Zonal Vehicle Fault Detection With Self-Diagnosis Preprocessing
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Solution Overview
Problem
Existing vehicle fault detection systems require high professional knowledge and often fail to detect faults in a timely manner, leading to increased maintenance costs and potential accidents.
Innovation Solution
A vehicle fault detection system comprising a master controller, sub-controllers, and a fault display, which divides the vehicle into zones, collects and preprocesses operating status information, and performs fault detection and classification using preset fault diagnosis models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user relies on professional knowledge to detect vehicle faults, then the detection accuracy may be improved, but the ease of operation deteriorates and the loss of time increases
Solution Approach 1:
The system enables self-diagnosis functionality where the vehicle automatically detects and identifies faults without requiring user expertise. The controller collects data from multiple sensors, performs automated analysis, and presents results in an easily understandable format, allowing ordinary users to obtain accurate fault detection without needing professional knowledge.
Solution Approach 2:
The patent replaces manual inspection methods with an automated electronic detection system. Sensors, controllers, and processing units substitute for human expert analysis, automatically collecting data, identifying fault patterns, and generating diagnostic results, thereby improving both accuracy and ease of operation.
2Reliability
If manual inspection methods are used, then the device complexity is reduced, but the reliability of fault detection deteriorates
Solution Approach 1:
The detection system is divided into modular functional units including sensors for data collection, controllers for processing, and output devices for presentation. Each module performs a specific function, making the complex system manageable and maintainable while achieving high reliability through distributed intelligence and specialized processing at each stage.
3Loss of time
If faults are not detected in time, then the loss of time is reduced, but the loss of substance increases due to large maintenance costs
Solution Approach 1:
The system continuously monitors vehicle parameters and performs preliminary fault detection before actual failures occur. By identifying potential issues early through ongoing data collection and analysis, the system enables preventive maintenance that reduces both the time to detect faults and the overall maintenance costs by addressing problems before they escalate.
Data Source
AI summary
A vehicle fault detection system comprises a master controller, a fault display, and a plurality of sub-controllers. The fault display and the plurality of sub-controllers are communicated with the master controller respectively. The vehicle comprises a plurality of zones. The plurality of sub-controllers are configured to collect operating status information of components in the plurality of zones of the vehicle respectively, and preprocess the operating status information to remove interference information to operating status information set to be processed, and send the operating status information set to the master controller. One of the plurality of sub-controllers corresponds to at least one of the plurality of zones. The master controller is configured to detect faults of the operating state information set and generate fault detection information. The fault display is configured to detect and classify the fault detection information and generate a fault detection result. A vehicle is also provided.