Development of Fault Monitoring Technique for Agitator Driving System

The fault monitoring technique is presented for identifying the status of the agitator driving system in thermal reduction reactor. For identifying a fault such as bearing defect or clearance blocking, Wavelet transform (WT) is applied to vibration signals and features are extracted. For classification, the fuzzy ARTMAP is employed. With the features from WT, a single training epoch and a single learning iteration are sufficient for the fuzzy ARTMAP to classify the faults. The test results show the perfect classification though some features extracted from the test data are distorted against those in the training data