Adaptive Network Fault Detection via Error Value Comparison
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Solution Overview
Problem
Modern motor vehicle networks face challenges in reliably detecting faults in adaptive network connections, particularly due to interference and aging issues, which can lead to undesirable interference radiation affecting other devices.
Innovation Solution
A method and system for monitoring adaptive networks using transceivers to determine mean error values, distinguishing between reference and actual error values to detect faults, with adaptive filtering and threshold-based detection to identify deviations in network connections, allowing for timely identification and correction of faulty components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If adaptive network connections are used to compensate interference influences, then the network's adaptability is improved, but the difficulty of detecting and measuring faults increases
Solution Approach 1:
The system performs preliminary characterization of the network connection by determining reference error values during a reference operating state (e.g., when the vehicle is at the end of the conveyor belt). This preliminary action establishes a baseline against which actual error values can be compared later, enabling fault detection despite the adaptive nature of the network
Solution Approach 2:
The system continuously monitors the network connection by comparing actual error values (determined during predefined operating states) with reference error values (determined during reference operating states). This feedback mechanism enables the system to detect faults by identifying significant deviations from the established baseline, resolving the difficulty of fault detection in adaptive networks
2Reliability
If network connections are monitored continuously, then the reliability of fault detection is improved, but the use of energy increases
Solution Approach 1:
Instead of continuous monitoring, the system performs fault detection at predefined operating states (e.g., engine start, connection status changes). This periodic approach maintains reliable fault detection by checking at critical moments while significantly reducing energy consumption compared to continuous monitoring
Data Source
AI summary
An adaptive network has respective network nodes and network connections between the network nodes, the network nodes each having a transceiver which is coupled with a respective network connection. The respective transceiver is designed for providing a mean error value (MSE_i) which is representative of deviations of a received signal from predefined reference signal values. In a reference operating state of the adaptive network, a respective reference error value (MSE_REF) is determined as a function of the mean error value (MSE_i) provided by the respective transceiver. In at least one predefined operating state of the adaptive network, a respective actual error value (MSE_AV) is determined as a function of the mean error value (MSE_i) provided by the respective transceiver. As a function of the respective reference error value (MSE_REF) and the assigned actual error value (MSE_AV), it is determined whether a fault is present in the respective network connection which is coupled with the respective transceiver.