Non-contact single-phase conductor current and voltage measuring method and system

Abstract

The invention relates to a non-contact single-phase conductor current and voltage measurement method and system, and the method comprises the steps: obtaining geometric parameters of a target conductor, and constructing an electromagnetic field phasor sequence database according to the geometric parameters and a Maxwell equation set; an electric field signal and a magnetic field signal of a target conductor are synchronously collected through an annular electromagnetic sensor array; filtering the electric field signal and the magnetic field signal, and generating a continuous electromagnetic field distribution phasor sequence for the filtered electric field signal and magnetic field signal through an interpolation method; matching the electromagnetic field distribution phasor sequence with an electromagnetic field phasor sequence database, and calculating a plurality of correlation coefficients; and according to the numerical value of each correlation coefficient and a preset threshold, determining a current measurement value and a voltage measurement value: taking the electric field signal and the magnetic field signal, which are greater than the preset threshold and correspond to the maximum correlation coefficient, in the correlation coefficients as the current measurement value and the voltage measurement value respectively. According to the invention, the stability and accuracy of non-contact measurement are improved.

Description

Technical Field

[0001] The present invention belongs to the field of power measurement technology, and specifically relates to a non-contact single-phase conductor current and voltage measurement method and system, and more particularly to a non-contact single-phase conductor current and voltage measurement method and system based on electromagnetic field mutual verification. Background Art

[0002] With the continuous development of high-voltage power systems and the widespread use of power cables in transmission and distribution systems, accurate measurement and real-time monitoring of current and voltage have become critical to ensuring the safe and stable operation of power systems. However, traditional contact measurement methods, such as current transformers (CTs) and voltage transformers (VTs), while capable of providing effective measurement results, pose certain safety risks due to their reliance on physical contact with power equipment. Especially in high-voltage environments, contact methods can cause personal injury and equipment damage.

[0003] While non-contact current and voltage measurement is becoming an increasingly important option, existing non-contact measurement technologies still have shortcomings. Measurement methods based on electric and magnetic field sensors, while avoiding the safety hazards associated with contact measurement, still face challenges in achieving high accuracy and robustness against interference. Electromagnetic interference sources are ubiquitous in power systems, and single electric or magnetic field sensors often struggle to provide stable signals with a high signal-to-noise ratio, thus impacting the accuracy of measurement results.

[0004] Currently, electric and magnetic field sensor technologies typically collect and analyze electric and magnetic field signals separately. However, these methods typically measure only a single signal source and lack effective multi-dimensional signal fusion and error correction. Therefore, improving measurement accuracy by combining electric and magnetic field signals, especially in complex environments with strong electromagnetic interference, is a key issue that needs to be addressed.

[0005] To address this challenge, a new non-contact current and voltage measurement method is urgently needed that can provide highly accurate and stable measurement results in complex electromagnetic environments. This method should not only avoid the safety hazards of traditional contact measurement but also have strong anti-interference capabilities to ensure stable operation of power systems during equipment maintenance and fault diagnosis. Summary of the Invention

[0006] In order to improve the accuracy and stability of the non-contact measurement method of the power system, a first aspect of the present invention provides a non-contact single-phase conductor current and voltage measurement method, including: obtaining the geometric parameters of the target conductor, and constructing an electromagnetic field phasor sequence database based on the current and voltage combination according to the geometric parameters and Maxwell's equations; synchronously collecting the electric field signal and magnetic field signal of the target conductor through a ring-shaped electromagnetic sensor array; filtering the electric field signal and magnetic field signal, and discretely reconstructing the filtered electric field signal and magnetic field signal through interpolation to generate a continuous electromagnetic field distribution phasor sequence; matching the electromagnetic field distribution phasor sequence with the electromagnetic field phasor sequence database, and calculating multiple correlation coefficients, the correlation coefficients including the electric field-voltage correlation coefficient and the magnetic field-current correlation coefficient; determining the current measurement value and the voltage measurement value according to the numerical value of each correlation coefficient and a preset threshold value: the electric field signal and the magnetic field signal corresponding to the maximum correlation coefficient in the correlation coefficient that are greater than the preset threshold value are used as the current measurement value and the voltage measurement value, respectively.

