Abstract
Abstract
The percussion-based method has become a hot spot for bolt looseness monitoring due to its advantages of non-contact sensing, portability, and low cost. However, the features of bolt looseness in percussion methods lack phase information. In this paper, a percussion method based on the all-pole group delay function in the phase domain is proposed for the first time, and the bolt looseness is determined by a convolutional neural network. Under the four signal-to-noise ratio levels (0, 2, 4 and 6 dB), the accuracy of the proposed method is 90.25%, 92.75%, 93.5% and 94%. The experiment proves the percussion audio signal of the structural point away from the bolt can reflect the looseness of the bolt. The phase feature can represent the information of bolt looseness and has fast training speed and high recognition accuracy, which is suitable for detecting bolt looseness torque.
Funder
Science and Technology Project of State Grid Shaanxi Electric Power Company Limited
Subject
Electrical and Electronic Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science,Atomic and Molecular Physics, and Optics,Civil and Structural Engineering,Signal Processing
Cited by
6 articles.
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