CN115469645A - Vehicle fault detection method and system based on cloud modeling technology - Google Patents
Vehicle fault detection method and system based on cloud modeling technology Download PDFInfo
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Abstract
The invention discloses a vehicle fault detection method based on a cloud modeling technology, which comprises the following steps: the method comprises the steps that a vehicle end obtains basic signal data of a vehicle; the method comprises the steps that a vehicle end obtains standard data of a preset basic signal of a vehicle; the vehicle end judges whether the basic signal data of the vehicle are abnormal or not according to the preset basic signal standard data of the vehicle, if so, the vehicle end generates vehicle fault information and uploads the vehicle fault information to a cloud end; the cloud generates a 3D fault model of the vehicle according to the vehicle fault information; the cloud generates fault prompt information according to the vehicle 3D fault model; and the cloud end sends the vehicle 3D fault model and the fault prompt information to vehicle display equipment of a vehicle end so as to prompt a driver of the vehicle to have a fault. The method and the device have the advantages that the user can be clear of the current working state of the vehicle and the internal fault position of the vehicle, the occupation of the local memory of the vehicle is greatly reduced due to the use of the cloud space, and meanwhile, the accuracy of system fault detection and vehicle modeling is guaranteed.
Description
Technical Field
The invention relates to a vehicle fault detection technology, in particular to a vehicle fault detection method based on a cloud modeling technology and a vehicle fault detection system based on the cloud modeling technology.
Background
In recent years, with the improvement of national economic level, vehicles have been moved to thousands of households and become necessities in life of people, but with the increase of the number of vehicles on the road, traffic accidents are more and more frequent. The generation of one part of traffic accidents is caused by vehicle internal faults, so that the safety inspection of the vehicle in real time and the accurate positioning of the vehicle internal faults are very necessary, the internal faults of the vehicle can be found and accurately positioned in time, and the safety factor of a driver can be greatly improved. However, no matter how carefully the vehicle operator checks the vehicle from the outside, the internal condition of the vehicle cannot be monitored and reported to the driver at all times, so it is important and necessary to detect the internal failure of the vehicle.
The cloud modeling technology is an upgrade of the traditional modeling technology and is a new application of a cloud space, and people can check the vehicle model at the cloud end by using the mobile terminal at any time and any place through the cloud modeling technology, so that the current state of the vehicle and the specific occurrence position and severity of the fault if the vehicle fault occurs are clear at a glance.
At present, vehicles on the market generally have a self-diagnosis function, and can independently generate fault codes according to faults, however, the vehicle fault codes can only provide the types of the faults sometimes, and cannot provide the specific conditions and severity of the faults; the manual investigation is more time-consuming and labor-consuming; through accomplishing the model to the vehicle and putting up, people just can be according to the accurate fault location who finds the vehicle of the model of vehicle to accomplish the repair, and people utilize cloud space to accomplish the vehicle model and put up, the local memory of mobile device on the saving vehicle that can be very big.
Disclosure of Invention
The invention aims to provide a vehicle fault detection method based on a cloud modeling technology and a vehicle fault detection system based on the cloud modeling technology, so as to solve at least one technical problem.
The invention provides the following scheme:
according to one aspect of the invention, a vehicle fault detection method based on cloud modeling technology is provided, and comprises the following steps:
the method comprises the steps that a vehicle end obtains basic signal data of a vehicle;
the method comprises the steps that a vehicle end obtains standard data of a preset basic signal of a vehicle;
the vehicle end judges whether the basic signal data of the vehicle are abnormal according to the standard data of the preset basic signal of the vehicle, if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not, and if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not according to the standard data of the preset basic signal of the vehicle
The vehicle end generates vehicle fault information and uploads the vehicle fault information to the cloud end;
the cloud generates a 3D fault model of the vehicle according to the vehicle fault information;
the cloud generates fault prompt information according to the vehicle 3D fault model;
and the cloud sends the vehicle 3D fault model and the fault prompt information to vehicle display equipment of a vehicle end so as to prompt a driver of a vehicle to have a fault.
