A FPGA chip embedded current transformer

Abstract

The present invention provides an FPGA chip embedded current transformer, comprising: a current transformer main structure and an FPGA chip, wherein the current transformer main structure comprises: an access module, a rectifier circuit and a magnetic field sensor, the magnetic field sensor is arranged in the access module, the access module is connected to the rectifier circuit, the rectifier circuit is connected to the FPGA chip, and the FPGA chip comprises: a signal processing module and a data processing center, the signal processing module processes and outputs the output signal of the magnetic field sensor and the output signal of the rectifier circuit, the data processing center obtains the circuit signal, and uses the FFT algorithm to perform multi-dimensional spectrum analysis. The present invention realizes the collection and real-time analysis of current signals by embedding an FPGA chip inside the current transformer, thereby reducing the time consumption and error of transmitting and outputting the processed signal, so that the current transformer can perform multi-dimensional spectrum analysis in time, and improves the response efficiency and accuracy of the current transformer.

Description

Technical Field

[0001] The present invention relates to the technical field of current transformers, and in particular to an FPGA chip embedded current transformer. Background Art

[0002] Current transformer is one of the most widely used measuring devices in power systems. It converts high current into smaller current that can be measured by standard instruments, thereby realizing the current measurement in high current systems. It is mainly used in the fields of electric energy metering, condition monitoring and relay protection.

[0003] At present, in the prior art, traditional current transformers usually only provide the instantaneous value of the current and cannot directly provide spectrum analysis of the current signal. Not only does it take time to transmit the signal over long distances, but the spectrum analysis will also be inaccurate due to transmission errors. Therefore, the present invention proposes an FPGA chip embedded current transformer, which embeds an FPGA chip inside the current transformer to realize the collection and real-time analysis of the current signal, thereby reducing the time consumption and error of transmitting the output processing signal, so that the current transformer can perform multi-dimensional spectrum analysis in a timely manner, while improving the response efficiency and accuracy of the current transformer. Summary of the invention

[0004] The purpose of the present invention is to provide a FPGA chip embedded current transformer to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an FPGA chip embedded current transformer, comprising: a current transformer main structure and an FPGA chip, wherein the current transformer main structure comprises: an access module, a rectifier circuit and a magnetic field sensor, the magnetic field sensor is arranged in the access module, the access module is connected to the rectifier circuit, the rectifier circuit is connected to the FPGA chip, the FPGA chip comprises: a signal processing module and a data processing center, the signal processing module is used to process and output the output signal of the magnetic field sensor and the output signal of the rectifier circuit, the data processing center is used to obtain the circuit signal and use the FFT algorithm to perform multi-dimensional spectrum analysis.

[0006] Preferably, the access module comprises: a magnetic core and a transmission line, and the magnetic core is a hybrid composite magnetic core, comprising: an inner iron core and an outer iron core, wherein the inner iron core is a complete annular iron core, and the outer iron core is an annular iron core with an air gap; the transmission line is accessed by passing through the inner iron core.

[0007] Preferably, the annular core with air gaps in the outer core is a plurality of identical annular core sheet segments, and the annular core sheet segments are evenly arranged on the outer wall of the complete annular core to form a plurality of air gaps, wherein the size of the air gaps is adapted to the size of the magnetic field sensor.

[0008] Preferably, the rectifier circuit includes: a rectifier resistor and a winding wire, the winding starting position is determined on the hybrid combination magnetic core, and then the winding wire is evenly wound on the hybrid combination magnetic core based on the winding starting position, and the rectifier resistor and the FPGA chip are connected in sequence after the winding wire is wound around the hybrid combination magnetic core.

[0009] Preferably, the signal processing module comprises: a power supply unit, a voltage stabilization unit, a temperature compensation unit, a zero adjustment unit, an amplification processing unit and an addition operation unit;

[0010] The voltage stabilizing unit converts the power supply voltage of the power supply unit into a target voltage using a voltage stabilizing circuit;

[0011] The temperature compensation unit uses a temperature compensation circuit to adjust the temperature offset problem of the magnetic field sensor;

[0012] The zero adjustment unit adjusts the potential of the magnetic field sensor by adjusting the resistance value of the potentiometer;

[0013] The amplification processing unit performs amplitude adjustment on the output signal of the magnetic field sensor and obtains the output adjustment signal of the magnetic field sensor;

[0014] The addition operation unit uses an adder to perform a logic operation according to the output adjustment signal of the magnetic field sensor and the output signal of the rectification circuit.

