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Ling Zhao, Xin Chi, Pan Li and Jiawei Ding
A rolling bearing vibration signal fault feature enhancement method based on adaptive complete ensemble empirical mode decomposition with adaptive noise algorithm (CEEMDAN) and maximum correlated kurtosis deconvolution (MCKD) is proposed to address the i...
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Kang Wang, Zhi-Jiang Xu, Yi Gong and Ke-Lin Du
Vibration signal analysis is the most common technique used for mechanical vibration monitoring. By using vibration sensors, the fault prognosis of rotating machinery provides a way to detect possible machine damage at an early stage and prevent property...
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Qiang Tu, Fei Yuan, Weidi Yang and En Cheng
Diver breathing sounds can be used as a characteristic for the passive detection of divers. This work introduces an approach for detecting the presence of a diver based on diver breathing sounds signals. An underwater channel model for passive diver dete...
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Yongqiang Duan, Chengdong Wang, Yong Chen and Peisen Liu
The fault frequencies are as they are and cannot be improved. One can only improve its estimation quality. This paper proposes a fault diagnosis method by combining local mean decomposition (LMD) and the ratio correction method to process the short-time ...
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Hung Ngoc Nguyen, Cheol-Hong Kim and Jong-Myon Kim
Exact evaluation of the degradation levels in bearing defects is one of the most essential works in bearing condition monitoring. This paper proposed an efficient evaluation method using a deep neural network (DNN) for correct prediction of degradation l...
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Benjamin Lumantarna
Pág. pp. 24 - 30
In the absence of design earthquake accelerogram, to do time history analysis the Indonesian Seismic code required the use of a minimum of four earthquake accelerograms. This procedure gives some difficulty in research. One possibility is to use a spect...
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