Optionally, the determining, by the vehicle end, whether the vehicle basic signal data is abnormal according to the vehicle preset basic signal standard data includes:
comparing the basic signal data of each vehicle with the corresponding standard data of the preset basic signal of the vehicle respectively, and if one or more of the basic signal data of each vehicle exceeds the preset range of the standard data of the preset basic signal of the vehicle, comparing the basic signal data of each vehicle with the standard data of the corresponding preset basic signal of the vehicle respectively, and if one or more of the basic signal data of each vehicle exceeds the preset range of the standard data of the preset basic signal of the vehicle, determining that the basic signal data of each vehicle exceeds the preset range of the standard data of the corresponding basic signal of the corresponding vehicle
And generating vehicle fault information according to the vehicle basic signal data exceeding the preset range of the vehicle preset basic signal standard data.
Optionally, the generating of the vehicle fault information according to the vehicle basic signal data exceeding a preset range of the vehicle preset basic signal standard data includes:
carrying out fault analysis on the vehicle basic signal data exceeding a preset range of vehicle preset basic signal standard data to obtain a fault occurrence reason, a fault position and a fault severity of the vehicle;
and generating vehicle fault information according to the fault occurrence reason, the fault position and the fault severity of the vehicle.
Optionally, when the vehicle fault information is uploaded to the cloud, the vehicle synchronously uploads the image information scanning signal data to the cloud, wherein,
and the image information scanning signal data comprises point cloud data of the detected vehicle scanned by laser so as to realize the construction of a 3D fault model of the vehicle.
Optionally, the cloud generating a vehicle 3D fault model according to the vehicle fault information includes:
acquiring the vehicle fault information;
associating the vehicle fault information with a preset fault dimension table to obtain a vehicle fault information dimension table;
acquiring image information scanning signal data;
and generating a 3D fault model of the vehicle according to the vehicle fault information dimension table and the image information scanning signal data.
Optionally, the generating a 3D vehicle fault model according to the vehicle fault information dimension table and the image information scanning signal data includes:
and positioning a vehicle abnormal function image area according to the vehicle fault information dimension table, and displaying the abnormal function image area of the vehicle 3D fault model as a special color.
Optionally, the generating, by the cloud, the fault notification information according to the vehicle 3D fault model includes:
generating corresponding fault repair prompt information according to the vehicle fault information dimension table, wherein,
the fault repair prompt message comprises a low-level prompt message, a middle-level prompt message and a high-level prompt message.
Optionally, the generating of the corresponding fault repair prompt information according to the vehicle fault information dimension table includes:
judging the severity of the fault according to the vehicle fault information dimension table, and generating low-level prompt information, medium-level prompt information or high-level prompt information according to the severity of the fault, wherein,
if the severity of the fault is lower than a first preset value, generating low-level prompt information;
if the severity of the fault is lower than a second preset value, generating intermediate prompt information;
and if the severity of the fault is higher than a third preset value, generating high-level prompt information.
Optionally, the vehicle base signal data comprises acceleration signal data, brake signal data, steering signal data, audio signal data, and electrical system signal data;
the acquiring vehicle base signal data includes:
acquiring acceleration signal data;
acquiring brake signal data;
acquiring steering signal data;
acquiring audio signal data;
electronic system signal data is acquired.
The invention further provides a vehicle fault detection system based on the cloud modeling technology, which comprises a vehicle end and a cloud end, wherein the vehicle end and the cloud end are matched to realize the vehicle fault detection method based on the cloud modeling technology.
Compared with the prior art, the invention has the following advantages:
the invention solves the problem that the fault code information displayed by the existing vehicle fault detection system aiming at the fault problem of the vehicle is single, the vehicle is virtually modeled and a corresponding virtual three-dimensional image is generated by acquiring, processing and finally judging the signals in the vehicle and establishing the fault dimension table at the cloud end by utilizing the cloud space and the wireless signal transmission technology, the established fault dimension table and the three-dimensional image can comprehensively, accurately and intuitively reflect the vehicle fault, and the vehicle model can be transmitted to the vehicle display equipment in real time, so that a driver can know the working state of the vehicle and the detailed position and the severity of the vehicle fault at any time. The method and the device have the advantages that the occupation of the local memory of the vehicle is greatly reduced due to the use of the cloud space, the fault detection in the method and the device monitor and collect a plurality of data with variable factors and compare the data with standard data, and the accuracy of system fault detection and vehicle modeling is greatly improved.
