An anti-interference connector for automotive electronic systems

Abstract

This invention relates to the field of signal data processing technology, specifically to an anti-interference connector for automotive electronic systems. This application first analyzes the characteristic behavior of the spectrum within the time period of arc flicker interference in the original signal, obtaining the arc flicker frequency band and arc flicker influence coefficient. Based on the arc flicker influence coefficient, and combined with baseline drift and signal fluctuation in the time series, the influence of electromagnetic interference, i.e., arc flicker interference, is more accurately quantified using the determined electromagnetic interference characteristic values. Furthermore, a sensitivity weight is determined to characterize the impact of the anti-interference connector's aging accumulation. Based on the sensitivity weights characterizing the interference components and the electromagnetic interference characteristic values, the simulated signal to be processed is corrected, making the obtained corrected simulated signal more accurate and improving the accuracy of anomaly monitoring in automotive electronic systems based on the corrected simulated signal.

Description

Technical Field

[0001] This invention relates to the field of signal data processing technology, and more specifically to an anti-interference connector for automotive electronic systems. Background Technology

[0002] Anti-interference connectors are connectors specifically designed to reduce or eliminate the effects of electromagnetic interference (EMI). Through specific design and material selection, they ensure that signals are protected from external interference during transmission, guaranteeing stable and accurate data. They are widely used in various scenarios requiring high-precision and high-reliability signal transmission.

[0003] Components in automobiles, such as motor controllers and high-voltage battery systems, generate high-frequency electromagnetic fields, which require shielding and filtering techniques to suppress radiated interference. Current technologies typically employ frequency domain filtering to process the transmitted signals of automotive electronic systems, thereby suppressing external noise interference.

[0004] However, due to the changing scenarios encountered during vehicle operation, the connectors inside the chassis need to withstand high or extremely cold temperatures, leading to material aging or insulation failure. The shielding effectiveness of the connectors will be significantly reduced due to insulation failure or changes in contact impedance caused by thermal expansion and contraction of materials, which exacerbates the corresponding signal baseline drift phenomenon. At this time, signal processing using frequency filtering methods will lose actual monitoring information due to excessive smoothing, resulting in poor suppression of external noise interference and lower accuracy in monitoring abnormalities in automotive electronic systems based on the smoothed signal. Summary of the Invention

[0005] To address the technical problem that signal processing using frequency filtering can result in the loss of actual monitoring information due to excessive smoothing, leading to poor suppression of external noise interference, this application aims to provide an anti-interference connector for automotive electronic systems. The specific technical solution adopted is as follows:

[0006] The first aspect of this application provides an anti-interference connector for an automotive electronic system, including a connector port, a photodetector, and an anti-interference device. The connector port is used to receive a simulated signal to be processed from the automotive electronic system. The photodetector is used to detect the timing of arc flashes. Both the photodetector and the connector port are signal-connected to the anti-interference device. The anti-interference device acquires the simulated signal to be processed from the automotive electronic system during vehicle operation and all the timings of arc flashes. The anti-interference device determines the arc flash frequency band based on the amplitude distribution of the spectrum corresponding to the neighboring signal segments of each arc flash timing in the simulated signal to be processed after time-frequency conversion.

[0007] Empirical mode decomposition is performed on the simulated signal to be processed to obtain at least two IMF component signals; the arc flicker influence coefficient at each sampling time in each IMF component signal is determined based on the overall magnitude of the frequency amplitude of the arc flicker frequency band and the frequency overlap with each IMF component signal.

[0008] In each IMF component signal, the corresponding electromagnetic interference characteristic value is determined based on the arc flicker influence coefficient and the baseline drift and signal fluctuation within the temporal neighborhood at each sampling time; the sensitivity weight of each IMF component signal during vehicle operation is determined based on the changes in the corresponding electromagnetic interference characteristic value during vehicle operation.

[0009] The acquisition process of each IMF component signal is corrected one by one according to the sensitivity weight and the electromagnetic interference characteristic value to determine the electromagnetic interference signal; the simulation signal to be processed is corrected according to the electromagnetic interference signal to determine the corrected simulation signal; and the abnormality monitoring of the automotive electronic system is performed according to the corrected simulation signal.

[0010] Furthermore, the process of obtaining the arc flicker frequency band includes:

[0011] On the simulated signal to be processed, a short-time Fourier transform is performed on the local signal segment within a preset neighborhood time period for each arc flash moment to obtain the corresponding spectrum signal; the amplitude of all frequencies in the spectrum signal is clustered to obtain at least two amplitude clusters; the amplitude cluster with the largest mean of all corresponding amplitudes is taken as the arc flash cluster; a reference frequency interval is determined based on the continuity of the frequency distribution in the arc flash cluster.

