Multiple Fault Diagnosis in Complex Physical Systems

Multiple fault diagnosis is a challenging problem because the number of candidates grows exponentially in the number of faults. In addition, multiple faults in dynamic systems may be hard to detect, because they can mask or compensate each other’s effects. The multiple fault problem is important, since the single fault assumption can lead to incorrect or failed diagnoses when multiple faults occur. We present an approach to simultaneous and cascaded multiple fault diagnosis in dynamical systems. Our approach is based on the TRANSCEND fault isolation scheme, where fault effects are represented as qualitative fault signatures. A notion of multiple fault diagnosability is introduced with respect to most likely minimal candidates. The online fault isolation algorithm explores the candidate space in increasing candidate size to generate minimal candidates. A mobile robot example demonstrates the approach.