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Intelligent vehicle condition monitoring method based on deep learning

A technology of intelligent monitoring and deep learning, applied in the direction of vehicle components, input parameters of external conditions, circuits or fluid pipelines, etc., can solve the problem of not recognizing the lane markings, losing the ability to distinguish potential dangers, and increasing the driving danger of the vehicle. and other problems, to achieve a good early warning effect, reduce maintenance difficulty and time, and achieve good accuracy and performance.

Inactive Publication Date: 2018-04-06
JIANGSU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above method proposes a way to identify the road traffic environment through the information processing module of the vehicle, and share the identification of potential danger early warning through inter-vehicle communication or the Internet, but it does not recognize road information such as lane lines, stop lines, and road signs. It cannot play a certain role in prompting the driver's illegal driving operation. For vehicles with damaged communication equipment, it means that they have lost the ability to distinguish potential dangers. Potential dangers are brought, which shows that the robustness of the system is poor

Method used

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  • Intelligent vehicle condition monitoring method based on deep learning
  • Intelligent vehicle condition monitoring method based on deep learning
  • Intelligent vehicle condition monitoring method based on deep learning

Examples

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example 1

[0056] Example 1: For automotive fault diagnosis

[0057] Suppose the car is driving normally on the road and suddenly feels a loud noise from the exhaust pipe when the car is accelerating. The system analyzes the car’s condition through cloud data in real time, the display shows a fault, and the speaker prompts the intake manifold pressure sensor malfunction.

example 2

[0058] Example 2: Used in car auxiliary safety

[0059] Such as figure 2 As shown, assuming that the car is running on the road, the data of the ADAS sensor is initially processed by the information processing module, and the convolutional neural network is used to obtain figure 2 The obstacle detection results of (a) and (b), the detection results from left to right in the figure are the obstacle category, the horizontal distance between the obstacle and the vehicle, and the longitudinal distance between the obstacle and the vehicle, and m represents the length in meters; then The data is uploaded to the remote cloud platform, combined with the current speed of the vehicle and its relative distance to the vehicle, the remote cloud platform uses BP neural network to analyze that the vehicle is in good condition, and the obstacles detected above will not collide with the vehicle .

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Abstract

The invention discloses an intelligent vehicle condition monitoring method based on deep learning. An information collecting module obtains output information of each sensor of an automobile, then aninformation processing module performs preliminary processing on the information, and the road traffic environment is perceived through a convolutional neural network; the well processed information is transmitted to a cloud platform through a communication module; and after the information is further processed through a BP neutral network of a remote cloud platform, a man-machine interaction module feeds vehicle condition state information of the automobile back to a user through vision and sound signals. According to the intelligent vehicle condition monitoring method, the intelligent monitoring of the vehicle interior and exterior conditions is achieved, and timely feeds prompt or warning information such as automobile faults and danger warning back to the user so that the user can knowin real time whether the working state of the automobile is good, and measures are taken timely to avoid dangerous accidents. Therefore, the method not only effectively improves the efficiency of theuse of the automobile, but also improves the driving safety of the automobile.

Description

technical field [0001] The invention relates to the technical field of vehicle condition intelligent monitoring, in particular to an intelligent vehicle condition monitoring method based on deep learning. Background technique [0002] In recent years, intelligent networking has become the main theme of the industry, and smart cars and Internet of Vehicles have gradually become hot issues in research at home and abroad. However, the two do not conflict, but complement each other and promote each other. When people enjoy the convenience brought by the car, they also regard the car as a kind of entertainment facility. By adding a lot of additional equipment to the car, it not only greatly increases the production cost, but also makes the car more and more cumbersome. The development theme of the car is contrary, so the independent intelligence that does not communicate with the outside world limits the pace of the car to a large extent. [0003] With the development of science...

Claims

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Application Information

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IPC IPC(8): B60W30/08B60W50/14B60R16/023
CPCB60R16/0232B60W30/08B60W50/14B60W2554/00B60W2554/801B60W2555/60
Inventor 刘军后士浩
Owner JIANGSU UNIV