Alternating current and direct current charging pile detection method, device and system

Abstract

The invention relates to the technical field of charging pile detection, and discloses an AC / DC charging pile detection method, device and system, and the method comprises the following steps: S1, applying a preliminary broadband disturbance signal to a to-be-detected charging pile; s2, generating an optimized composite disturbance signal according to the sensitive frequency band characteristics; s3, synchronously applying the optimized composite disturbance signal to a to-be-tested charging pile; s4, carrying out Fourier transform on the output response; s5, constructing a dynamic response signature matrix based on the transfer function; s6, after detection, calculating the difference between the dynamic response signature matrix and the stored reference data; and S7, when the judgment result is unqualified, carrying out structured deviation analysis on the difference. According to the technical scheme, the sensitive frequency band of the system is identified through preliminary broadband disturbance, then the optimized composite disturbance signal is generated according to the sensitive frequency band, and energy is concentrated on the sensitive frequency band for accurate excitation. The detection speed and the signal-to-noise ratio are improved, and the technical effect of rapid and efficient testing is achieved.

Description

Technical Field

[0001] The present invention relates to the field of charging pile detection technology, and in particular to an AC / DC charging pile detection method, device, and system. Background Art

[0002] Broadband scanning technology is currently widely used to evaluate the dynamic characteristics of charging piles. While this method can cover a wide frequency range, the test step size is typically large, resulting in excessively long test times. This is clearly unsuitable for high-volume production lines requiring rapid testing. Especially in the face of fierce market competition, lengthy testing times significantly limit production efficiency.

[0003] Existing technologies often focus on independent testing of the electrical or communication control domains. This single-dimensional testing approach fails to fully reflect the complex conditions that charging piles may encounter in real-world environments. Multi-domain coupling is a key factor affecting charging pile performance, yet traditional methods often overlook this aspect. This leads to potential performance flaws being missed, ultimately impacting product reliability and safety.

[0004] Even after detecting a defective product, traditional solutions often only provide a simple pass / fail judgment. This superficial result significantly limits subsequent troubleshooting. Technicians rely on experience to locate the fault, but experience itself carries uncertainty. This approach not only leads to low detection efficiency but also increases repair costs. Summary of the Invention

[0005] The purpose of the present invention is to provide an AC / DC charging pile detection method, device and system, which solves the problems of long testing time, inability to comprehensively evaluate multi-domain coupling characteristics and unclear fault location in existing charging pile detection technologies.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an AC / DC charging pile detection method, comprising the following steps: S1. Apply a preliminary broadband disturbance signal to the charging pile under test and obtain its response data to identify the system's sensitive frequency band. S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band and is used to stimulate the charging pile. S3. Synchronously applying the optimized composite disturbance signal to the charging pile to be tested to obtain its output response; S4. Calculating a transfer function between an input signal and an output signal by performing Fourier transform on the output response; S5. constructing a dynamic response signature matrix based on the transfer function, and storing the matrix as benchmark data; S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the eligibility of the charging pile and generate a test report; S7. When judging as unqualified, perform structured deviation analysis on the differences to achieve in-depth diagnosis of potential faults and generate a fault report.

[0007] Preferably, the response data in step S1 includes the output voltage and output current of the charging pile, and the sensitive frequency band is determined by performing spectrum analysis on the response data.

[0008] Preferably, the step of generating the optimized composite disturbance signal in step S2 is specifically: superimposing multiple sinusoidal wave signals to form the optimized composite disturbance signal, wherein the frequencies of the multiple sinusoidal wave signals are all set within the sensitive frequency band.

[0009] Preferably, the step of synchronously applying the optimized composite disturbance signal to the charging pile to be tested in step S3 is specifically: superimposing a component of the optimized composite disturbance signal on the AC input voltage of the charging pile to be tested through a programmable AC power supply, and at the same time superimposing another component of the optimized composite disturbance signal on the charging instruction sent to the charging pile to be tested through a controller local area network communication device.