[0015] Preferably, the addition operation unit uses an adder to perform a logic operation according to the output adjustment signal of the magnetic field sensor and the output signal of the rectifier circuit, including:

[0016] Converting the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor into carry prefix signals to obtain a first carry prefix signal and a second carry prefix signal respectively;

[0017] Analyze the first carry prefix signal and the second carry prefix signal based on the carry tree, and obtain a carry selection signal;

[0018] The output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor are summed to obtain a sum result, and the sum result is screened according to the carry selection signal to obtain an adder output result.

[0019] Preferably, the data processing center comprises: a collection and acquisition unit, a data analysis unit and a fault diagnosis unit.

[0020] The acquisition unit is used to acquire the output signal of the signal processing module to obtain an output processing signal;

[0021] The data analysis unit is used to perform multi-dimensional spectrum analysis on the output processing signal using an FFT algorithm to obtain multi-dimensional spectrum analysis data;

[0022] The fault diagnosis unit is used to perform fault detection analysis based on the convolutional neural network model according to the multi-dimensional spectrum analysis data to obtain a fault diagnosis result.

[0023] Preferably, the data analysis unit uses an FFT algorithm to perform multi-dimensional spectrum analysis on the output processing signal, including:

[0024] Performing Fourier transform on the output processing signal to obtain signal transformation information;

[0025] The signal transformation information is transformed in the frequency domain, and nonlinear characteristics are simulated. At the same time, multiple filters are used to perform bandpass filtering in the frequency domain to obtain the multi-dimensional spectrum characteristics of the output processing signal;

[0026] Adjacent frames of the output processed signal are combined and spliced ​​according to the multi-dimensional spectrum features to obtain multi-dimensional spectrum analysis data.

[0027] Preferably, after obtaining the multidimensional spectrum analysis data, the data analysis unit also performs visualization processing on the multidimensional spectrum analysis data, converts the multidimensional spectrum analysis data into a chart for presentation, determines multidimensional spectrum analysis data presentation information, and uses different colors to distinguish different parameters in the multidimensional spectrum analysis data presentation information.

[0028] Preferably, the fault diagnosis unit performs fault detection analysis based on a convolutional neural network model according to the multi-dimensional spectrum analysis data, including:

[0029] Build a convolutional neural network;

[0030] Set the number of network iteration parameters for convolutional neural networks;

[0031] Determine network training sample data, and use the network training sample data combined with the set network iteration number parameters to optimize the convolutional neural network, and adjust to obtain a convolutional neural network optimization model;

[0032] Obtain multi-dimensional spectrum analysis data;

[0033] The convolution neural network optimization model is used to perform convolution calculation on the multi-dimensional spectrum analysis data to obtain the characteristic value of the multi-dimensional spectrum analysis data;

[0034] Perform fault matching based on the characteristic values ​​of multi-dimensional spectrum analysis data to obtain characteristic matching similarity values;

[0035] Combined with the preset threshold, the feature matching similarity value is analyzed and judged to determine the fault diagnosis result;

[0036] Provide fault reminder according to the fault diagnosis results.

[0037] The present invention embeds an FPGA chip inside the current transformer, so that the current transformer can realize the collection and real-time analysis of current signals, reduce the transmission time consumption and error of the output processing signal, and enable the current transformer to perform multi-dimensional spectrum analysis in time, while improving the response efficiency and accuracy of the current transformer. Moreover, the current transformer can convert a large current into a small current, thereby expanding the depth and breadth of current monitoring and ensuring the safety of large current monitoring. Moreover, through the FPGA chip, not only the instantaneous value of the current can be measured in real time in the current transformer, but also the spectrum analysis of the circuit signal can be provided, reducing the back-end processing pressure and reducing the dependence on high-performance computing equipment. Moreover, the FPGA chip is flexible in design, and the reconfigurable chip structure has strong compatibility and can be compatible with large-scale integrated circuits for parallel computing. In addition, the large current is isolated by a transformer in the main structure of the current transformer, which ensures the safety of the current transformer and avoids the dangerous situation of direct measurement of the current transformer and the large current.