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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 some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic flow chart of a vehicle fault detection method based on cloud modeling technology according to an embodiment of the invention;
fig. 2 is a schematic diagram of a cloud modeling flow of a vehicle fault detection method based on a cloud modeling technology according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of cloud data processing of a vehicle fault detection method based on a cloud modeling technology according to an embodiment of the present invention;
fig. 4 is a structural diagram of an electronic device that can implement the vehicle fault detection method based on the cloud modeling technology of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
FIG. 1 is a schematic flow chart of a vehicle fault detection method based on cloud modeling technology according to an embodiment of the invention;
the vehicle fault detection method based on the cloud modeling technology as shown in fig. 1 comprises the following steps:
step 1: the method comprises the steps that a vehicle end obtains basic signal data of a vehicle;
and 2, step: the method comprises the steps that a vehicle end obtains standard data of a preset basic signal of a vehicle;
and step 3: the vehicle end judges whether the basic signal data of the vehicle are abnormal according to the standard data of the preset basic signal of the vehicle, if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not, and if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not according to the standard data of the preset basic signal of the vehicle
And 4, step 4: the vehicle end generates vehicle fault information and uploads the vehicle fault information to the cloud end;
and 5: the cloud generates a 3D fault model of the vehicle according to the fault information of the vehicle;
step 6: the cloud generates fault prompt information according to the 3D fault model of the vehicle;
and 7: the cloud sends the vehicle 3D fault model and the fault prompt information to vehicle display equipment of a vehicle end so as to prompt a driver of the vehicle to have a fault.
Compared with the prior art, the invention has the following advantages:
the invention solves the problem that the fault code information displayed by the existing vehicle fault detection system aiming at the fault problem of the vehicle is single, the vehicle is virtually modeled and a corresponding virtual three-dimensional image is generated by acquiring, processing and finally judging the signals in the vehicle and establishing the fault dimension table at the cloud end by utilizing the cloud space and the wireless signal transmission technology, the established fault dimension table and the three-dimensional image can comprehensively, accurately and intuitively reflect the vehicle fault, and the vehicle model can be transmitted to the vehicle display equipment in real time, so that a driver can know the working state of the vehicle and the detailed position and the severity of the vehicle fault at any time. The method and the device have the advantages that the occupation of the local memory of the vehicle is greatly reduced due to the use of the cloud space, the fault detection in the method and the device monitor and collect a plurality of data with variable factors and compare the data with standard data, and the accuracy of system fault detection and vehicle modeling is greatly improved.
In this embodiment, the determining, by the vehicle end, whether the vehicle basic signal data is abnormal according to the vehicle preset basic signal standard data includes:
and comparing the basic signal data of each vehicle with the corresponding preset basic signal standard data of the vehicle respectively, and if one or more of the basic signal data of the vehicle exceeds the preset range of the preset basic signal standard data of the vehicle, generating vehicle fault information according to the basic signal data of the vehicle exceeding the preset range of the preset basic signal standard data of the vehicle.
Specifically, in this embodiment, the vehicle end simply calculates and collects vehicle basic signal data, and at the same time, continuously compares the collected vehicle basic signal data with vehicle preset basic signal standard data (stores normal working data of a functional system in a normal working state in the vehicle in real time), analyzes and judges whether the vehicle basic signal data exceeds a preset range of the vehicle preset basic signal standard data, and if so, generates corresponding vehicle fault information; in this embodiment, the vehicle basic signal data includes data collected by sensors corresponding to an acceleration signal, a brake signal, a steering signal, an audio signal, and an electronic system signal, for example, a plurality of variable-factor data such as temperature data, pressure data, speed data, acceleration data, audio data, voltage data, and current data collected by a vehicle temperature sensor, a pressure sensor, a speed sensor, an acceleration sensor, an audio collector, a current monitor, and a voltage monitor, where the audio collector may collect audio signals of a vehicle during acceleration, braking, and steering operations, and calculate time domain characteristics and frequency domain characteristics of the audio signals.
