Vehicle failure diagnosis method and storage medium, vehicle, and electronic device
By collecting and analyzing the vehicle controller local area network, vibration and noise signals, the relationship between characteristic frequencies and amplitudes is determined, enabling early fault diagnosis of the vehicle's powertrain system. This solves the vehicle vibration and noise problem and improves vehicle reliability and user satisfaction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GREAT WALL MOTOR CO LTD
- Filing Date
- 2026-01-15
- Publication Date
- 2026-05-29
AI Technical Summary
Vibration and noise problems often occur in vehicles during use, which are difficult for users to detect in the early stages, leading to the expansion of potential faults and affecting the reliability and lifespan of the vehicle.
By collecting vehicle controller local area network signals, vehicle vibration signals, and noise signals, and performing spectrum analysis, the correspondence between characteristic frequencies and vibration amplitudes and noise levels is determined, enabling early fault diagnosis of the vehicle's powertrain system.
It improves the accuracy and efficiency of vehicle fault diagnosis, reduces the occurrence of unexpected faults, extends vehicle life, and enhances user satisfaction and overall reliability.
Smart Images
Figure CN122108630A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle technology, and in particular to a vehicle fault diagnosis method, a computer-readable storage medium, a vehicle, and an electronic device. Background Technology
[0002] Currently, complaints about vehicle vibration and noise are common during vehicle use. The root cause of these vibration and noise problems often points to malfunctions in certain components of the powertrain, chassis, body, or interior and exterior trim. Initially, the vibration and noise are usually minor and not easily noticed by users. As the vehicle is used, the malfunction gradually worsens, and by the time users become aware of it, it often results in significant damage and leads to user feedback and complaints. Reactively addressing these issues can also negatively impact the brand's image. Summary of the Invention
[0003] This application aims to at least partially address one of the technical problems in the related art. Therefore, the first objective of this application is to propose a vehicle fault diagnosis method that can detect potential faults in the vehicle's powertrain system earlier, facilitating preventative maintenance, reducing the occurrence of unexpected failures, thereby improving user satisfaction, overall vehicle reliability, and extending vehicle lifespan.
[0004] The second objective of this application is to provide a computer-readable storage medium.
[0005] The third objective of this application is to propose a vehicle.
[0006] The fourth objective of this application is to propose an electronic device.
[0007] To achieve the above objectives, a first aspect of this application proposes a vehicle fault diagnosis method, the method comprising: acquiring vehicle controller local area network signals, and acquiring vehicle vibration signals and noise signals; determining target characteristic frequencies of each powertrain system based on the vehicle controller local area network signals; performing spectral analysis on the vehicle vibration signals to determine a first correspondence between characteristic frequencies and vibration amplitudes, and performing spectral analysis on the noise signals to determine a second correspondence between characteristic frequencies and noise levels; determining a target vibration amplitude based on the target characteristic frequencies and the first correspondence, and / or determining a target noise level based on the target characteristic frequencies and the second correspondence; and performing vehicle fault diagnosis based on the target vibration amplitude and / or the target noise level.
[0008] According to the vehicle fault diagnosis method of this application, the following steps are taken: First, the vehicle controller local area network (VLAN) signal is collected, along with vehicle vibration and noise signals. Based on the VLAN signal, the target characteristic frequencies of each powertrain system are determined. Second, the vehicle vibration signals are subjected to spectral analysis to determine a first correspondence between the characteristic frequencies and vibration amplitudes. Third, the noise signals are subjected to spectral analysis to determine a second correspondence between the characteristic frequencies and noise levels. Finally, the target vibration amplitude is determined based on the target characteristic frequencies and the first correspondence, and / or the target noise level is determined based on the target characteristic frequencies and the second correspondence. Finally, vehicle fault diagnosis is performed based on the target vibration amplitude and / or the target noise level. Therefore, this method can detect potential faults in the vehicle's powertrain system earlier, facilitating preventative maintenance, reducing unexpected faults, thereby improving user satisfaction, overall vehicle reliability, and extending vehicle lifespan.
[0009] In addition, the vehicle fault diagnosis method according to the above embodiments of this application may also have the following additional technical features: According to one embodiment of this application, determining the target characteristic frequencies of each powertrain system of the vehicle based on the vehicle controller local area network signal includes: acquiring the vehicle's operating parameters based on the vehicle controller local area network signal, wherein the operating parameters include at least one of throttle opening, engine speed, engine torque, transmission speed, wheel speed, and vehicle speed; determining the target characteristic frequencies of each powertrain system of the vehicle based on the operating parameters and a preset mapping relationship, wherein the preset mapping relationship is used to indicate the relationship between the operating parameters and the characteristic frequencies of each powertrain system of the vehicle, and each powertrain system includes at least one of an engine system, a transmission system, a driveshaft system, and a wheel system.
[0010] According to one embodiment of this application, the step of performing spectrum analysis on the vehicle vibration signal to determine a first correspondence between characteristic frequency and vibration amplitude includes: performing a fast Fourier transform on the vehicle vibration signal to obtain a first spectrum, the first spectrum showing the amplitude corresponding to the characteristic frequency of different power transmission systems; determining the first correspondence based on the characteristic frequency and the amplitude, wherein the amplitude represents the vibration amplitude.
[0011] According to one embodiment of this application, the step of performing spectral analysis on the noise signal to determine a second correspondence between characteristic frequency and noise magnitude includes: performing a fast Fourier transform on the noise signal to obtain a second spectrum, the second spectrum showing the amplitude corresponding to the characteristic frequency of different power transmission systems; determining the second correspondence based on the characteristic frequency and the amplitude, wherein the amplitude represents the noise magnitude.
[0012] According to one embodiment of this application, the fault diagnosis of a vehicle based on the target vibration amplitude and / or the target noise level includes: obtaining the normal range of characteristic frequency vibration and the normal range of noise, wherein the normal range of characteristic frequency vibration and the normal range of noise are determined based on testing of the whole vehicle under different test conditions; if the target vibration amplitude of each powertrain system exceeds the normal range of vibration, and / or the target noise level exceeds the normal range of noise, determine that the corresponding powertrain system is faulty; if the vibration amplitude of each powertrain system is within the normal range of vibration and the noise level is within the normal range of noise, determine that each powertrain system is normal.
[0013] According to one embodiment of this application, the method further includes: when it is determined that there is a fault in the corresponding power transmission system, obtaining a first difference between the target vibration amplitude exceeding the upper limit of the normal range of the vibration and / or a second difference between the target noise magnitude exceeding the upper limit of the normal range of the noise; and determining a target diagnostic strategy based on the first difference and / or the second difference.
