Prime Label Fault Detection in Vehicle Control Systems
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Solution Overview
Problem
Modern vehicle control systems, comprising numerous interconnected subsystems and electronic control units, face challenges in efficiently detecting and locating faults, which increases production costs and reduces vehicle reliability.
Innovation Solution
A method and system that assign unique prime number labels to functional units, using a traversal value and unique prime factorization algorithm to detect faults by comparing the product of these labels with an expected value, identifying faulty units through a prime factorization process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fault detection methods are used in vehicle control systems, then the system can identify faults, but the complexity of locating specific faulty functional units increases and detection efficiency decreases
Solution Approach 1:
The system segments the vehicle control system into multiple functional units, each assigned a unique prime number label. This segmentation allows individual identification and isolation of faulty units through mathematical operations on their labels, simplifying the complexity of fault location in interconnected systems.
Solution Approach 2:
The system changes the parameter representation of functional units by assigning unique prime number labels instead of traditional identifiers. By using the fundamental theorem of arithmetic (unique prime factorization), the system transforms fault location into a mathematical problem where the product of prime labels uniquely identifies the set of faulty units, enabling efficient detection and localization.
2Reliability
If comprehensive testing of all functional units is performed, then fault detection coverage is improved, but production time and costs increase
Solution Approach 1:
The system performs preliminary assignment of unique prime number labels to all functional units during system configuration. This preliminary action enables rapid fault detection during production by simply multiplying the labels of called functional units and comparing against expected products, eliminating the need for complex real-time diagnostic procedures and significantly improving production efficiency.
Solution Approach 2:
The system creates a mathematical model (product of prime labels) that represents the expected state of functional units. By comparing the actual product against this pre-calculated expected product, the system efficiently detects faults without requiring physical inspection or complex testing of each unit, thus maintaining high detection coverage while improving productivity.
3Measurement precision
If the system calls and updates traversal values through multiple functional units, then fault detection accuracy is improved, but the time required for detection increases
Solution Approach 1:
The system uses periodic multiplication of prime labels during the traversal of functional units. This periodic mathematical operation maintains accuracy by ensuring that each functional unit's contribution is systematically recorded in the traversal value product, while the efficiency of multiplication operations keeps detection time minimal compared to more complex measurement methods.
Solution Approach 2:
The system replaces complex mechanical or logical fault detection mechanisms with mathematical operations (multiplication and prime factorization). This substitution maintains high detection accuracy through the unique properties of prime numbers while dramatically reducing detection time, as mathematical operations are computationally efficient and can be performed rapidly by processors.
Data Source
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AI summary
A method for detecting faults in a vehicle control system comprising functional units having an associated unique prime number label is provided. The method comprises calling each of the functional units, the call comprising a readable and updateable integer traversal value, and in case the functional unit is operating correctly, updating the traversal value to be the product of the value in the call and the label of the currently called functional unit, and in the case of a fault, not updating the traversal value. Further, the method comprises determining from the traversal value if any functional units are faulty by a comparison with an expected traversal value, and, in the case that the traversal value is not equivalent to the expected traversal value, determining which functional units are faulty by a unique prime factorization algorithm.