Abnormal noise detection method, device, storage medium, vehicle and program product

Abstract

The present disclosure relates to an abnormal noise detection method, device, storage medium, vehicle and program product, and relates to the field of vehicle technology; the abnormal noise detection method includes obtaining an audio signal corresponding to the motor drive system of the vehicle; determining the abnormal noise type of the motor drive system and the abnormal noise component of the motor drive system according to the audio signal, and the abnormal noise type is used to characterize the type of abnormal audio signal in the audio signal. This technical solution does not need to collect the vibration signal of the motor drive system, and abnormal noise detection can be achieved based on the audio signal, which can reduce the hardware cost of abnormal noise detection; and the analysis or processing of the audio signal is relatively simple, which can improve the efficiency of abnormal noise detection.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle technology, and in particular to an abnormal noise detection method, device, storage medium, vehicle and program product. Background Art

[0002] As vehicle technology develops, electric vehicles also develop. The motor drive system of an electric vehicle may produce abnormal noises during its service life, which may correspond to some kind of fault in the motor drive system. Therefore, it is necessary to perform abnormal noise detection on the motor drive system in order to determine the cause of the fault in the motor drive system. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present disclosure provides an abnormal noise detection method, device, storage medium, vehicle and program product.

[0004] According to a first aspect of an embodiment of the present disclosure, there is provided an abnormal noise detection method, comprising acquiring an audio signal corresponding to a motor drive system of a vehicle; determining an abnormal noise type of the motor drive system and abnormal noise components of the motor drive system based on the audio signal, the abnormal noise type being used to characterize the type of abnormal audio signal in the audio signal.

[0005] Optionally, determining the abnormal noise type of the motor drive system and the abnormal noise component of the motor drive system based on the audio signal includes: performing abnormal audio signal detection on the audio signal to determine the abnormal noise type; determining audio features of the audio signal based on the abnormal noise type, different abnormal noise types correspond to different audio features; and determining the abnormal noise component based on the audio features.

[0006] Optionally, performing abnormal audio signal detection on the audio signal to determine the type of abnormal sound includes: performing impact signal detection on the audio signal to obtain an impact signal detection result, and the impact signal detection result is used to characterize whether the audio signal includes an impact signal; if the impact signal detection result characterizes that the audio signal includes an impact signal, determining that the type of abnormal sound is an impact abnormal sound; if the impact signal detection result characterizes that the audio signal does not include an impact signal, determining that the type of abnormal sound is a howling abnormal sound.

[0007] Optionally, determining the audio feature of the audio signal according to the abnormal sound type includes: if the abnormal sound type is an impact abnormal sound, determining the impact signal frequency of the audio signal; if the abnormal sound type is a howling abnormal sound, determining the order corresponding to the audio signal.

[0008] Optionally, the abnormal sound detection method also includes: acquiring a preset spectrum and the rotational speed of the motor drive system, the preset spectrum being the spectrum corresponding to a normal audio signal; correspondingly, determining the order corresponding to the audio signal includes: determining the spectrum corresponding to the audio signal; determining the abnormal sound frequency according to the spectrum corresponding to the audio signal and the preset spectrum; determining the order corresponding to the audio signal according to the abnormal sound frequency and the rotational speed.

[0009] Optionally, determining the abnormal sound component based on the audio feature includes: obtaining a preset correspondence relationship, the preset correspondence relationship including multiple preset audio features and the abnormal sound components corresponding to the multiple preset audio features respectively; determining a target audio feature that matches the audio feature from the multiple preset audio features; and determining the abnormal sound component corresponding to the target audio feature as the abnormal sound component.

[0010] Optionally, the audio feature is the impulse signal frequency of the audio signal or the order corresponding to the audio signal, and the preset correspondence includes a first preset correspondence and a second preset correspondence, the first preset correspondence includes multiple preset impulse signal frequencies and abnormal sound components corresponding to the multiple preset impulse signal frequencies, and the second preset correspondence includes multiple preset orders and abnormal sound components corresponding to the multiple preset orders.

[0011] Optionally, the method of obtaining an audio signal corresponding to the motor drive system of the vehicle includes: in response to receiving an abnormal sound detection request triggered by a user, outputting a prompt message, wherein the prompt message is used to prompt the user to record an audio signal for abnormal sound detection; in response to receiving an audio recording request triggered by a user, starting to record audio data for the motor drive system; in response to receiving an end recording request triggered by a user, ending the recording of audio data for the motor drive system, and generating the audio signal based on the recorded audio data.

[0012] Optionally, the abnormal noise detection method further includes: if the abnormal noise type is a target abnormal noise type and the abnormal noise component is a target abnormal noise component, obtaining preset abnormal noise data, the preset abnormal noise data including abnormal noise levels corresponding to multiple vehicles of the same type; determining the abnormal noise level of the vehicle according to the volume of the audio signal; determining the abnormality ranking of the vehicle among vehicles of the same type according to the abnormal noise level of the vehicle and the preset abnormal noise data; and outputting the abnormal noise type, the abnormal noise component and the abnormality ranking.

[0013] Optionally, the target abnormal sound type is a howling abnormal sound, and the target abnormal sound component is a motor or a reducer.

[0014] According to a second aspect of an embodiment of the present disclosure, there is provided an abnormal sound detection device, comprising: an acquisition module, configured to acquire an audio signal corresponding to a motor drive system of a vehicle; a detection module, configured to determine an abnormal sound type of the motor drive system and abnormal sound components of the motor drive system based on the audio signal, wherein the abnormal sound type is used to characterize the type of abnormal audio signal in the audio signal.

[0015] According to a third aspect of an embodiment of the present disclosure, a vehicle is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to: execute the abnormal sound detection method as described in the first aspect.