[0038] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0039] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 is an overall schematic diagram of the current transformer of the present invention;

[0042] Figure 2 is a schematic diagram of a signal processing module in a current transformer according to the present invention;

[0043] Figure 3 It is a schematic diagram of the steps of the adding operation unit in the signal processing module of the current transformer according to the present invention;

[0044] Figure 4 It is a schematic diagram of a data processing center in a current transformer according to the present invention;

[0045] Figure 5 It is a schematic diagram of the steps of a data analysis unit in a data processing center of a current transformer according to the present invention;

[0046] Figure 6 The figure is a schematic diagram of the steps of the fault diagnosis unit in the data processing center of the current transformer according to the present invention. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0048] like Figure 1 As shown, an embodiment of the present invention provides an FPGA chip embedded current transformer, including: a current transformer main structure and an FPGA chip, wherein the current transformer main structure includes: an access module, a rectifier circuit and a magnetic field sensor, the magnetic field sensor is arranged in the access module, the access module is connected to the rectifier circuit, the rectifier circuit is connected to the FPGA chip, the FPGA chip includes: a signal processing module and a data processing center, the signal processing module is used to process and output the output signal of the magnetic field sensor and the output signal of the rectifier circuit, and the data processing center is used to obtain the circuit signal and use the FFT algorithm to perform multi-dimensional spectrum analysis.

[0049] In the above technical solution, the access module connects the transmission wire to the magnetic core, and generates a change in magnetic flux when the transmission wire is energized.

[0050] In the above technical solution, the magnetic field sensor is connected to the FPGA chip, and after the magnetic field sensor obtains the induced data signal, the induced data signal is wirelessly transmitted to the signal processing module.

[0051] In the above technical solution, the magnetic field sensor adopts a Wheatstone bridge structure.

[0052] In the above technical solution, the FPGA chip adopts a block design.

[0053] The above technical solution embeds an FPGA chip inside the current transformer, so that the current transformer can realize the collection and real-time analysis of current signals, reduce the transmission time consumption and error of the output processing signal, and enable the current transformer to perform multi-dimensional spectrum analysis in time, while improving the response efficiency and accuracy of the current transformer. Moreover, the current transformer can convert large current into small current, thereby expanding the depth and breadth of current monitoring and ensuring the safety of large current monitoring. In addition, the FPGA chip can not only measure the instantaneous value of the current in real time in the current transformer, but also provide spectrum analysis of the circuit signal, reduce the back-end processing pressure, and reduce the dependence on high-performance computing equipment. In addition, the FPGA chip is flexible in design, and the reconfigurable chip structure has strong compatibility and can be compatible with large-scale integrated circuits for parallel computing. In addition, the transformer isolates the large current in the main structure of the current transformer, which ensures the safety of the current transformer and avoids dangerous situations caused by direct measurement of the current transformer and large current.

[0054] In one embodiment provided by the present invention, the access module includes: a magnetic core and a transmission line, and the magnetic core adopts a hybrid composite magnetic core, including: an inner iron core and an outer iron core, wherein the inner iron core is a complete annular iron core, and the outer iron core is an annular iron core with an air gap; the transmission line is accessed by passing through the inner iron core.

[0055] In the above technical solution, the annular iron core with an air gap is composed of a plurality of annular iron core segments.

[0056] In the above technical solution, the outer wall of the outer iron core and the inner iron core are bonded together to form a hybrid composite magnetic core.

[0057] The above technical solution improves the saturation limit of the traditional magnetic core by mixing and combining the magnetic core, reduces the impact of the current transformer on the safe and stable operation of the transmission line, reduces the probability of the current signal in the rectifier circuit being deformed due to the saturation of the magnetic core, and reduces the error of the current transformer. In addition, the transmission line is connected by passing through the internal iron core, which not only facilitates the current transformer to monitor the transmission line, but also is simple and easy to operate. At the same time, current monitoring can be achieved without directly monitoring the transmission line, which effectively improves the depth and breadth of the current transformer's current monitoring.

[0058] In one embodiment provided by the present invention, the annular iron core with air gaps in the outer iron core is a plurality of identical annular iron core segments, and the annular iron core segments are evenly arranged on the outer wall of the complete annular iron core to form a plurality of air gaps, wherein the size of the air gaps is adapted to the size of the magnetic field sensor.

[0059] In the above technical solution, the magnetic field sensor is arranged in the air gap of the external iron core and is deployed in the middle position of the air gap.

[0060] In the above technical solution, the length of the air gap is slightly greater than the thickness of the shell of the magnetic field sensor.

