A method, system, electronic equipment and storage medium for intelligent monitoring of electric train sets

Abstract

The present invention discloses an intelligent monitoring method, system, electronic device and storage medium for a motor vehicle group, belonging to the technical field of motor vehicle groups. The present invention uses FPGA to obtain continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to a host computer database; at the same time, in conjunction with ARM joint analysis, the voltage transformer transfer function is combined to reconstruct and invert the primary side voltage waveform, and the overvoltage characteristic information is uploaded to the host computer database. The present invention solves the problem of inaccurate power quality calculation caused by inaccurate overvoltage data obtained by the motor vehicle group.

Description

Technical Field

[0001] The present invention belongs to the technical field of multiple unit trains, and in particular relates to a multiple unit train intelligent monitoring method, system, electronic equipment and storage medium. Background Art

[0002] With the rapid development of science and technology and economy, the number and speed of EMUs in my country are constantly increasing, which has greatly improved people's transportation problems. However, with the increasing demand for intelligent EMUs, the corresponding high-power equipment, asymmetric loads and other nonlinear load capacities are also increasing, causing a series of problems in the distribution network system, such as waveform distortion, harmonics and voltage flicker, which seriously affect the power quality of the power supply system.

[0003] The quality of electric energy is directly related to the safety and reliability of the power grid and EMUs. Good power quality can improve the efficiency of electrical equipment and reduce power grid losses, while poor power quality has a huge impact on the power grid. The main manifestations are: a large number of high-order harmonics generated by the operation of high-speed trains invading the power system will accelerate the aging of transformer insulation, cause motor failures, shorten the life of transmission lines, affect the normal operation of communication equipment, and even cause resonance, causing a sharp increase in harmonic currents and damage to electrical equipment.

[0004] Therefore, it is necessary to monitor and record the power quality of the EMU distribution network, control its power quality operation status, and use the power quality data as a basis to provide data support for the problems and solutions of the distribution network, thereby ensuring the reasonable and effective configuration of the EMU power quality and further ensuring the stable and safe operation of the EMU. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the intelligent monitoring method, system, electronic device and storage medium of the EMU provided by the present invention solve the problem of inaccurate power quality calculation caused by inaccurate overvoltage data obtained by the EMU.

[0006] In order to achieve the above-mentioned object of the invention, on the one hand, the present invention provides an EMU intelligent monitoring method, comprising the following steps:

[0007] S1, input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, and obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0008] S2, respectively converting the voltage signal V1(t) and the current signal I1(t) to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0009] S3, using FPGA to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n), and calculate the electrical parameters of the sampled data;

[0010] S4, according to the voltage transformer secondary side voltage signal V2(n), FPGA and ARM are combined to perform abnormal diagnosis on the power quality, and reconstruct the inverted voltage transformer primary side voltage signal;

[0011] S5. Display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters on the host computer to complete the detection of power quality.

[0012] In a second aspect, the present invention provides an EMU intelligent monitoring system, comprising:

[0013] The acquisition front-end adjustment subsystem is used to input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, so as to obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0014] The signal acquisition channel subsystem is used to convert the voltage signal V1(t) and the current signal I1(t) respectively to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0015] The electrical parameter calculation subsystem is used to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n) using FPGA, and calculate the electrical parameters of the sampled data;

[0016] The joint analysis subsystem is used to diagnose abnormal power quality based on the secondary voltage signal V2(n) of the voltage transformer, in conjunction with FPGA and ARM, and reconstruct the primary voltage signal of the inverted voltage transformer;

[0017] The host computer is used to display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters in the host computer to complete the detection of power quality.

[0018] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the EMU intelligent monitoring method when executing the computer program.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the EMU intelligent monitoring method are implemented.

[0020] The beneficial effects of the present invention are:

[0021] The present invention is based on a power quality analysis system for joint analysis of FPGA and ARM. The present invention uses FPGA to obtain continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to a host computer database; at the same time, in conjunction with the joint analysis of ARM, the primary side voltage waveform is reconstructed and inverted in combination with the voltage transformer transfer function, and the overvoltage characteristic information is uploaded to the host computer database. The present invention solves the problem of inaccurate power quality calculation caused by inaccurate overvoltage data obtained by the EMU, and can accurately analyze and obtain the power supply quality status of the EMU contact network when the EMU is running. At the same time, the reconstruction inversion algorithm is used based on the broadband transfer characteristics of the EMU voltage transformer, by measuring the secondary side voltage of the voltage transformer when overvoltage occurs, and using the secondary side voltage and the broadband transfer characteristics of the voltage transformer, the primary side voltage of the voltage transformer, that is, the overvoltage signal, is reconstructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of the method.

[0023] Figure 2 It is a logic block diagram of the present invention.

[0024] Figure 3 It is a step-by-step flow chart of step S2 in the present invention.

[0025] Figure 4 It is a step-by-step flow chart of step S4 in the present invention.

[0026] Figure 5 It is a step-by-step flow chart of step S401 in the present invention.

[0027] Figure 6 It is a step-by-step flow chart of step S402 in the present invention.

[0028] Figure 7 It is a schematic diagram of the reconstruction result in the embodiment of the present invention.

[0029] Figure 8 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0030] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0031] Those skilled in the art know that the embodiments of the present invention can realize a method, system, electronic device or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, microcode, resident software, etc.), or a combination of hardware and software.

[0032] Example 1

[0033] Based on the problems described in the background technology, the present invention provides an intelligent monitoring method for EMUs, which can effectively and timely obtain network voltage and current information, provide data support for troubleshooting overvoltage faults, and improve the safety and reliability of EMUs during operation. Figure 1 As shown, it includes steps S1 to S5:

[0034] S1, input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, and obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0035] S2, respectively converting the voltage signal V1(t) and the current signal I1(t) to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0036] S3, using FPGA to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n), and calculate the electrical parameters of the sampled data;

[0037] S4, according to the voltage transformer secondary side voltage signal V2(n), FPGA and ARM are combined to perform abnormal diagnosis on the power quality, and reconstruct the inverted voltage transformer primary side voltage signal;

[0038] S5. Display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters on the host computer to complete the detection of power quality.