[0016] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the abnormal sound detection method as described in the first aspect is implemented.

[0017] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including a computer program, which implements the abnormal sound detection method described in the first aspect when executed by a processor.

[0018] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0019] By acquiring the audio signal of the motor drive system of the vehicle, based on the audio signal, the abnormal sound type of the motor drive system and the abnormal sound component of the motor drive system are determined, wherein the abnormal sound type can characterize the type of abnormal audio signal in the audio signal, and the abnormal sound component can be used to locate the specific component of the motor drive system that produces the abnormal sound. Therefore, the technical solution does not need to collect the vibration signal of the motor drive system, and can realize abnormal sound detection based on the audio signal, which can reduce the hardware cost of abnormal sound detection; and the analysis or processing of the audio signal is relatively simple, which can improve the efficiency of abnormal sound detection.

[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0022] Figure 1 The figure is a flow chart of an abnormal sound detection method according to an exemplary embodiment.

[0023] Figure 2 The figure is a schematic diagram of a fault detection process according to an exemplary embodiment.

[0024] Figure 3 The figure is a schematic diagram of a background calculation process according to an exemplary embodiment.

[0025] Figure 4 The figure is a block diagram of an abnormal sound detection device according to an exemplary embodiment.

[0026] Figure 5 is a block diagram of a vehicle according to an exemplary embodiment.

[0027] Figure 6 The invention is a block diagram showing a device for implementing an abnormal sound detection method according to an exemplary embodiment.

[0028] Figure 7 It is a block diagram of another device for implementing an abnormal sound detection method according to an exemplary embodiment. DETAILED DESCRIPTION

[0029] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0030] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0031] As vehicle technology develops, electric vehicles also develop. The motor drive system of an electric vehicle may produce abnormal noises during its service life, which may correspond to some kind of failure in the motor drive system. In this case, the owner may complain; or it may cause safety issues.

[0032] Therefore, it is necessary to detect abnormal noises in the motor drive system in order to determine the cause of the failure of the motor drive system, and then guide the car owner to perform after-sales repairs to avoid safety problems or other losses.

[0033] In the related art, a vibration sensor is arranged on the motor drive system of the electric vehicle, and the abnormal noise fault detection of the electric vehicle is performed by collecting the vibration signal of the vibration sensor. This technical solution requires the introduction of more hardware such as vibration sensors, and the hardware cost is relatively high, so the application rate is not high.

[0034] In addition, when abnormal noise fault detection is performed based on vibration signals, a trained neural network model is usually used to compare and analyze the signal and output the abnormal noise fault type. This detection method requires big data training, which is difficult and difficult to detect abnormal noise fault types that have never appeared.

[0035] Based on this, the embodiment of the present disclosure provides a technical solution, which does not need to collect the vibration signal of the motor drive system, and can realize abnormal sound detection based on the audio signal, thereby reducing the hardware cost of abnormal sound detection; and the analysis or processing of the audio signal is relatively simple, which can improve the efficiency of abnormal sound detection.

[0036] In the embodiment of the present disclosure, the abnormal noise generated by the motor drive system is detected, and this abnormal noise detection can also be regarded as the fault detection of the motor drive system. Therefore, the abnormal noise detection result finally obtained can also be regarded as the fault detection result.

[0037] In the disclosed embodiment, the abnormal noise detection of the motor drive system can be realized by the vehicle's onboard system; the abnormal noise detection of the motor drive system can be realized by the terminal; or the abnormal noise detection of the motor drive system can be realized by the cloud. Regarding the cloud, it can be used as a cloud service platform for the vehicle system. Regarding the terminal, it can be various electronic devices.

[0038] It can be understood that if abnormal sound detection is implemented by a terminal or a cloud, the terminal or the cloud can establish a data transmission link with the vehicle system to obtain the data required for abnormal sound detection.

[0039] Figure 1 is a flow chart of an abnormal sound detection method according to an exemplary embodiment. Figure 1 , the abnormal sound detection method comprises:

[0040] Step S11, obtaining an audio signal corresponding to the motor drive system of the vehicle.

[0041] Step S12: determining the abnormal sound type of the motor drive system and the abnormal sound component of the motor drive system according to the audio signal, wherein the abnormal sound type is used to characterize the type of abnormal audio signal in the audio signal.

[0042] In the embodiment of the present disclosure, the vehicle may be an electric vehicle including a motor drive system.

[0043] In step S11 , the audio signal corresponding to the motor drive system may be an audio signal collected when an abnormal sound exists in the motor drive system.

[0044] In some embodiments, the vehicle includes a microphone, through which the audio signal corresponding to the motor drive system can be collected. It is understandable that a microphone is usually provided inside the vehicle, so there is no need to increase the hardware cost.

[0045] In some embodiments, the microphone can be controlled by the vehicle system to regularly collect audio signals of the motor drive system to obtain audio signals corresponding to the motor drive system. Accordingly, the vehicle system regularly detects abnormal sounds of the motor drive system. In this embodiment, the audio signal in step S11 can be an audio signal collected by the microphone during the current abnormal sound detection cycle.

[0046] In some embodiments, abnormal noise detection of the motor drive system can be triggered by the car owner, and thus, audio signal collection by the microphone also needs to be triggered by the car owner.

[0047] Therefore, as an optional implementation, step S11 includes: in response to receiving an abnormal sound detection request triggered by a user, outputting a prompt message, wherein the prompt message is used to prompt the user to record an audio signal for abnormal sound detection; in response to receiving an audio recording request triggered by a user, starting to record audio data for the motor drive system; in response to receiving an end recording request triggered by a user, ending the recording of audio data for the motor drive system, and generating an audio signal based on the recorded audio data.

