CN113945393A - Vehicle safety early warning method and device, electronic equipment and storage medium - Google Patents
Vehicle safety early warning method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113945393A CN113945393A CN202111217928.1A CN202111217928A CN113945393A CN 113945393 A CN113945393 A CN 113945393A CN 202111217928 A CN202111217928 A CN 202111217928A CN 113945393 A CN113945393 A CN 113945393A
- Authority
- CN
- China
- Prior art keywords
- target
- vehicle
- abnormal
- audio signal
- target part
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 230000005236 sound signal Effects 0.000 claims abstract description 66
- 230000002159 abnormal effect Effects 0.000 claims abstract description 47
- 230000005856 abnormality Effects 0.000 claims description 33
- 238000012549 training Methods 0.000 claims description 32
- 238000012544 monitoring process Methods 0.000 claims description 19
- 238000007781 pre-processing Methods 0.000 claims description 10
- 230000003993 interaction Effects 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 2
- 238000012806 monitoring device Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 230000008439 repair process Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000002372 labelling Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
Abstract
The invention provides a safety early warning method and device for a vehicle, electronic equipment and a storage medium, wherein the safety early warning method comprises the following steps: acquiring a target audio signal, wherein the target audio signal represents the sound emitted by a target part of a target vehicle when the target part works; and judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
Description
Technical Field
The present invention relates to the field of vehicles, and in particular, to a method and an apparatus for vehicle safety warning, an electronic device, and a storage medium.
Background
Various working parts such as an engine, a brake device and the like are arranged in the vehicle, however, along with the accumulation of working time, the parts are all possible to generate abnormity, and if the generated abnormity is not sufficiently concerned and timely treated, various accidents (such as brake failure, engine breakdown and the like) are possibly caused.
In the prior art, in order to determine whether an abnormality occurs in a middle part of a vehicle, the vehicle can be conveyed to a maintenance place, and then a special instrument or a professional is used for detecting a component, so that whether the abnormality occurs is judged.
Disclosure of Invention
The invention provides a safety early warning method and device for a vehicle, electronic equipment and a storage medium, and aims to solve the problem that means for timely detecting whether abnormity occurs in the daily vehicle using process is lacked.
According to a first aspect of the present invention, there is provided a safety warning method for a vehicle, comprising:
acquiring a target audio signal, wherein the target audio signal represents the sound emitted by a target part of a target vehicle when the target part works;
and judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
Optionally, the determining whether the target portion of the target vehicle is abnormal includes:
and inputting the target audio signal or the signal characteristic information thereof into a trained abnormity judgment model so as to judge whether the target part of the target vehicle is abnormal or not by using the abnormity judgment model.
Optionally, the safety warning method for a vehicle is characterized by further comprising:
and judging the abnormal type of the target part of the target vehicle by using the abnormal judgment model.
Optionally, the abnormality determination model is trained based on training samples: the training samples are formed based on audio signals for training, and the audio signals for training are acquired through a terminal when a target part of a vehicle is abnormal and works.
Optionally, the acquiring the target audio signal includes:
acquiring an audio monitoring signal; the audio monitoring signal is obtained by monitoring the sound emitted by the target part of the target vehicle when the target part of the target vehicle works;
and preprocessing the audio monitoring signal to obtain the target audio signal, wherein the preprocessing comprises filtering.
Optionally, the target site includes a motor and/or a brake device.
Optionally, after determining whether the target portion of the target vehicle is abnormal based on the target audio signal, the method further includes:
and if the target part of the target vehicle is abnormal, feeding back the abnormal target part to the user through a human-computer interaction module.
According to a second aspect of the present invention, there is provided a safety warning apparatus for a vehicle, comprising:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring a target audio signal which represents the sound emitted by a target part of a target vehicle when the target part works;
and the abnormity judging module is used for judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
According to a third aspect of the invention, there is provided an electronic device comprising a processor and a memory,
the memory is used for storing codes;
the processor is configured to execute the code in the memory to implement the method according to the first aspect and its alternatives.
According to a fourth aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, carries out the method of the first aspect and its alternatives.
