Multiple-Fault Diagnosis Based On Adaptive Diagnostic Test Pattern Generation

In this paper, we propose two fault-diagnosis methods for improving multiple-fault diagnosis resolution. The first method, based on the principle of single-fault activation and single-output observation, employs a new circuit transformation technique in conjunction with the use of a special type of diagnostic test pattern, named single-observation single-location-at-a-time (SO-SLAT) pattern. Given a list of candidate suspects (which could be stuck-at, transition, bridging, or other faults obtained by any existing diagnosis method), we generate a set of SO-SLAT patterns, each of which attempts to activate only one fault in the list and propagate its effects only to a specific observation point. Observing the responses of the circuit under diagnosis to the SO-SLAT patterns helps more precisely determine whether each fault suspect is a true or false candidate. The method can tolerate most of the timing hazards for a more accurate diagnosis of failures caused by timing faults. The second method generates and applies limited-cycle sequential tests, based on a Boolean satisfiability solver, to identify multiple defective signals which can jointly explain the circuit’s faulty behavior. These two methods can be applied independently and/or jointly after any existing state-of-the-art diagnosis process to further improve the diagnosis resolution. The experimental results demonstrate the effectiveness of the proposed methods for diagnosing multiple faults, including timing faults.