[0007] In some embodiments of the present invention, the discrete reconstruction of the filtered electric field signal and magnetic field signal by interpolation method to generate a continuous electromagnetic field distribution phasor sequence includes: interpolating the filtered electric field signal and magnetic field signal based on spherical harmonic functions to generate a continuous electromagnetic field distribution phasor sequence.

[0008] Furthermore, the interpolating the filtered electric field signal and magnetic field signal based on the spherical harmonic function includes: interpolating the electric field signal and magnetic field signal obtained by each sensor through Fourier series based on the measurement angle of each sensor and the total number of sensors.

[0009] In some embodiments of the present invention, before the discrete reconstruction of the filtered electric field signal and magnetic field signal by interpolation method, it also includes: calculating the confidence of the electric field signal and magnetic field signal of each sensor; performing anomaly detection on the electric field signal and magnetic field signal according to the confidence: if the confidence of the electric field signal or the magnetic field signal is lower than the preset value, the data is judged to be abnormal.

[0010] In some embodiments of the present invention, the method further includes: determining the optimal current measurement value and the optimal voltage measurement value through a global search method and a local optimization method.

[0011] Furthermore, the determination of the optimal current measurement value and the optimal voltage measurement value through the global search method and the local optimization method includes: constructing an optimization function based on the electric field signal error and the magnetic field signal error; determining the constraints of the optimization function based on the physical laws of the electromagnetic field; searching for a global solution of the optimization function with constraints through a genetic algorithm; and further optimizing the global solution through the Levenberg-Marquardt algorithm to obtain the optimal current measurement value and the optimal voltage measurement value.

[0012] The second aspect of the present invention provides a non-contact single-phase conductor current and voltage measurement system, comprising: a construction module for obtaining the geometric parameters of the target conductor, and constructing an electromagnetic field phasor sequence database based on the current and voltage combination according to the geometric parameters and Maxwell's equations; a generation module for synchronously collecting the electric field signal and magnetic field signal of the target conductor through a ring-shaped electromagnetic sensor array; filtering the electric field signal and magnetic field signal, and discretely reconstructing the filtered electric field signal and magnetic field signal through interpolation to generate a continuous electromagnetic field distribution phasor sequence; a matching module for matching the electromagnetic field distribution phasor sequence with the electromagnetic field phasor sequence database, and calculating multiple correlation coefficients, the correlation coefficients including the electric field-voltage correlation coefficient and the magnetic field-current correlation coefficient; a determination module for determining the current measurement value and the voltage measurement value according to the numerical value of each correlation coefficient and a preset threshold: the electric field signal and the magnetic field signal corresponding to the maximum correlation coefficient in the correlation coefficient that are greater than the preset threshold are used as the current measurement value and the voltage measurement value, respectively.

[0013] The third aspect of the present invention provides an electronic device comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the non-contact single-phase conductor current and voltage measurement method provided in the first aspect of the present invention.

[0014] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the non-contact single-phase conductor current and voltage measurement method provided in the first aspect of the present invention is implemented.

[0015] The beneficial effects of the present invention are: The non-contact current and voltage measurement method proposed in the present invention combines the synchronous acquisition and efficient fusion of electric field and magnetic field signals, and can provide high-precision measurement results in high electromagnetic interference environments. It has significant innovation and application value, can effectively improve the monitoring accuracy and safety of the power system, and provide strong support for the efficient maintenance and fault warning of power equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the basic flow of a non-contact single-phase conductor current and voltage measurement method in some embodiments of the present invention; Figure 2 Schematic diagram of a specific flow chart of a non-contact single-phase conductor current and voltage measurement method in some embodiments of the present invention; Figure 3 Schematic diagram of the structure of a non-contact single-phase conductor current and voltage measurement system in some embodiments of the present invention; Figure 4 Schematic diagram of the structure of an electronic device in some embodiments of the present invention. DETAILED DESCRIPTION

