Abstract: By the association rule mining algorithm, it can diagnose faults of complex equipment in a general and fast way without the need of subjective experience. The drawback is that the classical association rule algorithm requires that the frequency and importance of the items should be similar. However, in practical fault diagnosis applications, the contribution of each fault factor is different. To solve this problem, a new model called matrix-based weighted association rule mining algorithm suitable for equipment fault diagnosis is proposed by introducing minsupport expectation. Experiments show that the model improves the diagnostic efficiency while obviously increasing the accuracy of fault diagnosis. Then, an equipment fault diagnosis system is designed and implemented based on matrixbase weighted association rule mining algorithm (MWARMA) model.

Key words: equipment fault diagnosis, expert system, weighted association rule, minsupport expectation