Vibration signal–based fault diagnosis in complex structures: A beam-like structure approach

Abstract

Sensor network–based data-driven fault diagnosis in complex structures using limited prior knowledge is an interesting and hot topic in the literature. In this study, an integrated feature characterization and fuzzy decision method is developed based on a novel beam-like structure approach for fault diagnosis using available limited prior knowledge. Complex structures embedded with vibration sensors can be regarded as some virtual beam-like structures by considering the vibration transmission path from vibration sources to each sensor. The dynamic response of the structures in this vibration transmission path can demonstrate obvious fault features if there is a fault (typically, for example, cracks in connecting rods or around bolts, and bolt-loosening). These fault features can be effectively characterized and efficiently captured and utilized for fault diagnosis with a fuzzy decision method based on the virtual beam-like structure concept. This novel virtual beam-like structure approach needs only limited prior knowledge of the faults and does not require stationary response data. It is also not with respect to a specific structure design and is easy to implement within a sensor network. The effectiveness of the proposed method is well validated in the experiments for fault diagnosis including loosening bolts or cracks around bolts of complex structures such as bolted-base hanging structures in satellites.