[0012] The average of the maximum frequencies of all reference frequency intervals corresponding to all arc flash moments is taken as the upper limit of the arc flash frequency range; the average of the minimum frequencies of all reference frequency intervals corresponding to all arc flash moments is taken as the lower limit of the arc flash frequency range.

[0013] The arc flash frequency range is determined based on the upper limit and lower limit of the arc flash frequency range.

[0014] Furthermore, the process of obtaining the reference frequency range includes:

[0015] Obtain all continuous frequency intervals in the arc flicker cluster; the preceding and following frequencies of the continuous frequency interval do not belong to the arc flicker cluster, and all frequencies in the reference frequency interval are continuous and belong to the arc flicker cluster; the continuous frequency interval with the most frequencies is taken as the reference frequency interval.

[0016] Furthermore, the process of obtaining the arc flicker influence coefficient includes:

[0017] The length of the overlapping frequency segment between the frequency range corresponding to each IMF component signal and the arc flicker frequency segment is normalized to determine the arc flicker influence probability of each IMF component signal; the average amplitude of all frequencies in the arc flicker frequency segment is taken as the arc flicker influence amplitude.

[0018] The arc flicker influence amplitude and the arc flicker influence probability are positively correlated to determine the arc flicker influence coefficient of the sampling time that belongs to the arc flicker moment; the arc flicker influence coefficient of the sampling time that does not belong to the arc flicker moment is set as the preset influence coefficient.

[0019] Furthermore, the process of obtaining the electromagnetic interference characteristic values ​​includes:

[0020] In each IMF component signal, all sampling times within a preset neighborhood window at each sampling time are taken as the neighborhood window time; the range of signal values ​​at all neighborhood window times corresponding to each sampling time is normalized to determine the local fluctuation amplitude at each sampling time.

[0021] Based on the overall deviation between the mean envelope and the baseline across all neighborhood window times, the degree of local baseline drift at each sampling time is determined;

[0022] The product of the arc flicker influence coefficient, local fluctuation amplitude, and local baseline drift at each sampling time is normalized to determine the corresponding electromagnetic interference characteristic value.

[0023] Furthermore, the process of obtaining the degree of local baseline drift includes:

[0024] The difference between the value of the mean envelope corresponding to each neighborhood window time and the value of the baseline is taken as the corresponding instantaneous drift degree; the local baseline drift degree at each sampling time is determined based on the average of the instantaneous drift degrees of all neighborhood window times.

[0025] Furthermore, the process of obtaining the sensitivity weights includes:

[0026] For each IMF component signal, the electromagnetic interference characteristic values ​​at all sampling times are arranged in time sequence and then curve-fitted to determine the electromagnetic interference characteristic value curve. Based on the changing trend of the electromagnetic interference characteristic values ​​on the electromagnetic interference characteristic value curve, the aging accumulation amplitude is determined. Based on the aging accumulation amplitude and the initial intercept of the electromagnetic interference characteristic value curve, the sensitivity weight of each IMF component signal is determined. The aging accumulation amplitude and the initial intercept are both positively correlated with the sensitivity weight.

[0027] Furthermore, the process of obtaining the aging accumulation magnitude includes:

[0028] The average value of the tangent slope at all sampling times on the electromagnetic interference characteristic curve is taken as the aging accumulation amplitude.

[0029] Furthermore, the process of acquiring the electromagnetic interference signal includes:

[0030] In each IMF component signal, the product between the electromagnetic interference characteristic value at each sampling time and the sensitivity weight is positively correlated to determine the electromagnetic interference level of each IMF component signal; the mean envelope function of each IMF component signal is weighted by the electromagnetic interference level to determine the corresponding weighted envelope function.

[0031] In the process of obtaining each IMF component signal and residual signal by the empirical mode decomposition algorithm, the weighted envelope function of each IMF component signal is used to replace the original mean envelope function for empirical mode decomposition, and the final residual signal is used as the electromagnetic interference signal.

[0032] Furthermore, the process of acquiring the modified analog signal includes:

[0033] The electromagnetic interference signal is subtracted from the analog signal to be processed to obtain the corrected analog signal.