[0010] Preferably, the Fourier transform in step S4 uses a fast Fourier transform algorithm to process the output response and the input signal to obtain a frequency domain representation.

[0011] Preferably, the step of constructing the dynamic response signature matrix in step S5 is specifically: arranging the values ​​of the transfer function at multiple preset frequency points in frequency order to form a matrix with multiple rows and columns to represent the dynamic response characteristics of the charging pile at different frequencies.

[0012] Preferably, the step of calculating the difference in step S6 is specifically: obtaining a quantitative difference value for characterizing the overall degree of difference by calculating the Frobenius norm of the difference between the dynamic response signature matrix and the reference data.

[0013] Preferably, the structured deviation analysis in step S7 includes: Decompose the difference between the dynamic response signature matrix and the benchmark data into amplitude difference and phase difference, and establish the corresponding fault feature vectors respectively; The fault feature vector is matched with a preset fault mode database to determine the fault type and the corresponding fault component.

[0014] An AC / DC charging pile detection device includes a protective box; a display screen is fixedly connected to the exterior of the protective box, a charging gun connector is fixedly connected to the interior of the protective box, one end of the charging gun connector is electrically connected to a collector, an outer wall of the collector is fixedly connected to the interior of the protective box, one end of the collector is electrically connected to a storage battery, an outer wall of the storage battery is fixedly connected to the inner wall of the protective box, one end of the collector is electrically connected to a processing controller, an outer wall of the processing controller is fixedly connected to the inner wall of the protective box, one end of the processing controller is electrically connected to a signal generation module, and an outer wall of the signal generation module is fixedly connected to the inner wall of the protective box.

[0015] AC / DC charging pile detection system, including; A signal generation module is used to generate a preliminary broadband disturbance signal and an optimized composite disturbance signal, and synchronously apply them to the AC input terminal and communication control terminal of the charging pile under test; A data acquisition module, used to collect response data of the output voltage and output current of the charging pile to be tested; a processing control module for performing spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis; The report generation module is used to generate detection reports and fault reports.

[0016] In summary, the present invention includes at least one of the following beneficial technical effects: 1. The present invention uses a technical solution to identify the system's sensitive frequency bands through preliminary broadband perturbations, and then generates an optimized composite perturbation signal based on this, concentrating energy on the sensitive frequency bands for precise excitation. This approach greatly improves detection speed and signal-to-noise ratio, achieving the technical effect of fast and efficient testing. Compared to the test solution commonly used in the prior art to fully scan the entire frequency band, the present invention solves the shortcomings of long test times, low efficiency, and difficulty in meeting the fast-paced testing needs of large-scale production lines.

[0017] 2. The present invention synchronously applies optimized disturbance signals to the grid electrical domain and communication control domain of the charging pile and constructs a multi-dimensional dynamic response signature matrix. This approach can comprehensively and systematically characterize the dynamic characteristics of the charging pile under real complex working conditions, achieving more accurate and comprehensive detection results. Unlike the technical solutions in the prior art that only test from a single dimension, it solves the problem that it cannot effectively evaluate cross-domain coupling characteristics and is prone to missing potential stability and performance defects caused by multi-domain interactions.

[0018] 3. By quantitatively analyzing the differences between the measured matrix and the reference matrix and matching them with the fault database, this method directly enables automatic fault location. Compared to existing technologies that simply provide a pass / fail conclusion, this method overcomes the drawbacks of the existing technology, which cannot pinpoint the root cause of the fault and relies heavily on manual experience for subsequent repairs, significantly improving the efficiency and accuracy of fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of applying a preliminary broadband disturbance signal according to the present invention; Figure 3 This is a schematic diagram of generating an optimized composite disturbance signal according to the present invention; Figure 4 This is a schematic diagram of the dynamic response signature matrix structure of the present invention; Figure 5 Schematic diagram of the system framework of the present invention; Figure 6 A perspective view of the device of the present invention; Figure 7 It is a cross-sectional view of the protective box of the present invention.