[0061] In the above technical solution, the size of the air gap is related to the size of the magnetic field sensor, and the number of the annular iron core segments is determined according to the size of the air gap and the arc length of the annular iron core.

[0062] The above technical solution forms an external iron core through multiple identical annular iron core segments, so that the external iron core can have an air gap, thereby generating a diffraction phenomenon when the transmission line is connected to the current, and by setting the length of the air gap to be slightly larger than the shell thickness of the magnetic field sensor, the magnetic field sensor can be stably present in the air gap to avoid falling off or moving to affect the use of the magnetic field sensor, and by deploying the magnetic field sensor in the middle position of the air gap, the magnetic field sensor is located in an area where the diffraction phenomenon of the mixed combination magnetic core is relatively weak, thereby reducing the influence of the diffraction phenomenon on the current transformer and ensuring the accuracy of the current transformer.

[0063] In one embodiment provided by the present invention, the rectifier circuit includes: a rectifier resistor and a winding wire, the winding starting position is determined on a hybrid combination magnetic core, and then the winding wire is evenly wound on the hybrid combination magnetic core based on the winding starting position, and after the winding wire is wound around the hybrid combination magnetic core, the rectifier resistor and the FPGA chip are connected in sequence.

[0064] In the above technical solution, the starting position of the winding is the deployment position of the magnetic field sensor on the hybrid combined magnetic core.

[0065] In the above technical solution, when the winding wire is evenly wound on the mixed composite magnetic core, it is evenly wound on the inner core and the outer core according to the winding rules combined with the transmission line parameters.

[0066] The above technical solution realizes flexible adjustment of the integrated circuit by winding the resistive wire around the hybrid combined magnetic core, so that the integrated circuit can realize current monitoring according to the transmission line in any situation by adjusting the winding of the resistive wire on the hybrid combined magnetic core, thereby expanding the application scope of the current transformer and improving the depth and breadth of the current monitoring of the current transformer. In addition, the deployment position of the magnetic field sensor on the hybrid combined magnetic core is used as the winding starting position, and the magnetic field sensor is exposed during the process of winding the resistive wire around the hybrid combined magnetic core, so as to avoid the influence of the winding wire on the use of the magnetic field sensor, provide convenience for the output of the magnetic field sensor, and thus reduce the output error of the magnetic field sensor.

[0067] like Figure 2 As shown, in one embodiment provided by the present invention, the signal processing module includes: a power supply unit, a voltage stabilization unit, a temperature compensation unit, a zero adjustment unit, an amplification processing unit and an addition operation unit;

[0068] The voltage stabilizing unit converts the power supply voltage of the power supply unit into a target voltage using a voltage stabilizing circuit;

[0069] The temperature compensation unit uses a temperature compensation circuit to adjust the temperature offset problem of the magnetic field sensor;

[0070] The zero adjustment unit adjusts the potential of the magnetic field sensor by adjusting the resistance value of the potentiometer;

[0071] The amplification processing unit performs amplitude adjustment on the output signal of the magnetic field sensor and obtains the output adjustment signal of the magnetic field sensor;

[0072] The addition operation unit uses an adder to perform a logic operation according to the output adjustment signal of the magnetic field sensor and the output signal of the rectification circuit.

[0073] In the above technical solution, one end of the voltage stabilizing unit is connected to the power supply unit, and the other end is connected to the temperature compensation unit, the temperature compensation unit is connected to the magnetic field sensor, the zero adjustment unit is also connected to the magnetic field sensor, the output end of the magnetic field sensor is connected to the amplification processing unit, and the addition unit performs calculation processing based on the output of the amplification processing unit and the output signal of the rectifier circuit, wherein the power supply unit is also connected to the amplification processing unit and the addition unit.

[0074] In the above technical solution, when unequal potential occurs in the potential of the magnetic field sensor, the zero adjustment unit adjusts the resistance of the potentiometer, thereby reducing the unequal potential phenomenon existing in the magnetic field sensor.

[0075] In the above technical solution, when the amplification processing unit adjusts the amplitude of the output signal of the magnetic field sensor, an amplifier with low noise, low offset voltage and high common mode rejection ratio is used to adjust the amplitude of the output signal of the magnetic field sensor.