[0034] This application has the following beneficial effects:

[0035] This application analyzes the characteristic performance of the spectrum within the time period of arc flicker interference in the original signal, obtains the main affected arc flicker frequency bands and the arc flicker influence coefficients corresponding to the IMF component signals, and, based on the arc flicker influence coefficients, combines baseline drift and signal fluctuation in the time series to more accurately quantify the impact of electromagnetic interference, i.e., arc flicker interference, using the determined electromagnetic interference characteristic values. Furthermore, based on the changes in the electromagnetic interference characteristic values, it determines the sensitivity weights characterizing the impact of aging accumulation of the anti-interference connector. Further, based on the sensitivity weights characterizing the interference components and the electromagnetic interference characteristic values, the acquisition process of the IMF component signals is modified one by one, so that the obtained electromagnetic interference signals can more accurately characterize the baseline drift impact. Finally, the simulated signal to be processed is modified based on the electromagnetic interference signal, making the obtained modified simulated signal more accurate and improving the accuracy of abnormal monitoring of automotive electronic systems based on the modified simulated signal. Attached Figure Description

[0036] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of the hardware structure of an anti-interference connector for an automotive electronic system, provided as an embodiment of the present invention.

[0038] Figure 2 A data processing flowchart for an anti-interference connector for an automotive electronic system, provided as an embodiment of the present invention;

[0039] exist Figure 1 In the diagram, 1-Connection port; 2-Integrated resistor; 3-Shielding shell; 4-Photodetector; 5-Signal amplifier and converter; 6-Transmission line; 7-Anti-interference device; 8-Signal filter compensator. Detailed Implementation

[0040] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an anti-interference connector for automotive electronic systems proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment, and specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0042] The following description, in conjunction with the accompanying drawings, details a specific solution for an anti-interference connector for automotive electronic systems provided by the present invention.

[0043] This application provides an anti-interference connector for automotive electronic systems. Please refer to [link / reference]. Figure 1The diagram illustrates a hardware structure of an anti-interference connector for an automotive electronic system according to an embodiment of the present invention, including: a connection port 1, an integrated resistor 2, a shielding shell 3, a photodetector 4, a signal amplifier / converter 5, a transmission line 6, an anti-interference device 7, and a signal filter compensator 8.

[0044] The connector 1 is encased in a shielding shell 3, and a locking mechanism ensures a secure installation, forming a 360° all-around shielding layer. The shielding material is electroplated and treated with anti-corrosion coatings to improve durability and prevent direct interference from temperature, humidity, electromagnetic fields, and transient electric arcs from affecting the signal. An integrated resistor 2 monitors the overheating of the automotive electronic system load and external temperature and humidity interference in real time. A photodetector 4 between the signal amplifier / converter 5 and the shielding shell 3 detects transient electric arc flicker, i.e., the timing of the electric arc flicker is detected by the photodetector 4. When the air is dry, the motor starts or stops, or the voltage is too high, electric arcs are inevitable. An electric arc is a high-frequency electromagnetic interference source, and the broadband electromagnetic waves it generates can affect surrounding equipment through spatial radiation or conduction through wires, and may even burn connector contacts or insulation materials. Even if existing arc suppression or arc extinguishing designs reduce the harm of electric arcs, it may still cause problems with reduced transmission performance, such as the electromagnetic radiation of the electric arc interfering with the signal processing of the ECU (Electronic Control Unit). The shielding mesh sleeve on transmission line 6 is electrically connected to the shielding shell 3 through crimping or welding, ensuring continuous shielding coverage and reducing radiation leakage. Signals sent by the automotive electronic system are received through connection port 1 and then transmitted through transmission line 6 to the anti-interference device 7. The anti-interference device 7 processes the received analog signal from the automotive electronic system and the arc flash time according to a predetermined data processing procedure to obtain a corrected analog signal. Finally, the corrected analog signal is filtered and compensated using a signal filter compensator 8. For details on the predetermined data processing procedure, please refer to [link to relevant documentation]. Figure 2 The diagram illustrates a data processing flowchart for an anti-interference connector for an automotive electronic system, provided by an embodiment of the present invention, including the following steps:

[0045] Step S201: Obtain the analog signal to be processed from the vehicle's electronic system during vehicle operation and all arc flash times; determine the arc flash frequency range based on the amplitude distribution of the spectrum corresponding to the neighboring signal segments of each arc flash time in the analog signal to be processed after time-frequency conversion.

[0046] In one specific implementation of this invention, the moment when the photoelectric receiver 4 detects the instantaneous arc flash is taken as the arc flash moment; and the position of the arc flash moment in the analog signal to be processed is determined. The interference generated by the arc flash usually manifests as a sharp increase in amplitude within a concentrated frequency range in the spectrum. Therefore, in order to determine the arc flash frequency band, it is necessary to convert it into a spectrum for analysis.