[0017] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0018] refer to Figure 1 and Figure 2 In a first aspect of the present invention, a non-contact single-phase conductor current and voltage measurement method is provided, comprising: S100. obtaining geometric parameters of the target conductor, and constructing an electromagnetic field phasor sequence database based on the current and voltage combination according to the geometric parameters and Maxwell's equations; S200. synchronously collecting the electric field signal and the magnetic field signal of the target conductor through a ring-shaped electromagnetic sensor array; filtering the electric field signal and the magnetic field signal, and discretely reconstructing the filtered electric field signal and the magnetic field signal through an interpolation method to generate a continuous electromagnetic field distribution phasor sequence; S300. matching the electromagnetic field distribution phasor sequence with the electromagnetic field phasor sequence database, and calculating multiple correlation coefficients, the correlation coefficients including the electric field-voltage correlation coefficient and the magnetic field-current correlation coefficient; S400. determining the current measurement value and the voltage measurement value according to the value of each correlation coefficient and a preset threshold value: taking the electric field signal and the magnetic field signal corresponding to the maximum correlation coefficient in the correlation coefficient that is greater than the preset threshold value as the current measurement value and the voltage measurement value, respectively.

[0019] In step S100 of some embodiments of the present invention, geometric parameters of the target conductor are obtained, and an electromagnetic field phasor sequence database based on current and voltage combinations is constructed according to the geometric parameters and Maxwell's equations.

[0020] Specifically, in combination with the geometric parameters of the conductor to be measured, an analytical model of electric field-magnetic field-current-voltage is established based on Maxwell's equations, and the theoretical electromagnetic field phasor sequence under different current and voltage combinations is calculated to form an electromagnetic field phasor database; sensor array arrangement: a ring-shaped electromagnetic sensor array is installed on the periphery of the conductor, and the array contains alternating electric field sensors and magnetic field sensors. The center of the array coincides with the axis of the conductor, and the sensors are evenly distributed around the conductor, with the spacing between adjacent sensors being 1 / 4. , Therefore, based on the geometric parameters of the conductor to be measured and combined with Maxwell's equations, an analytical model between the electric field, electromagnetic field, current and voltage is established.

[0021] .

[0022] This analytical model provides a theoretical basis for calculating electric and magnetic field signals, and is discretized through the finite element method, ultimately providing an optimized calculation model for actual measurement data.

[0023] In some embodiments of the present invention, step S200 includes: S201. The electric field signal and magnetic field signal of the target conductor are synchronously collected by the annular electromagnetic sensor array; Specifically, the electric field signal is collected synchronously and magnetic field signals , and amplify, filter and digitize them; a circular electromagnetic sensor array is used to synchronously collect electric and magnetic field signals. The electric field sensors and magnetic field sensors in the array are arranged alternately to ensure that the electromagnetic field signals around the conductor to be measured can be fully measured. The spacing between the sensors is designed to be ,in The radius of the array is set to 1.5D to 3D (D is the conductor diameter), and it is ensured that the sensor can cover the entire surface area of the conductor to be measured.

[0024] S202. Filtering the electric field signal and the magnetic field signal, and discretely reconstructing the filtered electric field signal and the magnetic field signal by interpolation to generate a continuous electromagnetic field distribution phasor sequence; Specifically, by synchronously collecting electric field signals and magnetic field signals The signal is amplified, filtered, and digitized using a conditioning circuit module. This ensures signal quality and stability, providing accurate input data for subsequent data analysis. Interpolation is used to reconstruct the discrete electromagnetic field data measured by the sensor into a quasi-continuous electromagnetic field distribution phasor sequence.