[0076] In the above technical solution, the temperature compensation unit uses the temperature compensation circuit to adjust the temperature offset problem of the magnetic field sensor, including: performing temperature analysis and judgment on the magnetic field sensor to determine whether the temperature of the magnetic field sensor changes, when the temperature of the magnetic field sensor changes, obtaining temperature change data information, and determining the control target and control information in the temperature compensation circuit according to the temperature change data information, and then adjusting the control target according to the control information, so that the adjusted temperature compensation circuit acts on the magnetic field sensor to achieve temperature compensation of the magnetic field sensor. Wherein, when performing temperature analysis and judgment on the magnetic field sensor, an effective analysis is performed on the obtained temperature information, including: performing a preliminary analysis on the temperature information, determining the fluctuation data, and locking the target position based on the fluctuation data, and then calling the temperature information around the target position, combining the temperature information around the target position to further analyze the fluctuation data, and determine whether there is a temperature gradient change around the target position. When there is a temperature gradient change around the target position, the fluctuation data is valid data, and when there is no temperature gradient change around the target position, the fluctuation data is invalid data, and then it is determined whether the temperature of the magnetic field sensor changes according to the valid data.

[0077] In the above technical solution, the target voltage is a voltage that meets the requirements of the magnetic field sensor.

[0078] The above technical solution combines the output signal of the magnetic field sensor with the output signal of the rectifier circuit through the signal processing module for output, realizes the compensation of the output signal of the magnetic field sensor for the output signal of the rectifier circuit, avoids the output of the distorted rectifier circuit, ensures the effectiveness and rationality of the output signal, and provides guarantee for the analysis of the data processing center. In addition, the magnetic field sensor is regulated by the voltage stabilizing unit, the temperature compensation unit and the zeroing unit, so that the magnetic field sensor can output a stable signal according to the magnetic field effect generated by the damping branch, and the output signal of the magnetic field sensor is adjusted by the amplifying processing unit, which ensures the rationality and effectiveness of the output adjustment signal of the magnetic field sensor, so that the output adjustment signal of the magnetic field sensor can realize distortion compensation for the output signal of the rectifier circuit in the addition operation unit, avoids the output of the distorted signal in the rectifier circuit, ensures the effectiveness of the multi-dimensional spectrum analysis of the data processing center, and improves the accuracy of the current transformer. In addition, when the temperature compensation unit uses the temperature compensation circuit to adjust the temperature offset problem of the magnetic field sensor, it effectively analyzes the acquired temperature information to determine whether the temperature of the magnetic field sensor has changed based on the valid data, thereby achieving temperature compensation for the magnetic field sensor, avoiding the problem of temperature offset caused by individual anomalies in the temperature information obtained by the magnetic field sensor, which may affect the temperature compensation circuit in adjusting the magnetic field sensor, thereby ensuring temperature stability.

[0079] like Figure 3 As shown, in one embodiment provided by the present invention, the addition operation unit uses an adder to perform a logic operation according to the output adjustment signal of the magnetic field sensor and the output signal of the rectifier circuit, including:

[0080] A1. Converting the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor into carry prefix signals to obtain a first carry prefix signal and a second carry prefix signal respectively;

[0081] A2. Analyze the first carry prefix signal and the second carry prefix signal based on the carry tree, and obtain a carry selection signal;

[0082] A3. Perform a sum calculation on the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor to obtain a sum result, and filter the sum result according to the carry selection signal to obtain an adder output result.

[0083] In the above technical solution, the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor are converted into a carry prefix signal through 64 1-bit dynamic circuits.

[0084] In the above technical scheme, the carry tree adopts multi-layer point operation to analyze the carry prefix signal. For example, in the case of 3-layer point operation, the input of the first layer is the first carry prefix signal and the second carry prefix signal with an interval of 1 bit, the 1st bit is a 1-input point operation, the 2nd bit is a 2-input point operation, the 3rd bit is a 3-input point operation, and the 4th to 64th bits are a 4-input point operation; the input of the second layer is the first carry prefix signal and the second carry prefix signal output by the first layer with an interval of four bits, the 1st to 4th bits are a 1-input point operation, the 5th to 8th bits are a 2-input point operation, the 9th to 12th bits are a 3-input point operation, and the 13th to 64th bits are a 4-input point operation; the input of the third layer is the first carry prefix signal and the second carry prefix signal output by the second layer with an interval of 16 bits, the 1st to 16th bits are a 1-input point operation, the 17th to 32nd bits are a 2-input point operation, the 33rd to 48th bits are a 3-input point operation, and the 49th to 64th bits are a 4-input point operation.