[0020] Among them, 1. Protective box; 2. Display screen; 3. Charging gun connector; 4. Collector; 5. Storage battery; 6. Processing controller; 7. Signal generation module. DETAILED DESCRIPTION

[0021] The following is combined with Figure 1 -Attached Figure 4 , the present invention is described in further detail.

[0022] The present invention provides an AC / DC charging pile detection method, comprising: S1. Apply a preliminary broadband perturbation signal to the charging pile under test and obtain its response data to identify the system's sensitive frequency band. Specifically, in step S1 of this embodiment, a preliminary broadband perturbation signal is applied to the charging pile under test and its response data is obtained to identify the system's sensitive frequency band. This step is the foundation of the entire detection method, and the accuracy of its identification results directly determines the effectiveness of subsequent tests.

[0023] First, a preset preliminary broadband disturbance signal is applied to the charging pile under test. This signal is designed to uniformly excite the charging pile under test over a wide frequency range to fully stimulate its potential dynamic characteristics.

[0024] For example, the preliminary broadband disturbance signal can be a linear swept frequency signal (ChirpSignal), whose frequency is linearly or logarithmically swept from a low frequency (e.g., 1 Hz) to a high frequency (e.g., 10 kHz) within a preset time period. Alternatively, the signal can be a pseudo-random binary sequence (PRBS), whose spectrum is similar to white noise below the Nyquist frequency, and can simultaneously excite all frequency points in a short period of time.

[0025] This preliminary broadband disturbance signal is synchronously applied to multiple input ports of the charging station under test through the test system to simulate a real-world, complex operating environment. Specifically, one component of the signal is superimposed on the charging station's AC input voltage, while another component is modulated into its communication control instructions.

[0026] Throughout the entire process of applying the disturbance signal, a high-precision, highly synchronized data acquisition module collects the output response data of the charging pile under test in real time. Synchronous data acquisition is crucial to ensure the accuracy of subsequent analysis, as it ensures that the causal and phase relationships between the input disturbance and the output response are recorded without distortion.

[0027] The response data specifically includes the DC output voltage time domain signal V of the charging pile to be tested out (t) and the DC output current time domain signal I out (t).

[0028] After acquiring the time domain response data, the processing and control module performs spectrum analysis on it to determine the sensitive frequency band of the system. The spectrum analysis process is preferably implemented using a fast Fourier transform (FFT) algorithm, which can efficiently convert time domain signals to the frequency domain for analysis.

[0029] The transformation process can be expressed as follows: Where X[k] represents the frequency domain representation of the discrete Fourier transform (DFT) result, x[n] represents the discrete time signal sequence, which represents the value of the signal at discrete time n, N represents the total number of sampling points, and k represents the frequency index in the frequency domain. represents the part of the complex exponential, and j represents the imaginary unit.

[0030] By calculating the spectrum V out (f) and I out (f) Perform analysis to identify frequency bands with significant energy response. These frequency bands are defined as sensitive frequency bands Ω critical , which are characterized by the presence of resonant peaks in the spectrum graph, or areas where the amplitude or phase of the system transfer function (preliminary estimate) changes dramatically.

[0031] The resonant peak typically corresponds to the electrical resonance point within the system and is key to evaluating system stability. The region of sharp gain or phase changes is often related to the bandwidth of the system's control loop, reflecting the limits of control performance.

[0032] S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band and is used to stimulate the charging pile. Specifically, in step S2 of this embodiment, an optimized composite disturbance signal for accurately exciting the charging pile to be tested is generated according to the characteristics of the sensitive frequency band.

[0033] The purpose of this step is to focus the test energy on the frequency range that has the most significant impact on the system's dynamic characteristics, thereby replacing the traditional broadband, inefficient sweep to achieve shorter test time and higher response signal-to-noise ratio.

[0034] Specifically, this step is performed by a signal generation module. The signal generation module first receives the sensitive frequency band Ω determined in step S1 from the processing control module. critical This frequency band information is the core basis for generating the optimized composite disturbance signal.

