A vehicle fault reminding method, device and equipment and a storage medium

Abstract

The present disclosure relates to a vehicle fault reminding method, device, equipment and storage medium, the method comprising: acquiring a noise audio after the vehicle starts; extracting a voiceprint feature of the noise audio from the noise audio; judging whether the vehicle has a fault based on the voiceprint feature; and sending reminding information in response to the vehicle having a fault. The present disclosure extracts the voiceprint feature in the noise audio after the vehicle starts, judges whether the vehicle has a fault, and sends reminding information after determining that the vehicle has a fault, so as to judge whether the vehicle has a fault according to the sound when the vehicle is running, timely remind relevant personnel to overhaul the vehicle when there is a fault, eliminate safety hazards, and improve the safety of driving.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle technology, and in particular to a vehicle fault alert method, device, equipment, and storage medium. Background Technology

[0002] As vehicles age and mileage increases, the likelihood of component failure also rises. While some serious malfunctions can be detected by built-in monitoring equipment, minor issues like loose or missing screws are difficult to detect and require manual inspection. This is highly dependent on the operator's experience. If the operator lacks experience and fails to identify problems promptly, or if the owner neglects routine vehicle maintenance, these issues can become safety hazards while driving. Therefore, identifying potential vehicle malfunctions early and promptly alerting the owner is a crucial technical challenge that needs to be addressed. Summary of the Invention

[0003] To address the aforementioned technical problems, this disclosure provides a vehicle fault alert method, device, equipment, and storage medium.

[0004] A first aspect of this disclosure provides a vehicle fault alert method, the method comprising:

[0005] Acquire the noise audio after the vehicle starts;

[0006] Extract the voiceprint features of the noise audio from the noise audio;

[0007] Based on the voiceprint characteristics, it is determined whether the vehicle has malfunctioned;

[0008] In response to a malfunction in the vehicle, an alert message is sent.

[0009] A second aspect of this disclosure provides a vehicle fault warning device, the device comprising:

[0010] The acquisition module is used to acquire the noise audio after the vehicle starts;

[0011] An extraction module is used to extract the voiceprint features of the noise audio from the noise audio;

[0012] The judgment module is used to determine whether the vehicle has malfunctioned based on the voiceprint characteristics.

[0013] The reminder module is used to send a reminder message in response to a vehicle malfunction.

[0014] A third aspect of this disclosure provides a computer device including a memory and a processor, and a computer program, wherein the memory stores the computer program, and when the computer program is executed by the processor, it implements the vehicle fault reminder method of the first aspect described above.

[0015] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle fault alert method of the first aspect described above.

[0016] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0017] In the vehicle fault reminder method, apparatus, device, and storage medium provided in this disclosure embodiment, noise audio after vehicle startup is acquired, and the voiceprint features of the noise audio are extracted from the noise audio. Based on the voiceprint features, it is determined whether the vehicle has a fault. In response to the vehicle malfunction, a reminder message is sent. During the daily driving process of the vehicle, noise audio can be monitored, and the presence of a fault can be determined based on the monitored noise audio. Thus, when a fault is found, a reminder message is sent to the driver in a timely manner to remind the driver to inspect the vehicle, thereby eliminating safety hazards, improving driving safety, reducing the possibility of vehicle problems developing into more serious problems, and reducing vehicle maintenance costs. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a vehicle fault alert method provided in an embodiment of this disclosure;

[0021] Figure 2 This is a flowchart of a method for determining whether a vehicle has malfunctioned, provided in an embodiment of this disclosure;

[0022] Figure 3 This is a flowchart of a method for extracting voiceprint features provided in an embodiment of this disclosure;

[0023] Figure 4 This is a flowchart of another method for determining whether a vehicle has malfunctioned, provided in an embodiment of this disclosure;

[0024] Figure 5 This is a flowchart of a method for determining target voiceprint features provided in an embodiment of this disclosure;

[0025] Figure 6 This is a flowchart of a method for determining the location of a fault provided in an embodiment of this disclosure;

[0026] Figure 7 This is a flowchart of a method for marking fault locations provided in an embodiment of this disclosure;

[0027] Figure 8 This is a schematic diagram of the structure of a vehicle fault warning device provided in an embodiment of this disclosure;

[0028] Figure 9 This is a schematic diagram of the structure of a computer device provided in an embodiment of this disclosure. Detailed Implementation

[0029] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0030] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0031] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0032] Figure 1 This is a flowchart of a vehicle fault reminder method provided in an embodiment of the present disclosure. The method can be executed by a vehicle fault reminder device that can be installed on a vehicle.