[0039] In the embodiment of the present invention, the input EMU voltage signal and current signal are converted by voltage reduction, impedance transformation, etc. to obtain a voltage signal V1(t) and a current signal I1(t) that adapt to the system range and have the original signal characteristics. In the subsequent calculation process, the calculation results are made the same as the original input voltage and current signals.

[0040] In the embodiment of the present invention, in the joint FPGA and ARM for abnormal diagnosis of power quality, the FPGA mainly realizes the abnormal diagnosis of power quality, and at the same time packages the diagnosis data and uploads it to the host computer. The abnormal diagnosis of power quality includes: overvoltage, undervoltage, short-time interruption, unqualified frequency, and overcurrent; after a fault occurs, the data of up to 1 second before and after the fault (2 seconds in total) is recorded and uploaded in real time. When an overvoltage fault occurs, the FPGA and ARM communicate, and cooperate with the ARM to reconstruct and invert the voltage waveform on the primary side of the voltage transformer. Among them, the FPGA mainly completes Fourier transform (FFT) and inverse Fourier transform (IFFT).

[0041] In the embodiment of the present invention, the present invention is based on the SOC main chip, power supply and FLASH, which is the core part of the whole system, wherein both FPGA and MCU can select mature solution models. The FPGA of this solution adopts Xilinx ZYNQ 7Z045 series chip, including PS composed of dual-core ARM Cortex-A9 and PL composed of FPGA.

[0042] In the embodiment of the present invention, Figure 2 As shown in the figure, the PL composed of FPGA drives the 10Msps sampling rate ADC to complete the acquisition of the voltage and current raw signals; it provides a data cache function, which can cache the data within 1S before and after the fault point; it supports three modes of data packaging: 100K / s, 1M / s and 10M / s; the data packet header is configurable and has the ability to carry TCMS information.

[0043] In the embodiment of the present invention, Figure 2 As shown, ARM provides a TCP / UDP protocol stack to implement data upload, parameter configuration and system management functions; and implements the primary side waveform reconstruction algorithm processing.

[0044] In the embodiment of the present invention, Figure 2As shown, the working principle of the present invention is: converting the input voltage signal and current signal into a voltage signal V1(t) and a current signal I1(t) that adapt to the system through impedance transformation, etc.; converting the voltage signal V1(t) and the current signal I1(t) into a voltage signal V2(t) and a current signal I2(t) that can drive an ADC with a sampling rate of 10Msps, and converting the voltage analog signal V2(t) and the current analog signal I2(t) into a voltage digital signal V2(n) and a current digital signal I2(n); sampling the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n) based on FGPA, and calculating the electrical parameters of the sampled data, wherein, in the calculation result of the electrical parameters, the current transformer current signal I2(n) is used to calculate the current effective value, current harmonics, power and to determine whether an overcurrent fault occurs. In the present invention, in the FPGA, the calculation of conventional electrical parameters adopts 12.8k / s for data extraction; the ADC sampled voltage digital signal V2(n) and the current digital signal I2(n) are stored in the FIFO memory, and the original data upload, alarm monitoring, data packaging upload, FFT, IFFT and other operations are performed. Finally, the voltage waveform of the primary side of the voltage transformer is inverted in cooperation with ARM. Finally, the electrical parameter calculation results, the data uploaded by FPGA and ARM are uploaded to the host computer through the UDP / TCP protocol to complete the primary side waveform reconstruction operation, and complete the parameter configuration and system management operations.

[0045] Conventional electrical parameters mainly include: voltage effective value, current effective value, active power, apparent power, reactive power, power factor, frequency, DC offset, voltage deviation, frequency deviation, voltage fluctuation, voltage harmonics, current harmonics, voltage waveform distortion and current waveform distortion.

[0046] In the embodiment of the present invention, Figure 2 As shown in the figure, FPGA, ARM and the host computer are connected by Gigabit network, and the long connection communication is based on TCP / IP. FPGA and ARM are the server. The communication port and application protocol are shown in Table 1:

[0047] Table 1

[0048]

[0049] The binary custom protocol format is shown in Table 2:

[0050] Table 2

[0051]

[0052] In the embodiment of the present invention, Figure 2As shown, for voltage acquisition pre-stage conditioning, the secondary side voltage signal through the voltage transformer has a large span and a large signal bandwidth, and high requirements are placed on the bandwidth response and stability of the pre-stage processing. The voltage transformer cannot meet the requirements, so a dedicated pre-stage processing is required to increase the acquisition accuracy and stability of the acquisition channel.

[0053] In the embodiment of the present invention, Figure 2 As shown, when collecting voltage and current signals, the ADC sampling rate is 10Msps.

[0054] In the embodiment of the present invention, Figure 2 As shown, the original data is uploaded at a rate of 100k / s, undervoltage, short interruption, frequency failure, and overcurrent in the fault are uploaded at a rate of 1M / s, and overvoltage is uploaded at a speed of 10M / s. The primary side waveform is reconstructed for a maximum of 100ms (200ms in total) before and after the overvoltage type of a specific fault (peak voltage exceeds 50kV and lasts for not less than 20us, or peak value exceeds 85kV), and the reconstructed primary side waveform is uploaded at 10M / s.

[0055] In the embodiment of the present invention, Figure 2 As shown, the alarm detection includes: overvoltage, undervoltage, short interruption, ferromagnetic resonance, frequency failure and overcurrent.

[0056] In the embodiment of the present invention, the technical problem to be solved by the present invention is to obtain continuous overvoltage data at a high sampling frequency, sample the overvoltage data, perform electrical parameter calculation and analysis, and upload the electrical parameter calculation results to the host computer database; perform trigger threshold judgment on the overvoltage data, obtain various voltage transformer secondary side overvoltage waveforms exceeding the threshold, and based on the joint analysis of FPGA and ARM, reconstruct and invert the primary side voltage waveform in combination with the voltage transformer transfer function, analyze the inverted waveform, and upload the overvoltage characteristic information to the host computer database, wherein the waveform reconstruction of the present invention improves the current method for obtaining EMU overvoltage data, can obtain more accurate EMU overvoltage, and provides effective data support for accurate tracing of accidents caused by overvoltage and subsequent accident prevention.