[0035] According to a further limitation of another embodiment of the present invention, the optimized composite disturbance signal is generated by linearly superimposing multiple sinusoidal signals whose frequencies fall within the sensitive frequency band. This method can accurately construct the required energy distribution in the frequency domain.

[0036] The mathematical model of the optimized composite disturbance signal in the time domain can be expressed by the following formula: Where Δx OCPS (t) represents the time domain waveform of the optimized composite anti-disturbance signal finally generated, N represents the total number of sinusoidal waves constituting the composite signal, k represents the index of the sinusoidal component, and represents the kth sinusoidal component in the signal, f k Represents the frequency of the kth sinusoidal wave component, frequency f k is chosen in the sensitivity band Ω critical Within the determined range, A k represents the amplitude of the kth sine wave component, represents the initial phase of the kth sinusoidal wave component, and t represents the time variable.

[0037] The peak value of the composite signal is optimized by setting the phase of each component to ensure the optimal distribution of the signal's excitation energy and avoid excessive response or shock in the system.

[0038] The optimized composite disturbance signal generated in this way has its energy precisely confined to the pre-identified sensitive frequency band in the frequency domain. This technology significantly improves the signal-to-noise ratio at the target frequency point in subsequent response signal analysis, allowing a clear system response to be obtained using a disturbance signal with a smaller amplitude.

[0039] S3. Synchronously applying the optimized composite disturbance signal to the charging pile to be tested to obtain its output response; Specifically, in step S3 of this embodiment, the optimized composite disturbance signal is synchronously applied to the charging pile to be tested to obtain its output response under composite excitation.

[0040] The core of this step is to simulate the disturbances that the charging pile may encounter in actual operation, which come from both the electrical domain of the grid and the communication control domain, so as to stimulate and observe the dynamic characteristics caused by the multi-domain coupling effect.

[0041] Specifically, this step is performed in coordination with a synchronous controller. The synchronous controller ensures that the optimized composite disturbance signal Δx generated in step S2 OCPS (t), under the same time base, is decomposed and synchronously applied to the two different input ports of the charging pile under test.

[0042] According to a further limitation of another embodiment of the present invention, the specific implementation process of the synchronous application includes the following aspects.

[0043] First, a component of the optimized composite disturbance signal, namely the voltage disturbance component, is superimposed on the nominal AC input voltage supplied to the charging pile to be tested through a programmable AC power supply.

[0044] The mathematical model of this process can be expressed as: V in,AC (t) = V nom,AC (t)+ΔV OCPS (t); Where V in,AC (t) is the total voltage actually applied to the AC input terminal of the charging pile, V nom,AC (t) is the nominal AC voltage required for the normal operation of the charging pile, ΔV OCPS (t) is the voltage disturbance component.

[0045] At the same time, another component of the optimized composite disturbance signal, namely the instruction disturbance component, is superimposed on the charging instruction sent to the charging pile to be tested through a controller area network (CAN) communication device.

[0046] For example, the communication device modulates the charging current request value in real time in the standard charging control message. The process can be expressed as: I cmd,pert (t) = I cmd,nom +ΔI OCPS (t); Where, I cmd,pert (t) is the actual charging current command value sent to the charging pile after the disturbance is superimposed, I cmd,nom is the nominal charging current command value set under the current working conditions, ΔI OCPS (t) is the command disturbance component, and its waveform and amplitude are also determined by the optimized composite disturbance signal Δx OCPS (t) OK.

[0047] During the entire process of executing the above-mentioned synchronous application, the data acquisition module continues to work to obtain and record the output response of the charging pile to be tested in real time. The response data at least includes the time domain waveforms of its DC output voltage and DC output current.

[0048] S4. Calculate the transfer function of the input signal and the output signal by performing Fourier transform on the output response. Specifically, step S4 of this embodiment is to calculate the transfer function of the input signal and the output signal by performing Fourier transform on the output response.

[0049] This step is performed by a processing control module, which first receives the output response data from the data acquisition module and the input disturbance signal actually applied in step S3 and recorded by the synchronization controller.