[0025] Preferably, in order to ensure the smoothness of the reconstructed electric field and magnetic field data, the present invention adopts the spherical harmonic function expansion method to perform signal interpolation, thereby obtaining more accurate electromagnetic field distribution data. The interpolation method adopts the spherical harmonic function expansion: , The expansion order , N is the number of sensors, In addition to the spherical harmonics mentioned above, electromagnetic field data can also be interpolated using interpolation methods such as the finite element method, subregion expansion method, radial basis function interpolation, Kriging method, and dynamic interpolation methods (such as Hermite interpolation).

[0026] In step S200 of some embodiments of the present invention, before the discrete reconstruction of the filtered electric field signal and magnetic field signal by interpolation method, it also includes: calculating the confidence of the electric field signal and magnetic field signal of each sensor; performing anomaly detection on the electric field signal and magnetic field signal according to the confidence: if the confidence of the electric field signal or the magnetic field signal is lower than the preset value, the data is judged to be abnormal.

[0027] Specifically, the confidence index (CI) is used to assess data reliability and determine whether there is abnormal data. When the CI value is lower than the preset threshold, the system will determine it as abnormal data and initiate a redundant sensor replacement process or spatiotemporal interpolation method to repair the abnormal data, thereby ensuring the reliability and stability of the measurement results. The decision-making mechanism includes: Anomaly detection: When three consecutive sampling points meet any of the following conditions, they are marked as abnormal data points: , Data repair: Use spatiotemporal interpolation to reconstruct outlier data: , in is the sampling interval, and the repaired data is used to recalculate the correlation coefficient matrix.

[0028] The calculation method of the confidence index CI is: , in, and are the measured electric and magnetic field signals, and are the theoretical values calculated by the electromagnetic field model, and is the standard deviation of the electric and magnetic field signals, and N is the number of sensors.

[0029] When the confidence index CI is less than 0.95, it is judged as abnormal data and the sensor replacement process is initiated; when CI is greater than or equal to 0.95, the measurement data is considered reliable and regular data processing continues.

[0030] It can be understood that after reconstructing the electromagnetic field distribution, the present invention performs a mutual verification analysis by calculating the correlation coefficient between the observed phasor and the theoretical phasor. Specifically, the electric field-voltage correlation coefficient is calculated. and magnetic field-current correlation coefficient , used to verify the degree of match between current and voltage measurements and theoretical data. This analysis effectively determines the credibility of the measurement results and ensures data accuracy. To further improve measurement accuracy, the present invention employs a hybrid optimization algorithm, combining global search with local optimization to accurately determine the optimal estimates of current and voltage.

[0031] In step S500 of some embodiments of the present invention, the method further includes: determining the optimal current measurement value and the optimal voltage measurement value through a global search method and a local optimization method.

[0032] Specifically, the comparison and optimization of electromagnetic field data First, the collected electric field signal and magnetic field signals Processing is performed to obtain the theoretical electric field signal and theoretical magnetic field signal The theoretical value of the electromagnetic field signal is obtained through numerical simulation based on the known electromagnetic field model (such as Maxwell's equations) and actual current and voltage conditions.

[0033] The key to mutual verification is to calculate the correlation coefficient matrix between the measured value and the theoretical value. In this matrix, the correlation coefficients of electric field and voltage are included. and the correlation coefficient between magnetic field and current These two correlation coefficients represent the degree of agreement between the electric field signal and the voltage signal, and between the magnetic field signal and the current signal, respectively. By calculating these two correlation coefficients, we can determine whether the measurement results conform to theoretical predictions and decide whether to perform data correction.

[0034] 2. Optimization of the error function In order to quantify the error between the electric field signal and the magnetic field signal, the present invention defines a joint optimization error function , which is used to measure the difference between the actual measured signal and the theoretical calculated signal. The specific formula is as follows: , in: and are the electric and magnetic field signals measured at the i-th and j-th sensors, respectively, and It is the theoretical value of electric field and magnetic field calculated by electromagnetic field theory model. and are the standard deviations of the electric and magnetic field signals, N and M are the number of electric field and magnetic field sensors in the sensor array, respectively.

