Vehicle Fault Diagnosis Using Dynamic Data Stream Ranges
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Solution Overview
Problem
Existing vehicle diagnostic devices provide imprecise fault diagnosis results due to the use of empirical standard value ranges set by diagnosis software.
Innovation Solution
A vehicle diagnostic method and system that determines a standard range for failure diagnosis by collecting and counting sample data streams during normal vehicle operation, using the maximum and minimum values to establish a dynamic standard range for comparison with real-time data streams, and outputs corresponding alarm information based on deviations from this range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If empirical standard value ranges are used for fault diagnosis, then the diagnostic process is simple and fast, but the diagnosis precision is low
Solution Approach 1:
The system performs preliminary data collection during normal vehicle operation to establish standard value ranges before actual fault diagnosis occurs. Sample data streams are collected and processed in advance to create reference ranges for various vehicle parameters, so that when faults occur, the comparison can be made immediately against pre-established standards rather than using generic empirical values.
Solution Approach 2:
The standard value ranges are made dynamic rather than static. The system continuously collects sample data streams during normal operation and automatically updates the standard ranges based on the collected data. This allows the diagnostic standards to adapt to different vehicle conditions, models, and operational states, improving precision while maintaining automated operation.
2Adaptability or versatility
If fixed standard value ranges are used, then the diagnostic method is simple, but it cannot adapt to different vehicle models and conditions
Solution Approach 1:
The diagnostic system performs self-learning by automatically collecting sample data streams during normal vehicle operation and using this data to establish its own standard value ranges. The system processes the collected data to determine maximum and minimum values, automatically creating adaptive standards without requiring manual intervention or pre-programmed empirical values for each vehicle model.
Solution Approach 2:
The system changes the parameters used for diagnosis from fixed empirical values to dynamically determined ranges based on actual vehicle operation data. By collecting multiple sample data streams and calculating statistical parameters (maximum, minimum, and range values), the system adapts the diagnostic criteria to match the specific characteristics of each vehicle and its operating conditions.
Data Source
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AI summary
The present application is applicable to the technical field of vehicle diagnosis, and provides a vehicle diagnostic method, a vehicle diagnostic system, and a vehicle diagnostic device. The vehicle diagnostic method comprises: determining a standard range of vehicle fault diagnosis; reading a current data stream of a vehicle in real time when a vehicle diagnosis instruction is received, and determining whether values of the current data stream are within a standard range; and outputting prompt information indicative of normal vehicle operation if the values of the current data stream are within the standard range; or outputting corresponding vehicle fault alarm information if the values of the current data stream are beyond the standard range. This present application can improve an accuracy of vehicle fault diagnosis.