[0033] like Figure 1 As shown, the vehicle fault alert method provided in this embodiment includes the following steps:

[0034] S101, Obtain the noise audio after the vehicle starts.

[0035] The noise audio in this embodiment can be understood as the noise audio collected by an audio acquisition device, such as a microphone, after the vehicle starts. The noise audio includes the sounds emitted by various components of the vehicle during operation. The audio acquisition device can be installed on the vehicle malfunction warning device or in other locations on the vehicle. For example, the audio acquisition device can be installed under the vehicle chassis.

[0036] In this embodiment of the disclosure, the vehicle fault reminder device can collect the noise audio of various components working after the vehicle is started by using an audio acquisition device installed on the vehicle, such as a microphone.

[0037] In one exemplary embodiment of this disclosure, the vehicle fault reminder device can acquire noise audio collected in real time by an audio acquisition device installed on the vehicle after detecting that the vehicle has started, or it can acquire noise audio collected in advance by an audio acquisition device installed on the vehicle after the vehicle has started.

[0038] S102. Extract the voiceprint features of the noise audio from the noise audio.

[0039] The voiceprint features in this embodiment can be understood as features used to represent the spectrum of noisy audio. For example, voiceprint features may include parameter features such as frequency and amplitude, and are represented in the form of feature vectors, which are not limited here.

[0040] In this embodiment of the present disclosure, the vehicle fault reminder device can extract the acoustic signature features of the spectrum of the noise audio after obtaining the noise audio.

[0041] In one exemplary embodiment of this disclosure, the vehicle fault warning device can preprocess the noise audio after obtaining it, extract the start and end points of the noise from the noise audio, and then perform frame-by-frame processing on the audio data of the noise portion. After fast Fourier transform, filtering, logarithmic operation, discrete cosine transform, etc., the Mel-scale Frequency Cepstral Coefficients (MFCC) features are obtained and determined as the voiceprint features of the noise audio.

[0042] S103. Based on the voiceprint characteristics, determine whether the vehicle has malfunctioned.

[0043] In this embodiment of the present disclosure, the vehicle fault reminder device can analyze and process the voiceprint features after obtaining the voiceprint features of the noise audio, and determine whether the voiceprint features of the noise audio are the voiceprint features of the vehicle that has malfunctioned, thereby determining whether the vehicle has malfunctioned.

[0044] In one exemplary embodiment of this disclosure, the vehicle fault reminder device can search for the presence of the obtained noise audio voiceprint feature in the pre-stored voiceprint features after a vehicle fault occurs. If the voiceprint feature exists, the vehicle is considered to have a fault; otherwise, the vehicle is considered not to have a fault.

[0045] S104. In response to a malfunction in the vehicle, a reminder message is sent.

[0046] The reminder information in this embodiment can be understood as information used to remind the driver or other relevant personnel that the vehicle has malfunctioned. For example, the reminder information can be in the form of text, images, or audio, and there is no limitation thereto.

[0047] In this embodiment of the present disclosure, the vehicle malfunction reminder device can send a reminder message after determining that a vehicle malfunction has occurred.

[0048] In one exemplary embodiment of this disclosure, the vehicle malfunction reminder device can send reminder information to the occupants of the vehicle through an output device on the vehicle, such as a display screen or audio system, after determining that a vehicle malfunction has occurred. It can also send reminder information to a device or account bound to the vehicle malfunction reminder device.

[0049] This embodiment of the disclosure acquires noise audio after the vehicle starts, extracts voiceprint features from the noise audio, and determines whether the vehicle has malfunctioned based on the voiceprint features. In response to a vehicle malfunction, an alert message is sent. This allows for the monitoring of noise audio during the vehicle's daily operation and the determination of whether a malfunction exists based on the monitored noise audio. When a malfunction is found, an alert message is promptly sent to the driver to remind relevant personnel to inspect the vehicle, thereby eliminating safety hazards, improving driving safety, reducing the possibility of vehicle problems developing into more serious issues, and lowering vehicle maintenance costs.