According to the vehicle safety early warning method, the vehicle safety early warning device, the electronic equipment and the storage medium, whether the abnormality occurs can be judged based on the sound emitted when the target part of the target vehicle works after the target audio signal is obtained, and the emitted sound is usually special when the part is abnormal.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a first flowchart illustrating a safety precaution method for a vehicle according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating step S11 according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating step S12 according to an embodiment of the present invention;
FIG. 4 is a second flowchart illustrating a safety precaution method for a vehicle according to an embodiment of the invention;
FIG. 5 is a first block diagram illustrating the first process steps of a vehicle safety warning device according to an embodiment of the present invention;
FIG. 6 is a second schematic diagram of the program modules of the vehicle safety precaution device in one embodiment of the invention;
fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
The safety early warning method for the vehicle provided by the embodiment of the invention can be applied to the vehicle (such as a vehicle machine), a server and a terminal. Meanwhile, when the safety early warning method of the vehicle is realized, an audio monitoring device can be adopted, the audio monitoring device can be fixedly assembled on the vehicle and also can be detachably arranged on the vehicle, and the installation position of the audio monitoring device can be adapted to the audio signal of the monitored target part. The audio monitoring device may communicate directly or indirectly with an execution subject of a safety precaution method of the vehicle.
The target area may be any area of the vehicle where sound may occur during operation, and may include, for example, an engine and/or brakes.
The vehicle requiring a safety precaution is understood to be the target vehicle, which may be any model, type, make of vehicle.
Referring to fig. 1, an embodiment of the present invention provides a vehicle safety warning method, including:
s11: acquiring a target audio signal;
s12: and judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
The target audio signal represents a sound emitted by a target part of a target vehicle when the target part works; the target audio signal may be an audio signal collected by an audio monitoring device, or may be obtained after preprocessing the audio monitoring signal.
Therefore, referring to fig. 2, step S11 may include:
s111: acquiring an audio monitoring signal;
the audio monitoring signal is obtained by monitoring the sound emitted by the target part of the target vehicle when the target part of the target vehicle works; specifically, the information can be monitored by an audio monitoring device;
s112: and preprocessing the audio monitoring signal to obtain the target audio signal.
The pre-processing may include filtering, for example, audio signals in a partial frequency band (e.g., an apparently unrelated frequency band) may be filtered out, and for example, signals originating from a partial azimuth may be filtered out.
In one example, the filtering of the pre-processing may further be, for example: and taking the audio signal monitored by the audio monitoring device when the target part is not in operation as a background signal, and subtracting the background signal from the audio monitoring signal to obtain a target audio signal. Further, whether the target part works or not can be monitored, and then the audio signal which is monitored last time before the target part starts to work is extracted as the background signal. By the method, the audio signal of the target part can be accurately and effectively extracted.
According to the scheme, whether the abnormality occurs can be judged based on the sound emitted by the target part of the target vehicle during working after the target audio signal is acquired, and the emitted sound is usually quite special when the abnormality occurs at the part.
In one embodiment, referring to fig. 3, step S12 may include:
s121: and inputting the target audio signal or the signal characteristic information thereof into a trained abnormity judgment model so as to judge whether the target part of the target vehicle is abnormal or not by using the abnormity judgment model.
The abnormality determination model may be any model trained to determine whether an abnormality occurs, for example, the abnormality determination model may be implemented by using a neural network, and the implemented function of the abnormality determination model depends on a training sample for training the abnormality determination model and a label (or may be understood as a label) corresponding to the training sample.
Specifically, the abnormality determination model is trained based on training samples: the training samples are formed based on audio signals for training, and the audio signals for training are acquired through a terminal when a target part of a vehicle is abnormal and works.
In practical applications, taking the engine as an example of the target region, the training audio signal may be, for example:
when the owner knows the problem (namely abnormality) of the engine definitely, the owner can record the sound of the engine by using a terminal (such as a mobile phone) to obtain a corresponding audio signal and upload the audio signal to a server; furthermore, the audio signal can be used as the audio signal for training or extracted from the audio signal for training;
when a vehicle owner goes to repair the vehicle, a professional vehicle repair master can check and judge the engine, and then whether the vehicle repair can use a terminal (such as a mobile phone) to record the engine sound aiming at the abnormal engine so as to obtain a corresponding audio signal and upload the audio signal to a server; furthermore, the audio signal can be used as the audio signal for training or extracted from the audio signal for training;
in addition, no matter which way, the corresponding professional driver of the vehicle can be requested to carry out secondary data labeling, and only the part of the audio belonging to the vehicle is required to be labeled to be sent out, so that whether the audio is abnormal or not can be judged, the training sample after labeling can be obtained on the basis, and the training of the abnormal judgment model can be realized by inputting the training sample into the abnormal judgment model.