[0047] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the arc flicker frequency band includes: performing a short-time Fourier transform on the local signal segment within a preset neighborhood time period of each arc flicker moment on the analog signal to be processed to obtain the corresponding spectrum signal; performing cluster analysis on the amplitude of all frequencies in the spectrum signal to obtain at least two amplitude clusters; taking the amplitude cluster with the largest mean of all corresponding amplitudes as the arc flicker cluster; and determining a reference frequency interval based on the continuity of the frequency distribution in the arc flicker cluster. The process of obtaining the reference frequency interval includes: obtaining all continuous frequency intervals in the arc flicker cluster; ensuring that neither the preceding nor following frequency of a continuous frequency interval belongs to an arc flicker cluster, and that all frequencies in the reference frequency interval are continuous and belong to an arc flicker cluster; and taking the continuous frequency interval with the most frequencies as the reference frequency interval.

[0048] In one specific implementation of this invention, the preset neighborhood time period is set to 200ms, the clustering analysis method uses the K-means clustering algorithm, and the optimal k value is obtained through the elbow method, which can be adjusted according to the specific implementation environment. It should be noted that short-time Fourier transform, K-means clustering algorithm, and elbow method are techniques well-known to those skilled in the art, and will not be further limited or elaborated upon here. Since the interference generated by arc flash is characterized by a sharp increase in amplitude within a concentrated frequency range in the spectrum, the amplitude of the frequency corresponding to arc flash interference is usually large. Therefore, after obtaining amplitude clusters through cluster analysis, the amplitude cluster with the largest mean amplitude is selected as the arc flash cluster. Based on the arc flash cluster, and considering the characteristic that the interference generated by arc flash is characterized by concentrated frequency in the spectrum, the continuous frequency range with the largest number of continuously distributed amplitudes in the arc flash cluster is further selected as the reference frequency range characterizing the arc flash interference.

[0049] Since each arc flash moment corresponds to a reference frequency range, to more accurately determine the arc flash frequency segment, a comprehensive determination of the arc flash frequency segment is achieved by combining all reference frequency ranges corresponding to each arc flash moment. Specifically: the average of the maximum frequency values ​​of all reference frequency ranges corresponding to all arc flash moments is used as the upper limit of the arc flash frequency segment; the average of the minimum frequency values ​​of all reference frequency ranges corresponding to all arc flash moments is used as the lower limit of the arc flash frequency segment; and the arc flash frequency segment is determined based on the upper and lower limits. In other words, after determining the upper and lower limits of the arc flash frequency segment using the averaging method, the upper and lower limits of the arc flash frequency segment are used as frequency boundaries to determine the arc flash frequency segment.

[0050] Step S202: Perform empirical mode decomposition on the analog signal to be processed to obtain at least two IMF component signals; determine the arc flicker influence coefficient at each sampling time in each IMF component signal based on the overall magnitude of the frequency amplitude of the arc flicker frequency band and the frequency overlap with each IMF component signal.

[0051] For each arc flicker frequency band, the larger the overall amplitude of all frequencies, the greater the interference caused by the arc flicker. Therefore, when determining the arc flicker influence coefficient, it is necessary to analyze the overall magnitude of the frequency amplitude of the arc flicker frequency band. Furthermore, each IMF component signal typically corresponds to a certain frequency range; therefore, in addition to the overall magnitude of the frequency amplitude of the arc flicker frequency band, it is also necessary to analyze the frequency overlap between the arc flicker frequency band and each IMF component signal. It should be noted that empirical mode decomposition is a technique well-known to those skilled in the art and will not be elaborated upon further here.

[0052] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the arc flicker influence coefficient includes:

[0053] The length of the overlapping frequency segment between the frequency range corresponding to each IMF component signal and the arc flicker frequency segment is normalized to determine the arc flicker influence probability of each IMF component signal; the average amplitude of all frequencies in the arc flicker frequency segment is taken as the arc flicker influence amplitude; in a specific implementation of this invention, the method for normalizing the length of the overlapping frequency segment includes: taking the length of the frequency segment corresponding to the frequency range of each IMF component signal as a reference length; and taking the ratio between the length of the overlapping frequency segment and the corresponding reference length as the normalized value, i.e., the corresponding arc flicker influence probability.