[0057] Example 2

[0058] For step S2 in Example 1, Figure 3 As shown, it includes the following steps S201-S202:

[0059] S201, using the voltage signal acquisition channel, converting the voltage signal V1(t) into an analog voltage signal V2(t) capable of driving an ADC with a sampling rate of 10Msps, and converting the analog voltage signal V2(t) into a voltage transformer secondary side voltage signal V2(n);

[0060] S202 , using the current signal acquisition channel, convert the current signal I1 (t) into an analog current signal I2 (t) that can drive an ADC with a sampling rate of 10Msps, and convert the analog current signal I2 (t) into a current transformer current signal I2 (n).

[0061] In the embodiment of the present invention, the present invention converts the continuous voltage and current analog signals into discrete digital signals that are convenient for digital circuit processing and transmission.

[0062] Example 3

[0063] For step S4 in Example 1, Figure 4 As shown, it includes the following sub-steps S401-S402:

[0064] S401, using a signal generator and an oscilloscope to sweep frequency and measure the broadband transfer characteristics of the voltage transformer of the EMU;

[0065] S402, using FPGA to collect the voltage transformer secondary side voltage signal V2(n), and according to the broadband transmission characteristics of the EMU voltage transformer, cooperate with ARM to perform abnormal diagnosis of power quality, and reconstruct the inverted voltage transformer primary side voltage signal.

[0066] In the embodiment of the present invention, in order to obtain the broadband transfer characteristics of the voltage transformer of the EMU, a frequency sweep measurement is performed.

[0067] In the embodiment of the present invention, based on the joint analysis of FPGA and ARM, the primary side voltage waveform is reconstructed and inverted based on the combination of the voltage transformer transfer function and the voltage transformer secondary side voltage signal V2(n), and the inverted waveform is analyzed at the same time, and the overvoltage characteristic information is uploaded to the host computer database.

[0068] In the embodiment of the present invention, the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power quality status of the EMU contact network when the EMU is running, and at the same time, use the reconstruction inversion algorithm to obtain more accurate overvoltage data, which provides effective data support for accurately tracing the accidents caused by overvoltage and preventing subsequent accidents.

[0069] Example 4

[0070] For step S401 in Example 3, Figure 5 As shown, it includes the following sub-steps S4011 to S4016:

[0071] S4011. Generate a single-frequency sinusoidal signal using a signal generator, and inject the single-frequency sinusoidal signal into the primary side of the voltage transformer;

[0072] S4012. Use an oscilloscope to simultaneously measure the primary and secondary side signals of the voltage transformer;

[0073] S4013, respectively recording the amplitude and phase difference of the primary and secondary side signals of the voltage transformer, wherein the phase difference is the phase-frequency characteristic of the single frequency point;

[0074] S4014, determining the amplitude-frequency characteristic of the voltage transformer at the single frequency point according to the amplitudes of the primary side and the secondary side of the voltage transformer;

[0075] S4015, changing the signal frequency at a fixed frequency interval, and determining whether the signal frequency reaches a preset frequency threshold, if so, determining the phase-frequency characteristic and amplitude-frequency characteristic of the voltage transformer after the signal frequency is changed, and proceeding to step S4016, otherwise, returning to step S4011;

[0076] S4016. Combine the obtained multiple single-frequency amplitude-frequency characteristics and phase-frequency characteristics in ascending order according to frequency to obtain the wide-band transfer characteristics of the voltage transformer of the EMU.

[0077] In the embodiment of the present invention, when an overvoltage fault occurs, the voltage waveform on the primary side of the voltage transformer is restored by an inversion reconstruction algorithm.

[0078] In the embodiment of the present invention, in order to obtain the wide-band transfer characteristics of the voltage transformer of the EMU, a signal generator and an oscilloscope are used for frequency sweep measurement. The signal generator generates a single-frequency sinusoidal signal and injects it into the primary side of the voltage transformer. The oscilloscope is used to simultaneously measure the primary and secondary side signals of the voltage transformer, and the amplitudes M1 and M2 of the primary and secondary side signals, as well as the phase difference φ, are recorded. The amplitudes of the two are divided (primary side / secondary side) to obtain the amplitude-frequency characteristic A of the transformer at this frequency, and the phase difference φ (primary side phase minus secondary side phase) is the phase-frequency characteristic of this frequency. That is:

[0079]

[0080] By changing the signal frequency generated by the signal generator and repeating the above operation, the wide-band transfer characteristic H(ω) of the mutual inductor can be obtained, including the amplitude-frequency characteristic A(ω) and the phase-frequency characteristic φ(ω).

[0081] H(ω)=A(ω)*e i*φ(ω)

[0082] In an embodiment of the present invention, the present invention first determines the phase-frequency characteristic and amplitude-frequency characteristic of a single frequency point, and then changes the signal frequency at a certain frequency interval to obtain the phase-frequency characteristic and amplitude-frequency characteristic after the signal frequency is changed, and sorts and combines the amplitude-frequency characteristics and phase-frequency characteristics of multiple single-frequency points in ascending order of frequency to obtain a more accurate wide-band transfer characteristic of the voltage transformer, thereby providing a basis for subsequently obtaining more accurate overvoltage data.

[0083] In the embodiment of the present invention, the present invention simultaneously measures the primary and secondary side signals of the voltage transformer to determine the amplitude-frequency characteristic and phase-frequency characteristic of the voltage transformer at a single frequency point, thereby providing a basis for subsequent measurement of the wide-band transfer characteristics of the EMU voltage transformer.