In some embodiments, if a proper training sample and a corresponding label are configured during training, it can be determined whether or not an abnormality occurs in the target region, and the type of the abnormality, that is: step S12 may further include: and judging the abnormal type of the target part of the target vehicle by using the abnormal judgment model. For example, when labeling, a specific exception type may also be labeled.
In addition, different abnormality determination models can be trained and determined for different target portions and different types (or different manufacturers) of vehicles.
Therefore, in the scheme, the voice recognition of key parts of the vehicle such as a brake and an engine is completed by using a deep learning technology, so that the intelligent safety early warning of the vehicle is achieved, and accidents such as brake failure, engine breakdown and the like in the driving process are reduced.
In one embodiment, referring to fig. 4, after step S12, the method further includes:
s131: and if the target part of the target vehicle is abnormal, feeding back the abnormal target part to the user through a human-computer interaction module.
The man-machine interaction module can be any module capable of realizing man-machine interaction, such as a display screen, a voice playing device, an instrument and the like, and can also be a mobile terminal of a user.
In a specific example, the judgment result of the neural network is fed back to the vehicle owner in real time, and when the judgment result is abnormal, the vehicle owner automatically selects to stop the vehicle for rescue or drive the vehicle to a nearby repair shop for secondary inspection.
The scheme of the embodiment of the invention is positioned in the auxiliary early warning, the acceptable error rate is high, for example, the vehicle can go to a vehicle repair factory for secondary inspection through the early warning of the scheme for many times, but only one detection result is required to be consistent with the scheme identification result, and the occurrence of safety accidents is avoided.
In one embodiment, in step S11, the target audio signal (or audio monitoring signal) may be collected once every specified time period, and the length of the specified time period may vary with the number of times and/or frequency (the number of times that the target portion is determined to be abnormal per unit time) that the target portion is determined to be abnormal, for example, the more the times, the shorter the specified time period, the less the times, the longer the specified time period, and for example, the higher the frequency, the shorter the specified time period, the lower the frequency, and the shorter the specified time period. Meanwhile, in one example, the number and/or frequency may be manually cleared, and in another example, the number and/or frequency may be cleared after a set period of time has elapsed (e.g., once per week).
In one embodiment, since the abnormality of the engine and the brake is often caused by an accident, the step S11 of obtaining the target audio signal may be started only when the current vehicle accident is detected, and the subsequent steps S12 and S13 are executed.
In one embodiment, in step S12, since the external appearance of the target portion abnormality may be different under different environments and occasions, for example, the external appearance (represented by the audio signal) of the brake abnormality in rainy days and in non-rainy days may be different, and the external appearance (represented by the audio signal) of the brake abnormality in snowy days and in non-snowy days may be different, different abnormality determination models may be distinguished based on different conditions (at least one of weather, date, geographical range, etc.), for example, different weather conditions (for example, rainy days and sunny days may be regarded as different weather conditions), and then, in step S12, the matched abnormality determination model may be determined based on the current actual conditions, and whether the target portion of the target vehicle is abnormal or not may be determined by using the matched abnormality determination model, for example, if the current actual condition indicates that the current day is a sunny day, the abnormal determination model in the sunny day may be determined to be the matched abnormal determination model.
Furthermore, in this way, the accuracy of the determination can be improved by a finer design.
In one embodiment, in step S12, the signal characteristic information may be input into the abnormality determination model to determine whether the target portion of the target vehicle is abnormal, and the signal characteristic information may include the signal characteristic of the target audio signal, and may further include a vehicle characteristic of the target vehicle and/or an environmental characteristic of an environment where the vehicle is located.
For example, in the training, the signal characteristics of the audio signal for training, the vehicle characteristics (such as brand, model, type, and displacement) of the corresponding vehicle, and the environmental characteristics of the environment (such as weather and road type) of the corresponding vehicle may be extracted, the combined characteristics and the label may be input into the abnormality determination model after the characteristics are combined and the label (such as the label representing the abnormality of the target portion) is added thereto, so as to implement the training of the abnormality determination model.