[0035] By minimizing the error function , we can obtain the current and voltage measurement values that are most consistent with the theoretical values, thereby optimizing the measurement accuracy.

[0036] 3. Physical constraints When performing optimization, in addition to quantification through the error function, physical constraints must also be considered. Specifically, Faraday's law and the non-divergence of the magnetic field are important physical constraints that must be followed in the present invention. Faraday's law states that there is a certain relationship between the changes in the electric field and the magnetic field, and the divergence of the magnetic field is zero, that is: , , These constraints are used to ensure the physical consistency of the optimization results and further improve the accuracy of the measurement.

[0037] 4. Data repair and anomaly detection In order to improve the robustness of the system, in addition to calculating the correlation coefficient matrix and optimizing the error function, the present invention also designs a data repair mechanism. When it is detected that the deviation of the electric field or magnetic field signal of three consecutive sampling points exceeds the set threshold (for example, )or ), it is marked as an abnormal data point. For abnormal data points, spatiotemporal interpolation is used to repair them. The specific repair formula is as follows: , in, is the sampling interval, and the repaired data will be used to recalculate the correlation coefficient matrix and perform further optimization. The repaired field quantity satisfies: , 5. Calculation of confidence index To determine the reliability of measurement data, the present invention introduces a confidence index (CI). This index evaluates the quality of data by calculating the deviation between the measured value and the theoretical value, as well as their standard deviation. The specific calculation formula is as follows: , in, and are the measured electric and magnetic field signals, and is the calculated theoretical signal, and is the standard deviation of the electric and magnetic fields, and N is the number of sensors.

[0038] When CI is less than 0.95, it is considered that there is a large error in the measurement data, and the redundant sensor replacement process is started; When the data is reliable, normal data processing can continue.

[0039] Through these mutual verification analysis mechanisms, the present invention can achieve high-precision current and voltage measurement in an external electromagnetic interference environment while ensuring the reliability and accuracy of the measurement data.

[0040] refer to Figure 2 In one embodiment of the present invention, it is assumed that we measure a high voltage cable (conductor diameter ) current and voltage. This cable operates at a frequency of 50 Hz, with a current range of 80 A to 120 A and a voltage range of 9.5 kV to 10.5 kV. We will use the non-contact measurement method of this invention to accurately measure the current and voltage of this cable.

[0041] S1: Electromagnetic Field Theory Modeling First, based on the geometric parameters of the conductor , use Maxwell's equations to establish a model of the relationship between electric field, electromagnetic field, current and voltage.

[0042] Known parameters: (assuming current), (assuming voltage), (vacuum dielectric constant), (vacuum permeability), theoretical electric and magnetic field calculations: 1. Electric field formula (coaxial cable electric field model): , Where r is the radial distance from the cable center, is the outer diameter of the cable.

[0043] 2. Magnetic field formula (Biot-Savart law):

[0044] Through the above model calculation, we can get the theoretical values of the electric field and magnetic field. We can measure at a distance of 0.075m from the center of the cable (this is the radius of the sensor array), then: Calculation of electric field strength: , Magnetic field strength calculation: .

[0045] S2: Sensor array layout A circular electromagnetic sensor array is used to synchronously collect electric and magnetic field signals. The number of sensors is 12, and the electric field sensors and magnetic field sensors are arranged alternately. The array radius is , the distance between sensors should be less than , where the power frequency wavelength , which is easy to establish, so uniform distribution is sufficient. Therefore, the position of the sensor is determined by the angle coordinates Make arrangements, From 0 to Evenly distributed within the range.

[0046] S3: Signal Synchronous Acquisition and Conditioning Synchronously collect electric field signals through sensor arrays and magnetic field signals These signals pass through the conditioning circuit module for signal amplification, filtering and digital processing to ensure signal quality and stability.

