APPLICATION OF A SUBSPACE-BASED FAULT DETECTION METHOD TO INDUSTRIAL STRUCTURES

✍ Scribed by L. MEVEL; L. HERMANS; H. VAN DER AUWERAER

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 318 KB
• Volume: 13
• Category: Article
• ISSN: 0888-3270
• DOI: 10.1006/mssp.1999.1247

✦ Synopsis

Early detection and localization of damage allow increased expectations of reliability, safety and reduction of the maintenance cost. This paper deals with the industrial validation of a technique to monitor the health of a structure in operating conditions (e.g. rotating machinery, civil constructions subject to ambient excitations, etc.) and to detect slight deviations in a modal model derived from in-operation measured data. In this paper, a statistical local approach based on covariance-driven stochastic subspace identi"cation is proposed. The capabilities and limitations of the method with respect to health monitoring and damage detection are discussed and it is explained how the method can be practically used in industrial environments. After the successful validation of the proposed method on a few laboratory structures, its application to a sports car is discussed. The example illustrates that the method allows the early detection of a vibration-induced fatigue problem of a sports car.

1999 Academic Press R This work has been carried out within the framework of the Eureka project no. 1562 SINOPSYS (Model based Structural monitoring using in-operation system identi"cation) coordinated by LMS, Leuven, Belgium. The data analyses were performed when L. Mevel was at LMS, Leuven.