CN113942461A - Fault detection method, device and readable storage medium - Google Patents
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- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
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Abstract
The application provides a fault detection method, a fault detection device and a readable storage medium, wherein the fault detection method comprises the following steps: acquiring noise data in a vehicle acquired through a vehicle-mounted microphone; carrying out spectrum analysis on the noise data to obtain a spectrum analysis result; and detecting whether a target component of the vehicle breaks down or not based on a preset strategy according to the spectrum analysis result. According to the fault detection method, the fault detection device and the readable storage medium, whether the part of the vehicle breaks down or not is detected through the noise data in the vehicle collected by the vehicle-mounted microphone, the fault detection can be accurately and rapidly performed on the vehicle under the condition that the sound collection equipment is not additionally arranged, and the driving safety can be improved.
Description
Technical Field
The present application relates to the field of vehicle technologies, and in particular, to a fault detection method and apparatus, and a readable storage medium.
Background
At present, in order to pursue better acceleration, the torque and the power of the motor are continuously increased, so that the size of a rotor of the motor is increased, the influence of concentricity can be amplified due to the increase of the axial size, the influence of electromagnetic error can be amplified due to the increase of the circumferential size, the redundancy of a motor bearing is reduced, the motor bearing is damaged in the operation process, and the motor bearing fault is generated.
At present, no online detection method is available for motor bearing faults, and the problems can be found only when huge noise generated by serious damage is sensed or a vehicle cannot normally run due to the fact that a motor breaks down, or even the vehicle breaks down. However, in the prior art, how to effectively and accurately detect a vehicle failure is always under study.
Disclosure of Invention
The application provides a fault detection method, a fault detection device and a readable storage medium, wherein whether a part of a vehicle breaks down or not is detected through noise data in the vehicle collected by a vehicle-mounted microphone, and the fault detection can be accurately and quickly carried out on the vehicle under the condition that sound collection equipment is not additionally arranged, so that the driving safety can be improved.
In one aspect, the present application provides a fault detection method, specifically, the fault detection method includes: acquiring noise data in a vehicle acquired through a vehicle-mounted microphone; carrying out spectrum analysis on the noise data to obtain a spectrum analysis result; and detecting whether a target component of the vehicle breaks down or not based on a preset strategy according to the spectrum analysis result.
Optionally, the step S101 in the fault detection method includes: the acquiring noise data in the vehicle collected by the on-board microphone includes:
detecting whether the vehicle-mounted microphone is in a voice interaction state;
and when the vehicle-mounted microphone is not in a voice interaction state, triggering the vehicle-mounted microphone to acquire noise data in the vehicle.
Optionally, the performing spectral analysis on the noise data to obtain a spectral analysis result includes:
and carrying out Fourier transform on the noise data to obtain the order of various types of noise in the noise data and the frequency and amplitude corresponding to the order.
Optionally, the detecting, according to the spectrum analysis result, whether a target component of the vehicle is faulty based on a preset strategy includes:
determining a target order of noise emitted by a target component of the vehicle and a target amplitude corresponding to the target order according to the order of various types of noise in the noise data and/or the frequency corresponding to the order;
detecting whether the target order and the target amplitude are respectively matched with a preset order and a preset amplitude;
if yes, determining that the target component does not have a fault;
and if not, determining that the target component has a fault. .
Optionally, after determining that the target component fails, the method includes:
outputting a prompt message including an operational prompt for resolving the fault present in the target component.
Optionally, after detecting whether a target component of the vehicle is faulty based on a preset strategy according to the result of the spectrum analysis, the method includes:
counting the frequency of the target component failing within a preset first time period;
and when the frequency is determined to be greater than or equal to a preset frequency threshold value, sending out fault alarm information aiming at the vehicle.
Optionally, the sending out the fault warning information for the vehicle includes at least one of:
sending fault alarm information aiming at the vehicle to a vehicle networking platform;
and broadcasting fault alarm information aiming at the vehicle to nearby vehicles through the Internet of vehicles.
Optionally, after the sending of the failure warning information for the vehicle, the method includes:
and executing a preset second operation on the vehicle when the preset first operation aiming at the vehicle is not received within a preset second time length.