[0014] According to one embodiment of this application, determining the target diagnostic strategy based on the first difference and / or the second difference includes: issuing a fault reminder message to the driver based on a reminder device when the first difference is greater than a preset first difference threshold and / or the second difference is greater than a preset second difference threshold, wherein the reminder device includes at least one of a vehicle's display device, a speaker device, and a mobile device; and recording and storing the abnormal situation when the first difference is less than or equal to the preset first difference threshold and / or the second difference is less than or equal to the preset second difference threshold.
[0015] To achieve the above objectives, a second aspect of this application provides a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the vehicle fault diagnosis method described above.
[0016] The computer-readable storage medium according to the embodiments of this application implements the above-described vehicle fault diagnosis method during execution, which can detect potential faults in the vehicle powertrain system earlier, facilitate preventive maintenance, reduce the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability and extending vehicle life.
[0017] To achieve the above objectives, a vehicle is provided in a third aspect of this application, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described vehicle fault diagnosis method.
[0018] According to the embodiments of this application, by performing the above-described vehicle fault diagnosis method, potential faults in the vehicle's powertrain system can be detected earlier, which helps with preventive maintenance, reduces the occurrence of unexpected faults, and thus improves user satisfaction, overall vehicle reliability, and extends vehicle life.
[0019] To achieve the above objectives, an electronic device is proposed in the fourth aspect of this application, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described vehicle fault diagnosis method.
[0020] The electronic device according to the embodiments of this application, by performing the above-described vehicle fault diagnosis method, can detect potential faults in the vehicle powertrain system earlier, which helps preventive maintenance, reduces the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability and extending vehicle life.
[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0022] Figure 1 This is a flowchart of a vehicle fault diagnosis method according to an embodiment of this application.
[0023] Figure 2 This is a flowchart illustrating a specific example of a vehicle fault diagnosis method according to this application.
[0024] Figure 3 This is a block diagram of a vehicle according to an embodiment of this application.
[0025] Figure 4 This is a block diagram of an electronic device according to an embodiment of this application.
[0026] Figure 5 This is a block diagram of a vehicle fault diagnosis device according to an embodiment of this application. Detailed Implementation
[0027] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.
[0028] Current technologies for handling abnormal conditions inside vehicles involve placing sensors at specific locations to collect noise and vibration data, and then determining whether an anomaly has occurred at that location based on this data. However, this approach is limited to diagnosing anomalies at specific locations; for example, it focuses solely on handling anomalies in the rear axle assembly, including acquiring noise and vibration data, identifying the anomaly, determining the cause, and developing cause-based control strategies. Furthermore, once an anomaly is identified, the emphasis is on diagnosing the rear axle assembly anomaly and controlling the braking system based on the diagnostic results.
[0029] Therefore, this application proposes a vehicle fault diagnosis method that covers a wider range of diagnoses, including not only the rear axle assembly but also other power transmission systems such as the engine, transmission, driveshaft, and wheels. Furthermore, to reduce costs, it eliminates the need for numerous additional sensors. By integrating existing vehicle sensors, a simpler control program is sufficient to assess the overall vehicle fault condition and implement specific measures when vibration amplitude and noise levels exceed preset thresholds, enabling early diagnosis of potential vehicle faults. The entire process, from initial data acquisition (vehicle vibration and noise signals) to spectrum analysis, determining the correspondence between characteristic frequencies and vibration amplitude and noise levels, and finally formulating fault diagnosis and response strategies, embodies a systematic and integrated technological development path. This not only improves the accuracy and efficiency of fault diagnosis but also provides a scientific basis for vehicle maintenance and performance optimization.
[0030] The vehicle fault diagnosis method, computer-readable storage medium, vehicle, electronic device, and vehicle fault diagnosis apparatus proposed in this application are described below with reference to the accompanying drawings.
[0031] Figure 1 This is a flowchart of a vehicle fault diagnosis method according to an embodiment of this application.
[0032] like Figure 1 As shown, the vehicle fault diagnosis method of this application embodiment may include the following steps: S1 collects the vehicle controller local area network signal, and also collects the vehicle vibration signal and noise signal.
[0033] S2 determines the target characteristic frequency of each powertrain system based on the vehicle controller local area network signal.
[0034] S3 performs spectral analysis on the whole vehicle vibration signal to determine the first correspondence between the characteristic frequency and the vibration amplitude, and performs spectral analysis on the noise signal to determine the second correspondence between the characteristic frequency and the noise magnitude.
[0035] S4, determine the target vibration amplitude based on the target characteristic frequency and the first correspondence, and / or, determine the target noise magnitude based on the target characteristic frequency and the second correspondence.
[0036] S5, perform vehicle fault diagnosis based on target vibration amplitude and / or target noise level.
[0037] Specifically, during vehicle operation, CAN (Controller Area Network) signals and vehicle vibration and noise signals can be collected in real time. CAN is an automotive bus standard through which vehicle electronic control units send and receive signals, including but not limited to throttle opening, engine speed, torque, transmission speed, wheel speed, and vehicle speed. These CAN signals reflect key operating parameters of various vehicle systems and are crucial for monitoring vehicle status and diagnosing potential problems. Vibration signals can be acquired by accelerometers installed in key areas of the vehicle, such as near engine mounts or wheels. Noise signals can be obtained through cockpit microphones, which can be installed inside the cabin to record noise levels. These noises may originate from the engine, transmission, tires, or other vehicle components. Analyzing cabin noise helps assess vehicle comfort and identify potential noise-related faults. This provides comprehensive vehicle operating status data, laying the foundation for subsequent analysis and diagnosis, and enhancing the accuracy and reliability of fault diagnosis through multi-source data acquisition.
[0038] After acquiring the vehicle controller local area network (VLAN) signal, the target characteristic frequencies of each powertrain system can be determined. The powertrain system is a series of components in a vehicle responsible for transmitting power, including the engine, transmission, driveshaft, differential, and wheels. These components work together to transmit the power generated by the engine to the wheels, driving the vehicle forward. Target characteristic frequencies refer to the specific vibration frequencies expected to occur in each powertrain system during operation. These frequencies reflect the unique vibration characteristics of each system under its design and operating parameters. These frequencies are typically related to the vehicle's mechanical structure and operating characteristics, such as the engine's combustion frequency and the transmission's gear meshing frequency. For example, characteristic frequencies related to the powertrain system can be identified based on data acquired from the VLAN signal. For instance, engine speed can be directly used to calculate its dominant frequency (e.g., at an engine speed of 1500 RPM, the dominant frequency is 25 Hz). These frequencies will serve as a benchmark for subsequent vibration and noise analysis to identify anomalies.
