This book chapter deals with vibration-based SHM methods which enable a structure to deliver information about its current health status and help to predict its future remaining lifetime. Therefore, the structure has to be equipped with diagnostic sensor networks and sensors for monitoring of the loads. Computational algorithms are used to analyze these response data and perform a self-diagnosis with the goal that the structure can release early warnings about any critical health state, locate and classify type and size of damage. This paper intends to give an overview and point out recent developments of vibration-based methods for SHM. All these methods have in common that a structural change due to a damage results in a more or less significant change of the dynamic behavior. Unfortunately, also changing environmental and operational conditions have a non-negligible influence on the system behavior. Therefore, a diagnostic system must be able to distinguish between damage and other influences, learning the system behavior under varying conditions in the healthy state by means of classification techniques. Moreover, for a prognosis of the remaining useful life, the knowledge of the time-history of external deterministic or random loads is essential. An overview is given on currently used methods and a robust observer-based algorithm is presented in detail for on-line reconstruction of the unknown external loads from the vibration response data. Different practical examples show the applicability of the methods.
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- Vibration-Based Damage Diagnosis and Monitoring of External Loads
- Springer Vienna
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