The audio signal data is added to the vehicle basic signal data, and the purpose is to collect audio signals (mainly aiming at obtaining time domain characteristics and frequency domain characteristics of the signals) sent by a plurality of sound-emitting components on the vehicle. Acquiring audio signal data includes processing the audio signal, and the steps can be divided into the following steps: the collected and input audio signals are converted into electric signals, then the signals are transmitted to a collection module of a vehicle end for obtaining the signals to be sampled (the sampling frequency and the quantization digit of a selected signal collection unit can be changed according to actual needs), the signals are subjected to analog-to-digital conversion, then the audio signals are subjected to spectrum analysis, the time domain characteristics of the collected audio signals are converted into the frequency spectrum characteristics of the signals through Fourier transform, the obtained frequency spectrum characteristics of the sounds comprise the frequency of the sounds and the intensity value of each harmonic sound, and thus the frequency spectrum characteristics and the time domain characteristics of the audio signals can be obtained by the collection module of the vehicle end, errors existing in the vehicle fault detection process can be greatly reduced, and the fault source of the vehicle can be conveniently and accurately detected.
In this embodiment, generating the vehicle failure information from the vehicle basic signal data exceeding the preset range of the vehicle preset basic signal standard data includes:
carrying out fault analysis on the basic vehicle signal data which exceed the preset range of the preset basic vehicle signal standard data to obtain the fault occurrence reason, the fault position and the fault severity of the vehicle;
and generating vehicle fault information according to the fault occurrence reason, the fault position and the fault severity of the vehicle.
In the embodiment, when the vehicle fault information is uploaded to the cloud, the vehicle synchronously uploads the image information scanning signal data to the cloud, wherein,
the image information scanning signal data comprises point cloud data of the detected vehicle through laser scanning, so that the building of a 3D fault model of the vehicle is realized.
In this embodiment, the signals such as the temperature, the pressure, the sound, and the like are collected by a collection module that acquires the signals at the vehicle end, and then the detection diagnosis result of the detected component of the vehicle is obtained through fault analysis, conversion, and calculation, and then the detection result and the data are transmitted to the cloud for modeling, the accurate location of the fault in the model is in the form of a fault dimension table (for example, a table below), the information included in the table is shown in the table below, including id of the detected basic signal, name (including unit) of the detected basic signal, data value of the detected basic signal, allowable error of the detected basic signal, and preset standard data of the detected basic signal, if the detected basic signal is compared with the preset standard data of the detected basic signal and the allowable error of the data is found, the data of the detected basic signal in the table is marked red, for example, when a certain component in the vehicle has a fault, a voltage sensor at the vehicle end may detect a voltage anomaly and generate a fault information table, but cannot accurately locate the fault occurring position, and then, the fault location may be accurately located by adding fault detection information (such as the data of the temperature, the pressure, the sound, and the like) in another dimension or dimensions.
In this embodiment, the cloud generates the vehicle 3D fault model according to the vehicle fault information and includes:
acquiring vehicle fault information;
associating the vehicle fault information with a preset fault dimension table to obtain a vehicle fault information dimension table;
acquiring image information scanning signal data;
and generating a 3D fault model of the vehicle according to the vehicle fault information dimension table and the image information scanning signal data.
In the present embodiment, generating a 3D failure model of a vehicle from the vehicle failure information dimension table and the image information scanning signal data includes:
and positioning the vehicle abnormal function image area according to the vehicle fault information dimension table, and displaying the abnormal function image area of the vehicle 3D fault model as a special color.
In the embodiment, the cloud end processes image information scanning signal data uploaded by the vehicle end in a laser point cloud data processing mode and generates a three-dimensional vehicle model, all detected three-dimensional data information of a vehicle is contained in the three-dimensional vehicle model, if certain detected basic signal data is abnormal, a vehicle function abnormal image area in the three-dimensional vehicle model is located according to a vehicle fault information dimension table, the corresponding position is displayed to be a special color, the special color can be red, and a driver can be clear of faults occurring in the vehicle by marking the vehicle three-dimensional model function abnormal image area with red.
