Diagnosis of Intermittent Connection Faults for CAN Networks With Complex Topology

As the topologies of Controller Area Networks (CAN) in the industrial production systems become increasingly complex, robust and accurate diagnosis of network faults are essential to the system maintenance and reliability assurance. In CAN network, intermittent connection (IC) fault is a hidden problem, which deteriorates the performance and safety of the system. Although IC fault diagnosis methods had been studied, diagnosis of IC faults for CAN network with complex topology has not been systematically addressed. In this paper, a novel IC fault diagnosis methodology for CAN networks with complex topologies is proposed, which utilizes distributed measurement from data link layer information for error pattern analysis. First, the diagnosability of IC faults is defined and the analysis method is presented. Then, local and trunk IC faults localization algorithm is developed based on the integration of error patterns with the network topology. Third, a sequential fault diagnosis strategy is proposed to achieve the full diagnosis of IC faults by gradually compressing the non-diagnosable sub-networks. Testbed is constructed and case studies under various topologies and IC faults scenarios are conducted to demonstrate the effectiveness of the proposed methodology. Experiment results show that the IC faults locations diagnosed by the proposed methodology agree well with the experiment setups.