[0085] In the above technical solution, when the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor are summed, the output adjustment signal of the magnetic field sensor is used to compensate the output signal of the rectifier circuit.

[0086] The above technical solution adopts a carry adder to realize the processing of the addition unit, realizes the logic operation of the output adjustment signal of the magnetic field sensor and the output signal of the rectifier circuit in a simple way, has low power consumption, and can also enable the adder to realize the logic operation of the output adjustment signal of the magnetic field sensor and the output signal of the rectifier circuit in a shorter time, thereby improving the efficiency of the addition unit. Moreover, the structure of the adder is simple, which can effectively reduce the occupied area of ​​the addition unit on the FPGA chip.

[0087] like Figure 4 As shown, in one embodiment provided by the present invention, the data processing center includes: a collection and acquisition unit, a data analysis unit and a fault diagnosis unit.

[0088] The acquisition unit is used to acquire the output signal of the signal processing module to obtain an output processing signal;

[0089] The data analysis unit is used to perform multi-dimensional spectrum analysis on the output processing signal using an FFT algorithm to obtain multi-dimensional spectrum analysis data;

[0090] The fault diagnosis unit is used to perform fault detection analysis based on the convolutional neural network model according to the multi-dimensional spectrum analysis data to obtain a fault diagnosis result.

[0091] In the above technical solution, the acquisition unit, the data analysis unit and the fault diagnosis unit are connected in sequence.

[0092] In the above technical solution, the collection and acquisition unit includes: a collection unit and a monitoring unit. The monitoring unit monitors the output of the signal processing module, and the collection unit collects the output of the signal processing module. When the monitoring unit monitors the output information of the signal processing module, the collection unit acquires the output processing signal, thereby obtaining the output processing signal in the collection unit.

[0093] The above technical solution realizes data processing and analysis in the current transformer through the data processing center, so that the current transformer can not only realize current monitoring, but also directly perform multi-dimensional spectrum analysis on the output processing signal, reducing data transmission errors, reducing the delay of the data processing center, and ensuring the response speed and accuracy of the data processing center. The output signal of the signal processing module is monitored and acquired by the acquisition unit, so that when the signal processing module obtains the output signal, it is acquired by the acquisition unit in time, so that the output processing signal can be analyzed in time, reducing time waste, and the data analysis unit uses the FFT algorithm to perform multi-dimensional spectrum analysis on the output processing signal, so that the characteristics of the output processing signal can be fully understood, and then the current monitoring information of the transmission line can be more accurately understood. The self-inspection of the current transformer is realized through the fault diagnosis unit, so that the fault can be discovered in time when the current transformer is abnormal, reducing the impact of the fault.

[0094] like Figure 5 As shown, in one embodiment provided by the present invention, the data analysis unit uses an FFT algorithm to perform multi-dimensional spectrum analysis on the output processing signal, including:

[0095] B1. Perform Fourier transform on the output processed signal to obtain signal transformation information;

[0096] B2, performing axis transformation on the signal transformation information in the frequency domain, simulating nonlinear characteristics, and using multiple filters to perform bandpass filtering in the frequency domain to obtain multi-dimensional spectrum characteristics of the output processing signal;

[0097] B3. Adjacent frames of the output processed signal are combined and spliced ​​according to the multi-dimensional spectrum features to obtain multi-dimensional spectrum analysis data.

[0098] In the above technical solution, the filter used is a triangular filter.

[0099] In the above technical solution, when Fourier transform is performed on the output processed signal, short-time Fourier transform is performed on each frame in the output processed signal.

[0100] In the above technical solution, when M filters are used to perform bandpass filtering in the frequency domain, the multidimensional spectrum analysis data obtained is M×N-dimensional multidimensional spectrum features, where N is the total number of frames of the output processing signal.

[0101] The above technical solution realizes multi-dimensional spectrum analysis through the data analysis unit, so that the output processing signal can be better understood, so that the status of the current transformer can be better grasped with the help of the output processing signal, and then the transmission status of the transmission line can be more accurately determined, thereby ensuring the accuracy of the transmission line current monitoring.

[0102] In one embodiment provided by the present invention, after obtaining the multidimensional spectrum analysis data, the data analysis unit also performs visualization processing on the multidimensional spectrum analysis data, converts the multidimensional spectrum analysis data into a chart for presentation, determines the multidimensional spectrum analysis data presentation information, and uses different colors to distinguish different parameters in the multidimensional spectrum analysis data presentation information.