[0050] The input disturbance signal includes a voltage disturbance component ΔV applied to the AC input terminal. OCPS (t), and the command disturbance component ΔI applied to the communication control end OCPS (t). The output response data includes the DC output voltage time domain signal V of the charging pile out (t) and the DC output current time domain signal I out (t).

[0051] To obtain the frequency domain representation, the processing control module uses an efficient spectrum analysis algorithm. According to a further limitation of another embodiment of the present invention, the Fourier transform specifically uses a Fast Fourier Transform (FFT) algorithm to process the output response and the input signal.

[0052] The algorithm is applied to the above-mentioned input disturbance signal and output response signal respectively to calculate their discrete frequency points f contained in the optimized composite disturbance signal. k The general mathematical model of the transformation process can be expressed as: Where x(t) represents any time domain signal, represents the Fourier transform operator; X(f k ) represents the time domain signal x(t) at a specific frequency f k The complex spectrum value on , which contains amplitude and phase information.

[0053] After obtaining the frequency domain representation of all relevant signals, the processing control module further calculates the transfer function between the input signal and the output signal. k ) is defined as the frequency at a specific frequency f k The ratio of the complex spectrum of the output signal to the complex spectrum of the input signal.

[0054] The calculation formula is as follows: Where H Y←X (f k ) is the frequency from input X to output Y at f k The transfer function value on k ) is the complex spectrum of the output signal, X(f k ) is the complex spectrum of the input signal.

[0055] This step calculates at least the following four core transfer functions to fully characterize the dynamic characteristics of the charging pile as a dual-input, dual-output system: This step calculates at least the following four core transfer functions to fully characterize the dynamic characteristics of the charging pile as a dual-input, dual-output system: The transfer function from grid voltage to output voltage is: The transfer function from grid voltage to output current is: Transfer function from CAN command to output voltage: Transfer function from CAN command to output current:

[0056] S5. constructing a dynamic response signature matrix based on the transfer function, and storing the matrix as benchmark data; Specifically, in step S5 of this embodiment, a structured dynamic response signature matrix is ​​constructed based on the transfer function, and the matrix is ​​stored as benchmark data for subsequent comparison.

[0057] The purpose of this step is to integrate the discrete transfer function data obtained in the previous step, distributed across multiple frequency points, into a standardized, multi-dimensional mathematical entity. This entity can comprehensively and compactly represent the complete dynamic characteristics of the charging pile under specific operating conditions, forming its unique "dynamic fingerprint," thereby facilitating subsequent quantitative analysis and comparison.

[0058] The transfer function values ​​calculated in step S4 are used as input. These values ​​are obtained at N preset discrete frequency points f1, f2, ..., f N The transfer function from different input ports to different output ports is shown in Figure 1, where each frequency point is located in the previously determined sensitive frequency band Ω. critical within According to a further limitation of another embodiment of the present invention, the step of constructing a dynamic response signature matrix is ​​specifically: arranging the values ​​of the transfer function at multiple preset frequency points according to predefined row and column rules to form a multi-row and multi-column matrix, which can represent the dynamic response characteristics of the charging pile at different frequencies.

[0059] The structure of the dynamic response signature matrix is ​​a deterministic mapping, and its exemplary structure is as follows: Where DRSM is the constructed dynamic response signature matrix; each column of the matrix, identified by column index k=1,…,N, corresponds to a specific preset frequency point f k Each row of the matrix, identified by the row index, corresponds to a specific input-output transfer path; At frequency f k Above, the transfer function value from grid voltage input to output voltage; At frequency f k Above, the transfer function value from grid voltage input to output current; At frequency f k Above, the transfer function value from CAN command input to output voltage; At frequency f k The transfer function value from CAN command input to output current is shown in Figure 1.

[0060] Each element of this matrix is ​​a complex number that contains information about the amplitude gain and phase delay of the system response at that specific frequency point and transmission path. Therefore, this matrix provides a complete quantitative description of the multi-dimensional and cross-domain dynamic characteristics of the charging pile.