[0054] Based on the properties of IMF component signals, each IMF component signal corresponds to a certain frequency range. Therefore, for each IMF component signal, the greater the overlap between its corresponding frequency range and the arc flash frequency band, i.e., the greater the probability of arc flash influence, the greater the degree of interference it receives. The overall amplitude of the arc flash frequency band also characterizes the magnitude of the interference influence. Therefore, the greater the arc flash influence amplitude, the greater the degree of interference influence. Furthermore, the arc flash influence coefficient is determined by comprehensively considering the arc flash influence probability and arc flash influence amplitude, so that the larger the arc flash influence coefficient, the greater the interference influence on the corresponding IMF component signal.

[0055] In one specific implementation of this invention, by combining correlation relationships, a positive correlation mapping is performed on the product of the arc flicker influence amplitude and the arc flicker influence probability to determine the arc flicker influence coefficient for sampling times belonging to the arc flicker moment; the arc flicker influence coefficient for sampling times not belonging to the arc flicker moment is set as a preset influence coefficient. In one specific implementation of this invention, the preset influence coefficient is set to 1, which can be adjusted according to the specific implementation environment. The positive correlation mapping method includes: adding a real number 1 to the product of the arc flicker influence amplitude and the arc flicker influence probability to determine the arc flicker influence coefficient; ensuring that the interference influence of IMF component signals whose frequencies do not coincide with the arc flicker frequency band is also 1. Because arc flicker typically only significantly affects the signal data at the arc flicker moment, this application only performs correlation calculations and analyses on the flicker influence coefficient at the arc flicker moment.

[0056] Step S203: In each IMF component signal, determine the corresponding electromagnetic interference characteristic value based on the arc flicker influence coefficient and the baseline drift and signal fluctuation within the time-series neighborhood at each sampling time; determine the sensitivity weight of each IMF component signal during vehicle driving based on the changes in the corresponding electromagnetic interference characteristic value during vehicle driving.

[0057] The arc flicker influence coefficient characterizes the interference effect by measuring the magnitude of the arc's influence and its frequency distribution. For the IMF component signal itself, when there is instantaneous interference, it usually exhibits certain instantaneous fluctuations and baseline drift. Therefore, each IMF component signal can be further analyzed to further characterize the interference.

[0058] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining electromagnetic interference characteristic values ​​includes:

[0059] In each IMF component signal, all sampling times within a preset neighborhood window at each sampling time are taken as the neighborhood window time. The signal value range of all neighborhood window times corresponding to each sampling time is normalized to determine the local fluctuation amplitude at each sampling time. In a specific implementation of this invention, the method for normalizing the signal value range of all neighborhood window times corresponding to each sampling time is as follows: the signal value range of all sampling times in each IMF component signal is taken as the reference range; the ratio between the signal value range of all neighborhood window times corresponding to each sampling time and the reference range is taken as the normalized value, i.e., the local fluctuation amplitude. Implementers may also use other normalization methods according to the specific implementation environment, which will not be further elaborated here. The range represents the fluctuation range of a set of data. Therefore, the larger the signal value range, the larger the fluctuation range of the signal value within the preset neighborhood window, the larger the corresponding local fluctuation amplitude, the more it conforms to the local fluctuation characteristics of electromagnetic interference caused by arc flicker, and the greater the influence of electromagnetic interference. In one specific implementation of this invention, the preset neighborhood window is set to a 200ms window centered at each sampling time.

[0060] Based on the overall deviation between the mean envelope and the baseline across all neighborhood window times, the local baseline drift degree at each sampling time is determined. In a specific implementation of this invention, the process of obtaining the local baseline drift degree includes: taking the difference between the value of the mean envelope and the value of the baseline at each neighborhood window time as the corresponding instantaneous drift degree; and determining the local baseline drift degree at each sampling time based on the average of the instantaneous drift degrees at all neighborhood window times. First, for IMF component signals, the greater the difference between the mean envelope and the baseline at a certain sampling time, the more obvious the baseline drift phenomenon, and the greater the overall impact of the instantaneous interference on the corresponding IMF component signal. Therefore, for each sampling time, the greater the average of the instantaneous drift degrees at all neighborhood window times, the greater the corresponding local baseline drift degree, and the greater the influence of electromagnetic interference caused by arc flicker on the signal value at that sampling time. It should be noted that the difference represents the absolute value of the difference, which will not be further elaborated upon later.

[0061] Furthermore, the arc flicker influence coefficient, local fluctuation amplitude, and local baseline drift degree, which all characterize the interference effect, are combined to comprehensively determine the electromagnetic interference characteristic value of the magnitude of the pointer interference. In a specific implementation of this invention, the product of the arc flicker influence coefficient, local fluctuation amplitude, and local baseline drift degree at each sampling time is normalized to determine the corresponding electromagnetic interference characteristic value; wherein, the normalization method adopts linear normalization, which can be adjusted according to the specific implementation environment.

