Journal of System Simulation
Abstract
Abstract: In view of the wood component glue line defect, a method of wood structure nondestructive detection was proposed based on ant colony BP neural network. The wood specimens was tested to obtain the test signal by ultrasonic testing instrument, in order to eliminate the testing effect of the tester gain control and defect size, angle variation on the test defect echo amplitude, the defect signal amplitude was needed to normalization. The wood component decomposition of ultrasonic signals was de-composite to different frequency channels by the domain band-pass characteristics of the wavelet frequency. By extract characteristic of the original signal in different frequency channels, the ant colony neural network could train the parameters and examine the position of the wood components with defection. The test results show the effectiveness of the proposed method.
Recommended Citation
Zhou, Guoxiong; Zhou, Xianyan; Wang, Jiejun; and Huang, Te
(2020)
"Wood Structure Nondestructive Detection Based on Wavelet Analysis Ant-colony BP Network,"
Journal of System Simulation: Vol. 27:
Iss.
11, Article 26.
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol27/iss11/26
First Page
2804
Revised Date
2014-06-23
DOI Link
https://doi.org/
Last Page
2810
CLC
TP229
Recommended Citation
Zhou Guoxiong, Zhou Xianyan, Wang Jiejun, Huang Te. Wood Structure Nondestructive Detection Based on Wavelet Analysis Ant-colony BP Network[J]. Journal of System Simulation, 2015, 27(11): 2804-2810.
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