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A vehicle fault diagnosis method and system based on convolutional memory autoencoder network

A self-encoding network and automobile fault technology, applied in the field of automobile fault diagnosis, can solve the problems of large fault diagnosis coverage and impossibility, and achieve the effect of improving fault diagnosis coverage

Active Publication Date: 2022-02-18
ZHEJIANG UNIV
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Problems solved by technology

This fault diagnosis system is more based on the original OBD system and expert system to achieve fault diagnosis, but it still cannot achieve a large fault diagnosis coverage, especially for unknown faults

Method used

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  • A vehicle fault diagnosis method and system based on convolutional memory autoencoder network
  • A vehicle fault diagnosis method and system based on convolutional memory autoencoder network
  • A vehicle fault diagnosis method and system based on convolutional memory autoencoder network

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Embodiment Construction

[0057] The present invention will be further described below in conjunction with the accompanying drawings.

[0058] like figure 1 As shown, a kind of automobile fault diagnosis method based on convolutional memory self-encoding network provided by the embodiment of the present invention, the method is realized based on the automobile fault diagnosis system, and the system is composed of data acquisition equipment and remote fault diagnosis cloud platform; data acquisition The equipment includes a data acquisition module, a data management module and a data transmission module; the remote fault diagnosis cloud platform includes a data transmission module, a data storage module, a fault diagnosis module and a business logic module.

[0059] The data acquisition module of the data acquisition device acquires vehicle status data, such as accelerator pedal position, brake pedal position, engine torque mode, etc., through the analog-to-digital conversion chip, digital level port, C...

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Abstract

The invention discloses an automobile fault diagnosis method and system based on a convolutional memory self-encoding network, which realizes automobile state data acquisition, cleaning and northbound transmission to a fault diagnosis cloud platform through data acquisition equipment, specifically including automobile state data acquisition and abnormal values Processing steps, as well as car state data time stamp alignment, missing value processing and northbound transmission steps; store car state data through the fault diagnosis cloud platform, and realize fault detection and fault location; the present invention can realize detection and positioning of unknown faults, and improve Fault diagnosis coverage of the existing on-board self-diagnosis system, and provide fault visualization services for drivers and maintenance personnel.

Description

technical field [0001] The invention relates to the field of Internet of Vehicles, in particular to a method and system for diagnosing automobile faults based on a convolutional memory self-encoding network. Background technique [0002] With the development of society, the number of car ownership continues to increase. According to statistics from the Ministry of Public Security, as of June 2020, the number of cars in my country has reached 270 million. However, at present, the degree of networking and intelligence of automobiles is relatively low, and it is difficult to obtain better storage and management of automobile status data. The OBD system makes a simple logical judgment on the vehicle status data, and then analyzes the fault information, and saves the fault information. However, only fault information can be obtained during maintenance, but the running state of the car when it fails cannot be restored. At the same time, the OBD system realizes fault diagnosis t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B23/02
CPCG05B23/0213
Inventor 宋超超陈积明贺诗波史治国李传武
Owner ZHEJIANG UNIV
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