[0062] Besides external interference, the aging of the anti-interference connector itself must also be considered. During prolonged use, anti-interference connectors inevitably age, leading to a weakening of their interference suppression capabilities and increased susceptibility to electromagnetic interference. The aging of anti-interference connectors manifests as an overall increase in interference levels during vehicle operation, and the accumulation of aging results in a certain inherent level of interference, making them more sensitive to interference. Therefore, this invention uses sensitivity weighting to characterize the aging of the anti-interference connector, thereby further characterizing the degree of electromagnetic interference impact.

[0063] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the sensitivity weight includes:

[0064] For each IMF component signal, the electromagnetic interference characteristic values ​​at all sampling times are arranged in time sequence and then curve-fitted to determine the electromagnetic interference characteristic value curve; based on the changing trend of the electromagnetic interference characteristic values ​​on the electromagnetic interference characteristic value curve, the aging accumulation amplitude is determined.

[0065] The process of obtaining the aging accumulation amplitude includes: taking the average of the tangent slope values ​​at all sampling times on the electromagnetic interference characteristic value curve as the aging accumulation amplitude. A larger average tangent slope indicates an overall increasing trend in the interference level of the electromagnetic interference characteristic value during vehicle operation. Therefore, a larger aging accumulation amplitude indicates more severe aging of the anti-interference connector and a greater impact from interference. The initial intercept characterizes the material fatigue accumulation of the anti-interference connector during its historical aging process. A larger initial intercept also indicates more severe aging accumulation, a greater degree of aging, and a greater impact from interference. Therefore, the sensitivity weight of each IMF component signal is further determined based on the aging accumulation amplitude and the initial intercept of the electromagnetic interference characteristic value curve; both the aging accumulation amplitude and the initial intercept are positively correlated with the sensitivity weight. In a specific implementation of this invention, the arithmetic square root of the sum of the square of the aging accumulation amplitude and the square of the initial intercept of the electromagnetic interference characteristic value curve is used as the sensitivity weight of each IMF component signal; those skilled in the art can use other basic mathematical methods for implementation, which are not limited or elaborated here.

[0066] Step S204: Correct the acquisition process of each IMF component signal according to the sensitivity weight and electromagnetic interference characteristic value to determine the electromagnetic interference signal; correct the simulation signal to be processed according to the electromagnetic interference signal to determine the corrected simulation signal; perform abnormal monitoring of the automotive electronic system according to the corrected simulation signal.

[0067] According to empirical mode decomposition algorithms, the process of decomposing the analog signal to be processed involves constructing a mean envelope function based on the previous-level IMF component signal, and then subtracting the mean envelope function from the previous-level IMF component signal to obtain the next-level IMF component signal. When arc flicker interference exists at a certain sampling moment, the arc flicker interference component in the current component signal can be removed, so that it ultimately appears in the signal residue. Finally, the baseline drift caused by arc flicker can be eliminated by subtracting the residue containing the arc flicker interference from the analog signal to be processed. Therefore, for each IMF component signal, the more severe the interference, the fewer components should be retained in the previous-level component signal when obtaining the next-level component signal; that is, the coefficient of the mean envelope function should be larger.

[0068] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring electromagnetic interference signals includes:

[0069] In each IMF component signal, the product of the electromagnetic interference characteristic value and the sensitivity weight at each sampling time is positively correlated to determine the electromagnetic interference level of each IMF component signal. In a specific implementation of this invention, the positive correlation mapping method is as follows: the sum of the product of the electromagnetic interference characteristic value and the sensitivity weight at each sampling time, after linear normalization, and the real number 0.5, is used as the value after positive correlation mapping, i.e., the electromagnetic interference level. The value of the real number can be adjusted according to the specific implementation environment, and will not be further elaborated here. Through positive correlation mapping, the electromagnetic interference level is evenly distributed between 0.5 and 1.5. When the electromagnetic interference level is large, the mean of the subsequent mean envelope function is larger, the component retained in the previous level component signal is smaller, and the suppression effect on baseline drift is better. Further, the mean envelope function of each IMF component signal is weighted according to the degree of electromagnetic interference to determine the corresponding weighted envelope function. In a specific implementation of this invention, the specific process of weighting the mean envelope function of each IMF component signal according to the degree of electromagnetic interference includes: multiplying each function value on the mean envelope function of each IMF component signal by the degree of electromagnetic interference, and using the product of each function value and the degree of electromagnetic interference as the optimized function value of each function value; replacing each function value in the mean envelope function with the corresponding optimized function value to obtain the weighted envelope function.