[0048] In some embodiments, an interactive interface may be displayed on a display device of the vehicle system, wherein the interactive interface includes an abnormal sound detection request trigger control, and a user (vehicle owner) may trigger an abnormal sound detection request by performing a trigger operation on the trigger control.

[0049] In some embodiments, the user can also trigger an abnormal sound detection request through a voice command. For example, the user's terminal (mobile phone) is connected to the vehicle system, and the user can send a voice command to the terminal's artificial intelligence tool, and then the terminal analyzes the voice command and triggers an abnormal sound detection request to the vehicle system based on the analysis result.

[0050] Thus, when an abnormal sound detection request is received, a pre-configured prompt message may be output, for example, a voice prompt message or a text prompt message displayed on a display device of the vehicle system, which may remind the user that if abnormal sound detection is required, an audio signal recording is required.

[0051] After the prompt information is output, if the abnormal sound of the motor drive system still exists, the user does not need to reproduce the abnormal sound. If the abnormal sound of the motor drive system exists, the user may need to reproduce the abnormal sound. For example, the abnormal sound of the motor drive system is triggered based on the user's accelerator action. Then, the user may need to step on the accelerator again to reproduce the abnormal sound of the motor drive system.

[0052] Therefore, the audio recording request can be triggered by the user, that is, the user determines whether the abnormal sound still exists. If it still exists, the audio recording request can be directly triggered; if it does not exist, the abnormal sound can be reproduced after or before the audio recording request is triggered.

[0053] It is understood that the implementation method of the user triggering the audio recording request can refer to the implementation method of the user triggering the abnormal sound detection request. For example, the audio recording request can be triggered by voice triggering or control triggering.

[0054] After receiving a user-triggered audio recording request, the microphone is activated to start recording audio data for the motor drive system.

[0055] Correspondingly, after the user triggers the end recording request, the microphone can be turned off to stop recording the audio data of the motor drive system. In addition, the audio data recorded during the entire process is used to generate an audio signal, for example, the audio data is used to generate an audio signal in a time series.

[0056] It can be understood that the above-mentioned microphone startup and microphone shutdown are aimed at the microphone used to realize the audio recording of the motor drive system, and the microphones of other recording functions of the vehicle are not affected.

[0057] In some embodiments, a microphone for realizing audio recording of a motor drive system may be disposed in a vehicle cabin, thereby reducing irrelevant signals in the audio signal and improving the accuracy of abnormal sound detection.

[0058] In some embodiments, before executing step S12, the audio signal may be preprocessed to improve the quality of the audio signal. The preprocessing of the audio signal may include: noise reduction, filtering, and removal of irrelevant signals. The irrelevant signals include, for example, human voice and system announcement sound.

[0059] In step S12, the abnormal sound type is used to characterize the type of abnormal audio signal in the audio signal, and the abnormal sound component corresponds to a specific component in the motor drive system.

[0060] For example, the abnormal sound type may be an impact abnormal sound type or a howling abnormal sound type. Regarding the impact abnormal sound type, the corresponding abnormal audio signal is an impact signal, for example: a high-volume sound with a very short duration; regarding the howling abnormal sound type, the corresponding abnormal audio signal is a howling signal, for example: a continuous high-frequency screaming sound.

[0061] For example, the abnormal noise component may be a gear shaft, a motor, a reducer or a bearing. The motor drive system usually includes three gear shafts, so for the gear shafts, it is also necessary to distinguish them by, for example, gear shaft 1, gear shaft 2 and gear shaft 3.

[0062] In the embodiments of the present disclosure, different abnormal noise types may use different abnormal noise component determination methods.

[0063] Therefore, as an optional implementation, step S12 includes: performing abnormal audio signal detection on the audio signal to determine the type of abnormal sound; determining the audio characteristics of the audio signal according to the type of abnormal sound, and different abnormal sound types correspond to different audio characteristics; determining the abnormal sound component according to the audio characteristics.

[0064] In this embodiment, the abnormal sound type is first determined by abnormal audio signal detection. Since different abnormal sound types correspond to different abnormal sound audio signals, the corresponding audio features can be determined according to the abnormal sound type, and the abnormal sound component can be determined according to the corresponding audio features.

[0065] As an optional implementation, abnormal audio signal detection is performed on the audio signal to determine the type of abnormal sound, including: performing impact signal detection on the audio signal to obtain an impact signal detection result, the impact signal detection result is used to characterize whether the audio signal includes an impact signal; if the impact signal detection result characterizes that the audio signal includes an impact signal, the type of abnormal sound is determined to be an impact abnormal sound; if the impact signal detection result characterizes that the audio signal does not include an impact signal, the type of abnormal sound is determined to be a howling abnormal sound.

[0066] In some embodiments, the impact signal detection can be achieved by detecting the impact signal characteristics, for example, detecting whether there is an audio feature with a very short duration, and the intensity of the audio feature is obviously different from that of other audio features.

[0067] It can be understood that in the embodiment of the present disclosure, when the impact abnormal sound and the howling abnormal sound are defined, if it is detected that the audio signal includes an impact signal, the abnormal sound type can be determined to be an impact abnormal sound. If it is detected that the audio signal does not include an impact signal, the abnormal sound type can be directly determined to be a howling abnormal sound.

[0068] In other embodiments, if the audio signal is relatively complex, when it is detected that the audio signal does not include an impact signal, a howling feature may be further detected. When the howling feature is detected, the type of the abnormal sound is determined to be a howling abnormal sound.

[0069] Furthermore, based on the abnormal sound type, the audio features of the audio signal may be further determined.

[0070] In some embodiments, determining the audio features of the audio signal according to the abnormal sound type may include: if the abnormal sound type is impact abnormal sound, determining the impact signal frequency of the audio signal; if the abnormal sound type is howling abnormal sound, determining the order corresponding to the audio signal.