[0084] Example 5

[0085] For step S402 in Example 3, Figure 6 As shown, it includes the following sub-steps S4021 to S4026:

[0086] S4021. Using FPGA to collect the secondary side voltage signal V2(n) of the voltage transformer at a sampling rate of 10Msps;

[0087] S4022, the FPGA performs fast Fourier transform on the secondary side voltage signal V2(n) of the voltage transformer to obtain a secondary side frequency domain signal, and transmits the secondary side frequency domain signal to the ARM;

[0088] S4023, converting the secondary side frequency domain signal into a secondary side frequency domain symmetrical signal symmetrical at zero frequency point by the ARM;

[0089] S4024, supplementing the negative frequency of the broadband transfer characteristic, and performing linear interpolation processing on the supplemented broadband transfer characteristic to obtain a new broadband transfer characteristic;

[0090] S4025, calculating a primary side frequency domain signal according to the new wideband transfer characteristics and the secondary side frequency domain symmetric signal, and transmitting the primary side frequency domain signal to the FPGA;

[0091] S4026. The FPGA performs an inverse fast Fourier transform on the primary side frequency domain signal to obtain a primary side time domain signal, and smoothes the primary side time domain signal and transmits it to the ARM to complete the reconstruction inversion of the joint FPGA and ARM, wherein the primary side time domain signal is the primary side voltage signal of the voltage transformer.

[0092] In the embodiment of the present invention, the FPGA acquisition channel is used to measure the secondary voltage of the voltage transformer when the EMU has an overvoltage, and the primary signal of the voltage transformer is reconstructed using a reconstruction algorithm based on the broadband transfer characteristics of the transformer that have been measured. The reconstruction process is as follows:

[0093] (1) FPGA drives the 10Msps sampling rate ADC to measure and save the secondary side voltage V2(t), and performs fast Fourier transform (fft) on the secondary side voltage in the FPGA to obtain the secondary side frequency domain signal V2(ω) and transmit it to ARM. In the ARM, the frequency domain signal at this time is converted into data symmetrical about the zero frequency point, including the amplitude-frequency characteristic Mag(ω) and the phase-frequency characteristic Pha(ω).

[0094] V2(ω)=fft(V2(t))=Mag(ω)*e i*Pha(ω)

[0095] (2) The broadband transfer characteristics obtained by the above measurement are supplemented with the negative frequency part to ensure that the frequency distribution is symmetrical about the zero frequency point, the amplitude-frequency characteristics of the negative frequency and the positive frequency are equal, and the phase-frequency characteristics are opposite. The broadband transfer characteristics after supplementing the negative frequency are linearly interpolated to ensure that the frequency interval is the same as the frequency interval, and finally a new broadband transfer characteristic H1(ω) is obtained, including the amplitude-frequency characteristic A1(ω) and the phase-frequency characteristic φ1(ω).

[0096]

[0097] (3) Multiply the secondary side frequency domain signal with the wideband transfer characteristics, that is, multiply the amplitude-frequency characteristics and add the phase-frequency characteristics to obtain the primary side frequency domain signal V1(ω) and transmit it to the FPGA. In the FPGA, the obtained primary side frequency domain signal is subjected to inverse fast Fourier transform (ifft) to obtain the primary side time domain signal V1(t) and transmit it back to the ARM.

[0098]

[0099] V1(t)=ifft(V1(ω))

[0100] (4) The reconstructed primary side overvoltage signal is then smoothed using a smoothing algorithm to eliminate data oscillation.

[0101] In the embodiment of the present invention, the smoothing algorithm may adopt a moving smoothing algorithm, a local regression smoothing algorithm, a local weighted regression smoothing algorithm, an SG smoothing algorithm, a robust local regression smoothing algorithm, or a robust local weighted regression smoothing algorithm.

[0102] In an embodiment of the present invention, the reconstruction process includes a fast Fourier transform and an inverse fast Fourier transform. The secondary side voltage signal collected when the overvoltage occurs is fast Fourier transformed to obtain a secondary side frequency domain signal. The secondary side frequency domain signal is multiplied by the wide-band transfer characteristic, that is, the amplitude is multiplied, and the phase is added to obtain the overvoltage frequency domain signal. Finally, the overvoltage frequency domain signal is inversely fast Fourier transformed and smoothed to obtain the overvoltage (time domain) data.

[0103] In the embodiment of the present invention, Figure 7 This is the reconstructed result in the embodiment, and the reconstructed result is basically consistent with the actual result, which effectively improves the defects of the current EMU overvoltage acquisition method.

[0104] In the embodiment of the present invention, a reconstruction algorithm is used to obtain the primary side voltage, i.e., the overvoltage, based on the secondary side voltage of the voltage transformer and the wide-band transfer characteristics of the transformer when overvoltage occurs. This makes up for the defect that the current method for obtaining overvoltage cannot take into account the transfer characteristics of the transformer within a wide band, and effectively improves the accuracy of the obtained overvoltage data.

[0105] In the embodiment of the present invention, the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power quality status of the EMU contact network when the EMU is running, and at the same time, use the reconstruction inversion algorithm to obtain more accurate overvoltage data, which provides effective data support for accurately tracing the accidents caused by overvoltage and preventing subsequent accidents.

[0106] Example 6

[0107] The expression of the primary side voltage signal of the voltage transformer described in Example 5 is as follows:

[0108] V1(t)=ifft(V1(ω))

[0109]

[0110]

[0111] V2(ω)=fft(V2(t))=Mag(ω)*e i*Pha(ω)

[0112] Among them, V1(t) represents the reconstructed primary side voltage signal of the voltage transformer, ifft(·) represents the inverse fast Fourier transform, V1(ω) represents the primary side frequency domain signal, V2(ω) represents the secondary side frequency domain symmetric signal, H1(ω) represents the new wide-band transfer feature, Mag(ω) represents the amplitude-frequency characteristic of the secondary side frequency domain symmetric signal, A1(ω) represents the amplitude-frequency characteristic of the new wide-band transfer feature, e represents a natural constant, i represents an imaginary unit, Pha(ω) represents the phase-frequency characteristic of the secondary side frequency domain symmetric signal, φ1(ω) represents the phase-frequency characteristic of the new wide-band transfer feature, fft(·) represents the fast Fourier transform, and V2(t) represents the secondary side voltage measured at a fixed frequency.