[0050] Figure 2 This is a flowchart of a method for determining whether a vehicle has malfunctioned, as provided in an embodiment of this disclosure. Figure 2 As shown, based on the above embodiments, the following method can be used to determine whether a vehicle has malfunctioned.

[0051] S201. The voiceprint features are matched with the pre-acquired historical voiceprint features to obtain the first matching degree between the voiceprint features and the historical voiceprint features.

[0052] The historical voiceprint features in this embodiment can be understood as the voiceprint features of noise audio obtained when the vehicle has not malfunctioned. These historical voiceprint features can be voiceprint features obtained when the vehicle leaves the factory, or voiceprint features obtained at any time after it has been determined that the vehicle has not malfunctioned; no limitation is made here.

[0053] In this embodiment of the disclosure, the matching degree can be understood as a parameter that characterizes the degree of similarity between different voiceprint features. The higher the value of the matching degree, the higher the degree of similarity. The first matching degree can characterize the degree of similarity between the obtained voiceprint features and the historical voiceprint features.

[0054] In this embodiment of the present disclosure, after obtaining the voiceprint features of the noise audio, the vehicle fault reminder device can perform matching processing on the voiceprint features of the noise audio with the historical voiceprint features obtained in advance when the vehicle has not experienced a fault, so as to obtain a first matching degree between the obtained voiceprint features and the historical voiceprint features.

[0055] In one exemplary embodiment of this disclosure, the obtained voiceprint features of the noise audio and the historical voiceprint features can be represented in vector form. After obtaining the voiceprint feature vector of the noise audio and the historical voiceprint feature vector, the vehicle fault reminder device can calculate the cosine similarity or Euclidean distance between the two, and determine the first matching degree based on the calculation result.

[0056] S202. In response to the first matching degree being greater than or equal to the first preset threshold, it is determined that the vehicle has not malfunctioned.

[0057] The first preset threshold in this embodiment can be understood as a pre-set threshold for determining whether the voiceprint features of the noise audio match the historical voiceprint features. The specific value of the first preset threshold can be set according to the actual situation.

[0058] In this embodiment of the present disclosure, after obtaining the first matching degree between the voiceprint feature and the historical voiceprint feature, the vehicle fault reminder device can compare the numerical values ​​of the voiceprint feature and the historical voiceprint feature. If the first matching degree is greater than or equal to a first preset threshold, it is determined that the voiceprint feature of the noise audio matches the voiceprint feature when the vehicle has not malfunctioned, and the vehicle has not malfunctioned.

[0059] S203. In response to the first matching degree being less than the first preset threshold, it is determined that the vehicle has malfunctioned.

[0060] In this embodiment of the present disclosure, after obtaining the first matching degree between the voiceprint feature and the historical voiceprint feature, the vehicle fault reminder device can compare the numerical values ​​of the voiceprint feature and the historical voiceprint feature. If the first matching degree is less than a first preset threshold, it is determined that the voiceprint feature of the noise audio does not match the voiceprint feature when the vehicle is not faulty, and the vehicle has malfunctioned.

[0061] This embodiment of the present disclosure matches the voiceprint features with pre-acquired historical voiceprint features to obtain a first matching degree between the voiceprint features and the historical voiceprint features. If the first matching degree is greater than or equal to a first preset threshold, it is determined that the vehicle has not malfunctioned. If the first matching degree is less than the first preset threshold, it is determined that the vehicle has malfunctioned. When determining whether the vehicle has malfunctioned based on the voiceprint features, the voiceprint features are matched with the voiceprint features when the vehicle has not malfunctioned. This allows for the determination of vehicle malfunction when the voiceprint features of the noise audio differ significantly from the historical voiceprint features when the vehicle has not malfunctioned, making the judgment result more accurate and further improving driving safety.

[0062] Figure 3 This is a flowchart of a method for extracting voiceprint features provided in an embodiment of this disclosure, such as... Figure 3 As shown, based on the above embodiments, voiceprint features can be extracted using the following method.