In another aspect, the present application provides a fault detection apparatus, including: a processor and a memory storing a computer program which, when executed by the processor, implement the steps of the fault detection method as described above.
In another aspect, the present application provides a readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the fault detection method as described above.
As described above, according to the fault detection method, the fault detection device and the readable storage medium provided by the application, whether a component of the vehicle has a fault or not is detected through the noise data in the vehicle acquired by the vehicle-mounted microphone, so that the fault detection can be accurately and quickly performed on the vehicle without additionally arranging a sound acquisition device, and the driving safety can be improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a fault detection method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a fault detection apparatus according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings. With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like 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 application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the recitation of an element by the phrase "comprising an … …" does not exclude the presence of additional like elements in the process, method, article, or apparatus that comprises the element, and further, where similarly-named elements, features, or elements in different embodiments of the disclosure may have the same meaning, or may have different meanings, that particular meaning should be determined by their interpretation in the embodiment or further by context with the embodiment.
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Referring to fig. 1, for the fault detection method provided in the embodiment of the present application, the method may be executed by a fault detection apparatus provided in the embodiment of the present application, the apparatus may be implemented in a software and/or hardware manner, and the apparatus may specifically be a server, a vehicle-mounted electronic device such as a car machine, and the fault detection method provided in this embodiment includes the following steps:
step S101: acquiring noise data in a vehicle acquired through a vehicle-mounted microphone;
it will be appreciated that the source of noise within the vehicle may be various, such as motors, tires, wind, etc., i.e., the noise data may consist of multiple types of noise. Meanwhile, the acquiring of the noise data in the vehicle collected by the on-vehicle microphone may be acquiring of the noise data in the vehicle collected by the on-vehicle microphone in real time, sporadically or periodically.
Alternatively, step S101: acquiring noise data within a vehicle acquired by an onboard microphone, comprising: detecting whether the vehicle-mounted microphone is in a voice interaction state; and when the vehicle-mounted microphone is not in a voice interaction state, triggering the vehicle-mounted microphone to acquire noise data in the vehicle.
It can be understood that when the vehicle-mounted microphone is in a voice interaction state, that is, voice input by a user needs to be collected, it may not be suitable for the vehicle-mounted microphone to collect noise data in the vehicle, so that in order to avoid interference with the vehicle-mounted microphone, the vehicle-mounted microphone is triggered to collect noise data in the vehicle when the vehicle-mounted microphone is not in the voice interaction state, so that the vehicle-mounted microphone can preferentially respond to the user's demand. Specifically, whether the vehicle-mounted microphone is in the voice interaction state can be judged by detecting information such as whether the voice interaction application is awakened or in the working state. Therefore, when the vehicle-mounted microphone is not in a voice interaction state, the vehicle-mounted microphone is triggered to collect noise data in the vehicle, user requirements can be responded preferentially, and user experience can be improved.
Step S102: carrying out spectrum analysis on the noise data to obtain a spectrum analysis result;
alternatively, step S102: performing spectrum analysis on the noise data to obtain a spectrum analysis result, including:
and carrying out Fourier transform on the noise data to obtain the order of various types of noise in the noise data and the frequency and amplitude corresponding to the order.
It is understood that noise is a wave, and the noise data formed by mixing a plurality of types of different noise is a wave of various frequencies and amplitudes, and by performing fourier transform on the noise data, the order of each type of noise in the noise data and the frequency and amplitude corresponding to the order can be obtained. It should be noted that each type of noise may have one or more orders, and each order corresponds to a frequency and an amplitude. For example, taking the example that the noise data includes motor noise, after performing fourier transform on the noise data, different orders of the motor noise, and a frequency and an amplitude corresponding to each order can be obtained, wherein after performing fourier transform on the noise data, a frequency can be obtained first, and a corresponding order is calculated based on a corresponding relationship among the frequency, the order, and a motor frequency, which may be referred to in the prior art and is not described herein again.
Step S103: and detecting whether a target component of the vehicle breaks down or not based on a preset strategy according to the spectrum analysis result.
