Open AccessAn Application of Time-Frequency-Based Analysis Method for Identifying Bolt Anchorage System
Author(s) -
Haiqing Zheng,
Yang Zhang,
Han Gao,
Xiaoyun Sun
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/5296904
Subject(s) - frequency domain , time domain , identification (biology) , convolution (computer science) , short time fourier transform , time–frequency analysis , domain (mathematical analysis) , computer science , bar (unit) , system identification , engineering , structural engineering , algorithm , artificial intelligence , fourier transform , data mining , mathematics , computer vision , geology , fourier analysis , artificial neural network , mathematical analysis , oceanography , botany , filter (signal processing) , biology , measure (data warehouse)
A rock bolt refers to a reinforcing bar used commonly in geotechnical engineering. Also, defect identification of bolt anchorage system determines the safe operation of the reinforced structures. In the present paper, to accurately extract defect information, a CNN model based on time-frequency analysis is proposed, covering both time-domain and frequency-domain information. The effect of the number of convolution kernels on the defect identification results is discussed. By laboratory experiments, the performances of STFT-based CNN with those of time-domain input or frequency-domain input-based 1D CNN are compared, and the results demonstrate that the proposed method showed enhanced performance in identification accuracy.
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