[0047] Assume the signal sampling rate is 10 kHz, the acquisition time is 0.1 seconds, and there are 1000 sampling points. After the conditioning circuit, the amplified and filtered signal is: Electric field signal (unit: V / m) , Magnetic field signal (unit: T) .

[0048] S4. Reconstruction of electromagnetic field distribution Based on the theoretical models of electric and magnetic fields described above, we will use the spherical harmonic expansion method to interpolate the discrete data measured from the sensor array to obtain the accurate electromagnetic field distribution.

[0049] The spherical harmonic expansion formula is as follows: , in, is the position angle of the sensor, and is the expansion coefficient, (N is the number of sensors.) In this embodiment, the number of sensors is N = 12 and M = 5. Using this formula to interpolate the electric and magnetic field signals measured by the sensors reconstructs the quasi-continuous distribution of the electric and magnetic fields, thereby providing accurate electromagnetic field data. This reconstructed data is used for subsequent cross-verification analysis.

[0050] S5. Data repair and anomaly detection Calculation of confidence index: We have measured the electric field signals of 6 sensors: , The corresponding theoretical electric field signal: , Standard deviation of the electric field signal: ; Calculate the bias for each sensor and normalize: , We get: [0.9, 1.0, 0.9, 0.9, 1.0, 0.1] Therefore, the confidence index CI is calculated as: , At this time, when CI < 0.95, it is considered that there is a large error in the measurement data, and the redundant sensor replacement process or data repair is started; When the data is considered reliable, normal data processing can be continued. At this time, it is necessary to repair abnormal data points and calculate confidence indicators through spatiotemporal interpolation.

[0051] For an abnormal data point t=100, we have the electric field measurement data of the past 5 moments (sampling interval is ):

[0052]

[0053]

[0054]

[0055]

[0056] Now we need to fix outliers.

[0057] Calculate the repair value: According to the repair formula:

[0058] First calculate the exponential weighting coefficient:

[0059] ; The weighted sum of the repair values is: , molecular:

[0060] Repaired data: Therefore, the repaired electric field signal is .

[0061] S6: Mutual Verification Analysis Calculate the electric field-voltage correlation coefficient and magnetic field-current correlation coefficient To perform mutual verification analysis. The electric and magnetic fields use the above corrected values. Substituting into the calculation, we get: Electric field-voltage correlation coefficient: , Magnetic field-current correlation coefficient: , the consistency conditions are met and the calculation can continue.

[0062] S7: Optimal Estimation Decision Based on the mutual verification analysis, the present invention selects the current and voltage values with the highest correlation with the theoretical phasor sequence as the final measurement results. and magnetic field-current correlation coefficient ), we have already determined the degree of agreement between the measured signal and the theoretical signal. To further accurately estimate the current and voltage, the present invention uses a hybrid optimization algorithm that combines global search and local optimization to determine the optimal current and voltage values.

[0063] Through mutual verification analysis, the current value is preliminarily estimated to be .

[0064] The voltage value is estimated to be .

[0065] In order to further improve the measurement accuracy, the present invention adopts a hybrid optimization algorithm for optimal estimation, which includes two stages: global search and local optimization.

[0066] 1. Global Search (Genetic Algorithm) We use a population size of 100 solutions, a crossover probability of 0.8, and a mutation probability of 0.1. After several generations of optimization, the optimal solution is: Current estimation , Voltage estimation .

[0067] 2. Local Optimization (Levenberg-Marquardt Algorithm) The Levenberg-Marquardt algorithm is used in the local optimization phase. The preliminary current estimate obtained in the global search phase and voltage estimates , we further optimize it through the Levenberg-Marquardt algorithm to obtain the optimal current and voltage estimates: Final optimized current estimate: , the final optimized voltage estimate: Through these two stages of optimization, we can obtain the final optimal estimates of current and voltage, thus providing more accurate measurement results.