[0113] In the embodiment of the present invention, the present invention acquires continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to the host computer database; performs trigger threshold judgment on the overvoltage data, acquires various voltage transformer secondary side overvoltage waveforms exceeding the threshold, and simultaneously based on the joint analysis of FPGA and ARM, combines the voltage transformer transfer function to reconstruct and invert the primary side voltage waveform, analyzes the inverted waveform, and uploads the overvoltage characteristic information to the host computer database, wherein the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power supply quality status of the EMU contact network when the EMU is running, and the waveform reconstruction can make up for the defect that the current method for acquiring overvoltage cannot consider the transfer characteristics of the voltage transformer in a wide band, and effectively improves the accuracy of the acquired overvoltage data. At the same time, the present invention considers the transfer characteristics of the voltage transformer in a wide band, acquires more accurate overvoltage data, and provides effective data support for accurate tracing of accidents caused by overvoltage and subsequent accident prevention.

[0114] Example 7

[0115] Based on the same inventive concept, an embodiment of the present invention also provides an EMU intelligent monitoring system. Since the principle solved by the system is similar to that of the EMU intelligent monitoring method, the implementation of the system can refer to the implementation of the method, and the repeated parts will not be repeated.

[0116] Figure 8 is a structural block diagram of the EMU intelligent monitoring system provided in an embodiment of the present invention, such as Figure 8 As shown, including:

[0117] The acquisition front-end adjustment subsystem is used to input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, so as to obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0118] The signal acquisition channel subsystem is used to convert the voltage signal V1(t) and the current signal I1(t) respectively to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0119] The electrical parameter calculation subsystem is used to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n) using FPGA, and calculate the electrical parameters of the sampled data;

[0120] The joint analysis subsystem is used to diagnose abnormal power quality based on the secondary voltage signal V2(n) of the voltage transformer, in conjunction with FPGA and ARM, and reconstruct the primary voltage signal of the inverted voltage transformer;

[0121] The host computer is used to display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters in the host computer to complete the detection of power quality.

[0122] In one embodiment, the signal acquisition channel subsystem includes:

[0123] The voltage signal acquisition channel module is used to use the voltage signal acquisition channel to convert the voltage signal V1(t) into an analog voltage signal V2(t) that can drive the ADC with a sampling rate of 10Msps, and convert the analog voltage signal V2(t) into a voltage transformer secondary side voltage signal V2(n);

[0124] The current signal acquisition channel module is used to use the current signal acquisition channel to convert the current signal I1(t) into an analog current signal I2(t) that can drive an ADC with a sampling rate of 10Msps, and convert the analog current signal I2(t) into a current transformer current signal I2(n).

[0125] In one embodiment, the joint analysis subsystem includes:

[0126] A measurement module, used to measure the broadband transfer characteristics of the EMU voltage transformer by using a signal generator and an oscilloscope frequency sweep;

[0127] The reconstruction module is used to collect the secondary side voltage signal V2(n) of the voltage transformer using FPGA, and according to the broadband transmission characteristics of the EMU voltage transformer, cooperate with ARM to perform abnormal diagnosis of power quality and reconstruct the primary side voltage signal of the inverted voltage transformer.

[0128] In one embodiment, the measuring module comprises:

[0129] A signal generating unit, used for generating a single-frequency sinusoidal signal by using a signal generator, and injecting the single-frequency sinusoidal signal into the primary side of the voltage transformer;

[0130] A first calculation unit, used for simultaneously measuring the primary side and secondary side signals of the voltage transformer using an oscilloscope;

[0131] A second calculation unit is used to record the amplitude and phase difference of the primary side and secondary side signals of the voltage transformer respectively, wherein the phase difference is the phase-frequency characteristic of the single frequency point;

[0132] A third calculation unit, used to determine the amplitude-frequency characteristic of the voltage transformer at the single frequency point according to the amplitudes of the primary side and the secondary side of the voltage transformer;

[0133] A judging unit, used to change the signal frequency at a fixed frequency interval, and judge whether the signal frequency reaches a preset frequency threshold, if so, determine the phase-frequency characteristic and amplitude-frequency characteristic of the voltage transformer after the signal frequency is changed, otherwise, continue iteration;

[0134] The fourth calculation unit is used to combine the obtained multiple single-frequency amplitude-frequency characteristics and phase-frequency characteristics according to the ascending order of frequency to obtain the wide-band transfer characteristics of the voltage transformer of the EMU.

[0135] In one embodiment, the reconstruction module includes:

[0136] A fifth calculation unit, used for collecting a voltage transformer secondary side voltage signal V2(n) by using FPGA at a sampling rate of 10Msps;

[0137] a sixth calculation unit, configured to perform a fast Fourier transform on the secondary side voltage signal V2(n) of the voltage transformer by using the FPGA to obtain a secondary side frequency domain signal, and transmit the secondary side frequency domain signal to the ARM;

[0138] A seventh calculation unit, configured to convert the secondary side frequency domain signal into a secondary side frequency domain symmetrical signal symmetrical at a zero frequency point by means of the ARM;

[0139] an eighth calculation unit, used for supplementing the negative frequency of the broadband transfer characteristic, and performing linear interpolation processing on the supplemented broadband transfer characteristic to obtain a new broadband transfer characteristic;

[0140] a ninth calculation unit, configured to calculate a primary side frequency domain signal according to the new wideband transfer characteristic and the secondary side frequency domain symmetric signal, and transmit the primary side frequency domain signal to the FPGA;

[0141] The tenth computing unit is used to perform an inverse fast Fourier transform on the primary side frequency domain signal by FPGA to obtain the primary side time domain signal, and smooth the primary side time domain signal, and transmit it to ARM to complete the reconstruction inversion of the joint FPGA and ARM, wherein the primary side time domain signal is the primary side voltage signal of the voltage transformer.