Fig. 2 is a schematic diagram of a cloud modeling flow of a vehicle fault detection method based on a cloud modeling technology according to an embodiment of the present invention;
as shown in fig. 2, in this embodiment, the detected basic signal data is used as a pile of a three-dimensional model of a vehicle, and the three-dimensional image modeling of the vehicle is performed hierarchically according to a hierarchical modeling method from bottom to top, which has the advantage that small modules in each layer can be seen as a miniature model, and the miniature models form a model of the whole vehicle as a whole, so that a driver can more intuitively and deeply understand the state of the vehicle through the model, and if only a certain function of the vehicle is desired to be understood, the single small module model can be pulled out; besides the advantage of more intuition, the three-dimensional image modeling method has the advantages that when the modeling data of the middle layer of the vehicle model is wrong, the upper layer can directly call the modeling data of the lower layer, and the modeling of the whole vehicle three-dimensional image is smoothly and accurately completed.
In the present embodiment, the vehicle base signal data includes acceleration system signal data, brake system signal data, steering system signal data, audio system signal data, and electronic system signal data;
in this embodiment, acquiring the vehicle basic signal data includes:
acquiring temperature signal data;
acquiring pressure signal data;
acquiring speed signal data;
acquiring acceleration signal data;
acquiring current signal data;
acquiring voltage signal data;
acquiring sound signal data;
wheel speed signal data is acquired.
The fault detection in the invention realizes monitoring and acquisition of the data with variable factors and compares the data with standard data, thereby greatly increasing the accuracy of system fault detection and vehicle modeling. The problem that the fault code information displayed by the conventional vehicle fault detection system aiming at the fault problem of the vehicle is single is solved by a mode of reflecting the fault position of the vehicle three-dimensional model.
The present application is described in further detail below by way of examples, it being understood that the examples do not constitute any limitation to the present application.
In another embodiment of the present invention, the cloud generating the fault notification information according to the 3D fault model of the vehicle includes:
generating corresponding fault repair prompt information according to the vehicle fault information dimension table, wherein,
the fault repair prompt messages include low-level prompt messages, medium-level prompt messages and high-level prompt messages.
In this embodiment, generating the corresponding failure repair prompt information according to the vehicle failure information dimension table includes:
judging the severity of the fault according to the vehicle fault information dimension table, and generating low-level prompt information, medium-level prompt information or high-level prompt information according to the severity of the fault, wherein,
if the severity of the fault is lower than a first preset value, generating low-level prompt information;
if the severity of the fault is lower than a second preset value, generating intermediate prompt information;
and if the severity of the fault is higher than a third preset value, generating high-level prompt information.
In this embodiment, what level of prompt information is generated is determined according to the severity of the fault of the vehicle fault information dimension table, for example, when the severity of the fault is less than 30%, low-level prompt information is generated, for example, a driver is requested to perform regular inspection; when the fault severity is less than 50%, generating intermediate prompt information, and if the driver is required to go to a 4S store for vehicle inspection within preset time; when the severity of the fault is more than 70%, high-level prompt information is generated, for example, a driver is asked to go to a 4S store for vehicle inspection immediately, so that accidents caused by vehicle faults are avoided.
Fig. 3 is a schematic structural diagram of cloud data processing of a vehicle fault detection method based on a cloud modeling technology according to an embodiment of the present invention;
as shown in fig. 3, in this embodiment, the data processing by the cloud before generating the vehicle fault model includes adopting a star model among the multiple detected fault basic signal element tables, associating the fault fact as a center with several detected fault basic signal element tables, and performing star distribution, and the cloud may be modeled by a star structure among the tables.
It can be understood that, in another embodiment of the present invention, the cloud may remotely transmit the vehicle failure model generated according to the vehicle failure information dimension table and the image information scanning signal data to the mobile device of the driver who successfully pairs with the vehicle in a wireless transmission manner, where the mobile device may be a mobile phone, a tablet computer, or the like, so that the driver can know the state of the vehicle anytime and anywhere.
