Adaptive Fault Diagnosis Algorithm for Controller Area Network

A controller area network (CAN)-based distributed system may develop faults at run-time. These faults need to be detected and diagnosed. This paper proposes a new algorithm named adaptive fault diagnosis algorithm for CAN (AFDCAN). It is designed for low-cost resource-constrained distributed embedded systems. The proposed algorithm detects all faulty nodes on the CAN. It allows new node entry and reentry of repaired faulty nodes during a diagnostic cycle. AFDCAN is found to provide high fault tolerance and to ensure reliable communication. It uses single-channel communication deploying the bus-based standard CAN protocol. A hardware implementation of the proposed algorithm has been used to obtain the results. The results show that the proposed algorithm diagnoses all faults in the system. Analysis of the proposed algorithm proves that the algorithm uses a definite and bounded number of testing rounds and messages to complete one diagnostic cycle.

[1]  Yufei Xu,et al.  H∞ filter design for a class of networked control systems via T-S fuzzy model approach , 2010, International Conference on Fuzzy Systems.

[2]  Huaguang Zhang,et al.  Stabilization of Switched Nonlinear Systems With All Unstable Modes: Application to Multi-Agent Systems , 2011, IEEE Transactions on Automatic Control.

[3]  et al.,et al.  Design of intelligent distributed control systems: a dependability point of view , 2004, Reliab. Eng. Syst. Saf..

[4]  Nagarajan Kandasamy,et al.  Time-constrained failure diagnosis in distributed embedded systems: application to actuator diagnosis , 2005, IEEE Transactions on Parallel and Distributed Systems.

[5]  Günter Grünsteidl,et al.  TTP - A Protocol for Fault-Tolerant Real-Time Systems , 1994, Computer.

[6]  Supriya Kelkar,et al.  Comparison and analysis of Quotient Remainder Compression-algorithms for automotives , 2012, 2012 Annual IEEE India Conference (INDICON).

[7]  Douglas M. Blough,et al.  The Broadcast Comparison Model for On-Line Fault Diagnosis in Multicomputer Systems , 1999, IEEE Trans. Computers.

[8]  Sachin C. Patwardhan,et al.  FAULT DETECTION AND ISOLATION USING CORRESPONDENCE ANALYSIS , 2005 .

[9]  Erik Frisk,et al.  Distributed Diagnosis Using a Condensed Representation of Diagnoses With Application to an Automotive Vehicle , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[10]  Jianhui Luo,et al.  Data Reduction Techniques for Intelligent Fault Diagnosis in Automotive Systems , 2006, 2006 IEEE Autotestcon.

[11]  Thomas Nolte,et al.  Integrating reliability and timing analysis of CAN-based systems , 2002, IEEE Trans. Ind. Electron..

[12]  Sudhakar M. Reddy,et al.  A Diagnosis Algorithm for Distributed Computing Systems with Dynamic Failure and Repair , 1984, IEEE Transactions on Computers.

[13]  Kenneth H. Rosen,et al.  Discrete Mathematics and its applications , 2000 .

[14]  T. Führer,et al.  Time Triggered Communication on CAN ( Time Triggered CAN-TTCAN ) , 2000 .

[15]  Michael J. Pont,et al.  Fault-Tolerant Time-Triggered Communication Using CAN , 2007, IEEE Transactions on Industrial Informatics.

[16]  Zehui Mao,et al.  $H_\infty$-Filter Design for a Class of Networked Control Systems Via T–S Fuzzy-Model Approach , 2010, IEEE Transactions on Fuzzy Systems.

[17]  R. Hugel,et al.  Fault tolerant TTCAN networks , 2002 .

[18]  Kyung-Yong Chwa,et al.  Schemes for Fault-Tolerant Computing: A Comparison of Modularly Redundant and t-Diagnosable Systems , 1981, Inf. Control..

[19]  Julian Proenza,et al.  An active star topology for improving fault confinement in CAN networks , 2006, IEEE Transactions on Industrial Informatics.

[20]  Santosh B. Noronha,et al.  Polar classification with correspondence analysis for fault isolation , 2009 .

[21]  S. Louis Hakimi,et al.  An optimal algorithm for distributed system level diagnosis , 1991, [1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium.

[22]  P. Dash,et al.  ICA Methods for Blind Source Separation of Instantaneous Mixtures: A Case Study , 2007 .

[23]  Abhijit Sengupta,et al.  On self-diagnosable multiprocessor systems: diagnosis by the comparison approach , 1989, [1989] The Nineteenth International Symposium on Fault-Tolerant Computing. Digest of Papers.

[24]  Chi-Man Vong,et al.  A New Framework of Simultaneous-Fault Diagnosis Using Pairwise Probabilistic Multi-Label Classification for Time-Dependent Patterns , 2013, IEEE Transactions on Industrial Electronics.

[25]  Aurobinda Routray,et al.  Data reduction and clustering techniques for fault detection and diagnosis in automotives , 2010, 2010 IEEE International Conference on Automation Science and Engineering.

[26]  Amiya Nayak,et al.  Comparison-Based System-Level Fault Diagnosis: A Neural Network Approach , 2012, IEEE Transactions on Parallel and Distributed Systems.

[27]  Juan R. Pimentel,et al.  A Flexible Architecture for Highly Dependable Embedded Applications , 2004 .

[28]  Sampath Rangarajan,et al.  A Distributed System-Level Diagnosis Algorithm for Arbitrary Network Topologies , 1995, IEEE Trans. Computers.

[29]  Sachin C. Patwardhan,et al.  Data reduction algorithm based on principle of distributional equivalence for fault diagnosis , 2012 .

[30]  Danwei Wang,et al.  Fault Detection Isolation and Estimation in a Vehicle Steering System , 2012, IEEE Transactions on Industrial Electronics.

[31]  Julian Proenza,et al.  Quantitative Comparison of the Error-Containment Capabilities of a Bus and a Star Topology in CAN Networks , 2011, IEEE Transactions on Industrial Electronics.

[32]  Miroslaw Malek,et al.  A comparison connection assignment for diagnosis of multiprocessor systems , 1980, ISCA '80.

[33]  Supriya Kelkar,et al.  Control area network based quotient remainder compression-algorithm for automotive applications , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[34]  Takashi Nanya,et al.  A Hierarachical Adaptive Distributed System-Level Diagnosis Algorithm , 1998, IEEE Trans. Computers.