Condition Monitoring of Industrial Equipment Based on Multi-Variables State Estimate Technique

Abstract

Unexpected failures commonly occur in industrial equipment, and condition monitoring could significantly improve the efficiency of maintenance and failure of early alarm. A condition monitoring method using multi-variables state estimate technique (MSET) is proposed, and an improved multi-variables memory matrix construction method is employed, furthermore, an analysis of comprehensive similarity index that considering variable weights is accomplished, and incipient failure alarm thresholds are determined, which lead to effective early detection of failure. The method proposed in this paper is validated using actual data for blower fan in a thermal power plant, and the simulation and comparison results are discussed. The verification results reveal that the proposed method is effective for failure monitoring modeling and achieve a superior accuracy, and incipient failure could be accurately detected.