The invention also provides a vehicle fault detection system based on the cloud modeling technology, which comprises a vehicle end and a cloud end, wherein the vehicle end and the cloud end are matched to realize the vehicle fault detection method based on the cloud modeling technology.
Fig. 4 is a structural diagram of an electronic device that can implement the vehicle fault detection method based on the cloud modeling technology of the present invention.
As shown in fig. 4, the electronic apparatus includes: the system comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus; the memory has stored therein a computer program which, when executed by the processor, causes the processor to perform the steps of the cloud modeling technique based vehicle fault detection method.
The present application also provides a computer readable storage medium storing a computer program executable by an electronic device, which when run on the electronic device, causes the electronic device to perform the steps of the vehicle fault detection method based on the cloud modeling technique.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The electronic device includes a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on top of the operating system. The hardware layer includes hardware such as a Central Processing Unit (CPU), a Memory Management Unit (MMU), and a Memory. The operating system may be any one or more computer operating systems that implement control of the electronic device through a Process (Process), such as a Linux operating system, a Unix operating system, an Android operating system, an iOS operating system, or a windows operating system. In the embodiment of the present invention, the electronic device may be a handheld device such as a smart phone and a tablet computer, or an electronic device such as a desktop computer and a portable computer, which is not particularly limited in the embodiment of the present invention.
The execution main body of the electronic device control in the embodiment of the present invention may be the electronic device, or a functional module capable of calling a program and executing the program in the electronic device. The electronic device may obtain the firmware corresponding to the storage medium, the firmware corresponding to the storage medium is provided by a vendor, and the firmware corresponding to different storage media may be the same or different, which is not limited herein. After the electronic device acquires the firmware corresponding to the storage medium, the firmware corresponding to the storage medium may be written into the storage medium, specifically, the firmware corresponding to the storage medium is burned into the storage medium. The process of burning the firmware into the storage medium can be implemented by adopting the prior art, and is not described in the embodiment of the present invention.
The electronic device may further acquire a reset command corresponding to the storage medium, where the reset command corresponding to the storage medium is provided by a vendor, and the reset commands corresponding to different storage media may be the same or different, which is not limited herein.
At this time, the storage medium of the electronic device is a storage medium in which the corresponding firmware is written, and the electronic device may respond to the reset command corresponding to the storage medium in which the corresponding firmware is written, so that the electronic device resets the storage medium in which the corresponding firmware is written according to the reset command corresponding to the storage medium. The process of resetting the storage medium according to the reset command can be implemented by the prior art, and is not described in detail in the embodiment of the present invention.
For convenience of description, the above devices are described as being divided into various units and modules by functions, respectively. Of course, the functions of the units and modules may be implemented in one or more software and/or hardware when the present application is implemented.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For simplicity of explanation, the method embodiments are described as a series of acts or combinations, but those skilled in the art will appreciate that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently with other steps in accordance with the embodiments of the invention. Further, those of skill in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the embodiments of the invention.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments.
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 vehicle fault detection method based on a cloud modeling technology is characterized by comprising the following steps:
the method comprises the steps that a vehicle end obtains basic signal data of a vehicle;
the method comprises the steps that a vehicle end obtains standard data of a preset basic signal of a vehicle;
the vehicle end judges whether the basic signal data of the vehicle are abnormal according to the standard data of the preset basic signal of the vehicle, if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not, and if so, the vehicle end judges whether the basic signal data of the vehicle are abnormal or not according to the standard data of the preset basic signal of the vehicle
The vehicle end generates vehicle fault information and uploads the vehicle fault information to the cloud end;
the cloud generates a 3D fault model of the vehicle according to the vehicle fault information;
the cloud generates fault prompt information according to the vehicle 3D fault model;
and the cloud end sends the vehicle 3D fault model and the fault prompt information to vehicle display equipment of a vehicle end so as to prompt a driver of the vehicle to have a fault.