[0061] During the initialization or calibration phase of this method, baseline data must be established. This process involves selecting a fully verified benchmark charging station whose performance indicators fully meet the design specifications and performing steps S1 to S5 on it to obtain its corresponding dynamic response signature matrix.

[0062] The matrix generated by the reference charging station is then designated as the reference data DRSM refThe processing control module converts this reference matrix DRSM ref Stored in a storage module of the test system.

[0063] S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the eligibility of the charging pile and generate a test report; Specifically, in step S6 of this embodiment, the difference between the dynamic response signature matrix and the pre-stored benchmark data is calculated to determine the performance of the charging pile, and finally generate a test report.

[0064] First, the dynamic response signature matrix of the charging pile to be tested is obtained from step S5, which is recorded as DRSM UUT , and retrieve the pre-stored benchmark data from the storage module, recorded as DRSM ref .

[0065] The processing control module then calculates the difference matrix ΔDRSM between the two matrices by subtracting the corresponding elements of the two matrices: ΔDRSM=DRSM UUT -DRSM ref ; Each element δ of the difference matrix ΔDRSM ij They all represent the complex deviations of the charging pile under test from the reference state at a specific frequency point and a specific transmission path.

[0066] According to a further limitation of another embodiment of the present invention, the step of calculating the difference is specifically to obtain a quantitative difference value for characterizing the overall difference degree by calculating the Frobenius norm (FrobeniusNorm) of the difference matrix ΔDRSM.

[0067] The calculation formula of the quantitative difference value D is as follows: Where: D represents the final quantitative difference value, which indicates the size of the quantitative difference value and is used to measure the degree of difference in the data matrix.

[0068] ||·|| F represents the Frobenius norm, which is the square root of the sum of the squares of the matrix elements; m and n represent the number of rows and columns of the matrix ΔDRSM, respectively; δ ij is the element in the i-th row and j-th column of the matrix ΔDRSM; |δ ij | represents a complex element δ ij Model.

[0069] This quantitative difference value D compresses the deviation information of the entire matrix into a single scalar, intuitively reflecting the overall distance between the dynamic characteristics of the charging pile under test and its ideal reference state.

[0070] The processing control module compares the calculated quantitative difference value D with a preset quality control threshold T QC The threshold T QC It is a value that is pre-set based on product design tolerance, production process statistics or aging test data and stored in the test system.

[0071] The decision logic is: if the calculated quantitative difference value D is less than or equal to the quality control threshold T QC , the processing control module determines that the charging pile to be tested is qualified. On the contrary, if D is greater than T QC , it is judged as unqualified. Finally, based on the judgment result, the system automatically generates a structured test report. The report contains at least the following information: the unique product identifier of the charging pile to be tested, the date and time of the test execution, the calculated quantitative difference value D, the set quality control threshold T QC , and the final qualified or unqualified judgment conclusion.

[0072] S7. When judging as unqualified, perform structured deviation analysis on the differences to achieve in-depth diagnosis of potential faults and generate a fault report: Specifically, in step S7 of this embodiment, a structured deviation analysis is performed on the aforementioned calculated differences to achieve in-depth diagnosis of potential faults and generate a corresponding fault report.

[0073] The purpose of this step is to go beyond the simple "pass / fail" binary judgment and provide precise, data-driven guidance for locating the root cause of the fault by deeply mining the structured information in the dynamic response signature matrix.

[0074] Specifically, upon receiving the unqualified determination instruction, the processing control module will initiate a structured deviation analysis process, which first obtains the calculated difference matrix ΔDRSM from step S6 as the initial input for the analysis.

[0075] According to a further limitation of another embodiment of the present invention, the first stage of the structured deviation analysis includes decomposing the complex difference matrix ΔDRSM into amplitude difference and phase difference to reveal the deviation of system performance from different physical dimensions. Exemplarily, the decomposition process is performed by ref and the matrix to be measured DRSM UUT Each corresponding element in is processed separately to establish an independent amplitude difference matrix ΔM and phase difference matrix ΔΦ.