[0068] It can be understood that the present invention establishes an analytical model between the electric field, magnetic field, current and voltage based on the Maxwell equations, and combines the geometric information of the conductor to be measured to calculate the electric field and magnetic field phasor sequence under different current and voltage combinations. A circular electromagnetic sensor array is used to synchronously collect electric field and magnetic field signals, and the signal is amplified, filtered and digitized through a conditioning circuit module. The data processing module reconstructs the electromagnetic field distribution based on the spatial position information of the sensor, and calculates the correlation coefficient between the quasi-continuous observation phasor sequence and the theoretical database. Finally, the current and voltage values with the highest correlation with the theoretical electromagnetic field phasor sequence are selected as the final measurement results. In order to ensure the reliability of the data, the method also includes the calculation of a confidence index, and abnormal data is detected and repaired by comparing the deviation between the observed data and the theoretical value. The present invention can achieve high-precision, interference-resistant current and voltage measurements in complex electromagnetic environments, ensuring accurate and reliable monitoring of electrical parameters in power systems.

[0069] Example 2 refer to Figure 3 According to a second aspect of the present invention, a non-contact single-phase conductor current and voltage measurement system 1 is provided, comprising: a construction module 11 for acquiring geometric parameters of a target conductor, and constructing an electromagnetic field phasor sequence database based on a current and voltage combination according to the geometric parameters and Maxwell's equations; a generation module 12 for synchronously collecting electric field signals and magnetic field signals of the target conductor through a ring-shaped electromagnetic sensor array; filtering the electric field signals and magnetic field signals, and discretely reconstructing the filtered electric field signals and magnetic field signals through an interpolation method to generate a continuous electromagnetic field distribution phasor sequence; a matching module 13 for matching the electromagnetic field distribution phasor sequence with the electromagnetic field phasor sequence database, and calculating multiple correlation coefficients, wherein the correlation coefficients include electric field-voltage correlation coefficients and magnetic field-current correlation coefficients; a determination module 14 for determining a current measurement value and a voltage measurement value according to the value of each correlation coefficient and a preset threshold value: the electric field signal and the magnetic field signal corresponding to the maximum correlation coefficient in the correlation coefficient that is greater than the preset threshold value are used as the current measurement value and the voltage measurement value, respectively.

[0070] Furthermore, it also includes: an optimization module, which is used to determine the optimal current measurement value and the optimal voltage measurement value through a global search method and a local optimization method.

[0071] Example 3 refer to Figure 4 According to a third aspect of the present invention, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the non-contact single-phase conductor current and voltage measurement method according to the first aspect of the present invention.

[0072] The electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. Various programs and data required for the operation of the electronic device 500 are also stored in the RAM 503. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0073] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Figure 4 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 4 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0074] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed. It should be noted that the computer-readable medium described in the embodiment of the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can 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 of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wire, optical cable, RF (radio frequency), etc., or any suitable combination thereof.

[0075] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device. The computer-readable medium carries one or more computer programs, which, when executed by the electronic device, cause the electronic device to: Computer program code for performing the operations of embodiments of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, Python, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may 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 may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0076] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A non-contact single-phase conductor current and voltage measurement method, characterized in that: include: Acquiring geometric parameters of the target conductor, and constructing an electromagnetic field phasor sequence database based on current and voltage combinations according to the geometric parameters and Maxwell's equations; Synchronously collecting electric field signals and magnetic field signals of the target conductor through a ring-shaped electromagnetic sensor array; Filtering the electric field signal and the magnetic field signal, and discretely reconstructing the filtered electric field signal and the magnetic field signal by an interpolation method to generate a continuous electromagnetic field distribution phasor sequence; Matching the electromagnetic field distribution phasor sequence with an electromagnetic field phasor sequence database, and calculating a plurality of correlation coefficients, wherein the correlation coefficients include an electric field-voltage correlation coefficient and a magnetic field-current correlation coefficient; The current measurement value and the voltage measurement value are determined according to the value of each correlation coefficient and the preset threshold: the electric field signal and the magnetic field signal corresponding to the correlation coefficient greater than the preset threshold and the maximum correlation coefficient are respectively used as the current measurement value and the voltage measurement value.