Alternatively, step S103: according to the spectrum analysis result, whether a target component of the vehicle breaks down or not is detected based on a preset strategy, and the method comprises the following steps:
determining a target order of noise emitted by a target component of the vehicle and a target amplitude corresponding to the target order according to the order and/or the frequency of each type of noise in the noise data;
detecting whether the target order and the target amplitude are respectively matched with a preset order and a preset amplitude;
if yes, determining that the target component does not have a fault;
and if not, determining that the target component has a fault.
It can be understood that, since different noises have different frequencies and orders, the noise data may be divided according to the order and/or frequency of each type of noise to obtain noise data emitted by different noise sources, and then the noise data emitted by one or more noise sources may be analyzed.
Specifically, the determining of the target order of the noise emitted by the target component of the vehicle and the target amplitude corresponding to the target order according to the order and/or the frequency of each type of noise in the noise data may be extracting the noise data emitted by the target component of the vehicle from the noise data according to the order and/or the frequency of each type of noise in the noise data, and further determining the target order of the noise emitted by the target component of the vehicle and the target amplitude corresponding to the target order based on the spectrum analysis result and the noise data emitted by the target component of the vehicle.
The target order may be one or more, and for each target order, there is one target frequency and one target amplitude. The detecting whether the target order and the target amplitude are respectively matched with a preset order and a preset amplitude may be: and detecting whether each target order is the same as a corresponding preset order or not, and whether a target amplitude corresponding to the target order is the same as a corresponding preset amplitude or larger than the corresponding preset amplitude or not, wherein each preset order corresponds to one preset amplitude. If each target order is the same as the corresponding preset order, and the target amplitude corresponding to the target order is the same as or greater than the corresponding preset amplitude, indicating that the target component does not fail; and if at least one target order is different from the corresponding preset order, and/or the target amplitude corresponding to the target order is different from the corresponding preset amplitude or smaller than the corresponding preset amplitude, indicating that the target component has a fault.
Specifically, the target component may be a motor, a bearing, or the like. Taking the target component as an example of a motor, assuming that the preset order of noise when the motor normally works is a multiple of a, and the corresponding amplitude is also a multiple of B, that is, when the order is a, the corresponding amplitude should be B, and when the order is 2A, the corresponding amplitude should be 2B, and so on, if it is detected that the target orders of noise emitted by the motor are a, 2A, and 3A, respectively, and the target amplitudes corresponding to the target orders are also B, 2B, and 3B, respectively, it is described that the motor does not fail; if the target orders of the noise emitted by the motor are detected to be A, 2.5A and 3A respectively, the motor is proved to be in failure.
In summary, according to the fault detection method, the fault detection device and the readable storage medium provided by the application, whether a component of the vehicle has a fault or not is detected through the noise data in the vehicle, which is acquired by the vehicle-mounted microphone, so that the fault detection can be accurately and quickly performed on the vehicle without additionally arranging a sound acquisition device, and the driving safety can be improved.
Optionally, after determining that the target component fails, the method includes:
outputting a prompt message including an operational prompt for resolving the fault present in the target component.
It can be understood that, for some drivers who have insufficient driving experience or do not know about the vehicle, the driver is usually overwhelmed when the vehicle has a fault, and at this time, a prompt message including an operation prompt for solving the fault existing in the target component may be output through a speaker or a display screen of the vehicle, so that the driver of the vehicle can perform a fault-removing operation on the vehicle according to the prompt message, and the user experience can be improved.
Optionally, after detecting whether a target component of the vehicle is faulty based on a preset strategy according to the result of the spectrum analysis, the method includes:
counting the frequency of the target component failing within a preset first time period;
and when the frequency is determined to be greater than or equal to a preset frequency threshold value, sending out fault alarm information aiming at the vehicle.
Here, the first duration may be set according to actual requirements, for example, the first duration may be set to 20 seconds, 50 seconds, or the like. If the number of times of failure of the target component within the preset first time period is greater than or equal to the preset number threshold, it is determined that the target component has failed, and at this time, failure alarm information for the vehicle may be sent, for example, the failure alarm information for the vehicle may be output through a speaker or a display screen of the vehicle, so that a driver of the vehicle may know in time, and thus driving safety may be further improved.