[0063] S301. The pre-acquired reverse audio of the vehicle is superimposed with the noise audio to obtain a first audio, wherein the reverse audio is the reverse audio of the audio collected when the vehicle is not malfunctioning.

[0064] In this embodiment of the disclosure, the reverse audio can be understood as an audio waveform that is opposite to the waveform of the audio collected when the vehicle is not malfunctioning, and can cancel out after being superimposed with the audio collected when the vehicle is not malfunctioning.

[0065] The first audio in this embodiment can be understood as the part of the noise audio that is different from the audio collected when the vehicle is not malfunctioning. When the vehicle is malfunctioning, the first audio includes the sound emitted from the location of the malfunction.

[0066] In this embodiment of the present disclosure, the vehicle fault reminder device can acquire the audio of the vehicle when no fault occurs in advance, and obtain the reverse audio of the audio. After obtaining the noise audio, the pre-acquired reverse audio is superimposed with the noise audio to cancel out the part of the noise audio that is the same as the audio of the vehicle when no fault occurs, so as to obtain a first audio in the noise audio that is different from the audio of the vehicle when no fault occurs.

[0067] S302. Based on a preset voiceprint feature extraction model, extract the voiceprint features of the first audio from the first audio.

[0068] The voiceprint feature extraction model in this embodiment can be understood as a pre-trained model capable of extracting voiceprint features from audio.

[0069] In this embodiment of the present disclosure, after obtaining the first audio, the vehicle fault reminder device can input the obtained first audio into a pre-trained voiceprint feature extraction model to obtain the voiceprint features of the output first audio, and determine the voiceprint features of the first audio as the voiceprint features of the noise audio.

[0070] In one exemplary embodiment of this disclosure, the vehicle fault reminder device can convert the first audio into a sound wave spectrum after obtaining the first audio, and then perform feature extraction processing on the sound wave spectrum according to a preset voiceprint feature extraction model. For example, the voiceprint feature extraction model can be based on a convolutional neural network (CNN), or it can be based on a deep neural network (DNN), or it can be established in other ways, which are not limited here.

[0071] This embodiment of the present disclosure obtains a first audio by superimposing a pre-acquired reverse audio of the vehicle with a noise audio. The reverse audio is the reverse audio of the audio collected when the vehicle is not malfunctioning. Based on a preset voiceprint feature extraction model, the voiceprint features of the first audio are extracted from the first audio. This can eliminate the parts of the noise audio that are the same as the audio collected when the vehicle is not malfunctioning, making the voiceprint of the fault part in the extracted voiceprint features clearer. As a result, a more accurate judgment result is obtained when judging the vehicle fault condition based on the voiceprint features in the future, thereby further improving driving safety.

[0072] Figure 4 This is a flowchart of another method for determining whether a vehicle has malfunctioned, provided in an embodiment of this disclosure. Figure 4 As shown, based on the above embodiments, the following method can be used to determine whether a vehicle has malfunctioned.

[0073] S401. The voiceprint features are matched with the pre-acquired target voiceprint features to obtain a second matching degree, wherein the target voiceprint features are the voiceprint features of the vehicle that has malfunctioned.

[0074] The target voiceprint feature in this embodiment can be understood as the voiceprint feature of a vehicle that has malfunctioned, such as the voiceprint feature of a vehicle after a screw has come loose.

[0075] The second matching degree in this embodiment can be understood as a parameter characterizing the similarity between the obtained voiceprint features and the target voiceprint features.

[0076] In this embodiment of the present disclosure, after obtaining the voiceprint features of the noise audio, the vehicle fault reminder device can perform matching processing on the voiceprint features of the noise audio with the target voiceprint features of the pre-acquired faulty vehicle to obtain a second matching degree between the obtained voiceprint features and the target voiceprint features.

[0077] S402. In response to the second matching degree being greater than the second preset threshold, it is determined that the vehicle has malfunctioned.

[0078] The second preset threshold in this embodiment can be understood as a pre-set threshold for judging whether the voiceprint features of the noise audio and the target voiceprint features match. The specific value of the second preset threshold can be set according to the actual situation.