[0039] After acquiring the vehicle's vibration and noise signals, spectral analysis can be performed on the vibration signals to determine the primary correspondence between characteristic frequencies and vibration amplitudes, and spectral analysis can be performed on the noise signals to determine the secondary correspondence between characteristic frequencies and noise levels. Accelerometers are installed in key parts of the vehicle (such as the engine, transmission, and wheels), and their output is an analog signal representing acceleration as a function of time. Microphones are installed in key locations inside the vehicle (such as near the driver's seat and passenger seats), and their output is an analog signal representing sound pressure level as a function of time.
[0040] For example, vibration and noise signals can be analyzed using the Short-Time Fourier Transform (SFT). The SFT is a time-frequency analysis method that divides a long-duration signal into multiple short-time segments and then performs a Fourier transform on each segment. This method is suitable for analyzing signal frequency variations over time. It decomposes the signal into different frequency components and identifies characteristic frequencies related to the vehicle's powertrain. For each identified characteristic frequency, the amplitude of that frequency component is measured. The amplitude corresponding to the vehicle vibration signal can be expressed as acceleration (g or m / s²), reflecting the intensity of the vibration. The amplitude corresponding to the noise signal can be expressed as sound pressure level (dB), reflecting the intensity of the noise.
[0041] It should be noted that vibration signals are collected from key parts of the vehicle (such as the engine, transmission, and wheels) using a whole-vehicle acceleration sensor. The collected analog vibration signals can be digitally processed, including amplification, filtering (removing noise and irrelevant frequency components), and sampling. By analyzing the preprocessed vibration signals, characteristic frequencies related to various vehicle systems are identified. This can be achieved through various signal processing techniques, such as using bandpass filters to extract signal components within a specific frequency range, or using wavelet transform to analyze the details of the signal at different frequencies. For each identified characteristic frequency, the vibration amplitude at that frequency is measured. The vibration amplitude can be the peak value, root mean square value, or other statistical measures representing the intensity of the vibration. The final mapping relationship is a dataset containing characteristic frequencies and their corresponding vibration amplitudes. This relationship can be expressed as: First mapping relationship = {(f1,A1),(f2,A2),…,(fn,A2)}, where fn represents the nth characteristic frequency, and An represents the vibration amplitude at the characteristic frequency fn, where n can be a positive integer.
[0042] Noise signals are collected within the vehicle cabin using microphones. The collected analog noise signals can also be digitally processed, including amplification, filtering, and sampling. By analyzing the pre-processed noise signals, characteristic frequencies associated with various vehicle systems are identified. This can be achieved, for example, by extracting signal components within a specific frequency range and analyzing the details of the signal at different frequencies. For each identified characteristic frequency, the noise level at that frequency is measured. Noise level is typically expressed in sound pressure level (dB), which can be obtained by calculating the root mean square value of the signal and converting it to dB. The resulting mapping is a dataset containing characteristic frequencies and their corresponding noise levels. This relationship can be expressed as: Second mapping = {(f1,N1),(f2,N2),…,(fn,Nn)}, where fn represents the nth characteristic frequency, and Nn represents the noise level at characteristic frequency fn, where n can be a positive integer.
[0043] For example, assuming the engine's characteristic frequency is identified as 25Hz, analysis of the accelerometer signal reveals a vibration amplitude of 0.5g at 25Hz. This indicates that the engine's vibration intensity is 0.5g at 25Hz. Similarly, assuming the transmission's characteristic frequency is identified as 50Hz, analysis of the microphone signal reveals a noise amplitude of 70dB at 50Hz. This indicates that the noise intensity inside the vehicle is 70dB at 50Hz. This method effectively monitors and analyzes vehicle vibration and noise, providing a scientific basis for vehicle maintenance and fault diagnosis.
[0044] After determining the first and second correspondences, the target vibration amplitude can be determined based on the target characteristic frequency and the first correspondence, or the target noise level can be determined based on the target characteristic frequency and the second correspondence, or both can be used simultaneously. In other words, the target vibration amplitude and target noise level at a specific characteristic frequency are determined using the established first correspondence between characteristic frequency and vibration amplitude, and the second correspondence between characteristic frequency and noise level. For example, for each target characteristic frequency, the vibration amplitude recorded in the first correspondence is looked up. For instance, if the target characteristic frequency is 25 Hz, the vibration amplitude corresponding to 25 Hz is found in the first correspondence, assumed to be 0.5 g. Similarly, for each target characteristic frequency, the noise level recorded in the second correspondence is looked up. For instance, for the same 25 Hz characteristic frequency, the second correspondence might show a noise level of 70 dB.
[0045] This allows for the assessment of a vehicle's health status and the diagnosis of potential faults using defined target vibration amplitude and target noise levels. For example, the vehicle's health status can be assessed based solely on the target vibration amplitude, or solely on the target noise level, or both simultaneously for a more accurate assessment. For instance, a fault diagnosis system can be pre-built based on expert knowledge and rules; by inputting the target vibration amplitude and target noise level into the system, it can provide fault causes and repair recommendations.
[0046] Therefore, by collecting the vehicle's CAN signal and performing spectrum analysis using the vehicle's vibration and noise signals to identify the characteristic frequencies of each powertrain system and determine its vibration amplitude and noise level, early diagnosis of potential vehicle faults can be achieved, improving the reliability and safety of vehicle operation, while optimizing maintenance plans, reducing maintenance costs, and enhancing passenger comfort.
[0047] According to one embodiment of this application, determining the target characteristic frequencies of each powertrain system of a vehicle based on vehicle controller local area network signals includes: acquiring vehicle operating parameters based on vehicle controller local area network signals, wherein the operating parameters include at least one of throttle opening, engine speed, engine torque, transmission speed, wheel speed, and vehicle speed; determining the target characteristic frequencies of each powertrain system of the vehicle based on the operating parameters and a preset mapping relationship, wherein the preset mapping relationship is used to indicate the relationship between the operating parameters and the characteristic frequencies of each powertrain system of the vehicle, and each powertrain system includes at least one of engine system, transmission system, driveshaft system, and wheel system.
