Bolt loosening detection based on audio classification

Abstract

As the most widely used coupling structure in electromechanical systems, bolt coupling is the important part in these systems. The reliability and strength of bolted joint are affected by pretension force, which is one of the most important factors to ensure the stability of bolt coupling. The inspection personnel hit the bolt with a hammer and judge the state of the bolt based on the sound. Although this method is very simple, the ability of the human ear to distinguish the knocking sound is poor, it can only distinguish the bolt with larger looseness. So a bolt loosening detection method based on audio classification is presented in this article. First, the hammering sound at different levels of bolt loosening was collected by smartphone. Then, the audio data were extracted to form a dataset. Finally, the support vector machine was used to train and test the dataset, and obtain the bolt loosening quantitative detection. A series of experiments were carried on to verify the accuracy and stability of this method. The results show that this method has high recognition accuracy and strong noise immunity. Therefore, this method can effectively reduce the occurrence of disasters.