Optionally, the sending out the fault warning information for the vehicle includes at least one of:
sending fault alarm information aiming at the vehicle to a vehicle networking platform;
and broadcasting fault alarm information aiming at the vehicle to nearby vehicles through the Internet of vehicles.
It is to be understood that the failure alarm information may include the vehicle information, such as a color, a model, a license plate, etc. of the vehicle, and may further include target component information that the vehicle has failed, such as a model of a target component, etc. Therefore, the fault alarm information of the vehicle is sent to the Internet of vehicles platform, so that the Internet of vehicles platform can timely know the fault information of the vehicle and timely provide help. And broadcast the fault alarm information to nearby vehicles through the car networking, can make the driver of nearby vehicle notice in advance to dodge the vehicle, also can make nearby vehicle in time to help the vehicle to can further promote driving safety.
Optionally, after the sending of the failure warning information for the vehicle, the method further includes:
and executing a preset second operation on the vehicle when the preset first operation aiming at the vehicle is not received within a preset second time length.
It is understood that, when a target component of the vehicle has a fault, an abnormal condition of the vehicle may occur at any time, for example, an abnormality such as automatic deceleration, flameout, brake failure, etc., and in order to improve the safety of the vehicle, a preset second operation may be performed on the vehicle when it is determined that a preset first operation for the vehicle has not been received within a preset second time period. The first operation and the second operation may be set according to actual needs, for example, the first operation may be a deceleration operation, and the second operation may be a turn-on hazard warning lamp and a deceleration operation, or the first operation may be a parking operation, and the second operation may be a turn-on right turn lamp and a deceleration operation. The second time period may be set according to actual requirements, for example, the second time period may be set to 30 seconds, 60 seconds, or the like. Therefore, when the vehicle breaks down and the user does not timely carry out operations such as troubleshooting or danger avoidance on the vehicle, the driving safety can be further improved by executing the preset operation on the vehicle.
Based on the same inventive concept as the previous embodiment, an embodiment of the present invention provides a fault detection apparatus, as shown in fig. 2, including: a processor 310 and a memory 311 storing computer programs; the processor 310 illustrated in fig. 2 is not used to refer to the number of the processors 310 as one, but is only used to refer to the position relationship of the processor 310 relative to other devices, and in practical applications, the number of the processors 310 may be one or more; similarly, the memory 311 shown in fig. 2 is also used in the same sense, i.e. it is only used to refer to the position relationship of the memory 311 with respect to other devices, and in practical applications, the number of the memory 311 may be one or more. The fault detection method applied to the above-described fault detection apparatus is implemented when the processor 310 runs the computer program.
The fault detection device may further include: at least one network interface 312. The various components of the fault detection apparatus are coupled together by a bus system 313. It will be appreciated that the bus system 313 is used to enable communications among the components connected. The bus system 313 includes a power bus, a control bus, and a status signal bus in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 313 in FIG. 2.
The memory 311 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 311 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 311 in the embodiment of the present invention is used to store various types of data to support the operation of the failure detection apparatus. Examples of such data include: any computer program for operating on the fault detection device, such as operating systems and application programs; contact data; telephone book data; a message; a picture; video, etc. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs may include various application programs such as a Media Player (Media Player), a Browser (Browser), etc. for implementing various application services. Here, the program that implements the method of the embodiment of the present invention may be included in an application program.
Based on the same inventive concept of the foregoing embodiments, the present application further provides a readable storage medium, and in particular, the readable storage medium stores a computer program thereon, where the readable storage medium may be a Memory such as a magnetic random access Memory (FRAM), a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read Only Memory (CD-ROM), and the like; or may be a variety of devices including one or any combination of the above memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc. The computer program stored in the readable storage medium, when executed by a processor, implements the steps of the fault detection method as in the above embodiments. Please refer to the description of the embodiment shown in fig. 1 for a specific step flow realized when the computer program is executed by the processor, which is not described herein again.