[0048] Specifically, when determining the target characteristic frequencies of each powertrain system of a vehicle based on the vehicle controller local area network (VLAN) signals, the vehicle's operating parameters can be collected first, i.e., the real-time operating status of key vehicle components can be obtained. These statuses are crucial for subsequent characteristic frequency calculations. For example, at least one of the following operating parameters can be collected in real-time from the CAN bus: throttle opening: the position of the accelerator pedal, affecting the engine's fuel supply; engine speed: the speed of the engine crankshaft, usually expressed in revolutions per minute (rpm); engine torque: the rotational torque output by the engine, affecting the vehicle's acceleration performance; transmission speed: the speed of the transmission's input or output shaft, affecting power transmission efficiency; wheel speed: the speed of the wheels, directly related to vehicle speed and traction; and vehicle speed: the actual speed of the vehicle. These vehicle operating parameters provide comprehensive vehicle operating status data, providing fundamental information for subsequent characteristic frequency calculations and fault diagnosis.
[0049] Based on the collected operating parameters, the target characteristic frequencies of each powertrain system of the vehicle can be determined according to the operating parameters and preset mapping relationships. These frequencies serve as the benchmark for subsequent vibration and noise analysis. The preset mapping relationships indicate the relationship between the operating parameters and the characteristic frequencies of each powertrain system of the vehicle, which includes at least one of the engine system, transmission system, driveshaft system, and wheel system.
[0050] For example, a preset mapping relationship between operating parameters and characteristic frequencies can be established based on vehicle design parameters and historical data. This preset mapping relationship indicates the relationship between operating parameters and the characteristic frequencies of each powertrain system in the vehicle. After determining a certain operating parameter, the characteristic frequency of the corresponding powertrain system can be determined based on the preset mapping relationship. For example, the characteristic frequencies of each powertrain system include the engine's primary order, engine oil pump order, transmission gear order, drive shaft second order, drive shaft third order, and wheel first order, etc. The engine's primary order is the frequency directly related to the engine speed. For example, if the engine speed is 1500 RPM, then its primary order frequency is 1500 / 60 = 25 Hz. The engine oil pump order is the frequency related to the engine oil pump's speed; the oil pump's order frequency can be related to the oil pump's speed and number of teeth. The transmission gear order is the frequency related to the transmission gear meshing frequency. For example, if the transmission input shaft speed is 3000 RPM and the gear ratio is 2:1, then the output shaft speed is 1500 RPM, and the basic meshing frequency is 50 Hz. The second-order frequency of the driveshaft is related to its rotational frequency. For example, if the wheel speed is 1000 RPM, then the fundamental frequency of the driveshaft is 1000 / 60 ≈ 16.7 Hz, and the second-order frequency is twice that. The third-order frequency of the drive shaft is related to its rotational frequency. For example, if the driveshaft speed is 1200 RPM, then the fundamental frequency is 1200 / 60 = 20 Hz, and the third-order frequency is three times that. The first-order frequency of the wheel is related to its rotational frequency. For example, if the wheel speed is 800 RPM, then the fundamental frequency is 800 / 60 ≈ 13.3 Hz.
[0051] Therefore, through these steps, key information can be systematically extracted from the vehicle controller's local area network signals, and the target characteristic frequencies of each powertrain system can be calculated, providing a scientific basis for subsequent vibration and noise analysis and fault diagnosis. This method not only improves vehicle maintenance efficiency but also enhances vehicle safety and reliability.
[0052] According to one embodiment of this application, a spectrum analysis is performed on the vibration signal of the whole vehicle to determine a first correspondence between the characteristic frequency and the vibration amplitude, including: performing a fast Fourier transform on the vibration signal of the whole vehicle to obtain a first spectrum, the first spectrum showing the amplitude corresponding to the characteristic frequency of different power transmission systems; determining the first correspondence based on the characteristic frequency and the amplitude, wherein the amplitude represents the vibration amplitude.
[0053] Specifically, when performing spectral analysis on the vehicle vibration signal to determine the primary correspondence between characteristic frequencies and vibration amplitudes, a Fast Fourier Transform (FFT) can be performed on the vehicle vibration signal to obtain a first spectrum. Accelerometers can then be installed at key vehicle components (such as the engine, transmission, and wheels) to measure the vibration acceleration at those locations. A data acquisition system records the analog signals output by the accelerometers in real time. These analog signals are then converted to digital signals via an analog-to-digital converter (ADC) for subsequent processing. Digital filters are applied to remove noise or unwanted frequency components, retaining the frequency range relevant to the vehicle system vibration. Next, a Fast Fourier Transform (FFT) is performed on the preprocessed digital signal to convert the time-domain signal to a frequency-domain signal. The FFT result generates the first spectrum, displaying different characteristic frequency components and their corresponding amplitudes. Characteristic frequencies related to various powertrain systems of the vehicle are identified in the first spectrum; these frequencies are represented by peak values in the spectrum. For each identified characteristic frequency, its corresponding amplitude is measured. The amplitude represents the vibration intensity (vibration amplitude) at that frequency, usually expressed in units of acceleration (such as g or m / s²). Thus, based on the identified characteristic frequency and the measured amplitude, a first correspondence between the characteristic frequency and the vibration amplitude is established.
[0054] Assuming an accelerometer is installed in the engine area, the acquired signal is processed by FFT to obtain a spectrum. If a significant peak with an amplitude of 0.5 g is observed at 25 Hz, this indicates a vibration intensity of 0.5 g at 25 Hz (potentially the engine's dominant frequency). This establishes the first correspondence: {25 Hz -> 0.5 g}, meaning that at the characteristic frequency of 25 Hz, the vibration amplitude in the engine area is 0.5 g. Therefore, this method can establish a correspondence between characteristic frequencies and vibration amplitudes for various powertrain systems in a vehicle, providing data support for subsequent fault diagnosis and performance evaluation.
[0055] According to one embodiment of this application, performing spectral analysis on a noise signal to determine a second correspondence between characteristic frequencies and noise levels includes: performing a fast Fourier transform on the noise signal to obtain a second spectrum, the second spectrum showing the amplitude corresponding to the characteristic frequencies of different power transmission systems; and determining the second correspondence based on the characteristic frequencies and amplitudes, wherein the amplitude represents the noise level.
