Loosening state monitoring and identification of multi-bolted flange joints based on nonlinear wave energy transmission

Looseness detection of complex multi-bolted flange joints has long been an important problem to be focused on, especially for the scene of unknown multi-bolt loosening at the same time. In this study, a stable, efficient and robust guided wave recognition method for multi-bolt loosening is proposed for the first time by taking long-term monitoring data. This method studies the nonlinear characteristics of transmitted wave energy with bolt preload by formula. Then, a novel probability indicator reflecting the loosening position is proposed and a prior prediction model of bolt loosening degree is established. The prediction model is based on prior data fitting in a small number of working conditions, which has obvious advantages over deep learning. The simulation and experimental results based on flange pipes show that the proposed indicator can effectively determine the loosening positions of multiple bolts, and the prediction model also performs well in degree recognition. The proposed detection method has great potential in real-time monitoring applications by virtue of its high sensitivity to the loosening of multi-bolted joint structures.