[0070] In the process of obtaining each IMF component signal and residual signal using the Empirical Mode Decomposition (EMD) algorithm, the weighted envelope function of each IMF component signal replaces the original mean envelope function for EMD, and the final residual signal is used as the electromagnetic interference (EMI) signal. In a specific implementation of this invention, analysis begins with the first IMF component signal. The first IMF component signal is subtracted from its corresponding weighted envelope function to obtain the second IMF component signal. Further calculations and analysis are performed on the second IMF component signal to obtain its corresponding weighted envelope function, and this is subtracted again to obtain the third IMF component signal. Subsequent analysis continues in the same way until the final residual signal is obtained. The corresponding residual signal is the EMI signal representing the interference component. Therefore, to correct the analog signal to be processed, subtracting the EMI signal representing the interference component from the analog signal to be processed yields a more accurate and optimized corrected analog signal.

[0071] After determining the corrected analog signal, the corrected analog signal is input into the signal filter compensator 8 for conventional filtering operations, and the fault monitoring of the automotive electronic system is performed based on the filtered corrected analog signal. In a specific implementation of this invention, the filtered corrected analog signal is input into a trained convolutional neural network, and the output shows whether a system fault exists. The method for fault monitoring of the automotive electronic system based on the filtered corrected analog signal can be adjusted according to the specific implementation environment, for example, by setting a fixed threshold for monitoring, which will not be further elaborated here.

[0072] In summary, this application analyzes the characteristic performance of the spectrum within the time period of arc flicker interference in the original signal, obtains the main affected arc flicker frequency bands and the arc flicker influence coefficients corresponding to the IMF component signals, and, based on the arc flicker influence coefficients, combines baseline drift and signal fluctuation in the time series to more accurately quantify the impact of electromagnetic interference, i.e., arc flicker interference, using the determined electromagnetic interference characteristic values. Furthermore, based on the changes in the electromagnetic interference characteristic values, a sensitivity weight is determined to characterize the impact of aging accumulation of the anti-interference connector. Further, the acquisition process of the IMF component signals is modified one by one according to the sensitivity weights characterizing the interference components and the electromagnetic interference characteristic values, so that the obtained electromagnetic interference signals can more accurately characterize the baseline drift impact. Finally, the simulated signal to be processed is modified based on the electromagnetic interference signal, making the obtained modified simulated signal more accurate and improving the accuracy of abnormal monitoring of automotive electronic systems based on the modified simulated signal.

[0073] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An anti-jamming connector monitoring method for automotive electronic systems, characterized by, It includes a connector, a photoelectric receiver, and an anti-interference device; the connector is used to receive analog signals to be processed from the automotive electronic system; the photoelectric receiver is used to detect the timing of arc flashes; both the photoelectric receiver and the connector are signal-connected to the anti-interference device. The anti-interference device acquires the analog signal to be processed from the vehicle's electronic system during vehicle operation, as well as all arc flash times. Based on the amplitude distribution of the spectrum corresponding to the neighboring signal segments of each arc flash time in the analog signal to be processed after time-frequency conversion, the arc flash frequency segment is determined. Empirical mode decomposition is performed on the simulated signal to be processed to obtain at least two IMF component signals; the arc flicker influence coefficient at each sampling time in each IMF component signal is determined based on the overall magnitude of the frequency amplitude of the arc flicker frequency band and the frequency overlap with each IMF component signal. In each IMF component signal, the corresponding electromagnetic interference characteristic value is determined based on the arc flicker influence coefficient and the baseline drift and signal fluctuation within the temporal neighborhood at each sampling time; the sensitivity weight of each IMF component signal during vehicle operation is determined based on the changes in the corresponding electromagnetic interference characteristic value during vehicle operation. The acquisition process of each IMF component signal is corrected one by one according to the sensitivity weight and the electromagnetic interference characteristic value to determine the electromagnetic interference signal; the simulation signal to be processed is corrected according to the electromagnetic interference signal to determine the corrected simulation signal. Anomaly monitoring of automotive electronic systems based on corrected analog signals; The process of obtaining the arc flicker frequency band includes: On the simulated signal to be processed, a short-time Fourier transform is performed on the local signal segment within a preset neighborhood time period for each arc flash moment to obtain the corresponding spectrum signal; the amplitude of all frequencies in the spectrum signal is clustered to obtain at least two amplitude clusters; the amplitude cluster with the largest mean of all corresponding amplitudes is taken as the arc flash cluster; a reference frequency interval is determined based on the continuity of the frequency distribution in the arc flash cluster. The average of the maximum frequencies of all reference frequency intervals corresponding to all arc flash moments is taken as the upper limit of the arc flash frequency range; the average of the minimum frequencies of all reference frequency intervals corresponding to all arc flash moments is taken as the lower limit of the arc flash frequency range. The arc flash frequency range is determined based on the upper limit value and the lower limit value of the arc flash frequency range. The process of obtaining the arc flicker influence coefficient includes: The length of the overlapping frequency segment between the frequency range corresponding to each IMF component signal and the arc flicker frequency segment is normalized to determine the arc flicker influence probability of each IMF component signal; the average amplitude of all frequencies in the arc flicker frequency segment is taken as the arc flicker influence amplitude. The product of the arc flash influence amplitude and the arc flash influence probability is positively mapped to determine an arc flash influence coefficient of a sampling moment belonging to an arc flash moment; and the arc flash influence coefficient of a sampling moment not belonging to an arc flash moment is set as a preset influence coefficient.