[0056] Specifically, when performing spectral analysis on the noise signal to determine the second correspondence between characteristic frequencies and noise levels, a Fast Fourier Transform (FFT) is performed on the noise signal to obtain a second spectrogram. Microphones can be installed at suitable locations within the vehicle cabin (such as near the driver or passenger seats) to capture noise signals inside the vehicle. A data acquisition system records the analog signals captured by the microphones in real time, and these signals change as the vehicle operates. The analog signals are then converted into digital signals for subsequent processing. Filters can be applied to remove noise or unwanted frequency components from the signal, retaining the frequency components relevant to the vehicle system noise. A Fast Fourier Transform is performed on the preprocessed digital signal to convert the time-domain signal into a frequency-domain signal. The FFT result generates the second spectrogram, with the horizontal axis representing characteristic frequencies (Hz) and the vertical axis representing the noise amplitude (usually expressed in dB as sound pressure level). In the second spectrogram, characteristic frequencies related to the vehicle's powertrain system (such as the engine, transmission, driveshaft, and wheels) are identified. These frequencies are generally represented by peaks in the spectrogram. For each identified characteristic frequency, its corresponding amplitude is measured. Amplitude represents the noise intensity at a specific frequency, usually expressed as sound pressure level (dB), thus establishing a second correspondence between the characteristic frequency and the noise magnitude based on the identified characteristic frequency and the measured amplitude.
[0057] Assuming a microphone is installed inside the vehicle cabin, the collected signal, after being processed by FFT, yields a spectrum. In this spectrum, a significant peak with an amplitude of 70 dB is observed at 25 Hz. This indicates a noise level of 70 dB at 25 Hz (potentially the engine's primary frequency). Therefore, a second correspondence can be established: {25 Hz -> 70 dB}. This means that at the characteristic frequency of 25 Hz, the noise level inside the vehicle is 70 dB. In this way, a correspondence between characteristic frequencies and noise levels can be established for each powertrain system of the vehicle, providing data support for subsequent fault diagnosis and performance evaluation. This method helps improve vehicle maintenance efficiency and enhances vehicle safety and reliability.
[0058] According to one embodiment of this application, vehicle fault diagnosis based on target vibration amplitude and / or target noise level includes: obtaining the normal range of characteristic frequency vibration and the normal range of noise, wherein the normal range of characteristic frequency vibration and the normal range of noise are determined based on testing of the whole vehicle under different test conditions; determining that the corresponding powertrain system has a fault when the target vibration amplitude of each powertrain system exceeds the normal range of vibration and / or the target noise level exceeds the normal range of noise; and determining that each powertrain system is normal when the target vibration amplitude of each powertrain system is within the normal range of vibration and the target noise level is within the normal range of noise.
[0059] Specifically, when diagnosing vehicle faults based on target vibration amplitude and / or target noise levels, the normal ranges for characteristic frequency vibration and noise can be obtained first. These normal ranges are determined based on testing the entire vehicle under different test conditions. For example, by testing the vehicle under different conditions (such as different speeds, loads, road conditions, etc.) and recording the characteristic frequency vibration amplitude and noise levels of each powertrain system during the test, the test data can be analyzed to determine the statistical distribution of vibration amplitude and noise levels, such as the mean, median, and standard deviation. Based on the statistical analysis results, the normal range for the characteristic frequency vibration amplitude and noise levels of each powertrain system can be set. For example, this range can be defined as the mean plus or minus a certain number of standard deviations.
[0060] The system monitors the target vibration amplitude and target noise level of the characteristic frequencies of each powertrain system during vehicle operation in real time. By comparing the target vibration amplitude with the normal vibration range, a fault in the corresponding powertrain system can be identified when the target vibration amplitude exceeds the normal range. Similarly, a fault in the corresponding powertrain system can be identified when the target noise level exceeds the normal noise range. Alternatively, both the target vibration amplitude and target noise level can be compared simultaneously; a fault in the corresponding powertrain system can be identified when both exceed the normal vibration and noise ranges. In other words, this could be due to factors such as wear and tear on components like bearings, gears, or belts from prolonged use, leading to increased vibration and noise; loosening of fasteners due to vibration; misalignment of components due to impact, causing abnormal vibration; or loss of balance in rotating components (such as wheels or drive shafts) due to impact or manufacturing defects, resulting in additional vibration and noise, thus exceeding the normal range.
[0061] By comparing the target vibration amplitude with the normal vibration range and the target noise level with the normal noise range, it can be determined that each power transmission system is normal if the target vibration amplitude and the target noise level are both within the normal range. In other words, this indicates that the various components of the power transmission system (such as the engine, transmission, and drive shaft) are operating smoothly without abnormal mechanical stress or damage. A noise level within the normal range means that the acoustic noise generated during system operation is within acceptable limits, and usually also indicates that there is no abnormal friction or impact within the system.
[0062] This allows for real-time monitoring of vehicle health, ensuring optimal vehicle operation and providing crucial decision support information for drivers and maintenance personnel.
[0063] According to one embodiment of this application, the vehicle fault diagnosis method further includes: when it is determined that there is a fault in the corresponding powertrain system, obtaining a first difference between the target vibration amplitude exceeding the upper limit of the normal vibration range and / or a second difference between the target noise magnitude exceeding the upper limit of the normal noise range; and determining a target diagnosis strategy based on the first difference and / or the second difference.
[0064] Specifically, the target vibration amplitude and target noise level of each powertrain system are monitored in real time, and the monitored target vibration amplitude and target noise level are compared with preset normal ranges. If at least one of the target vibration amplitude or target noise level exceeds the normal range, a fault can be determined in the corresponding powertrain system. If a fault is determined in the corresponding powertrain system, a first difference between the target vibration amplitude and the upper limit of the normal vibration range is obtained, and a target diagnostic strategy is determined based on the first difference. For example, the target diagnostic strategy can be determined through a pre-defined correspondence; for instance, the relationship between the first difference and the target diagnostic strategy is predetermined. Once the first difference is determined, the correspondence is directly invoked to determine the target diagnostic strategy.
[0065] Alternatively, a second difference value can be obtained where the target noise level exceeds the upper limit of the normal noise range, and the target diagnostic strategy can be determined based on this second difference value. For example, the target diagnostic strategy can be determined through a pre-defined correspondence, such as pre-determining the relationship between the second difference value and the target diagnostic strategy. Once the second difference value is determined, the correspondence can be directly invoked to determine the target diagnostic strategy. Alternatively, a first difference value can be obtained where the target vibration amplitude exceeds the upper limit of the normal vibration range, and a second difference value can be obtained where the target noise level exceeds the upper limit of the normal noise range. The target diagnostic strategy can then be determined based on both the first and second difference values.
[0066] In other words, the difference between the target vibration amplitude and the upper limit of the normal vibration range (first difference) can be calculated, and the difference between the target noise level and the upper limit of the normal noise range (second difference) can be calculated. By analyzing the first and second differences, the severity of the fault can be assessed. Based on the magnitude of the difference, the following diagnostic strategies can be determined: if the difference is small, routine inspection or simple adjustments may be sufficient; if the difference is moderate, more detailed diagnosis may be required, such as component testing or replacement; if the difference is large, immediate overhaul or replacement of critical components may be necessary.