[0079] In this embodiment of the present disclosure, after obtaining the second matching degree between the voiceprint feature and the target voiceprint feature, the vehicle fault reminder device can compare the numerical values ​​of the voiceprint feature and the target voiceprint feature. If the second matching degree is greater than a second preset threshold, it is determined that the voiceprint feature of the noise audio matches the target voiceprint feature of the vehicle that has malfunctioned, and the vehicle has malfunctioned.

[0080] S403. In response to the second matching degree being less than or equal to the second preset threshold, it is determined that the vehicle has not malfunctioned.

[0081] In this embodiment of the present disclosure, after obtaining the second matching degree between the voiceprint feature and the target voiceprint feature, the vehicle fault reminder device can compare the numerical values ​​of the voiceprint feature and the target voiceprint feature. If the second matching degree is less than or equal to a second preset threshold, it is determined that the voiceprint feature of the noise audio does not match the target voiceprint feature of the vehicle that has malfunctioned, and the vehicle has not malfunctioned.

[0082] This embodiment of the present disclosure matches the voiceprint features with pre-acquired target voiceprint features to obtain a second matching degree. The target voiceprint features are the voiceprint features of the vehicle that has malfunctioned. If the second matching degree is greater than a second preset threshold, it is determined that the vehicle has malfunctioned. If the second matching degree is less than or equal to the second preset threshold, it is determined that the vehicle has not malfunctioned. When determining whether a vehicle has malfunctioned based on voiceprint features, the voiceprint features are matched with the target voiceprint features when the vehicle has malfunctioned. Thus, when the voiceprint features of the noise audio match the target voiceprint features, it is determined that the vehicle has malfunctioned, making the judgment result more accurate and further improving driving safety.

[0083] Figure 5 This is a flowchart illustrating a method for determining target voiceprint features according to an embodiment of this disclosure. Figure 5 As shown, based on the above embodiments, the target voiceprint features can be determined by the following method.

[0084] S501. Obtain the vehicle model information.

[0085] The vehicle model information in this embodiment can be understood as vehicle type information. For example, vehicle model information may include fuel vehicles, electric vehicles, hybrid vehicles, trucks, off-road vehicles, sedans, etc., or it may be information about a specific vehicle model, which is not limited here.

[0086] In this embodiment of the disclosure, the vehicle fault reminder device can obtain vehicle model information.

[0087] In one exemplary embodiment of this disclosure, the vehicle fault reminder device can obtain the vehicle model information through the vehicle identification code.

[0088] S502. Based on the correspondence between vehicle model information and fault voiceprint features, determine the target voiceprint features corresponding to the vehicle model information.

[0089] The fault voiceprint features in this embodiment can be understood as the voiceprint features of different vehicle models when a fault occurs.

[0090] In this embodiment of the present disclosure, after obtaining the vehicle model information, the vehicle fault reminder device can determine the fault voiceprint feature corresponding to the model information as the target voiceprint feature based on the pre-stored correspondence between the model information and the fault voiceprint feature.

[0091] This embodiment of the disclosure obtains vehicle model information and determines the target voiceprint feature corresponding to the vehicle model information based on the correspondence between the vehicle model information and the fault voiceprint feature. When matching the obtained voiceprint feature with the target voiceprint feature, the target voiceprint feature corresponding to the vehicle model information can be selected for matching, eliminating the influence of the difference in target voiceprint features between different vehicle models on the matching result, further improving the accuracy of judging vehicle fault conditions and improving driving safety.

[0092] Figure 6 This is a flowchart illustrating a method for determining fault location provided in an embodiment of this disclosure. Figure 6 As shown, based on the above embodiments, the fault location can be determined by the following method.

[0093] S601, acquire noise audio from multiple directions respectively.

[0094] In this embodiment of the present disclosure, the vehicle fault reminder device can acquire noise audio from multiple directions through audio acquisition devices facing multiple directions.

[0095] S602, Obtain the first volume of the first audio corresponding to each noise audio.

[0096] In this embodiment of the present disclosure, the vehicle fault reminder device can, after obtaining multiple noise audios from multiple directions, superimpose each noise audio with the reverse audio of the audio collected when the vehicle is not faulty to obtain multiple first audios, and determine the volume of each first audio as the first volume corresponding to each noise audio.