[0071] In this embodiment, for the impact abnormal sound type, the frequency of the impact signal is used as an audio feature to determine the abnormal sound component. For the howling abnormal sound type, the order corresponding to the audio signal is used as an audio feature to determine the abnormal sound component.

[0072] The frequency of the impulse signal can be determined by the impulse signal detection result, for example, according to the occurrence frequency of the detected impulse feature in the entire audio signal.

[0073] For example, if the audio signal involves 50 time points, 10 of which involve impact features, then the impact signal frequency is 10 / 50=0.2.

[0074] The order corresponding to the audio signal can be determined by combining the abnormal sound frequency and the motor speed, and the abnormal sound frequency can be determined by combining the spectrum.

[0075] Therefore, the abnormal sound detection method may further include: acquiring a preset frequency spectrum and a rotation speed of the motor drive system, wherein the preset frequency spectrum is a frequency spectrum corresponding to a normal audio signal.

[0076] The rotational speed of the motor drive system is an operating parameter of the motor drive system and can be obtained from a controller of the motor drive system or from a corresponding detection sensor.

[0077] As for the preset spectrum, it can be preset in the vehicle system and can be directly obtained when needed.

[0078] Furthermore, determining the order corresponding to the audio signal may include: determining a frequency spectrum corresponding to the audio signal; determining an abnormal sound frequency according to the frequency spectrum corresponding to the audio signal and a preset frequency spectrum; and determining the order corresponding to the audio signal according to the abnormal sound frequency and the rotation speed.

[0079] The spectrum can be determined through spectrum analysis, which can decompose the audio signal into multiple simple signals of different frequencies. Based on the analysis of multiple simple signals, the information of the audio signal at different frequencies, such as amplitude, power, intensity or phase, can be determined, so as to understand the frequency composition of the audio signal.

[0080] Spectral analysis can be achieved by performing Fourier transform on the signal, which can convert the time domain signal into the frequency domain signal and then obtain the spectrum. In audio signal processing, spectrum analysis can determine the frequency characteristics of the audio signal, including the fundamental frequency period and harmonic components.

[0081] In some embodiments, the frequency spectrum corresponding to the audio signal is compared with a preset frequency spectrum to determine the abnormal frequency. For example, the frequency corresponding to the part where the frequency spectrum corresponding to the audio signal and the preset frequency spectrum are different is determined as the abnormal sound frequency.

[0082] Furthermore, the order corresponding to the audio signal can be determined according to the abnormal sound frequency and the rotation speed, wherein the order corresponding to the audio signal can be understood as the order corresponding to the abnormal frequency.

[0083] It can be understood that the abnormal sound frequency can represent the number of abnormal events, and the order can describe the number of events occurring per revolution. Therefore, the ratio of the abnormal sound frequency to the rotation speed can be determined as the order.

[0084] Furthermore, the abnormal sound component can be determined based on the audio feature. As an optional implementation, the abnormal sound component is determined based on the audio feature, including: obtaining a preset correspondence relationship, the preset correspondence relationship includes multiple preset audio features and abnormal sound components corresponding to the multiple preset audio features; determining a target audio feature that matches the audio feature from the multiple preset audio features; and determining the abnormal sound component corresponding to the target audio feature as the abnormal sound component.

[0085] In this embodiment, a corresponding relationship is preset, and the preset corresponding relationship represents the corresponding relationship between the preset audio feature and the abnormal sound component. Based on the preset corresponding relationship, a search can be performed to determine the target audio feature that matches the audio feature. Thus, the abnormal sound component corresponding to the target audio feature can be determined as the abnormal sound component.

[0086] Here, matching with the audio feature can be understood as being consistent with the audio feature, for example, being consistent in order or being consistent in frequency.

[0087] In some embodiments, the preset audio feature may be a specific audio feature or an audio feature range, and may cover multiple audio features.

[0088] In some embodiments, the audio feature is the impact signal frequency of the audio signal or the order corresponding to the audio signal, and the preset correspondence relationship includes a first preset correspondence relationship and a second preset correspondence relationship. The first preset correspondence relationship includes multiple preset impact signal frequencies and abnormal sound components corresponding to multiple preset impact signal frequencies respectively, and the second preset correspondence relationship includes multiple preset orders and abnormal sound components corresponding to multiple preset orders respectively.

[0089] Then, if the audio feature is frequency, the abnormal sound component is searched based on the first preset corresponding relationship. If the audio feature is order, the abnormal sound component is searched based on the second preset corresponding relationship.

[0090] For example, for impact-related abnormal noise, it is related to the failure of the electric drive gear shaft. There are 3 gear shafts inside the electric drive, and the frequency corresponding to the failure of each gear shaft is different. If the impact frequency corresponds to the 3 gear shafts, the corresponding gear shaft fault can be output. If it does not correspond, it cannot be identified. Therefore, please refer to Table 1, which is an example of the first preset correspondence. As shown in Table 1, the 3 gear shafts correspond to different frequencies, namely N1, N2 and N3. By searching, the corresponding abnormal noise component can be determined.

[0091] Table 1

[0092]

[0093] For example, for abnormal noises such as howling, the spectrum is calculated, and the spectrum is compared with the standard spectrum to confirm the frequency of the abnormal noise, and then the order can be determined according to the electric drive speed. Each rotating component of the motor drive system has a corresponding order. If the abnormal order can be matched, the abnormal component can be output, otherwise it cannot be identified. Therefore, please refer to Table 2, which is an example of the second preset correspondence. As shown in Table 2, the three abnormal noise components correspond to different orders, namely: E1 / E2 / E3 / En, T1 / T2 / T3 / Tn and B1 / B2 / B3 / Bn. By searching, the corresponding abnormal noise component can be determined.