[0103] In the above technical solution, different parameters can be set to different colors.

[0104] The above technical solution makes the multi-dimensional spectrum analysis data more intuitive by visualizing the data, and uses different colors to distinguish different parameters so that it can be better identified in the multi-dimensional spectrum analysis data presentation information, so that relevant personnel can obtain key information from the multi-dimensional spectrum analysis data presentation information more efficiently and accurately.

[0105] like Figure 6 As shown, in one embodiment provided by the present invention, the fault diagnosis unit performs fault detection analysis based on a convolutional neural network model according to multi-dimensional spectrum analysis data, including:

[0106] C1. Establish a convolutional neural network;

[0107] C2. Setting the number of network iterations for the convolutional neural network;

[0108] C3. Determine network training sample data, and use the network training sample data combined with the set network iteration number parameters to optimize the convolutional neural network, and adjust to obtain a convolutional neural network optimization model;

[0109] C4, obtain multi-dimensional spectrum analysis data;

[0110] C5. Use the convolution neural network optimization model to perform convolution calculation on the multi-dimensional spectrum analysis data to obtain the characteristic value of the multi-dimensional spectrum analysis data;

[0111] C6. Perform fault matching based on the characteristic values ​​of the multi-dimensional spectrum analysis data to obtain characteristic matching similarity values;

[0112] C7. Analyze and judge the feature matching similarity value in combination with the preset threshold to determine the fault diagnosis result;

[0113] C8. Provide fault reminder according to the fault diagnosis results.

[0114] In the above technical scheme, when the convolutional neural network is optimized using the network training sample data combined with the set network iteration number parameters, when the current network iteration number is equal to the set network iteration number parameters, an error analysis is performed on the convolutional neural network, and the convolutional neural network parameters when the convolutional neural network error is the smallest are taken as the optimal parameters, and then the convolutional neural network optimization model is obtained according to the optimal parameters. When the current network iteration number is less than the set network iteration number parameters and the convolutional neural network error is 0, the convolutional neural network parameters are the optimal parameters. At this time, there is no need to continue adjusting the network iteration number parameters and updating the current network iteration number, and the convolutional neural network optimization model can be obtained according to the optimal parameters.

[0115] In the above technical scheme, when a convolutional neural network optimization model is used to perform convolution calculations on multidimensional spectrum analysis data, the step value, convolution kernel height, and convolution kernel width are combined with the weight coefficient matrix and the normalized fault characteristics to perform convolution operations, and the bias coefficient is used to correct the convolution operation results to obtain the characteristic values ​​of the multidimensional spectrum analysis data.

[0116] In the above technical scheme, the feature matching similarity value is analyzed and judged in combination with the preset threshold to determine the fault diagnosis result. When the feature matching similarity value is greater than the preset threshold, the fault diagnosis result is that the current transformer is faulty. When the feature matching similarity value is not greater than the preset threshold, the fault diagnosis result is that the current transformer is not faulty.

[0117] The above technical solution realizes fault analysis and judgment through the fault diagnosis unit, so that abnormal phenomena in the current transformer can be discovered in time, and a convolutional neural network model is used for fault detection and analysis, which not only has a high correct judgment rate but also a low missed detection rate, effectively ensuring the accuracy of the fault diagnosis unit. After establishing the convolutional neural network, the network training sample data is combined with the set network iteration number parameters to optimize the convolutional neural network, reducing the error of the convolutional neural network and improving the accuracy of the characteristic values ​​of the multi-dimensional spectrum analysis data, thereby ensuring the accuracy of the fault diagnosis results.

[0118] Those skilled in the art should understand that the first and second in the present invention merely refer to different application stages.