[0076] The process can be expressed as follows: ΔM ij =|H UUT,ij |-|H ref,ij |; ΔΦ ij =∠H UUT,ij -∠H ref,ij ; Where; ΔM ij Represents the matrix element H UUT and H ref The difference in amplitude between the elements in row i and column j; ΔΦ ij Represents the matrix element H UUT and H ref The phase difference of the element in row i and column j; |H UUT,ij | represents the matrix H UUT The amplitude of the element in row i and column j; |H ref,ij | represents the matrix H ref The amplitude of the element in row i and column j; ∠H UUT,ij Represents the matrix H UUT The phase (angle) of the element in row i and column j; ∠H ref,ij Represents the matrix H ref The phase (angle) of the element in the i-th row and j-th column.

[0077] After obtaining the difference matrices in both magnitude and phase dimensions, the analysis process continues by extracting normalized fault feature vectors from these matrices. These feature vectors map the original matrix deviation data into a lower-dimensional space that is strongly correlated with a specific physical subsystem or failure mode.

[0078] The next stage of the analysis process is to match the extracted fault feature vectors with a pre-established fault pattern database. This database is a data set that stores the mapping relationship between various typical faults and their corresponding fault feature vectors.

[0079] The database is established by performing a large number of fault injection experiments and system simulations on charging piles.

[0080] The matching process is achieved by calculating the similarity or distance between the fault feature vector of the charging pile under test and the feature vectors of each fault mode stored in the database. The fault type corresponding to the database entry with the highest similarity is determined to be the most likely fault of the charging pile under test.

[0081] Finally, based on the matching results, the processing control module determines the specific type of fault and the faulty component that may have problems.

[0082] The AC / DC charging pile detection system described below and the AC / DC charging pile detection method described above may refer to each other.

[0083] Please see the attached Figure 5 ,The present invention also provides an AC / DC charging pile detection system, including; A signal generation module is used to generate a preliminary broadband disturbance signal and an optimized composite disturbance signal, and synchronously apply them to the AC input terminal and communication control terminal of the charging pile under test; A data acquisition module, used to collect response data of the output voltage and output current of the charging pile to be tested; a processing control module for performing spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis; Report generation module, used to generate detection reports and fault reports The system of this embodiment can be used to execute the above method embodiments, and its principles and technical effects are similar, so they will not be repeated here.

[0084] Please see the attached Figure 6-7 The present invention also provides an AC / DC charging pile detection device, including a protective box 1; a display screen 2 is fixedly connected to the outside of the protective box 1, a charging gun connector 3 is fixedly connected to the inside of the protective box 1, one end of the charging gun connector 3 is electrically connected to a collector 4, an outer wall of the collector 4 is fixedly connected to the inside of the protective box 1, one end of the collector 4 is electrically connected to a storage battery 5, an outer wall of the storage battery 5 is fixedly connected to the inner wall of the protective box 1, one end of the collector 4 is electrically connected to a processing controller 6, an outer wall of the processing controller 6 is fixedly connected to the inner wall of the protective box 1, one end of the processing controller 6 is electrically connected to a signal generating module 7, and an outer wall of the signal generating module 7 is fixedly connected to the inner wall of the protective box 1.

[0085] Specifically, by inserting the charging gun into the charging gun connector 3, and applying a preliminary broadband disturbance signal to the charging pile to be tested through the signal generation module 7, its response data is obtained to identify the sensitive frequency band of the system, and then the output response of the charging pile is obtained through the collector 4, and the electricity is stored in the storage battery 5. The collected data is transmitted to the processing controller 6 to perform spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation and structured deviation analysis.