[0097] S603. Among the various noise audio frequencies, the direction corresponding to the first target noise audio frequency with the highest volume is determined as the direction of the fault location.

[0098] The fault location in this embodiment can be understood as the location where the fault occurs on the vehicle. The fault location can be the precise location of the faulty part or a general range, and is not limited here.

[0099] In this embodiment of the present disclosure, the vehicle fault reminder device can, after obtaining the first volume corresponding to each noise audio, determine the noise audio with the highest first volume as the target noise audio, and determine the acquisition direction of the target noise audio as the direction of the fault location.

[0100] S604. Determine the distance to the fault location based on the first volume corresponding to the target noise audio.

[0101] In this embodiment of the present disclosure, the vehicle fault reminder device can determine the distance between the fault location and the audio acquisition device based on the first volume after determining the target audio and the first volume of the target audio.

[0102] In one exemplary embodiment of this disclosure, the vehicle fault warning device can determine the distance between the fault location and the audio acquisition device based on a pre-trained distance determination model and a first volume level.

[0103] S605. Determine the fault location based on the direction and distance of the fault location.

[0104] In this embodiment of the present disclosure, the vehicle fault reminder device can determine the fault location at a corresponding distance in the corresponding direction after determining the direction and distance of the fault location, starting from the location of the data acquisition device.

[0105] This embodiment of the present disclosure acquires noise audio from multiple directions, obtains the first volume of the first audio corresponding to each noise audio, and determines the direction corresponding to the target noise audio with the highest first volume as the direction of the fault location. The distance of the fault location is determined based on the first volume corresponding to the target noise audio. Based on the direction and distance of the fault location, the approximate location of the fault on the vehicle can be calculated based on the volume of the first audio, thereby enabling targeted troubleshooting during subsequent vehicle maintenance, improving maintenance efficiency, and further reducing maintenance costs.

[0106] Figure 7 This is a flowchart illustrating a method for marking fault locations according to an embodiment of this disclosure. For example... Figure 7 As shown, based on the above embodiments, the fault location can be marked using the following method.

[0107] S701. Based on the fault location, add annotation information to the pre-acquired vehicle structure diagram.

[0108] The annotation information in this embodiment can be understood as information that marks the target location or target object in the image using a bounding box.

[0109] In this embodiment of the present disclosure, the vehicle fault reminder device can add annotation information to the fault location in the pre-acquired vehicle structure diagram after determining the fault location. Specifically, the target location can be marked by an identifier box.

[0110] S702. Display the vehicle structure diagram containing the labeled information.

[0111] In this embodiment of the present disclosure, the vehicle fault reminder device can display the vehicle structure diagram with added annotation information through a display device, such as an in-vehicle screen, after adding annotation information to the vehicle structure diagram.

[0112] This embodiment of the disclosure adds annotation information to a pre-acquired vehicle structure diagram based on the fault location, and displays a vehicle structure diagram containing the annotation information. This allows for an intuitive display of the location of the vehicle fault through images, making it easier for drivers or other relevant personnel to understand the vehicle's fault situation, improving subsequent maintenance efficiency, and further reducing maintenance costs.

[0113] Figure 8 This is a schematic diagram of the structure of a vehicle fault warning device provided in an embodiment of this disclosure. Figure 8 As shown, the vehicle fault reminder device 800 includes: an acquisition module 810, an extraction module 820, a judgment module 830, and a reminder module 840. The acquisition module 810 is used to acquire noise audio after the vehicle starts; the extraction module 820 is used to extract the voiceprint features of the noise audio from the noise audio; the judgment module 830 is used to determine whether the vehicle has malfunctioned based on the voiceprint features; and the reminder module 840 is used to send a reminder message in response to the vehicle malfunctioning.

[0114] Optionally, the judgment module 830 includes: a first matching unit, configured to perform matching processing on the voiceprint feature and pre-acquired historical voiceprint features to obtain a first matching degree between the voiceprint feature and the historical voiceprint features; a first determining unit, configured to determine that the vehicle has not malfunctioned in response to the first matching degree being greater than or equal to a first preset threshold; and a second determining unit, configured to determine that the vehicle has malfunctioned in response to the first matching degree being less than the first preset threshold.