[0119] Other embodiments of the present disclosure will be readily apparent to those skilled in the art after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0120] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An FPGA chip embedded current transformer, characterized in that: include: A current transformer main structure and an FPGA chip, wherein the current transformer main structure includes: an access module, a rectifier circuit and a magnetic field sensor, the magnetic field sensor is arranged in the access module, the access module is connected to the rectifier circuit, the rectifier circuit is connected to the FPGA chip, the FPGA chip includes: a signal processing module and a data processing center, the signal processing module is used to process and output the output signal of the magnetic field sensor and the output signal of the rectifier circuit, the data processing center is used to obtain the circuit signal and use the FFT algorithm to perform multi-dimensional spectrum analysis; The signal processing module includes: a power supply unit, a voltage stabilizing unit, a temperature compensation unit, a zeroing unit, an amplifying unit and an adding unit; the voltage stabilizing unit uses a voltage stabilizing circuit to convert the power supply voltage of the power supply unit into a target voltage; the temperature compensation unit uses a temperature compensation circuit to adjust the temperature offset problem of the magnetic field sensor; the zeroing unit adjusts the potential of the magnetic field sensor by adjusting the resistance of the potentiometer; the amplifying unit adjusts the amplitude of the output signal of the magnetic field sensor and obtains the output adjustment signal of the magnetic field sensor; the adding unit uses an adder to perform a logical operation according to the output adjustment signal of the magnetic field sensor and the output signal of the rectifier circuit, including: converting the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor into carry prefix signals, respectively obtaining a first carry prefix signal and a second carry prefix signal; analyzing the first carry prefix signal and the second carry prefix signal based on a carry tree, and obtaining a carry selection signal; performing a summation calculation on the output signal of the rectifier circuit and the output adjustment signal of the magnetic field sensor to obtain a summation result, and filtering the summation result according to the carry selection signal to obtain an adder output result; The data processing center includes: an acquisition unit, a data analysis unit and a fault diagnosis unit. The acquisition unit is used to acquire the output signal of the signal processing module to obtain the output processing signal; the data analysis unit is used to use the FFT algorithm to perform multi-dimensional spectrum analysis on the output processing signal to obtain multi-dimensional spectrum analysis data, including: performing Fourier transform on the output processing signal to obtain signal transformation information; performing axis transformation on the signal transformation information in the frequency domain, simulating nonlinear characteristics, and using multiple filters to perform bandpass filtering in the frequency domain to obtain multi-dimensional spectrum characteristics of the output processing signal; splicing and combining the multi-dimensional spectrum characteristics in combination with adjacent frames of the output processing signal to obtain multi-dimensional spectrum analysis data; the fault diagnosis unit is used to perform fault detection analysis based on the convolutional neural network model according to the multi-dimensional spectrum analysis data to obtain fault diagnosis results.

2. The current transformer according to claim 1, characterized in that: The access module includes: a magnetic core and a transmission wire. The magnetic core is a hybrid composite magnetic core, including: an inner core and an outer core, wherein the inner core is a complete annular core and the outer core is an annular core with an air gap. The transmission wire is accessed by passing through the inner core.

3. The current transformer according to claim 2, characterized in that: The annular core with air gaps in the outer core is a plurality of identical annular core segments, and the annular core segments are evenly arranged on the outer wall of the complete annular core to form a plurality of air gaps, wherein the size of the air gaps is adapted to the size of the magnetic field sensor.

4. The current transformer according to claim 2, characterized in that: The rectifier circuit includes: a rectifier resistor and a winding wire. The winding starting position is determined on a hybrid combined magnetic core, and then the winding wire is evenly wound on the hybrid combined magnetic core based on the winding starting position. After the winding wire is wound around the hybrid combined magnetic core, the rectifier resistor and the FPGA chip are connected in sequence.

5. The current transformer according to claim 1, characterized in that: After obtaining the multidimensional spectrum analysis data, the data analysis unit also performs visualization processing on the multidimensional spectrum analysis data, converts the multidimensional spectrum analysis data into a chart for presentation, determines multidimensional spectrum analysis data presentation information, and uses different colors to distinguish different parameters in the multidimensional spectrum analysis data presentation information.

6. The current transformer according to claim 1, characterized in that: The fault diagnosis unit performs fault detection analysis based on the convolutional neural network model according to the multi-dimensional spectrum analysis data, including: Build a convolutional neural network; Set the number of network iteration parameters for convolutional neural networks; Determine network training sample data, and use the network training sample data combined with the set network iteration number parameters to optimize the convolutional neural network, and adjust to obtain a convolutional neural network optimization model; Obtain multi-dimensional spectrum analysis data; The convolution neural network optimization model is used to perform convolution calculation on the multi-dimensional spectrum analysis data to obtain the characteristic value of the multi-dimensional spectrum analysis data; Perform fault matching based on the characteristic values ​​of multi-dimensional spectrum analysis data to obtain characteristic matching similarity values; Combined with the preset threshold, the feature matching similarity value is analyzed and judged to determine the fault diagnosis result; Provide fault reminder according to the fault diagnosis results.

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