[0086] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. AC / DC charging pile detection method, characterized in that: The following steps are involved: S1. Apply a preliminary broadband disturbance signal to the charging pile under test and obtain its response data to identify the system's sensitive frequency band. S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band and is used to stimulate the charging pile. S3. Synchronously applying the optimized composite disturbance signal to the charging pile to be tested to obtain its output response; S4. Calculating a transfer function between an input signal and an output signal by performing Fourier transform on the output response; S5. constructing a dynamic response signature matrix based on the transfer function, and storing the matrix as benchmark data; S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the eligibility of the charging pile and generate a test report; S7. When judging as unqualified, perform structured deviation analysis on the differences to achieve in-depth diagnosis of potential faults and generate a fault report.

2. The AC / DC charging pile detection method according to claim 1, characterized in that: The response data in step S1 includes the output voltage and output current of the charging pile, and the sensitive frequency band is determined by performing spectrum analysis on the response data.

3. The AC / DC charging pile detection method according to claim 1, characterized in that: The step of generating the optimized composite disturbance signal in step S2 is specifically: superimposing multiple sinusoidal wave signals to form the optimized composite disturbance signal, wherein the frequencies of the multiple sinusoidal wave signals are all set within the sensitive frequency band.

4. The AC / DC charging pile detection method according to claim 1, characterized in that: The step of synchronously applying the optimized composite disturbance signal to the charging pile to be tested in step S3 is specifically: superimposing one component of the optimized composite disturbance signal on the AC input voltage of the charging pile to be tested through a programmable AC power supply, and at the same time superimposing another component of the optimized composite disturbance signal on the charging instruction sent to the charging pile to be tested through a controller local area network communication device.

5. The AC / DC charging pile detection method according to claim 1, characterized in that: In the step S4, the Fourier transform uses a fast Fourier transform algorithm to process the output response and the input signal to obtain a frequency domain representation.

6. The AC / DC charging pile detection method according to claim 1, characterized in that: The step of constructing the dynamic response signature matrix in step S5 is specifically: arranging the values ​​of the transfer function at multiple preset frequency points in frequency order to form a matrix with multiple rows and columns to represent the dynamic response characteristics of the charging pile at different frequencies.

7. The AC / DC charging pile detection method according to claim 1, characterized in that: The step of calculating the difference in step S6 is specifically: obtaining a quantitative difference value for characterizing the overall degree of difference by calculating the Frobenius norm of the difference between the dynamic response signature matrix and the reference data.

8. The AC / DC charging pile detection method according to claim 1, characterized in that: The structured deviation analysis in step S7 includes: Decompose the difference between the dynamic response signature matrix and the benchmark data into amplitude difference and phase difference, and establish the corresponding fault feature vectors respectively; The fault feature vector is matched with a preset fault mode database to determine the fault type and the corresponding fault component.

9. An AC / DC charging pile detection device, applied to the AC / DC charging pile detection method according to any one of claims 1 to 8, characterized in that: The invention comprises a protective box (1); the outer surface of the protective box (1) is fixedly connected to a display screen (2); the interior of the protective box (1) is fixedly connected to a charging gun connector (3); one end of the charging gun connector (3) is electrically connected to a collector (4); the outer wall of the collector (4) is fixedly connected to the interior of the protective box (1); one end of the collector (4) is electrically connected to a storage battery (5); the outer wall of the storage battery (5) is fixedly connected to the inner wall of the protective box (1); one end of the collector (4) is electrically connected to a processing controller (6); the outer wall of the processing controller (6) is fixedly connected to the inner wall of the protective box (1); one end of the processing controller (6) is electrically connected to a signal generating module (7); the outer wall of the signal generating module (7) is fixedly connected to the inner wall of the protective box (1).

10. An AC / DC charging pile detection system, applied to the AC / DC charging pile detection method according to any one of claims 1 to 8, characterized in that: include; A signal generation module is used to generate a preliminary broadband disturbance signal and an optimized composite disturbance signal, and synchronously apply them to the AC input terminal and communication control terminal of the charging pile under test; A data acquisition module, used to collect response data of the output voltage and output current of the charging pile to be tested; a processing control module for performing spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis; The report generation module is used to generate detection reports and fault reports.

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