2. The non-contact single-phase conductor current and voltage measurement method according to claim 1, characterized in that: The step of discretely reconstructing the filtered electric field signal and magnetic field signal by interpolation to generate a continuous electromagnetic field distribution phasor sequence includes: The filtered electric field signal and magnetic field signal are interpolated based on spherical harmonic functions to generate a continuous electromagnetic field distribution phasor sequence.

3. The non-contact single-phase conductor current and voltage measurement method according to claim 2, characterized in that: The interpolation of the filtered electric field signal and magnetic field signal based on the spherical harmonic function comprises: Based on the measurement angle of each sensor and the total number of sensors, the electric field signal and magnetic field signal obtained by each sensor are interpolated through Fourier series.

4. The non-contact single-phase conductor current and voltage measurement method according to claim 1, characterized in that: Before the discrete reconstruction of the filtered electric field signal and magnetic field signal by the interpolation method is performed, the method further includes: Calculate the confidence level of the electric field signal and magnetic field signal of each sensor; Anomaly detection is performed on the electric field signal and the magnetic field signal according to the confidence level: if the confidence level of the electric field signal or the magnetic field signal is lower than a preset value, the data is judged to be abnormal.

5. The non-contact single-phase conductor current and voltage measurement method according to claim 1, characterized in that: Also includes: The optimal current measurement value and the optimal voltage measurement value are determined through global search method and local optimization method.

6. The non-contact single-phase conductor current and voltage measurement method according to claim 5, characterized in that: Determining the optimal current measurement value and the optimal voltage measurement value by using a global search method and a local optimization method includes: Based on the electric field signal error and the magnetic field signal error, an optimization function is constructed; based on the physical laws of the electromagnetic field, the constraints of the optimization function are determined; Searching for global solutions to optimization functions with constraints using genetic algorithms; The global solution is further optimized using the Levenberg-Marquardt algorithm to obtain the optimal current measurement value and the optimal voltage measurement value.

7. A non-contact single-phase conductor current and voltage measurement system, characterized in that: include: A construction module is used to obtain geometric parameters of the target conductor and construct an electromagnetic field phasor sequence database based on current and voltage combinations according to the geometric parameters and Maxwell's equations; a generation module for synchronously collecting electric field signals and magnetic field signals of a target conductor through a ring-shaped electromagnetic sensor array; filtering the electric field signals and magnetic field signals, and discretely reconstructing the filtered electric field signals and magnetic field signals through an interpolation method to generate a continuous electromagnetic field distribution phasor sequence; a matching module, configured to match the electromagnetic field distribution phasor sequence with an electromagnetic field phasor sequence database, and calculate a plurality of correlation coefficients, wherein the correlation coefficients include an electric field-voltage correlation coefficient and a magnetic field-current correlation coefficient; The determination module is used to determine the current measurement value and the voltage measurement value according to the value of each correlation coefficient and the preset threshold: the electric field signal and the magnetic field signal corresponding to the correlation coefficient greater than the preset threshold and the maximum correlation coefficient are used as the current measurement value and the voltage measurement value respectively.

8. The non-contact single-phase conductor current and voltage measurement system according to claim 7, characterized in that: Also includes: The optimization module is used to determine the optimal current measurement value and the optimal voltage measurement value through a global search method and a local optimization method.

9. An electronic device comprising: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the non-contact single-phase conductor current and voltage measurement method according to any one of claims 1 to 6.

10. A computer-readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the non-contact single-phase conductor current and voltage measurement method according to any one of claims 1 to 6 is implemented.

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