Quantitative identification of broken wire for steel rope based on BP neural network
Quantitative identification of broken wire for steel rope based on BP neural network
- Author(s): Dou Zhijuan and Wang Minhua
- DOI: 10.1049/cp.2012.1293
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- Author(s): Dou Zhijuan and Wang Minhua Source: International Conference on Automatic Control and Artificial Intelligence (ACAI 2012), 2012 p. 1614 – 1616
- Conference: International Conference on Automatic Control and Artificial Intelligence (ACAI 2012)
- DOI: 10.1049/cp.2012.1293
- ISBN: 978-1-84919-537-9
- Location: Xiamen, China
- Conference date: 3-5 March 2012
- Format: PDF
To counter the problem in quantitative identification of broken wire for steel rope, a BP neural network model was set up by using Matlab in the article. According to the simulative and real detection data, its features of reliability and usability were proved.
Inspec keywords: neural nets; ropes; steel; reliability; backpropagation; condition monitoring; mechanical engineering computing; wires
Subjects: Maintenance and reliability; Neural computing techniques; Mechanical components; Civil and mechanical engineering computing; Mechanical engineering applications of IT
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