[0142] In one embodiment, the expression of the primary side voltage signal of the voltage transformer is as follows:

[0143] V1(t)=ifft(V1(ω))

[0144]

[0145]

[0146] V2(ω)=fft(V2(t))=Mag(ω)*e i*Pha(ω)

[0147] Among them, V1(t) represents the reconstructed primary side voltage signal of the voltage transformer, ifft(·) represents the inverse fast Fourier transform, V1(ω) represents the primary side frequency domain signal, V2(ω) represents the secondary side frequency domain symmetric signal, H1(ω) represents the new wide-band transfer feature, Mag(ω) represents the amplitude-frequency characteristic of the secondary side frequency domain symmetric signal, A1(ω) represents the amplitude-frequency characteristic of the new wide-band transfer feature, e represents a natural constant, i represents an imaginary unit, Pha(ω) represents the phase-frequency characteristic of the secondary side frequency domain symmetric signal, φ1(ω) represents the phase-frequency characteristic of the new wide-band transfer feature, fft(·) represents the fast Fourier transform, and V2(t) represents the secondary side voltage measured at a fixed frequency.

[0148] In an embodiment of the present invention, the present application can divide the functional units according to the intelligent monitoring method of the EMU. For example, each function can be divided into each functional unit, or two or more functions can be integrated into one processing unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. It should be noted that the division of units in the present invention is schematic and is only a logical division. There may be other division methods in actual implementation.

[0149] In the embodiment of the present invention, in order to realize the principles and beneficial effects of the intelligent monitoring method of the EMU, the intelligent monitoring system of the EMU includes hardware structures and / or software modules corresponding to the execution of various functions. Those skilled in the art should easily realize that, in combination with the various schematic units and algorithm steps described in the embodiments disclosed in the present invention, the present invention can be implemented in the form of hardware and / or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven manner depends on the specific application and design constraints of the technical solution. Different methods can be used for each specific application to implement the described function, but such implementation should not be considered to exceed the scope of this application.

[0150] In the embodiment of the present invention, the present invention acquires continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to the host computer database; based on the alarm detection in the FPGA, the overvoltage data is triggered to judge the threshold value, and various voltage transformer secondary side overvoltage waveforms exceeding the threshold value are acquired; at the same time, based on the joint analysis of FPGA and ARM, the primary side voltage waveform is inverted in combination with the voltage transformer transfer function reconstruction, the inverted waveform is analyzed, and the overvoltage characteristic information is uploaded to the host computer database, wherein the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power supply quality status of the EMU contact network when the EMU is running, and the waveform reconstruction can make up for the defect that the current method for acquiring overvoltage cannot consider the transfer characteristics of the voltage transformer in a wide band, and effectively improves the accuracy of the acquired overvoltage data. At the same time, the present invention considers the transfer characteristics of the voltage transformer in a wide band, obtains more accurate overvoltage data, and provides effective data support for accurate tracing of accidents caused by overvoltage and subsequent accident prevention.

[0151] Example 8

[0152] An electronic device includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of the EMU intelligent monitoring method described in any one of Embodiments 1 to 6 are implemented. For example, when the processor executes the computer program, the following contents may be implemented:

[0153] S1, input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, and obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0154] S2, respectively converting the voltage signal V1(t) and the current signal I1(t) to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0155] S3, using FPGA to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n), and calculate the electrical parameters of the sampled data;

[0156] S4, according to the voltage transformer secondary side voltage signal V2(n), FPGA and ARM are combined to perform abnormal diagnosis on the power quality, and reconstruct the inverted voltage transformer primary side voltage signal;

[0157] S5. Display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters on the host computer to complete the detection of power quality.

[0158] In an embodiment of the present invention, the electronic device may include: a processor, a memory, a bus and a communication interface. The processor, the communication interface and the memory are connected via a bus. The memory stores a computer program that can be run on the processor. When the processor runs the computer program, it executes part or all of the steps of the EMU intelligent monitoring method provided in any of the aforementioned embodiments 1 to 6 of the present application.

[0159] In the embodiment of the present invention, the present invention acquires continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to the host computer database; performs trigger threshold judgment on the overvoltage data, acquires various voltage transformer secondary side overvoltage waveforms exceeding the threshold, and simultaneously based on the joint analysis of FPGA and ARM, combines the voltage transformer transfer function to reconstruct and invert the primary side voltage waveform, analyzes the inverted waveform, and uploads the overvoltage characteristic information to the host computer database, wherein the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power supply quality status of the EMU contact network when the EMU is running, and the waveform reconstruction can make up for the defect that the current method for acquiring overvoltage cannot consider the transfer characteristics of the voltage transformer in a wide band, and effectively improves the accuracy of the acquired overvoltage data. At the same time, the present invention considers the transfer characteristics of the voltage transformer in a wide band, acquires more accurate overvoltage data, and provides effective data support for accurate tracing of accidents caused by overvoltage and subsequent accident prevention.

[0160] Example 9

[0161] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the EMU intelligent monitoring method described in any one of Embodiments 1 to 6 are implemented. For example, when the processor executes the computer program, the following contents may be implemented:

[0162] S1, input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, and obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics;

[0163] S2, respectively converting the voltage signal V1(t) and the current signal I1(t) to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n);

[0164] S3, using FPGA to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n), and calculate the electrical parameters of the sampled data;

[0165] S4, according to the voltage transformer secondary side voltage signal V2(n), FPGA and ARM are combined to perform abnormal diagnosis on the power quality, and reconstruct the inverted voltage transformer primary side voltage signal;

[0166] S5. Display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters on the host computer to complete the detection of power quality.

[0167] The above-mentioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or their combination, such as static random access memory (SRAM), erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special computer. The readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. The readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application-specific integrated circuit (ASIC). The processor and the readable storage medium can also exist as discrete components in the EMU intelligent monitoring system.

[0168] The embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. With reference to the process and / or block diagram of the method, device (device), and computer program product according to the embodiments of the present invention, it should be understood that each process and / or block diagram in the flow chart and / or block diagram, as well as the combination of the flow chart and / or block diagram, can be implemented by computer program instructions, and these computer program instructions can be provided to a computer-readable memory of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device that works in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which is implemented in the flow chart. Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing one or more processes and / or blocks in the flowchart. Figure 1 The steps for the functions specified in one or more boxes.