[0067] Therefore, this method allows for a more scientific assessment of the health status of a vehicle's powertrain system and the development of reasonable maintenance strategies, thereby improving vehicle operating efficiency and safety.
[0068] According to one embodiment of this application, determining a target diagnostic strategy based on a first difference and / or a second difference includes: when the first difference is greater than a preset first difference threshold and / or the second difference is greater than a preset second difference threshold, issuing a fault reminder message to the driver based on a reminder device, wherein the reminder device includes at least one of a vehicle's display device, a speaker device, and a mobile device; and when the first difference is less than or equal to the preset first difference threshold and / or the second difference is less than or equal to the preset second difference threshold, recording and storing the abnormal situation. The first preset difference threshold and the preset second difference threshold can be determined according to actual conditions. The first preset difference threshold can be used to determine the degree to which the vibration amplitude exceeds the normal range, and the second difference threshold can be used to determine the degree to which the noise level exceeds the normal range.
[0069] Specifically, when determining the target diagnostic strategy based on a first difference and / or a second difference, or when determining the target diagnostic strategy based on both the first and second differences, the magnitude of the first difference relative to a preset first difference threshold is judged; or the magnitude of the second difference relative to a preset second difference threshold is judged; or the magnitude relationship between the first difference and the preset first difference threshold, and the second difference and the preset second difference threshold are judged simultaneously. If the first difference is greater than the preset first difference threshold, it indicates that the target vibration amplitude significantly exceeds the upper limit of the normal range. A fault warning message can be issued to the driver based on a warning device, which includes at least one of the vehicle's display device, speaker device, and mobile device. That is, for situations severely exceeding the safe range, immediate action may be necessary, such as advising the driver to stop and inspect the vehicle or contact a service station as soon as possible. If the first difference is less than or equal to the preset first difference threshold, it indicates that the target vibration amplitude only slightly exceeds the upper limit of the normal range. In this case, the abnormality can be recorded and stored. The relevant information can be retrieved using a diagnostic tool when the user brings the vehicle in for maintenance. Furthermore, the recorded abnormality should be continuously monitored to observe whether there is a worsening trend.
[0070] Similarly, if the second difference is greater than a preset second difference threshold, it indicates that the target noise level significantly exceeds the upper limit of the normal range. A fault warning message can be issued to the driver based on a warning device, which includes at least one of the vehicle's display device, speaker device, and mobile device. That is, for situations severely exceeding the safe range, immediate action may be necessary, such as advising the driver to stop and check the vehicle as soon as possible or contact a service station. If the first difference is less than or equal to a preset first difference threshold, it indicates that the target noise level only slightly exceeds the upper limit of the normal range. In this case, the abnormality can be recorded and stored. The relevant information can be retrieved using a diagnostic tool when the user brings the vehicle in for maintenance. Furthermore, the recorded abnormality should be continuously monitored to observe whether there is a worsening trend.
[0071] Alternatively, if the first difference is greater than a preset first difference threshold and the second difference is greater than a preset second difference threshold, it indicates that both the target vibration amplitude and the target noise exceed their respective upper limits of normal range by a significant margin. In this case, a fault warning message can be issued to the driver based on a warning device, which includes at least one of the vehicle's display device, speaker device, and mobile device. That is, for situations that seriously exceed the safe range, immediate action may be required, such as advising the driver to stop and check as soon as possible or contact a service station. If the first difference is less than or equal to a preset first difference threshold and the second difference is less than or equal to a preset second difference threshold, it indicates that the target vibration amplitude and the target noise are only slightly beyond the upper limit of normal range. In this case, the abnormal situation can be recorded and stored, and the relevant information can be read using a diagnostic tool when the user brings the vehicle in for maintenance. The recorded abnormal situation should be continuously monitored to observe whether there is a worsening trend.
[0072] For example, vehicle display devices include the instrument panel and central control screen. The instrument panel can display various warning lights or information, such as "Check engine" or "Repair transmission," while the central control screen can display more detailed fault information or prompts. Speaker equipment consists of in-vehicle speakers, which can be used to play voice warnings, such as "Please note, abnormal vibration detected in the vehicle." Mobile devices include smartphones or tablets. Through vehicle-smartphone connectivity, fault information can be pushed to the owner's smartphone application, such as via Bluetooth or the vehicle's infotainment system. The comprehensive use of these alert devices ensures that the driver is aware of vehicle malfunctions immediately and can take appropriate measures, thereby improving vehicle reliability and safety.
[0073] Therefore, through real-time monitoring and comparison, fault alerts can be promptly issued to the driver, improving driving safety. By recording and analyzing abnormal situations, preventative maintenance can be performed to avoid potential serious malfunctions. In this way, the vehicle's health status can be monitored in real time, ensuring that problems are resolved before they become serious, thereby improving the overall performance of the vehicle and passenger comfort.
[0074] The following is combined with Figure 2 The method described in this application is used to describe the method.
[0075] As a specific example, taking fault diagnosis based on both target vibration amplitude and target noise simultaneously as an example, the vehicle fault diagnosis method of this application may include the following steps: S101 collects the vehicle controller local area network signals, as well as the vehicle vibration and noise signals.
[0076] S102, based on the vehicle controller local area network signal, collects the vehicle's operating parameters, including at least one of throttle opening, engine speed, engine torque, transmission speed, wheel speed and vehicle speed.
[0077] S103, determine the target characteristic frequency of each power transmission system of the vehicle based on the operating parameters and the preset mapping relationship, wherein the preset mapping relationship is used to indicate the relationship between the operating parameters and the characteristic frequencies of each power transmission system of the vehicle, and each power transmission system includes at least one of the engine system, transmission system, drive shaft system and wheel system.
[0078] S104, perform a fast Fourier transform on the whole vehicle vibration signal to obtain a first spectrum, determine the first correspondence based on the characteristic frequency and amplitude, and perform a fast Fourier transform on the noise signal to obtain a second spectrum, determine the second correspondence based on the characteristic frequency and amplitude.
[0079] S105, determine the target vibration amplitude based on the target characteristic frequency and the first correspondence, and determine the target noise level based on the target characteristic frequency and the second correspondence.
[0080] S106, obtain the normal range of characteristic frequency vibration and the normal range of noise.
[0081] S107, determine whether the target vibration amplitude of each power transmission system exceeds the normal range of vibration, and whether the target noise level exceeds the normal range of noise. If yes, proceed to step S108; if no, proceed to step S112.