[0094] Table 2

[0095]

[0096] It is understandable that, based on the audio features, there may be a situation where the abnormal noise component cannot be located. For example, when searching according to the preset correspondence, if no audio features matching the current audio features can be found, it is considered that the search has failed. In this case, a prompt message indicating the failure of abnormal noise detection can be output so that the user can take corresponding measures, such as requesting assistance from a vehicle maintenance organization.

[0097] In some embodiments, after step S12, the abnormal sound type and the abnormal sound component may be output so that the user can know the abnormal sound detection situation.

[0098] Among the above-mentioned abnormal noise components, the whistling abnormal noise of the motor and reducer is usually a normal sound, but if the sound is too loud, it is an abnormal sound. Therefore, in order to alleviate the user's anxiety about the abnormal noise detection result, the abnormal noise detection method may also include: if the abnormal noise type is the target abnormal noise type, and the abnormal noise component is the target abnormal noise component, obtain preset abnormal noise data, the preset abnormal noise data includes the abnormal noise levels corresponding to multiple vehicles of the same type; determine the abnormal noise level of the vehicle according to the volume of the audio signal; determine the abnormality ranking of the vehicle among vehicles of the same type according to the abnormal noise level of the vehicle and the preset abnormal noise data; output the abnormal noise type, abnormal noise component and abnormality ranking.

[0099] In this embodiment, the preset abnormal sound data may be data generated by big data analysis, and the data includes the abnormal sound levels of multiple vehicles of the same type. Thus, based on the current audio, the abnormal sound level of the current vehicle can be determined. Then, by comparing with the preset abnormal sound data, the abnormal degree ranking of the vehicle among vehicles of the same type can be determined. Furthermore, the abnormal sound type, abnormal sound component, and abnormal degree ranking can be output together.

[0100] In some embodiments, the abnormal sound type and abnormal sound component may be output first, and after the user triggers a ranking request, the abnormality degree ranking may be determined and output.

[0101] In some embodiments, the preset abnormal sound data may include not only the abnormal sound levels corresponding to the same type of vehicles, but also the abnormal sound levels corresponding to different types of vehicles. Furthermore, the final ranking may also include the abnormality ranking among different types of vehicles.

[0102] In some embodiments, the target abnormal noise type is a howling abnormal noise, and the target abnormal noise component is a motor or a reducer.

[0103] That is, when abnormal howling noise is detected in the motor or the reducer, the above-mentioned abnormality ranking determination process is executed.

[0104] In some embodiments, when outputting the abnormal sound type, abnormal sound component and abnormal degree ranking, it can be achieved by displaying the abnormal sound type, abnormal sound component and abnormal degree ranking in a preset display format.

[0105] Among them, the preset display form, for example, arranges the abnormal sound type, abnormal sound component and abnormal degree ranking in order, and the display format of the abnormal sound type, abnormal sound component and abnormal degree ranking is different, such as color, font size and font format.

[0106] Through the above implementation, the ranking information can be informed to the user without affecting the driving of the vehicle due to abnormal vehicle noise, so as to alleviate the user's anxiety and improve the user experience.

[0107] In some embodiments, after the user learns about the noisy components and the types of the noises, they can also upload them to the cloud, which then provides feedback to the vehicle manufacturer so that the vehicle manufacturer can improve the design of the vehicle.

[0108] Figure 2 FIG. 1 is a schematic diagram of a fault detection process according to an exemplary embodiment. The fault detection process is implemented based on the abnormality detection solution of the embodiment of the present disclosure. Figure 2 As shown, the fault detection process includes three parts: vehicle operation, data collection and background calculation.

[0109] exist Figure 2 In the above, the fault mode may correspond to the aforementioned abnormal noise type and abnormal noise component. That is, the abnormal noise type and abnormal noise component may be output as a fault mode. For example, the bearing whistling abnormal noise is regarded as a fault mode.

[0110] In the vehicle operation part, it is necessary to design a fault diagnosis mode and remind the owner that recording and data collection will be performed. Design start and end options on the vehicle display interface to accurately record abnormal noises. After the owner chooses to start reproducing the abnormal noise, the abnormal noise reproduction condition is performed.

[0111] In the data collection section, signal collection starts and ends synchronously according to the start and end options selected by the owner.

[0112] In the background calculation part, after receiving the signal, the background can choose to process the audio signal locally or upload it to the cloud.

[0113] Furthermore, the audio signal is first subjected to noise reduction filtering, and then it is identified whether there is an impact feature, if so, the corresponding processing flow of the audio signal of the impact abnormal sound type is entered. If not, the corresponding processing flow of the audio signal of the howling abnormal sound type is entered.

[0114] Furthermore, if the detection is successful, the corresponding failure mode, that is, the abnormal noise component and the abnormal noise type, can be output. And, if the detection fails, a prompt message of the detection failure can be output.

[0115] Figure 3 is a schematic diagram of a background calculation process according to an exemplary embodiment. Figure 3 As shown, in Figure 2 Based on the background calculation process shown, an abnormality ranking process is also added.

[0116] When the detection result is motor or reducer howling, the database is used to confirm whether there are similar problems, and the ranking of the vehicle's fault degree in big data is calculated and output.

[0117] Thus, the final output result is the fault mode and / or ranking. It can be understood that in some embodiments, when the ranking is determined, only the ranking can be output without outputting the fault mode, that is, without outputting the abnormal noise type and abnormal noise component.

[0118] In addition, Figure 3 In the process, before determining the ranking, it is also possible to first query whether there is a failure mode that is the same as the failure mode of the vehicle in the database, and if so, further determine the ranking. If not, then end the detection.

