Journal
MEASUREMENT
Volume 152, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2019.107271
Keywords
Quantitative diagnosis; Beam defects; Non-contact random excitation; Laser Doppler; Continuous wavelet transform; Convolutional neural network
Funding
- National Natural Science Foundation of China [51305339]
- Natural Science Basic Research Plan in Shaanxi Province of China [2017JM5029]
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The beam structure is prone to defect damage during its use, and the rapid quantitative diagnosis of the beam structure can detect the defects of the beam in real time and quantitatively. In this article, the method of obtaining the vibration time-domain signal under random excitation of beam structure is proposed by using random vibration excitation and Laser Doppler principle. Based on this, the defect quantitative identification algorithm of beam structure is proposed based on fast Fourier, continuous wavelet transform and convolutional neural network. The random vibration of different parts of steel beams with artificial defects is measured by Laser Doppler method. The experimental results show that the defect size of the beam structure can be effectively identified only by the random vibration signal of the finite point. The method is expected to help to develop an online real-time assessment instrument for beam structure defects in service state. (C) 2019 Elsevier Ltd. All rights reserved.
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