[0082] S108 indicates that a fault exists in the corresponding powertrain system.
[0083] S109, obtain the first difference between the target vibration amplitude exceeding the upper limit of the normal vibration range and the second difference between the target noise magnitude exceeding the upper limit of the normal noise range.
[0084] S110, determine whether the first difference is greater than a preset first difference threshold and whether the second difference is greater than a preset second difference threshold. If yes, proceed to step S111; if no, proceed to step S113.
[0085] S111, based on the reminder device, sends a fault reminder message to the driver.
[0086] S112, confirm that all power transmission systems are functioning normally.
[0087] S113, record and store abnormal situations.
[0088] In summary, the vehicle fault diagnosis method according to the embodiments of this application collects vehicle controller local area network signals, vibration signals, and noise signals. Based on the vehicle controller local area network signals, it determines the target characteristic frequencies of each powertrain system. It performs spectral analysis on the vehicle vibration signals to determine a first correspondence between characteristic frequencies and vibration amplitudes, and performs spectral analysis on the noise signals to determine a second correspondence between characteristic frequencies and noise levels. Based on the target characteristic frequencies and the first correspondence, it determines the target vibration amplitude, and / or, based on the target characteristic frequencies and the second correspondence, it determines the target noise level. Finally, it performs vehicle fault diagnosis based on the target vibration amplitude and / or the target noise level. Therefore, this method can detect potential faults in the vehicle's powertrain system earlier, facilitating preventative maintenance, reducing the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability, and extending vehicle lifespan.
[0089] Corresponding to the above embodiments, this application also proposes a computer-readable storage medium.
[0090] The computer-readable storage medium of this application embodiment stores a program that, when executed by a processor, implements the vehicle fault diagnosis method described above.
[0091] According to the computer-readable storage medium of the embodiments of this application, by executing the above-described vehicle fault diagnosis method, potential faults in the vehicle powertrain system can be detected earlier, which helps preventive maintenance, reduces the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability and extending vehicle life.
[0092] Corresponding to the above embodiments, this application also proposes a vehicle.
[0093] like Figure 3As shown, the vehicle 200 in this embodiment may include: a memory 210, a processor 220, and a program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, it implements the above-described vehicle fault diagnosis method.
[0094] According to the embodiments of this application, by performing the above-described vehicle fault diagnosis method, potential faults in the vehicle's powertrain system can be detected earlier, which helps with preventive maintenance, reduces the occurrence of unexpected faults, and thus improves user satisfaction, overall vehicle reliability, and extends vehicle life.
[0095] Corresponding to the above embodiments, this application also proposes an electronic device.
[0096] like Figure 4 As shown, the electronic device 300 of this application embodiment may include: a memory 310, a processor 320, and a program stored in the memory 310 and executable on the processor 320. When the processor 320 executes the program, it implements the above-described vehicle fault diagnosis method.
[0097] The electronic device according to the embodiments of this application, by performing the above-described vehicle fault diagnosis method, can detect potential faults in the vehicle powertrain system earlier, which helps preventive maintenance, reduces the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability and extending vehicle life.
[0098] Corresponding to the above embodiments, this application also proposes a vehicle fault diagnosis device.
[0099] like Figure 5 As shown, the vehicle fault diagnosis device 100 of this application embodiment includes: a data acquisition module 110, a first determination module 120, a second determination module 130, a third determination module 140, and a diagnosis module 150.
[0100] The acquisition module 110 is used to acquire vehicle controller local area network signals, as well as vehicle vibration and noise signals. The first determination module 120 is used to determine the target characteristic frequency of each powertrain system based on the vehicle controller local area network signals. The second determination module 130 is used to perform spectral analysis on the vehicle vibration signals to determine a first correspondence between characteristic frequencies and vibration amplitudes, and to perform spectral analysis on the noise signals to determine a second correspondence between characteristic frequencies and noise levels. The third determination module 140 is used to determine the target vibration amplitude based on the target characteristic frequency and the first correspondence, and / or, based on the target characteristic frequency and the second correspondence, to determine the target noise level. The diagnostic module 150 is used to determine the fault status of each powertrain system based on the target vibration frequency and / or the target noise level.
[0101] According to one embodiment of this application, the first determining module 120 determines the target characteristic frequencies of each powertrain system of the vehicle based on the vehicle controller local area network signal. Specifically, it is used to: collect the vehicle's operating parameters based on the vehicle controller local area network signal, wherein the operating parameters include at least one of throttle opening, engine speed, engine torque, transmission speed, wheel speed, and vehicle speed; and determine the target characteristic frequencies of each powertrain system of the vehicle based on the operating parameters and a preset mapping relationship, wherein the preset mapping relationship is used to indicate the relationship between the operating parameters and the characteristic frequencies of each powertrain system of the vehicle, and each powertrain system includes at least one of the engine system, transmission system, driveshaft system, and wheel system.
[0102] According to one embodiment of this application, the second determining module 130 performs spectrum analysis on the vehicle vibration signal to determine a first correspondence between the characteristic frequency and the vibration amplitude. Specifically, it is used to: perform a fast Fourier transform on the vehicle vibration signal to obtain a first spectrum diagram, which displays the amplitude corresponding to the characteristic frequency of different power transmission systems; and determine the first correspondence based on the characteristic frequency and the amplitude, wherein the amplitude represents the vibration amplitude.
[0103] According to one embodiment of this application, the third determining module 140 performs spectral analysis on the noise signal to determine a second correspondence between the characteristic frequency and the noise magnitude. Specifically, it is used to: perform a fast Fourier transform on the noise signal to obtain a second spectrum, which shows the amplitude corresponding to the characteristic frequency of different power transmission systems; and determine the second correspondence based on the characteristic frequency and the amplitude, wherein the amplitude represents the noise magnitude.
[0104] According to one embodiment of this application, the diagnostic module 150 performs fault diagnosis on the vehicle based on the target vibration amplitude and / or the target noise level. Specifically, it is used to: obtain the normal range of characteristic frequency vibration and the normal range of noise, wherein the normal range of characteristic frequency vibration and the normal range of noise are determined based on the vehicle under different test conditions; if the target vibration amplitude of each powertrain system exceeds the normal vibration range, and / or the target noise level exceeds the normal noise range, it determines that the corresponding powertrain system is faulty; if the target vibration amplitude of each powertrain system is within the normal vibration range and the target noise level is within the normal noise range, it determines that each powertrain system is normal.