In the scheme, the differences of different vehicles and environments can be fully distinguished, and the universality and the accuracy of the abnormal recognition are guaranteed.
Referring to fig. 5, an embodiment of the present invention further provides a vehicle safety precaution device 2, including:
an obtaining module 21, configured to obtain a target audio signal, where the target audio signal represents a sound emitted by a target portion of a target vehicle when the target portion works;
and an abnormality determination module 22, configured to determine whether an abnormality occurs in a target portion of the target vehicle based on the target audio signal.
Optionally, the abnormality determining module 22 is specifically configured to:
and inputting the target audio signal or the signal characteristic information thereof into a trained abnormity judgment model so as to judge whether the target part of the target vehicle is abnormal or not by using the abnormity judgment model.
Optionally, the abnormality determining module 22 is further configured to:
and judging the abnormal type of the target part of the target vehicle by using the abnormal judgment model.
Optionally, the abnormality determination model is trained based on training samples: the training samples are formed based on audio signals for training, and the audio signals for training are acquired through a terminal when a target part of a vehicle is abnormal and works.
Optionally, the obtaining module 21 is specifically configured to:
acquiring an audio monitoring signal; the audio monitoring signal is obtained by monitoring the sound emitted by the target part of the target vehicle when the target part of the target vehicle works;
and preprocessing the audio monitoring signal to obtain the target audio signal, wherein the preprocessing comprises filtering.
Optionally, the target site includes a motor and/or a brake device.
Optionally, referring to fig. 6, the vehicle safety precaution device 2 further includes:
and the feedback module 23 is configured to, if the target portion of the target vehicle is abnormal, feed back the abnormal target portion to the user through the human-computer interaction module.
Referring to fig. 7, an electronic device 30 is provided, which includes:
a processor 31; and the number of the first and second groups,
a memory 32 for storing executable instructions of the processor;
wherein the processor 31 is configured to perform the above-mentioned method via execution of the executable instructions.
The processor 31 is capable of communicating with the memory 32 via a bus 33.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the above-mentioned method.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A safety early warning method for a vehicle, comprising:
acquiring a target audio signal, wherein the target audio signal represents the sound emitted by a target part of a target vehicle when the target part works;
and judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
2. The vehicle safety warning method according to claim 1,
the judging whether the target part of the target vehicle is abnormal or not comprises the following steps:
and inputting the target audio signal or the signal characteristic information thereof into a trained abnormity judgment model so as to judge whether the target part of the target vehicle is abnormal or not by using the abnormity judgment model.
3. The vehicle safety warning method according to claim 2, further comprising:
and judging the abnormal type of the target part of the target vehicle by using the abnormal judgment model.
4. The vehicle safety warning method according to claim 2,
the abnormality judgment model is trained based on training samples: the training samples are formed based on audio signals for training, and the audio signals for training are acquired through a terminal when a target part of a vehicle is abnormal and works.
5. The vehicle safety warning method according to any one of claims 1 to 4,
the acquiring of the target audio signal includes:
acquiring an audio monitoring signal; the audio monitoring signal is obtained by monitoring the sound emitted by the target part of the target vehicle when the target part of the target vehicle works;
and preprocessing the audio monitoring signal to obtain the target audio signal, wherein the preprocessing comprises filtering.
6. The vehicle safety precaution method according to any one of claims 1 to 4, wherein the target site includes an engine and/or a brake device.
7. The vehicle safety warning method according to any one of claims 1 to 4,
after determining whether the target portion of the target vehicle is abnormal based on the target audio signal, the method further includes:
and if the target part of the target vehicle is abnormal, feeding back the abnormal target part to the user through a human-computer interaction module.
8. A safety warning device for a vehicle, comprising:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring a target audio signal which represents the sound emitted by a target part of a target vehicle when the target part works;
and the abnormity judging module is used for judging whether the target part of the target vehicle is abnormal or not based on the target audio signal.