[0169] In the embodiment of the present invention, the present invention acquires continuous overvoltage data at a high sampling frequency, performs sampling processing on the overvoltage data, performs electrical parameter calculation and analysis, and uploads the electrical parameter calculation results to the host computer database; performs trigger threshold judgment on the overvoltage data, acquires various voltage transformer secondary side overvoltage waveforms exceeding the threshold, and simultaneously based on the joint analysis of FPGA and ARM, combines the voltage transformer transfer function to reconstruct and invert the primary side voltage waveform, analyzes the inverted waveform, and uploads the overvoltage characteristic information to the host computer database, wherein the power quality analysis system based on the joint analysis of FPGA and ARM can accurately analyze and obtain the power supply quality status of the EMU contact network when the EMU is running, and the waveform reconstruction can make up for the defect that the current method for acquiring overvoltage cannot consider the transfer characteristics of the voltage transformer in a wide band, and effectively improves the accuracy of the acquired overvoltage data. At the same time, the present invention considers the transfer characteristics of the voltage transformer in a wide band, acquires more accurate overvoltage data, and provides effective data support for accurate tracing of accidents caused by overvoltage and subsequent accident prevention.

[0170] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for intelligent monitoring of a train set, characterized in that: The following steps are involved: S1, input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, and obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics; S2, respectively converting the voltage signal V1(t) and the current signal I1(t) to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n); S3, using FPGA to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n), and calculate the electrical parameters of the sampled data; S4. According to the voltage transformer secondary side voltage signal V2(n), FPGA and ARM are combined to perform abnormal diagnosis on the power quality, and the inverted voltage transformer primary side voltage signal is reconstructed, which is specifically: S401, using a signal generator and an oscilloscope to sweep frequency and measure the broadband transfer characteristics of the voltage transformer of the EMU; S402, using FPGA to collect the voltage transformer secondary side voltage signal V2(n), and according to the broadband transmission characteristics of the EMU voltage transformer, cooperate with ARM to perform abnormal diagnosis of power quality, and reconstruct the inverted voltage transformer primary side voltage signal, which is specifically: S4021. Using FPGA to collect the secondary side voltage signal V2(n) of the voltage transformer at a sampling rate of 10Msps; S4022, the FPGA performs fast Fourier transform on the secondary side voltage signal V2(n) of the voltage transformer to obtain a secondary side frequency domain signal, and transmits the secondary side frequency domain signal to the ARM; S4023, converting the secondary side frequency domain signal into a secondary side frequency domain symmetrical signal symmetrical at zero frequency point by the ARM; S4024, supplementing the negative frequency of the broadband transfer characteristic, and performing linear interpolation processing on the supplemented broadband transfer characteristic to obtain a new broadband transfer characteristic; S4025, calculating a primary side frequency domain signal according to the new wideband transfer characteristics and the secondary side frequency domain symmetric signal, and transmitting the primary side frequency domain signal to the FPGA; S4026, the FPGA performs an inverse fast Fourier transform on the primary side frequency domain signal to obtain a primary side time domain signal, and smoothes the primary side time domain signal and transmits it to the ARM to complete the reconstruction inversion of the joint FPGA and ARM, wherein the primary side time domain signal is the primary side voltage signal of the voltage transformer; S5. Display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters on the host computer to complete the detection of power quality.

2. The intelligent monitoring method for EMU according to claim 1 is characterized in that: The step S2 comprises the following sub-steps: S201, using the voltage signal acquisition channel, converting the voltage signal V1(t) into an analog voltage signal V2(t) capable of driving an ADC with a sampling rate of 10Msps, and converting the analog voltage signal V2(t) into a voltage transformer secondary side voltage signal V2(n); S202 , using the current signal acquisition channel, convert the current signal I1 (t) into an analog current signal I2 (t) that can drive an ADC with a sampling rate of 10Msps, and convert the analog current signal I2 (t) into a current transformer current signal I2 (n).

3. The intelligent monitoring method for EMU according to claim 1 is characterized in that: The step S401 includes the following steps: S4011. Generate a single-frequency sinusoidal signal using a signal generator, and inject the single-frequency sinusoidal signal into the primary side of the voltage transformer; S4012. Use an oscilloscope to simultaneously measure the primary and secondary side signals of the voltage transformer; S4013, respectively recording the amplitude and phase difference of the primary and secondary side signals of the voltage transformer, wherein the phase difference is the phase-frequency characteristic of the single frequency point; S4014, determining the amplitude-frequency characteristic of the voltage transformer at the single frequency point according to the amplitudes of the primary side and the secondary side of the voltage transformer; S4015, changing the signal frequency at a fixed frequency interval, and determining whether the signal frequency reaches a preset frequency threshold, if so, determining the phase-frequency characteristic and amplitude-frequency characteristic of the voltage transformer after the signal frequency is changed, and proceeding to step S4016, otherwise, returning to step S4011; S4016. Combine the obtained multiple single-frequency amplitude-frequency characteristics and phase-frequency characteristics in ascending order according to frequency to obtain the wide-band transfer characteristics of the voltage transformer of the EMU.

4. The intelligent monitoring method for EMU according to claim 1, characterized in that: The expression of the primary side voltage signal of the voltage transformer is as follows: V1(t)=ifft(V1(ω)) V2(ω)=fft(V2(t))=Mag(ω)*e i*Pha(ω) Among them, V1(t) represents the reconstructed primary side voltage signal of the voltage transformer, ifft(·) represents the inverse fast Fourier transform, V1(ω) represents the primary side frequency domain signal, V2(ω) represents the secondary side frequency domain symmetric signal, H1(ω) represents the new wide-band transfer feature, Mag(ω) represents the amplitude-frequency characteristic of the secondary side frequency domain symmetric signal, A1(ω) represents the amplitude-frequency characteristic of the new wide-band transfer feature, e represents a natural constant, i represents an imaginary unit, Pha(ω) represents the phase-frequency characteristic of the secondary side frequency domain symmetric signal, φ1(ω) represents the phase-frequency characteristic of the new wide-band transfer feature, fft(·) represents the fast Fourier transform, and V2(t) represents the secondary side voltage measured at a fixed frequency.