[0119] It can be seen from the introduction of the embodiments of the present disclosure that the technical solution of the embodiments of the present disclosure can be used to diagnose abnormal noises that can be perceived by end users (i.e., vehicle passengers) without adding additional hardware costs. For end users, they can make preliminary diagnoses by themselves without having to go to the store for diagnosis. For OEMs (which can be understood as vehicle manufacturers), actual feedback from end users can be collected to guide design improvements.

[0120] Figure 4 is a block diagram of an abnormal sound detection device 400 according to an exemplary embodiment. Figure 4 , the device comprises:

[0121] The acquisition module 401 is configured to acquire an audio signal corresponding to the motor drive system of the vehicle.

[0122] The detection module 402 is configured to determine the abnormal sound type of the motor drive system and the abnormal sound component of the motor drive system according to the audio signal, wherein the abnormal sound type is used to characterize the type of the abnormal audio signal in the audio signal.

[0123] Optionally, the detection module 402 is further configured to: perform abnormal audio signal detection on the audio signal to determine the type of abnormal sound; determine the audio characteristics of the audio signal according to the type of abnormal sound, different abnormal sound types correspond to different audio characteristics; determine the abnormal sound component according to the audio characteristics.

[0124] Optionally, the detection module 402 is further configured to: perform impact signal detection on the audio signal to obtain an impact signal detection result, wherein the impact signal detection result is used to characterize whether the audio signal includes an impact signal; if the impact signal detection result characterizes that the audio signal includes an impact signal, determine that the type of abnormal sound is an impact abnormal sound; if the impact signal detection result characterizes that the audio signal does not include an impact signal, determine that the type of abnormal sound is a howling abnormal sound.

[0125] Optionally, the detection module 402 is further configured to: if the abnormal sound type is an impact abnormal sound, determine the impact signal frequency of the audio signal; if the abnormal sound type is a howling abnormal sound, determine the order corresponding to the audio signal.

[0126] Optionally, the acquisition module 401 is further configured to: acquire a preset spectrum and the rotational speed of the motor drive system, the preset spectrum being the spectrum corresponding to a normal audio signal; the detection module 402 is further configured to: determine the spectrum corresponding to the audio signal; determine the abnormal sound frequency according to the spectrum corresponding to the audio signal and the preset spectrum; determine the order corresponding to the audio signal according to the abnormal sound frequency and the rotational speed.

[0127] Optionally, the acquisition module 401 is also configured to: obtain a preset correspondence relationship, wherein the preset correspondence relationship includes multiple preset audio features and abnormal sound components corresponding to the multiple preset audio features respectively; the detection module 402 is also configured to: determine a target audio feature that matches the audio feature from the multiple preset audio features; and determine the abnormal sound component corresponding to the target audio feature as the abnormal sound component.

[0128] Optionally, the audio feature is the impulse signal frequency of the audio signal or the order corresponding to the audio signal, and the preset correspondence includes a first preset correspondence and a second preset correspondence, the first preset correspondence includes multiple preset impulse signal frequencies and abnormal sound components corresponding to the multiple preset impulse signal frequencies, and the second preset correspondence includes multiple preset orders and abnormal sound components corresponding to the multiple preset orders.

[0129] Optionally, the acquisition module 401 is also configured to: in response to receiving an abnormal sound detection request triggered by a user, output a prompt message, wherein the prompt message is used to prompt the user to record an audio signal for abnormal sound detection; in response to receiving an audio recording request triggered by a user, start recording audio data for the motor drive system; in response to receiving an end recording request triggered by a user, end recording audio data for the motor drive system, and generate the audio signal based on the recorded audio data.

[0130] Optionally, the device also includes a ranking module, which is configured to: if the abnormal noise type is a target abnormal noise type and the abnormal noise component is a target abnormal noise component, obtain preset abnormal noise data, the preset abnormal noise data including abnormal noise levels corresponding to multiple vehicles of the same type; determine the abnormal noise level of the vehicle according to the volume of the audio signal; determine the abnormality ranking of the vehicle among vehicles of the same type according to the abnormal noise level of the vehicle and the preset abnormal noise data; and output the abnormal noise type, the abnormal noise component and the abnormality ranking.

[0131] Optionally, the abnormal noise type is: impact noise or howling noise, and the abnormal noise component includes: at least one of: a gear shaft, a motor, a reducer and a bearing; the target abnormal noise type is howling noise, and the target abnormal noise component is a motor or a reducer.

[0132] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0133] The present disclosure also provides a computer-readable storage medium on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the abnormal sound detection method provided by the present disclosure are implemented.

[0134] Figure 5 is a block diagram of a vehicle 500 according to an exemplary embodiment. For example, the vehicle 500 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 500 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0135] Reference Figure 5 , the vehicle 500 may include various subsystems, for example, an infotainment system 510, a perception system 520, a decision control system 530, a drive system 540, and a computing platform 550. The vehicle 500 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 500 may be interconnected by wire or wireless means.

[0136] In some embodiments, the infotainment system 510 may include a communication system, an entertainment system, and a navigation system, among others.

[0137] The perception system 520 may include several sensors for sensing information about the environment around the vehicle 500. For example, the perception system 520 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0138] The decision control system 530 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0139] The drive system 540 may include components that provide powered motion for the vehicle 500. In one embodiment, the drive system 540 may include an engine, an energy source, a transmission system, and wheels. The engine may be an internal combustion engine, an electric motor, an air compression engine, or a combination of one or more thereof. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0140] Some or all functions of the vehicle 500 are controlled by a computing platform 550. The computing platform 550 may include at least one first processor 551 and a first memory 552, and the first processor 551 may execute instructions 553 stored in the first memory 552.