According to the fault detection method, the fault detection device and the readable storage medium, whether the part of the vehicle breaks down or not is detected through the noise data in the vehicle collected by the vehicle-mounted microphone, the fault detection can be accurately and rapidly performed on the vehicle under the condition that the sound collection equipment is not additionally arranged, and the driving safety can be improved.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A method of fault detection, comprising:
acquiring noise data in a vehicle acquired through a vehicle-mounted microphone;
carrying out spectrum analysis on the noise data to obtain a spectrum analysis result;
and detecting whether a target component of the vehicle breaks down or not based on a preset strategy according to the spectrum analysis result.
2. The fault detection method of claim 1, wherein said obtaining noise data within the vehicle collected by an onboard microphone comprises:
detecting whether the vehicle-mounted microphone is in a voice interaction state;
and when the vehicle-mounted microphone is not in a voice interaction state, triggering the vehicle-mounted microphone to acquire noise data in the vehicle.
3. The method according to claim 1 or 2, wherein the performing spectral analysis on the noise data to obtain a spectral analysis result comprises:
and carrying out Fourier transform on the noise data to obtain the order of various types of noise in the noise data and the frequency and amplitude corresponding to the order.
4. The fault detection method according to claim 3, wherein the detecting whether the target component of the vehicle is faulty based on a preset strategy according to the result of the spectrum analysis includes:
determining a target order of noise emitted by a target component of the vehicle and a target amplitude corresponding to the target order according to the order and/or the frequency of each type of noise in the noise data;
detecting whether the target order and the target amplitude are respectively matched with a preset order and a preset amplitude;
if yes, determining that the target component does not have a fault;
and if not, determining that the target component has a fault.
5. The fault detection method of claim 4, wherein said determining that the target component has failed comprises:
outputting a prompt message including an operational prompt for resolving the fault present in the target component.
6. The fault detection method according to claim 1, wherein after detecting whether a target component of the vehicle is faulty based on a preset strategy according to the result of the spectrum analysis, the method comprises:
counting the frequency of the target component failing within a preset first time period;
and when the frequency is determined to be greater than or equal to a preset frequency threshold value, sending out fault alarm information aiming at the vehicle.
7. The fault detection method according to claim 6, wherein said issuing fault alarm information for the vehicle includes at least one of:
sending fault alarm information aiming at the vehicle to a vehicle networking platform;
and broadcasting fault alarm information aiming at the vehicle to nearby vehicles through the Internet of vehicles.
8. The failure detection method according to claim 6, said issuing failure warning information for the vehicle being followed by:
and executing a preset second operation on the vehicle when the preset first operation aiming at the vehicle is not received within a preset second time length.
9. A fault detection device, comprising: a processor and a memory storing a computer program which, when executed by the processor, implement the steps of the fault detection method of any one of claims 1 to 8.
10. A readable storage medium, characterized in that the readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the fault detection method according to any one of claims 1 to 8.
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| CN110006672A (en) * | 2019-04-09 | 2019-07-12 | 唐山百川智能机器股份有限公司 | Rail vehicle fault monitoring method based on acoustic imaging technology |
| CN110572764A (en) * | 2019-09-19 | 2019-12-13 | 吉旗物联科技（上海）有限公司 | Remote fault diagnosis method and device for vehicle-mounted audio equipment |
| CN112068076A (en) * | 2020-08-28 | 2020-12-11 | 深圳市元征科技股份有限公司 | Method and device for displaying abnormal sound position of vehicle, vehicle-mounted terminal and storage medium |
| CN113464272A (en) * | 2021-06-30 | 2021-10-01 | 湖南道依茨动力有限公司 | Method and system for monitoring state of component to be tested, vehicle and computer storage medium |
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| WO2023138581A1 (en) * | 2022-01-20 | 2023-07-27 | 清华大学 | Method and apparatus for detecting polygonal fault of wheel set of rail transit locomotive |
| CN114999537A (en) * | 2022-06-22 | 2022-09-02 | 歌尔科技有限公司 | Abnormal sound signal detection method, device and equipment and readable storage medium |
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