[0115] Optionally, the vehicle fault reminder device 800 further includes: an overlay module, used to overlay the pre-acquired reverse audio of the vehicle with the noise audio to obtain a first audio, wherein the reverse audio is the reverse audio of the audio collected when the vehicle is not faulty; the extraction module 820 is specifically used to: extract the voiceprint features of the first audio from the first audio based on a preset voiceprint feature extraction model.

[0116] Optionally, the judgment module 830 includes: a second matching unit, configured to match the voiceprint feature with a pre-acquired target voiceprint feature to obtain a second matching degree, wherein the target voiceprint feature is the voiceprint feature of a vehicle that has malfunctioned; a third determining unit, configured to determine that the vehicle has malfunctioned in response to the second matching degree being greater than a second preset threshold; and a fourth determining unit, configured to determine that the vehicle has not malfunctioned in response to the second matching degree being less than or equal to the second preset threshold.

[0117] Optionally, the vehicle fault reminder device 800 further includes: a vehicle model acquisition module for acquiring vehicle model information; and a determination module for determining the target voiceprint feature corresponding to the vehicle model information based on the correspondence between the vehicle model information and the fault voiceprint feature.

[0118] Optionally, the acquisition module 810 is specifically used to: acquire noise audio from multiple directions respectively; the vehicle fault reminder device 800 further includes: a volume acquisition module, used to acquire the first volume of the first audio corresponding to each noise audio; a direction determination module, used to determine the direction corresponding to the target noise audio with the highest first volume among the noise audio as the direction where the fault location is located; a distance determination module, used to determine the distance of the fault location based on the first volume corresponding to the target noise audio; and a location determination module, used to determine the fault location based on the direction and distance where the fault location is located.

[0119] Optionally, the vehicle fault reminder device 800 further includes: a labeling module, used to add labeling information to a pre-acquired vehicle structure diagram based on the fault location; and a display module, used to display the vehicle structure diagram containing the labeling information.

[0120] The vehicle fault reminder device provided in this embodiment can perform the method described in any of the above embodiments. Its execution method and beneficial effects are similar, and will not be repeated here.

[0121] Figure 9 This is a schematic diagram of the structure of a computer device provided in an embodiment of this disclosure.

[0122] like Figure 9 As shown, the computer device may include a processor 910 and a memory 920 storing computer program instructions.

[0123] Specifically, the processor 910 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0124] Memory 920 may include a large-capacity storage for information or instructions. For example, and not limitingly, memory 920 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 920 may include removable or non-removable (or fixed) media. Where appropriate, memory 920 may be internal or external to the integrated gateway device. In a particular embodiment, memory 920 is a non-volatile solid-state memory. In a particular embodiment, memory 920 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (Electrically Programmable ROM, EPROM), an electrically erasable programmable PROM (EEPROM), an electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0125] The processor 910 reads and executes computer program instructions stored in the memory 920 to perform the steps of the vehicle fault reminder method provided in this embodiment of the present disclosure.

[0126] In one example, the computer device may also include a transceiver 930 and a bus 940. Wherein, as... Figure 9As shown, the processor 910, memory 920 and transceiver 930 are connected via bus 940 and communicate with each other.

[0127] Bus 940 may include hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 940 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0128] This disclosure also provides a computer-readable storage medium that can store a computer program. When the computer program is executed by a processor, the processor implements the vehicle fault reminder method provided in this disclosure.

