Probabilistic diagnosis for sparsely interconnected systems

摘要

In this paper, we present a system level fault diagnosis algorithm for identifying faulty and fault-free units in sparsely interconnected systems. The algorithm is partially based on a comparison approach where identical test vectors are applied to all units and their outputs are compared among themselves. Typical comparison diagnosis schemes based on majority voting or voting with threshold=1 are shown to be inappropriate for diagnosing those systems implemented on a single chip or wafer. Unlike other schemes, our scheme can adjust algorithm parameters depending on unit yield, degree of connectivity, and the probability that common mode failures will occur. Further improvements in fault coverage are made by disseminating test results to neighbors. The fault coverage of our diagnosis algorithm is remarkably high, and diagnosis decisions are made in a distributed fashion.