[0141] The first processor 551 may be any conventional processor, such as a commercially available CPU. The first processor 551 may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0142] The first memory 552 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0143] In addition to the instructions 553 , the first memory 552 may also store data, such as road maps, route information, and data such as the location, direction, and speed of the vehicle. The data stored in the first memory 552 may be used by the computing platform 550 .

[0144] In the embodiment of the present disclosure, the first processor 551 may execute instruction 553 to complete all or part of the steps of the abnormal sound detection method described above.

[0145] Figure 6 6 is a block diagram of a device 600 for implementing an abnormal sound detection method according to an exemplary embodiment. For example, the device 600 may be a mobile phone, a computer, a messaging device, a tablet device, a personal digital assistant, etc.

[0146] Reference Figure 6 , the device 600 may include one or more of the following components: a first processing component 602 , a second memory 604 , a first power component 606 , a multimedia component 608 , an audio component 610 , a first input / output interface 612 , a sensor component 614 , and a communication component 616 .

[0147] The first processing component 602 generally controls the overall operation of the device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The first processing component 602 may include one or more second processors 620 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the first processing component 602 may include one or more modules to facilitate the interaction between the first processing component 602 and other components. For example, the first processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the first processing component 602.

[0148] The second memory 604 is configured to store various types of data to support operations on the device 600. Examples of such data include instructions for any application or method operating on the device 600, contact data, phone book data, messages, pictures, videos, etc. The second memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0149] The first power source component 606 provides power to various components of the device 600. The first power source component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 600.

[0150] The multimedia component 608 includes a screen that provides an output interface between the device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0151] The audio component 610 is configured to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC), and when the device 600 is in an operation mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the second memory 604 or sent via the communication component 616. In some embodiments, the audio component 610 also includes a speaker for outputting audio signals.

[0152] The first input / output interface 612 provides an interface between the first processing component 602 and a peripheral interface module, which may be a keyboard, a click wheel, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0153] The sensor assembly 614 includes one or more sensors for providing various aspects of status assessment for the device 600. For example, the sensor assembly 614 can detect the open / closed state of the device 600, the relative positioning of components, such as the display and keypad of the device 600, and the sensor assembly 614 can also detect the position change of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, the orientation or acceleration / deceleration of the device 600, and the temperature change of the device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0154] The communication component 616 is configured to facilitate wired or wireless communication between the device 600 and other devices. The device 600 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0155] In an exemplary embodiment, the apparatus 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-mentioned abnormal sound detection method.

[0156] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a second memory 604 including instructions, and the instructions can be executed by a second processor 620 of the device 600 to complete the abnormal sound detection method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0157] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a programmable device. The computer program has a code portion for executing the abnormal noise detection method when executed by the programmable device.

[0158] Figure 7 is a block diagram of another apparatus 700 for implementing an abnormal sound detection method according to an exemplary embodiment. For example, the apparatus 700 may be provided as a server. Figure 7 The apparatus 700 includes a second processing component 722, which further includes one or more third processors, and a memory resource represented by a third memory 732, for storing instructions executable by the second processing component 722, such as an application. The application stored in the third memory 732 may include one or more modules, each corresponding to a set of instructions. In addition, the second processing component 722 is configured to execute instructions to perform the above-mentioned abnormal sound detection method.

[0159] The device 700 may further include a second power supply component 726 configured to perform power management of the device 700, a wired or wireless network interface 750 configured to connect the device 700 to a network, and a second input / output interface 758. The device 700 may operate based on an operating system stored in the memory 732, such as Windows Server™, Mac OSX™, Unix™, Linux™, FreeBSD™ or the like.

[0160] Those skilled in the art may also understand that the various illustrative logical blocks and steps listed in the embodiments of the present application may be implemented by electronic hardware, computer software, or a combination of the two. Whether such functions are implemented by hardware or software depends on the specific application and the design requirements of the entire system. Those skilled in the art may use various methods to implement the functions described for each specific application, but such implementation should not be understood as exceeding the scope of protection of the embodiments of the present application.

[0161] In addition, the word "exemplary" is used herein to indicate serving as an example, instance, or diagram. Any aspect or design described as "exemplary" in this article is not necessarily understood to be advantageous compared to other aspects or designs. On the contrary, the use of the word exemplary is intended to present concepts in a specific way. As used herein, the term "or" is intended to represent an inclusive "or" rather than an exclusive "or". That is, unless otherwise specified or clear from the context, "X applies A or B" is intended to represent any one of the natural inclusive arrangements. That is, if X applies A; X applies B; or X applies both A and B, "X applies A or B" is satisfied under any of the aforementioned examples. In addition, unless otherwise specified or clearly pointed to a singular form from the context, the articles "one" and "an" as used in this application and the appended claims are generally understood to mean "one or more".

[0162] Likewise, although the present disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art after reading and understanding the specification and drawings. The present disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components (e.g., elements, resources, etc.) described above, unless otherwise indicated, the terms used to describe such components are intended to correspond to any component (functionally equivalent) that performs the specific functions of the described components, even if the structure is not equivalent to the disclosed structure. In addition, although specific features of the present disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations as may be desired and beneficial to any given or specific application. In addition, with respect to "including", "having", "having", "having", or variations thereof used in a specific embodiment or claim, such terms are intended to be inclusive in a manner similar to the term "comprising".

[0163] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

[0164] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0165] It should be understood that, unless otherwise specifically noted, the features of some embodiments of the various present disclosures described herein may be combined with each other. As used herein, the term "and / or" includes any one of the related listed items and any combination of any two or more; similarly, "at least one of . . . " includes any one of the related listed items and any combination of any two or more.

