Searched for: subject%3A%22Planetary%255C+gear%22
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Liu, C. (author), Cheng, Gang (author), Chen, Xihui (author), Pang, Y. (author)
Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was...
journal article 2018
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Kuai, Moshen (author), Cheng, Gang (author), Pang, Y. (author), Li, Yong (author)
For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete...
journal article 2018
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Li, Y. (author), Cheng, G. (author), Pang, Y. (author), Kuai, Moshen (author)
Poor working environment leads to frequent failures of planetary gear trains. However, complex structure and variable transmission make the vibration signal strongly non-linear and non-stationary, which brings big problems to fault diagnosis. A method of planetary gear fault diagnosis via feature image extraction based on multi central...
journal article 2018