2. The anti-jamming connector monitoring method for automotive electronic systems according to claim 1, characterized in that, The acquisition process of the reference frequency interval comprises: All continuous frequency intervals in the arc flash clustering cluster are acquired; the previous frequency and the next frequency of the continuous frequency interval do not belong to the arc flash clustering cluster, and all frequencies in the reference frequency interval are continuous and belong to the arc flash clustering cluster; and the continuous frequency interval with the largest number of frequencies is taken as the reference frequency interval.

3. The anti-jamming connector monitoring method for automotive electronic systems of claim 1, wherein, The acquisition process of the electromagnetic interference characteristic value comprises: In each IMF component signal, all sampling moments in a preset neighborhood window of each sampling moment are taken as neighborhood window moments; and signal value ranges of all neighborhood window moments corresponding to each sampling moment are normalized to determine a local fluctuation amplitude of each sampling moment. According to overall deviation conditions between the mean envelope line and the baseline at all neighborhood window moments, a local baseline drift degree of each sampling moment is determined. The product of the arc flash influence coefficient, the local fluctuation amplitude and the local baseline drift degree of each sampling moment is normalized to determine a corresponding electromagnetic interference characteristic value.

4. The anti-jamming connector monitoring method for automotive electronic systems according to claim 3, characterized in that, The acquisition process of the local baseline drift degree comprises: A difference between a value of the mean envelope line and a value of the baseline corresponding to each neighborhood window moment is taken as a corresponding instantaneous drift degree; and a local baseline drift degree of each sampling moment is determined according to a mean value of the instantaneous drift degrees of all neighborhood window moments.

5. The anti-tamper connector monitoring method for automotive electronic systems of claim 1, wherein, The acquisition process of the sensitivity weight comprises: In each IMF component signal, electromagnetic interference characteristic values of all sampling moments are arranged in time sequence and curve fitting is performed to determine an electromagnetic interference characteristic value curve; an aging accumulation amplitude is determined according to a variation trend of the electromagnetic interference characteristic values on the electromagnetic interference characteristic value curve; and a sensitivity weight of each IMF component signal is determined according to the aging accumulation amplitude and an initial intercept of the electromagnetic interference characteristic value curve; wherein, the aging accumulation amplitude and the initial intercept are in positive correlation with the sensitivity weight.

6. The anti-tamper connector monitoring method for automotive electronic systems of claim 5, wherein, The acquisition process of the aging accumulation amplitude comprises: A mean value of tangent slope values of all sampling moments on the electromagnetic interference characteristic value curve is taken as the aging accumulation amplitude.

7. The anti-jamming connector monitoring method for automotive electronic systems of claim 1, wherein, The acquisition process of the electromagnetic interference signal comprises: In each IMF component signal, a product of the electromagnetic interference characteristic value of each sampling moment and the sensitivity weight is positively mapped to determine an electromagnetic interference degree of each IMF component signal; and a weighted envelope line function corresponding to each IMF component signal is determined by weighting the mean envelope line function of each IMF component signal according to the electromagnetic interference degree. In the process of acquiring the IMF component signals and the residual signal by the empirical mode decomposition algorithm, the weighted envelope line function of each IMF component signal is substituted for the original mean envelope line function to perform the empirical mode decomposition, and the finally obtained residual signal is taken as the electromagnetic interference signal.

8. The anti-tamper connector monitoring method for automotive electronic systems of claim 1, wherein, The acquisition process of the corrected analog signal comprises: Subtracting the electromagnetic interference signal from the analog signal to be processed, to obtain a corrected analog signal.

Images