frequency shift of tiny current signal; The tiny current signal is obtained according to the tiny current signal frequency shift and the secondary clustering result, and the expression is: , where y(n) is a small current signal.

2. The method for measuring a small current according to claim 1, characterized in that: The processing of the original tiny current signal sequence by using a fuzzy clustering algorithm comprises: Obtain the current signal disturbance factor and sampling time point, and obtain the mathematical description of the first current signal component, which is: , where A i is the i-th first current signal component, S i is the output value of the ith fuzzy clustering algorithm, φ is the current signal disturbance factor, th is the channel noise generated by the current signal, t * is the sampling time point; Obtain the clustering result of the original tiny current signal sequence, and obtain the mathematical description of the second current signal component according to the clustering result, which is: , where B i is the i-th second current signal component, y is the original small current signal sequence, is the clustering result, and b is the second clustering coefficient.

3. The method for measuring a small current according to claim 1, characterized in that: The removing of the variation amplitude of the tiny current signal comprises: Normalizing the tiny current signal to obtain a normalized tiny current signal; Processing the normalized tiny current signal through a filtering circuit to obtain a filtered tiny current signal; The amplitude-limited tiny current signal is obtained by dividing the filtered tiny current signal.

4. The method for measuring a small current according to claim 3, characterized in that: The step of processing the normalized tiny current signal by a filtering circuit comprises: The topological structure of the filtering circuit is composed of an operational amplifier, a resistor and a power supply, the resistor includes a feedback resistor, a grounding resistor and a second-order resistor, the second-order resistor includes a second-order resistor 1 and a second-order resistor 2, the power supply includes a power supply 1 and a power supply 2, and the second-order resistor, the power supply 1 and the grounding resistor constitute a filtering network; The filter circuit parameters are determined according to the filter circuit, and the normalized tiny current signal is input into the filter circuit for determining the filter circuit parameters to obtain the filtered tiny current signal.

5. The method for measuring a small current according to claim 3, characterized in that: The segmenting of the filtered tiny current signal comprises: The filtered tiny current signal is divided into overlapping blocks and overlapping blocks are obtained. The number of zero crossings is calculated based on the overlapping blocks. The calculation formula is: ,in, is the number of zero crossings, K is the size of the overlapping blocking window, For overlapping blocking, is the preset overlapping blocking threshold; When the filtered tiny current signal is not disturbed, the signal noise of the filtered tiny current signal is all contributed to the zero crossing number, and the expression for obtaining the limited tiny current signal is: , where S(n) is the limited small current signal, Q is the number of overlapping blocks, and h(n) q To filter the signal characteristics of the tiny current signal at the qth overlapping block, To filter the small current signal The signal characteristics at the overlapping blocks are is the autocorrelation lag coefficient.

6. The method for measuring a minute current according to claim 1, characterized in that: The denoising process of the amplitude-limited tiny current signal by using a continuous wavelet basis function comprises: Performing continuous wavelet transform on the amplitude-limited tiny current signal based on the continuous wavelet basis function; The limited small current signal is decomposed into a small current signal to be reconstructed after continuous wavelet transformation, and the expression is: , where I is the small current signal to be reconstructed, I1 is the high-frequency information of the signal obtained by the first-layer decomposition, I2 is the high-frequency information of the signal obtained by the second-layer decomposition, and I D is the high-frequency information of the signal decomposed at the Dth layer, and E is the low-frequency information of the signal; The to-be-reconstructed tiny current signal is reconstructed based on the signal high-frequency information and the signal low-frequency information to obtain the final-state tiny current signal.

7. A micro-current measuring device based on fuzzy clustering, characterized in that: The device is applied to the fuzzy clustering-based micro-current measurement method as described in any one of claims 1 to 6, comprising a signal capture module, a signal limiting module, and a signal denoising module; The signal capture module is used to capture tiny current signals by improving the fuzzy clustering method; The signal limiting module is used to remove the variation amplitude of the small current signal to obtain a limited small current signal; The signal denoising module is used to perform denoising processing on the amplitude-limited tiny current signal through a continuous wavelet basis function to obtain a final-state tiny current signal.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the tiny current measurement method based on fuzzy clustering as described in any one of claims 1 to 6 is implemented.

9. A storage medium containing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to execute the minute current measurement method based on fuzzy clustering as described in any one of claims 1 to 6.

Images