[0166] Although terms such as "first", "second" and "third" can be used herein to describe various components, parts, regions, layers or sections, these components, parts, regions, layers or sections are not limited to these terms. On the contrary, these terms are only used to distinguish one component, component, region, layer or section from another component, component, region, layer or section. Therefore, without departing from the teachings of each example, the first component, component, region, layer or section mentioned in the examples described herein may also be referred to as the second component, component, region, layer or section. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first" and "second" may expressly or implicitly include at least one of the features. In the description herein, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

Claims

1. A method for detecting abnormal sound, characterized in that: include: Acquire an audio signal corresponding to a motor drive system of the vehicle; Determine, according to the audio signal, an abnormal sound type of the motor drive system and an abnormal sound component of the motor drive system, wherein the abnormal sound type is used to characterize a type of an abnormal audio signal in the audio signal; If the abnormal sound type is a target abnormal sound type, and the abnormal sound component is a target abnormal sound component, obtaining preset abnormal sound data, the preset abnormal sound data includes abnormal sound levels corresponding to a plurality of vehicles of the same type, the target abnormal sound type includes whistling abnormal sound, and the target abnormal sound component includes a motor and / or a reducer; Determining the degree of abnormal noise of the vehicle according to the volume of the audio signal; Determining the abnormality ranking of the vehicle among vehicles of the same type according to the abnormal noise level of the vehicle and the preset abnormal noise data; The noise type, the noise component, and the abnormality degree ranking are output.

2. The abnormal sound detection method according to claim 1, characterized in that: The step of determining the abnormal sound type of the motor drive system and the abnormal sound component of the motor drive system according to the audio signal includes: Performing abnormal audio signal detection on the audio signal to determine the type of abnormal sound; Determining, according to the abnormal sound type, an audio feature of the audio signal, where different abnormal sound types correspond to different audio features; The abnormal noise component is determined according to the audio feature.

3. The abnormal sound detection method according to claim 2, characterized in that: The performing abnormal audio signal detection on the audio signal to determine the abnormal sound type includes: Performing impact signal detection on the audio signal to obtain an impact signal detection result, wherein the impact signal detection result is used to indicate whether the audio signal includes an impact signal; If the impact signal detection result indicates that the audio signal includes an impact signal, determining that the abnormal sound type is an impact abnormal sound; If the impact signal detection result indicates that the audio signal does not include an impact signal, it is determined that the abnormal sound type is a howling abnormal sound.

4. The abnormal sound detection method according to claim 2, characterized in that: The step of determining the audio feature of the audio signal according to the abnormal sound type includes: If the abnormal sound type is an impact abnormal sound, determining the impact signal frequency of the audio signal; If the abnormal sound type is a howling abnormal sound, determine the order corresponding to the audio signal.

5. The abnormal sound detection method according to claim 4, characterized in that: The abnormal sound detection method further comprises: Acquire a preset spectrum and a rotation speed of the motor drive system, wherein the preset spectrum is a spectrum corresponding to a normal audio signal; The determining the order corresponding to the audio signal includes: Determine a frequency spectrum corresponding to the audio signal; Determining the abnormal sound frequency according to the frequency spectrum corresponding to the audio signal and the preset frequency spectrum; An order corresponding to the audio signal is determined according to the abnormal sound frequency and the rotation speed.

6. The abnormal sound detection method according to claim 2, characterized in that: The determining the abnormal sound component according to the audio feature includes: Acquire a preset corresponding relationship, where the preset corresponding relationship includes a plurality of preset audio features and abnormal sound components corresponding to the plurality of preset audio features respectively; Determining a target audio feature that matches the audio feature from the multiple preset audio features; The abnormal sound component corresponding to the target audio feature is determined as the abnormal sound component.

7. The abnormal sound detection method according to claim 6, characterized in that: The audio feature is the impulse signal frequency of the audio signal or the order corresponding to the audio signal, and the preset correspondence includes a first preset correspondence and a second preset correspondence. The first preset correspondence includes multiple preset impulse signal frequencies and abnormal sound components corresponding to the multiple preset impulse signal frequencies, and the second preset correspondence includes multiple preset orders and abnormal sound components corresponding to the multiple preset orders.

8. The abnormal sound detection method according to any one of claims 1 to 7, characterized in that: The step of obtaining an audio signal corresponding to the motor drive system of the vehicle includes: In response to receiving an abnormal sound detection request triggered by a user, outputting prompt information, wherein the prompt information is used to prompt the user to record an audio signal for abnormal sound detection; In response to receiving a user-triggered audio recording request, starting to record audio data for the motor drive system; In response to receiving a user-triggered end-recording request, the recording of audio data for the motor drive system is ended, and the audio signal is generated according to the recorded audio data.

9. An abnormal sound detection device, characterized in that: include: An acquisition module is configured to acquire an audio signal corresponding to a motor drive system of a vehicle; a detection module configured to determine, according to the audio signal, an abnormal sound type of the motor drive system and an abnormal sound component of the motor drive system, wherein the abnormal sound type is used to characterize a type of an abnormal audio signal in the audio signal; The ranking module is configured to: if the abnormal sound type is a target abnormal sound type and the abnormal sound component is a target abnormal sound component, obtain preset abnormal sound data, the preset abnormal sound data including abnormal sound levels corresponding to a plurality of vehicles of the same type, the target abnormal sound type includes a whistling abnormal sound, and the target abnormal sound component includes a motor and / or a reducer; determine the abnormal sound level of the vehicle according to the volume of the audio signal; determine the abnormality ranking of the vehicle among vehicles of the same type according to the abnormal sound level of the vehicle and the preset abnormal sound data; The noise type, the noise component, and the abnormality degree ranking are output.

10. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: execute the abnormal sound detection method as described in any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the abnormal sound detection method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the abnormal sound detection method according to any one of claims 1 to 8.

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