[0129] The aforementioned storage medium may, for example, include a memory 920 containing computer program instructions, which can be executed by the processor 910 of the vehicle fault warning device to complete the vehicle fault warning method provided in this embodiment. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), compact disc-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device. The aforementioned computer program may be written in any combination of one or more programming languages ​​to perform the operations of this embodiment. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code may be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0130] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0131] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle fault alert method, characterized in that, include: Acquire the noise audio after the vehicle starts; Extract the voiceprint features of the noise audio from the noise audio; Based on the voiceprint characteristics, it is determined whether the vehicle has malfunctioned; In response to a malfunction in the vehicle, an alert message is sent; Before extracting the voiceprint features of the noise audio from the noise audio, the method includes: The reverse audio of the vehicle acquired in advance is superimposed with the noise audio to obtain the first audio, wherein the reverse audio is the reverse audio of the audio collected when the vehicle is not malfunctioning; Extracting the voiceprint features of the noise audio from the noise audio includes: Based on a preset voiceprint feature extraction model, the voiceprint features of the first audio are extracted from the first audio. The step of determining whether the vehicle has malfunctioned based on the voiceprint features includes: The voiceprint features are matched with the pre-acquired target voiceprint features to obtain a second matching degree, wherein the target voiceprint features are the voiceprint features of the vehicle that has malfunctioned. If the second matching degree is greater than a second preset threshold, it is determined that the vehicle has malfunctioned; If the second matching degree is less than or equal to the second preset threshold, it is determined that the vehicle has not malfunctioned. Before performing the matching process between the voiceprint features and the pre-acquired target voiceprint features to obtain the second matching degree, the method further includes: Obtain the vehicle model information; Based on the correspondence between vehicle model information and fault voiceprint features, the target voiceprint features corresponding to the vehicle model information are determined. The acquisition of noise audio after vehicle startup includes: Acquire noise audio from multiple directions respectively; The method further includes responding to a vehicle malfunction by: Get the first volume of the first audio corresponding to each noise audio; Among the various noise audio frequencies, the direction corresponding to the first target noise audio frequency with the highest volume is determined as the direction of the fault location; The distance to the fault location is determined based on the first volume corresponding to the target noise audio. The fault location is determined based on the direction and distance of the fault location.

2. The method according to claim 1, characterized in that, The step of determining whether the vehicle has malfunctioned based on the voiceprint features includes: The voiceprint features are matched with the pre-acquired historical voiceprint features to obtain the first matching degree between the voiceprint features and the historical voiceprint features; If the first matching degree is greater than or equal to a first preset threshold, it is determined that the vehicle has not malfunctioned. If the first matching degree is less than the first preset threshold, then it is determined that the vehicle has malfunctioned.

3. The method according to claim 1, characterized in that, After determining the fault location based on the direction and distance of the fault location, the method further includes: Based on the location of the fault, add annotation information to the pre-acquired vehicle structure diagram; Display a vehicle structure diagram containing the labeled information.

4. A vehicle fault warning device, characterized in that, include: The acquisition module is used to acquire the noise audio after the vehicle starts; An extraction module is used to extract the voiceprint features of the noise audio from the noise audio; The judgment module is used to determine whether the vehicle has malfunctioned based on the voiceprint characteristics. The reminder module is used to send a reminder message in response to a vehicle malfunction. The vehicle fault reminder device further includes: an overlay module, used to overlay the pre-acquired reverse audio of the vehicle with the noise audio to obtain a first audio, wherein the reverse audio is the reverse audio of the audio collected when the vehicle is not faulty; the extraction module is specifically used to: extract the voiceprint features of the first audio from the first audio based on a preset voiceprint feature extraction model. The judgment module includes: a second matching unit, used to match the voiceprint feature with a pre-acquired target voiceprint feature to obtain a second matching degree, wherein the target voiceprint feature is the voiceprint feature of a vehicle that has malfunctioned; a third determining unit, used to determine that the vehicle has malfunctioned in response to the second matching degree being greater than a second preset threshold; and a fourth determining unit, used to determine that the vehicle has not malfunctioned in response to the second matching degree being less than or equal to the second preset threshold. The vehicle fault reminder device further includes: a vehicle model acquisition module for acquiring vehicle model information; and a determination module for determining the target voiceprint feature corresponding to the vehicle model information based on the correspondence between the vehicle model information and the fault voiceprint feature. The acquisition module is specifically used to: acquire noise audio from multiple directions respectively; the vehicle fault reminder device further includes: a volume acquisition module, used to acquire the first volume of the first audio corresponding to each noise audio; a direction determination module, used to determine the direction corresponding to the target noise audio with the highest first volume among the noise audio as the direction where the fault location is located; a distance determination module, used to determine the distance of the fault location based on the first volume corresponding to the target noise audio; and a location determination module, used to determine the fault location based on the direction and distance where the fault location is located.

5. A computer device, characterized in that, include: Memory; processor; And a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the vehicle fault reminder method as described in any one of claims 1-3.

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