[0105] According to one embodiment of this application, the diagnostic module 150 is further configured to: when it is determined that there is a fault in the corresponding power transmission system, obtain a first difference between the target vibration amplitude exceeding the upper limit of the normal range of vibration and / or a second difference between the target noise magnitude exceeding the upper limit of the normal range of noise; and determine a target diagnostic strategy based on the first difference and / or the second difference.
[0106] According to one embodiment of this application, the diagnostic module 150 determines a target diagnostic strategy based on a first difference and / or a second difference, specifically for: issuing a fault reminder message to the driver based on a reminder device when the first difference is greater than a preset first difference threshold and / or the second difference is greater than a preset second difference threshold, wherein the reminder device includes at least one of a vehicle's display device, a speaker device, and a mobile device; and recording and storing the abnormal situation when the first difference is less than or equal to the preset first difference threshold and / or the second difference is less than or equal to the preset second difference threshold.
[0107] It should be noted that for details not disclosed in the vehicle fault diagnosis device of this application embodiment, please refer to the details disclosed in the vehicle fault diagnosis method of this application embodiment, which will not be repeated here.
[0108] According to the vehicle fault diagnosis device of this application embodiment, the acquisition module is used to acquire vehicle controller local area network signals, and to acquire vehicle vibration signals and noise signals. The first determination module is used to determine the target characteristic frequency of each powertrain system based on the vehicle controller local area network signals. The second determination module is used to perform spectrum analysis on the vehicle vibration signals to determine a first correspondence between the characteristic frequency and the vibration amplitude, and to perform spectrum analysis on the noise signals to determine a second correspondence between the characteristic frequency and the noise level. The third determination module is used to determine the target vibration amplitude based on the target characteristic frequency and the first correspondence, and / or, to determine the target noise level based on the target characteristic frequency and the second correspondence. The diagnosis module is used to determine the fault condition of each powertrain system based on the target vibration frequency and / or the target noise level. Therefore, this device can detect potential faults in the vehicle powertrain system earlier, which helps in preventative maintenance, reduces the occurrence of unexpected faults, thereby improving user satisfaction, overall vehicle reliability, and extending vehicle life.
[0109] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0110] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0111] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0112] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0113] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.
[0114] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.
Claims
1. A vehicle fault diagnosis method, characterized in that, The method includes: Collect vehicle controller local area network signals, and collect vehicle vibration and noise signals; The target characteristic frequencies of each powertrain system are determined based on the local area network signals of the vehicle controller. The vibration signal of the whole vehicle is subjected to spectral analysis to determine the first correspondence between the characteristic frequency and the vibration amplitude, and the noise signal is subjected to spectral analysis to determine the second correspondence between the characteristic frequency and the noise magnitude. The target vibration amplitude is determined based on the target characteristic frequency and the first correspondence, and / or the target noise magnitude is determined based on the target characteristic frequency and the second correspondence; Vehicle fault diagnosis is performed based on the target vibration amplitude and / or the target noise level.
2. The vehicle fault diagnosis method according to claim 1, characterized in that, The determination of the target characteristic frequencies of each powertrain system of the vehicle based on the vehicle controller local area network signal includes: The vehicle's operating parameters are collected based on the vehicle controller local area network signal, wherein the operating parameters include at least one of throttle opening, engine speed, engine torque, transmission speed, wheel speed and vehicle speed; The target characteristic frequencies of each powertrain system of the vehicle are determined based on the operating parameters and the preset mapping relationship, wherein the preset mapping relationship is used to indicate the relationship between the operating parameters and the characteristic frequencies of each powertrain system of the vehicle, and each powertrain system includes at least one of the engine system, transmission system, driveshaft system and wheel system.
3. The vehicle fault diagnosis method according to claim 1, characterized in that, The step of performing spectral analysis on the vehicle vibration signal to determine the first correspondence between characteristic frequencies and vibration amplitudes includes: The vehicle vibration signal is subjected to a fast Fourier transform to obtain a first spectrum, which shows the amplitude corresponding to the characteristic frequency of different power transmission systems. The first correspondence is determined based on the characteristic frequency and the amplitude, wherein the amplitude represents the vibration amplitude.
4. The vehicle fault diagnosis method according to claim 1, characterized in that, The step of performing spectral analysis on the noise signal to determine a second correspondence between characteristic frequencies and noise levels includes: The noise signal is subjected to a fast Fourier transform to obtain a second spectrum, which shows the amplitude corresponding to the characteristic frequency of different power transmission systems. The second correspondence is determined based on the characteristic frequency and the amplitude, wherein the amplitude represents the noise level.
5. The vehicle fault diagnosis method according to claim 1, characterized in that, The fault diagnosis of the vehicle based on the target vibration amplitude and / or the target noise level includes: Obtain the normal range of characteristic frequency vibration and the normal range of noise, wherein the normal range of characteristic frequency vibration and the normal range of noise are determined based on the testing of the whole vehicle under different test conditions. If, in any of the power transmission systems, the target vibration amplitude exceeds the normal range of the vibration, and / or the target noise level exceeds the normal range of the noise, it is determined that the corresponding power transmission system has a fault. If the target vibration amplitude corresponding to each power transmission system is within the normal range of the vibration and the target noise level is within the normal range of the noise, then each power transmission system is determined to be normal.
6. The vehicle fault diagnosis method according to claim 5, characterized in that, The method further includes: If a fault is found in the corresponding power transmission system, a first difference value is obtained where the target vibration amplitude exceeds the upper limit of the normal range of the vibration and / or a second difference value is obtained where the target noise magnitude exceeds the upper limit of the normal range of the noise. The target diagnostic strategy is determined based on the first difference and / or the second difference.
7. The vehicle fault diagnosis method according to claim 6, characterized in that, The method for determining the target diagnostic strategy based on the first difference and / or the second difference includes: If the first difference is greater than a preset first difference threshold and / or the second difference is greater than a preset second difference threshold, a fault reminder message is issued to the driver based on the reminder device, wherein the reminder device includes at least one of the vehicle's display device, speaker device, and mobile device; If the first difference is less than or equal to a preset first difference threshold and / or the second difference is less than or equal to a preset second difference threshold, the abnormal situation is recorded and stored.
8. A computer-readable storage medium, characterized in that, It stores a program that, when executed by a processor, implements the vehicle fault diagnosis method according to any one of claims 1-7.
9. A vehicle, characterized in that, include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the vehicle fault diagnosis method according to any one of claims 1-7.
10. An electronic device, characterized in that, include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the vehicle fault diagnosis method according to any one of claims 1-7.