9. An electronic device, comprising a processor and a memory,
the memory is used for storing codes;
the processor to execute code in the memory to implement the method of any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program which, when executed by a processor, carries out the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111217928.1A CN113945393A (en) | 2021-10-19 | 2021-10-19 | Vehicle safety early warning method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111217928.1A CN113945393A (en) | 2021-10-19 | 2021-10-19 | Vehicle safety early warning method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113945393A true CN113945393A (en) | 2022-01-18 |
Family
ID=79331519
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111217928.1A Pending CN113945393A (en) | 2021-10-19 | 2021-10-19 | Vehicle safety early warning method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113945393A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106596123A (en) * | 2016-11-22 | 2017-04-26 | 东软集团股份有限公司 | Device fault diagnosis method, device fault diagnosis device, and device fault diagnosis system |
| CN109785460A (en) * | 2019-01-03 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Vehicle trouble recognition methods, device, computer equipment and storage medium |
| CN111829649A (en) * | 2019-04-23 | 2020-10-27 | 罗伯特·博世有限公司 | Vehicle state monitoring method, noise monitoring module and vehicle |
| CN113450826A (en) * | 2020-03-26 | 2021-09-28 | 丰田自动车株式会社 | Abnormal sound generation location specifying method, non-temporary storage medium, and in-vehicle device |
-
2021
- 2021-10-19 CN CN202111217928.1A patent/CN113945393A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106596123A (en) * | 2016-11-22 | 2017-04-26 | 东软集团股份有限公司 | Device fault diagnosis method, device fault diagnosis device, and device fault diagnosis system |
| CN109785460A (en) * | 2019-01-03 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Vehicle trouble recognition methods, device, computer equipment and storage medium |
| CN111829649A (en) * | 2019-04-23 | 2020-10-27 | 罗伯特·博世有限公司 | Vehicle state monitoring method, noise monitoring module and vehicle |
| CN113450826A (en) * | 2020-03-26 | 2021-09-28 | 丰田自动车株式会社 | Abnormal sound generation location specifying method, non-temporary storage medium, and in-vehicle device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20240013588A1 (en) | System, method, and computer-readable medium for facilitating treatment of a vehicle damaged in a crash | |
| US9721399B2 (en) | Vehicle diagnosing apparatus, vehicle diagnosing system, and diagnosing method | |
| CN105913059B (en) | Automatic identification system for vehicle VIN code and control method thereof | |
| US20150363983A1 (en) | Determining a remedial action for a motorized vehicle based on sensed vibration | |
| CN113902233A (en) | Vehicle safety early warning method, big data platform device, vehicle-mounted terminal and vehicle | |
| CN115742954A (en) | Vehicle fault reminding method, device, equipment and storage medium | |
| CN109466473B (en) | Vehicle machine fault detection method and device | |
| CN110853306A (en) | Vehicle anomaly detection and rescue system and method | |
| CN115577151A (en) | Vehicle fault real-time diagnosis method and device, electronic equipment and storage medium | |
| CN111881808A (en) | Method for identifying abnormal operation behaviors of driver in starting stage of electric bus based on continuous tracking data | |
| CN114616441A (en) | Method for evaluating an external event on a vehicle glazing | |
| CN111158350A (en) | Quality monitoring platform and system based on diagnosis | |
| CN108254199B (en) | Vehicle health prediction method, device and equipment | |
| CN113945393A (en) | Vehicle safety early warning method and device, electronic equipment and storage medium | |
| CN112132448A (en) | Car life cycle management system | |
| CN111855230A (en) | Vehicle detection method and related equipment | |
| CN107861980A (en) | A kind of vehicle identification method and its terminal | |
| CN116775464A (en) | Whole vehicle testing method and system | |
| CN111145380A (en) | Reported data processing method and device adaptive to vehicle-mounted equipment and electronic equipment | |
| CN114564002B (en) | Method and device for quickly diagnosing lost packet and computer equipment | |
| CN114407585B (en) | Tire pressure sensor address writing method and device, electronic equipment and storage medium | |
| CN113561710B (en) | Automobile tire diagnosis method and system | |
| CN112185058B (en) | Monitoring alarm method, system, equipment and storage medium | |
| CN115265566A (en) | Automatic driving positioning data collecting and processing method, device, medium and vehicle | |
| CN110987448B (en) | Engine air inlet state monitoring method, device and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |