CN117711087A - Real-time vehicle state monitoring method, electronic equipment and storage medium - Google Patents
Real-time vehicle state monitoring method, electronic equipment and storage medium Download PDFInfo
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- CN117711087A CN117711087A CN202311586835.5A CN202311586835A CN117711087A CN 117711087 A CN117711087 A CN 117711087A CN 202311586835 A CN202311586835 A CN 202311586835A CN 117711087 A CN117711087 A CN 117711087A
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Abstract
The application discloses a vehicle state real-time monitoring method, electronic equipment and a storage medium. Wherein the method comprises the following steps: collecting real-time state information of a vehicle; acquiring a vehicle diagnosis result based on the BP neural network for the real-time state information of the vehicle; judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not; if the vehicle running information is greater than the first threshold value, carrying out diagnosis again according to the supplementary information provided by the local vehicle running information database; if the vehicle diagnosis result is smaller than the rule, verifying the vehicle diagnosis result through an expert system, and judging whether the vehicle diagnosis result accords with the rule of a knowledge base; if the parameters do not accord with the rules, the parameters to be adjusted are fed back to the BP neural network through an expert system according to the rules of the knowledge base, so that the BP neural network performs network training. And if yes, outputting a vehicle diagnosis result. The method can solve the problem that the state of the vehicle cannot be monitored in real time in the prior art, reduce maintenance cost and faults, and improve self-maintenance sensing capability of equipment.
Description
Technical Field
The present invention relates to the field of real-time vehicle monitoring technologies, and in particular, to a real-time vehicle state monitoring method, an electronic device, and a storage medium.
Background
In recent years, with increasing importance of the use of self-propelled vehicles, the management of drivers, passengers and vehicles by units of various levels has become more and more strict, particularly the inspection of critical parts of the vehicle, in order to ensure the good and stable operation state of the self-propelled vehicles during operation. The application unit requires drivers and passengers to check the key parts of the vehicle before, during and after taking out, so as to prevent abnormal problems in the running of the vehicle and cause personal casualties and property loss, but the drivers and passengers check the key parts of the vehicle according to the requirement, so that the checking result is good, and no effective monitoring and management means exists at present.
Therefore, a real-time vehicle state monitoring method is needed, accurate identification and judgment of key parts of a vehicle are achieved, predictive maintenance and early fault diagnosis are carried out, key loss of equipment and facilities is identified at an early stage, maintenance cost and faults are reduced, and self-maintenance sensing capability of equipment is improved.
Disclosure of Invention
The invention mainly aims to provide a real-time vehicle state monitoring method, electronic equipment and a storage medium, so as to solve the problem that the real-time vehicle state monitoring cannot be realized in the prior art, realize accurate identification and judgment of key parts of a vehicle, develop predictive maintenance and early fault diagnosis, identify key loss of equipment and facilities at the early stage, reduce maintenance cost and faults and improve self-maintenance sensing capability of equipment.
In a first aspect, the present invention provides a method for monitoring a vehicle state in real time, including:
collecting real-time state information of a vehicle;
acquiring a vehicle diagnosis result based on the BP neural network for the real-time state information of the vehicle;
judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not;
if the adjustment times of the vehicle diagnosis results are greater than the preset times, performing diagnosis again according to the supplementary information provided by the local vehicle operation information database;
if the adjustment times of the vehicle diagnosis results are smaller than the preset times, verifying the vehicle diagnosis results through an expert system, and judging whether the vehicle diagnosis results accord with rules of a knowledge base or not;
if the vehicle diagnosis result does not accord with the rule of the knowledge base, feeding back parameters to be adjusted to the BP neural network through an expert system according to the rule of the knowledge base, so that the BP neural network performs network training;
and if the vehicle diagnosis result accords with the rule of the knowledge base, outputting the vehicle diagnosis result.
Optionally, the vehicle real-time state information includes a vehicle real-time speed, a vehicle real-time pressure, a vehicle real-time temperature, and a vehicle real-time voltage.
Optionally, if the number of times of adjustment of the vehicle diagnosis result is greater than a preset number of times, the step of re-diagnosing according to the supplementary information provided by the local vehicle operation information database includes:
sending a supplementary information request to the cloud platform;
acquiring supplementary information provided by a local vehicle operation information database sent by a cloud platform;
the diagnosis is performed again based on the supplementary information provided by the local vehicle operation information database.
According to a second aspect of an embodiment of the present invention, the present invention provides a vehicle state real-time monitoring device, including:
and the acquisition module is used for: the system is used for collecting real-time state information of the vehicle;
a first diagnostic module: the method comprises the steps of obtaining a vehicle diagnosis result for the real-time state information of the vehicle based on a BP neural network;
a first judging module: the method comprises the steps of judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not;
a second diagnostic module: for re-diagnosing based on the supplemental information provided by the local vehicle operating information database;
and a second judging module: the expert system is used for verifying the vehicle diagnosis result and judging whether the vehicle diagnosis result accords with rules of a knowledge base;
and a feedback module: the system is used for feeding back parameters to be adjusted to the BP neural network through an expert system according to the rule of the knowledge base, so that the BP neural network performs network training;
and an output module: for outputting the vehicle diagnostic result.
Optionally, the acquisition module includes: the device comprises a speed acquisition unit, a pressure acquisition unit, a temperature acquisition unit and a voltage acquisition unit.
Optionally, the second diagnostic module includes a request unit: the method comprises the steps of sending a supplementary information request to a cloud platform; and acquiring the supplementary information provided by the local vehicle operation information database sent by the cloud platform.
Optionally, the apparatus further includes a sharing module: for sharing the vehicle real-time status information.
Optionally, the device further comprises an alarm module: for communication failure alerting through the speaker when a network communication failure is detected.
According to a third aspect of embodiments of the present invention, there is provided an electronic device, including a memory and a processor, where the memory is configured to store one or more computer instructions, and where the one or more computer instructions, when executed by the processor, implement the vehicle state real-time monitoring method according to any one of the first aspects.
According to a fourth aspect of embodiments of the present invention, there is provided a storage medium in which a program is stored which, when executed by a computer, implements the vehicle state real-time monitoring method of any one of the above first aspects.
One or more embodiments of the above-described solution may have the following advantages or benefits compared to the prior art:
the invention obtains the data required by the fault diagnosis of the vehicle; and establishing a fault diagnosis algorithm model based on the BP neural network and an expert system to perform fault diagnosis. The method realizes accurate identification and judgment of the key parts of the vehicle, carries out predictive maintenance and early diagnosis of faults, identifies the key loss of equipment and facilities at the early stage, reduces maintenance cost and faults, and improves the self-maintenance sensing capability of the equipment.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic diagram of a neural network expert system serial diagnosis flow for a vehicle state real-time monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a fault diagnosis flow of a real-time vehicle state monitoring method according to an embodiment of the present invention.
Detailed Description
The following will describe embodiments of the present invention in detail with reference to the drawings and examples, thereby solving the technical problems by applying technical means to the present invention, and realizing the corresponding technical effects can be fully understood and implemented accordingly. The embodiment of the invention and the characteristics in the embodiment can be mutually combined on the premise of no conflict, and the formed technical scheme is within the protection scope of the invention.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a method for monitoring a vehicle state in real time, including:
and (3) state alarm: after the power-on, the equipment performs initialization self-checking, and when network communication faults are detected, the equipment performs communication fault alarm through a loudspeaker to remind drivers and passengers to process in time; when abnormality exists after the collected data are processed in real time and analyzed in diagnosis, voice prompt alarm of corresponding abnormality information is carried out through a loudspeaker.
After the network is determined to be normal, vehicle state data are collected in real time:
collecting vehicle temperature information:
the vehicle-mounted device (the axle temperature alarm device) can be directly connected to obtain the vehicle-related temperature information through the external communication interface, and the vehicle-related temperature information can also be obtained through connecting to other temperature communication ports of the vehicle.
Collecting vehicle speed information:
the vehicle running speed information can be obtained by directly accessing the vehicle-mounted equipment (the railway vehicle running control equipment) through the external communication interface, and also can be obtained by accessing the vehicle instrument end speed communication interface.
Collecting vehicle pressure information:
the vehicle pressure information can be obtained by directly accessing the vehicle-mounted equipment (the railway vehicle operation control equipment) through the external communication interface, and also can be obtained by accessing the vehicle instrument pressure communication interface.
Collecting vehicle power supply voltage information:
the vehicle input voltage information can be obtained by directly accessing the vehicle-mounted equipment (UPS power supply) through the external communication interface, and the vehicle voltage information can also be obtained by accessing the vehicle instrument voltage communication interface.
And (3) data acquisition wireless backhaul analysis processing:
the method comprises the steps of sending collected data information and vehicle position information to a ground comprehensive management platform in real time through a public mobile communication network, then processing, analyzing and storing data by a ground comprehensive management platform server, carrying out on-line monitoring on key equipment of a vehicle based on a temperature sensor, a pressure sensor, a speed sensor and a power supply level, realizing accurate identification and judgment of key parts of the vehicle through various sensors and a machine learning mode, timely finding whether abnormality exists in the running of the vehicle, and displaying analysis and diagnosis results to a client or other mobile terminals in real time.
Data sharing:
after the vehicle data information is collected, the collected data information can be shared through an external interface, and important parameter information of the vehicle is provided for other vehicle-mounted equipment or platforms.
Reserving an extended acquisition function interface:
other information acquisition interfaces are reserved, and the real-time monitoring and acquisition of other information of the vehicle or vehicle-mounted equipment can be increased in the later period, so that the acquisition, monitoring, analysis, diagnosis and processing functions of the device are further expanded.
As shown in fig. 1 and fig. 2, by adopting an intelligent fault diagnosis method combining a BP neural network and an expert system, the deducing results of various fault types are obtained through the process of analyzing faults by the BP network. The expert system verifies the diagnosis result obtained by the BP network and judges whether the diagnosis result accords with the rule of the knowledge base, if the diagnosis result does not accord with the rule of the knowledge base, the expert system feeds back the parameters to be adjusted to the neural network according to the rule of the knowledge base, and network training is continued, so that the identification capability of the system to the target is improved, and the system performance is obviously improved.
If the adjustment times of the BP neural network are greater than the set times, the method applies for sending the supplementary information to the cloud platform, and re-diagnoses the cloud platform according to the supplementary information provided by the local vehicle operation information database, so that the calculation efficiency is high, the requirement of on-line monitoring can be met, the monitoring of the output result can comprehensively reflect the operation state of the system, and the method is favorable for accurately and timely finding out the faults of the system.
The fault diagnosis algorithm model is established by adopting a serial mode of a front BP neural system and a rear expert system, so that the problems of difficult acquisition of expert system knowledge, low reasoning efficiency and the like can be solved, and the expert system is utilized to explain the neural network to deduce the vehicle fault.
Example two
The invention provides a vehicle state real-time monitoring device, comprising:
and the acquisition module is used for: the system is used for collecting real-time state information of the vehicle;
a first diagnostic module: the method comprises the steps of obtaining a vehicle diagnosis result for the real-time state information of the vehicle based on a BP neural network;
a first judging module: the method comprises the steps of judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not;
a second diagnostic module: for re-diagnosing based on the supplemental information provided by the local vehicle operating information database;
and a second judging module: the expert system is used for verifying the vehicle diagnosis result and judging whether the vehicle diagnosis result accords with rules of a knowledge base;
and a feedback module: the system is used for feeding back parameters to be adjusted to the BP neural network through an expert system according to the rule of the knowledge base, so that the BP neural network performs network training;
and an output module: for outputting the vehicle diagnostic result.
Optionally, the acquisition module includes: the device comprises a speed acquisition unit, a pressure acquisition unit, a temperature acquisition unit and a voltage acquisition unit.
Optionally, the second diagnostic module includes a request unit: the method comprises the steps of sending a supplementary information request to a cloud platform; and acquiring the supplementary information provided by the local vehicle operation information database sent by the cloud platform.
Optionally, the apparatus further includes a sharing module: for sharing the vehicle real-time status information.
Optionally, the device further comprises an alarm module: for communication failure alerting through the speaker when a network communication failure is detected.
Example III
The embodiment of the invention provides electronic equipment which can be a mobile phone, a tablet personal computer and the like, and comprises a memory and a processor, wherein the memory is used for storing one or more computer instructions, and the real-time vehicle state monitoring method described in the embodiment is realized when the one or more computer instructions are executed by the processor.
Wherein the processor is configured to execute all or part of the steps in the vehicle state real-time monitoring method as in the first embodiment. The memory is used to store various types of data such as vehicle speed information and the like.
The processor may be an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), a digital vehicle state real-time monitor (Digital Signal Processor, abbreviated as DSP), a digital vehicle state real-time monitoring device (Digital Signal Processing Device, abbreviated as DSPD), a programmable logic device (Programmable LogicDevice, abbreviated as PLD), a field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), a controller, a microcontroller, a microprocessor, or other electronic components for executing the vehicle state real-time monitoring method in the first embodiment.
The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk or optical disk.
Example IV
The functional units in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program verification codes.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other manners as well. The apparatus embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that in this disclosure, 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, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
While the embodiments disclosed in the present disclosure are described above, the above description is only an embodiment adopted for the purpose of facilitating understanding of the present disclosure, and is not intended to limit the present disclosure. Any person skilled in the art to which this disclosure pertains will appreciate that numerous modifications and variations in form and detail can be made without departing from the spirit and scope of the disclosure, but the scope of the disclosure is to be determined by the appended claims.
Claims (10)
1. A real-time monitoring method for vehicle state is characterized in that,
collecting real-time state information of a vehicle;
acquiring a vehicle diagnosis result based on the BP neural network for the real-time state information of the vehicle;
judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not;
if the adjustment times of the vehicle diagnosis results are greater than the preset times, performing diagnosis again according to the supplementary information provided by the local vehicle operation information database;
if the adjustment times of the vehicle diagnosis results are smaller than the preset times, verifying the vehicle diagnosis results through an expert system, and judging whether the vehicle diagnosis results accord with rules of a knowledge base or not;
if the vehicle diagnosis result does not accord with the rule of the knowledge base, feeding back parameters to be adjusted to the BP neural network through an expert system according to the rule of the knowledge base, so that the BP neural network performs network training;
and if the vehicle diagnosis result accords with the rule of the knowledge base, outputting the vehicle diagnosis result.
2. The method of claim 1, wherein the vehicle real-time status information comprises vehicle real-time speed, vehicle real-time pressure, vehicle real-time temperature, vehicle real-time voltage.
3. The method according to claim 1, wherein the step of re-diagnosing according to the supplementary information provided from the local vehicle operation information database if the number of adjustments of the vehicle diagnosis result is greater than a preset number comprises:
sending a supplementary information request to the cloud platform;
acquiring supplementary information provided by a local vehicle operation information database sent by a cloud platform;
the diagnosis is performed again based on the supplementary information provided by the local vehicle operation information database.
4. A vehicle condition real-time monitoring device, comprising:
and the acquisition module is used for: the system is used for collecting real-time state information of the vehicle;
a first diagnostic module: the method comprises the steps of obtaining a vehicle diagnosis result for the real-time state information of the vehicle based on a BP neural network;
a first judging module: the method comprises the steps of judging whether the adjustment times of the vehicle diagnosis result are larger than preset times or not;
a second diagnostic module: for re-diagnosing based on the supplemental information provided by the local vehicle operating information database;
and a second judging module: the expert system is used for verifying the vehicle diagnosis result and judging whether the vehicle diagnosis result accords with rules of a knowledge base;
and a feedback module: the system is used for feeding back parameters to be adjusted to the BP neural network through an expert system according to the rule of the knowledge base, so that the BP neural network performs network training;
and an output module: for outputting the vehicle diagnostic result.
5. The apparatus of claim 4, wherein the acquisition module comprises: the device comprises a speed acquisition unit, a pressure acquisition unit, a temperature acquisition unit and a voltage acquisition unit.
6. The apparatus of claim 4, wherein the second diagnostic module comprises a requesting unit: the method comprises the steps of sending a supplementary information request to a cloud platform; and acquiring the supplementary information provided by the local vehicle operation information database sent by the cloud platform.
7. The apparatus of claim 4, wherein the apparatus further comprises a sharing module: for sharing the vehicle real-time status information.
8. The apparatus of claim 4, further comprising an alarm module: for communication failure alerting through the speaker when a network communication failure is detected.
9. An electronic device comprising a memory and a processor, the memory for storing one or more computer instructions, wherein the one or more computer instructions when executed by the processor implement the vehicle condition real-time monitoring method of any one of claims 1 to 3.
10. A computer-readable storage medium in which a program is stored, characterized in that the program, when executed by a computer, implements the vehicle state real-time monitoring method according to any one of claims 1 to 3.
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| CN202311586835.5A CN117711087A (en) | 2023-11-24 | 2023-11-24 | Real-time vehicle state monitoring method, electronic equipment and storage medium |
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| CN202311586835.5A CN117711087A (en) | 2023-11-24 | 2023-11-24 | Real-time vehicle state monitoring method, electronic equipment and storage medium |
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