2. The vehicle fault detection method based on the cloud modeling technology as claimed in claim 1, wherein the determining, by the vehicle end, whether the vehicle basic signal data is abnormal according to the vehicle preset basic signal standard data includes:
comparing the basic signal data of each vehicle with the corresponding standard data of the preset basic signal of the vehicle respectively, and if one or more of the basic signal data of each vehicle exceeds the preset range of the standard data of the preset basic signal of the vehicle, comparing the basic signal data of each vehicle with the standard data of the corresponding preset basic signal of the vehicle respectively, and if one or more of the basic signal data of each vehicle exceeds the preset range of the standard data of the preset basic signal of the vehicle, determining that the basic signal data of each vehicle exceeds the preset range of the standard data of the corresponding basic signal of the corresponding vehicle
And generating vehicle fault information according to the vehicle basic signal data exceeding the preset range of the vehicle preset basic signal standard data.
3. The cloud modeling technology-based vehicle fault detection method as claimed in claim 2, wherein said generating vehicle fault information from the vehicle base signal data that exceeds a preset range of vehicle preset base signal standard data comprises:
carrying out fault analysis on the vehicle basic signal data exceeding the preset range of the vehicle preset basic signal standard data to obtain the fault occurrence reason, the fault position and the fault severity of the vehicle;
and generating vehicle fault information according to the fault occurrence reason, the fault position and the fault severity of the vehicle.
4. The vehicle fault detection method based on the cloud modeling technology of claim 3, wherein when the vehicle fault information is uploaded to the cloud, the vehicle side synchronously uploads the image information scanning signal data to the cloud, wherein,
the image information scanning signal data comprise point cloud data of the detected vehicle scanned by laser, so that the building of a 3D fault model of the vehicle is realized.
5. The cloud modeling technology-based vehicle fault detection method of claim 4, wherein the cloud generating a vehicle 3D fault model from the vehicle fault information comprises:
acquiring the vehicle fault information;
associating the vehicle fault information with a preset fault dimension table to obtain a vehicle fault information dimension table;
acquiring image information scanning signal data;
and generating a 3D fault model of the vehicle according to the vehicle fault information dimension table and the image information scanning signal data.
6. The cloud modeling technology-based vehicle fault detection method of claim 5, wherein said generating a 3D fault model of a vehicle from the vehicle fault information dimension table and image information scan signal data comprises:
and positioning a vehicle abnormal function image area according to the vehicle fault information dimension table, and displaying the abnormal function image area of the vehicle 3D fault model as a special color.
7. The cloud modeling technology-based vehicle fault detection method of claim 6, wherein the cloud generating fault notification information according to the 3D fault model of the vehicle comprises:
generating corresponding fault repair prompt information according to the vehicle fault information dimension table, wherein,
the fault repair prompt message comprises a low-level prompt message, a middle-level prompt message and a high-level prompt message.
8. The vehicle fault detection method based on the cloud modeling technology as claimed in claim 7, wherein the generating of the corresponding fault repair prompt information according to the vehicle fault information dimension table includes:
judging the severity of the fault according to the vehicle fault information dimension table, and generating low-level prompt information, medium-level prompt information or high-level prompt information according to the severity of the fault, wherein,
if the severity of the fault is lower than a first preset value, generating low-level prompt information;
if the severity of the fault is lower than a second preset value, generating intermediate prompt information;
and if the severity of the fault is higher than a third preset value, generating high-level prompt information.
9. The cloud modeling technology-based vehicle fault detection method of claim 1, wherein the vehicle base signal data includes acceleration signal data, braking signal data, steering signal data, audio signal data, and electronic system signal data;
the acquiring vehicle base signal data includes:
acquiring acceleration signal data;
acquiring brake signal data;
acquiring steering signal data;
acquiring audio signal data;
electronic system signal data is acquired.
10. The vehicle fault detection system based on the cloud modeling technology is characterized by comprising a vehicle end and a cloud end, wherein the vehicle end and the cloud end are matched to realize the vehicle fault detection method based on the cloud modeling technology according to any one of claims 1 to 9.
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