On-line fault diagnosing techniques for a class of manufacturing equipment

This research develops an intelligent on-line monitoring and diagnosis system for a class of key manufacturing equipment. Important issues concerning the fault diagnosis system are discussed in this paper, including wide-band sensor, high-speed data acquisition for on-line monitoring, advanced signal processing techniques to suppress severe interference in manufacturing environment, and computational intelligence techniques to recognize fault patterns. Successful implementation of the intelligent monitoring and diagnosis system has provided decision-making support for equipment serviceability and condition-based maintenance.