Health monitoring and detection of a fatigue problem of a sports car

Early detection and location of damage allow increased expectations of reliability and 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, ...) and to detect damage in an early stage. A relevant approach is to early 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 identification is proposed. The paper illustrates that the method allows to early detect a vibration-induced fatigue problem of a sports car. 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.