5. An intelligent monitoring system for EMUs, characterized in that: include: The acquisition front-end adjustment subsystem is used to input the acquired EMU voltage signal and current signal into the voltage acquisition front-end conditioning channel and the current acquisition front-end conditioning channel one by one for conversion, so as to obtain the voltage signal V1(t) and current signal I1(t) with original signal characteristics; The signal acquisition channel subsystem is used to convert the voltage signal V1(t) and the current signal I1(t) respectively to obtain the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n); The electrical parameter calculation subsystem is used to sample the voltage transformer secondary side voltage signal V2(n) and the current transformer current signal I2(n) using FPGA, and calculate the electrical parameters of the sampled data; The joint analysis subsystem is used to diagnose abnormal power quality based on the secondary voltage signal V2(n) of the voltage transformer, in conjunction with FPGA and ARM, and reconstruct the primary voltage signal of the inverted voltage transformer; The joint analysis subsystem includes: A measurement module, used to measure the broadband transfer characteristics of the EMU voltage transformer by using a signal generator and an oscilloscope frequency sweep; The reconstruction module is used to collect the secondary voltage signal V2(n) of the voltage transformer using FPGA, and according to the broadband transmission characteristics of the EMU voltage transformer, cooperate with ARM to diagnose abnormal power quality and reconstruct the primary voltage signal of the inverted voltage transformer; The reconstruction module includes: A fifth calculation unit, used for collecting a voltage transformer secondary side voltage signal V2(n) by using FPGA at a sampling rate of 10Msps; a sixth calculation unit, configured to perform a fast Fourier transform on the secondary side voltage signal V2(n) of the voltage transformer by using the FPGA to obtain a secondary side frequency domain signal, and transmit the secondary side frequency domain signal to the ARM; A seventh calculation unit, configured to convert the secondary side frequency domain signal into a secondary side frequency domain symmetrical signal symmetrical at a zero frequency point by means of the ARM; an eighth calculation unit, used for supplementing the negative frequency of the broadband transfer characteristic, and performing linear interpolation processing on the supplemented broadband transfer characteristic to obtain a new broadband transfer characteristic; a ninth calculation unit, configured to calculate a primary side frequency domain signal according to the new wideband transfer characteristic and the secondary side frequency domain symmetric signal, and transmit the primary side frequency domain signal to the FPGA; A tenth calculation unit is used to perform an inverse fast Fourier transform on the primary side frequency domain signal by FPGA to obtain a primary side time domain signal, and smooth the primary side time domain signal, and transmit it to ARM to complete the reconstruction inversion of the joint FPGA and ARM, wherein the primary side time domain signal is the primary side voltage signal of the voltage transformer; The host computer is used to display the waveform of the primary side voltage signal of the voltage transformer and the calculation results of the electrical parameters in the host computer to complete the detection of power quality.

6. The intelligent monitoring system for EMUs according to claim 5 is characterized in that: The signal acquisition channel subsystem includes: The voltage signal acquisition channel module is used to use the voltage signal acquisition channel to convert the voltage signal V1(t) into an analog voltage signal V2(t) that can drive the ADC with a sampling rate of 10Msps, and convert the analog voltage signal V2(t) into a voltage transformer secondary side voltage signal V2(n); The current signal acquisition channel module is used to use the current signal acquisition channel to convert the current signal I1(t) into an analog current signal I2(t) that can drive an ADC with a sampling rate of 10Msps, and convert the analog current signal I2(t) into a current transformer current signal I2(n).

7. The intelligent monitoring system for EMUs according to claim 5 is characterized in that: The measuring module comprises: A signal generating unit, used for generating a single-frequency sinusoidal signal by using a signal generator, and injecting the single-frequency sinusoidal signal into the primary side of the voltage transformer; A first calculation unit, used for simultaneously measuring the primary side and secondary side signals of the voltage transformer using an oscilloscope; A second calculation unit is used to record the amplitude and phase difference of the primary side and secondary side signals of the voltage transformer respectively, wherein the phase difference is the phase-frequency characteristic of the single frequency point; A third calculation unit, used to determine the amplitude-frequency characteristic of the voltage transformer at the single frequency point according to the amplitudes of the primary side and the secondary side of the voltage transformer; A judging unit, used to change the signal frequency at a fixed frequency interval, and judge whether the signal frequency reaches a preset frequency threshold, if so, determine the phase-frequency characteristic and amplitude-frequency characteristic of the voltage transformer after the signal frequency is changed, otherwise, continue iteration; The fourth calculation unit is used to combine the obtained multiple single-frequency amplitude-frequency characteristics and phase-frequency characteristics according to the ascending order of frequency to obtain the wide-band transfer characteristics of the voltage transformer of the EMU.

8. The intelligent monitoring system for EMUs according to claim 5 is characterized in that: The expression of the primary side voltage signal of the voltage transformer is as follows: V1(t)=ifft(V1(ω)) V2(ω)=fft(V2(t))=Mag(ω)*e i*Pha(ω) Among them, V1(t) represents the reconstructed primary side voltage signal of the voltage transformer, ifft(·) represents the inverse fast Fourier transform, V1(ω) represents the primary side frequency domain signal, V2(ω) represents the secondary side frequency domain symmetric signal, H1(ω) represents the new wide-band transfer feature, Mag(ω) represents the amplitude-frequency characteristic of the secondary side frequency domain symmetric signal, A1(ω) represents the amplitude-frequency characteristic of the new wide-band transfer feature, e represents a natural constant, i represents an imaginary unit, Pha(ω) represents the phase-frequency characteristic of the secondary side frequency domain symmetric signal, φ1(ω) represents the phase-frequency characteristic of the new wide-band transfer feature, fft(·) represents the fast Fourier transform, and V2(t) represents the secondary side voltage measured at a fixed frequency.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the EMU intelligent monitoring method described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the EMU intelligent monitoring method described in any one of claims 1 to 4 are implemented.

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