Multi-Sensor Data Driven with PARAFAC-IPSO-PNN for Identification of Mechanical Nonstationary Multi-Fault Mode

Multi-Sensor Data Driven with PARAFAC-IPSO-PNN for Identification of Mechanical Nonstationary Multi-Fault Mode

Data analysis has wide applications in eliminating the irrelevant and redundant components in signals to reveal the important informational characteristics that are required. Conventional methods for multi-dimensional data analysis via the decomposition of time and frequency information that ignore...

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Hlavní autoři: Hanxin Chen, Yunwei Xiong, Shaoyi Li, Ziwei Song, Zhenyu Hu, Feiyang Liu
Médium: Článek
Jazyk:English
Vydáno: MDPI AG 2022-02-01
Edice:Machines
Témata:
parallel factor analysis (PFA)
feature extraction
probabilistic neural network (PNN)
fault diagnosis
On-line přístup:https://www.mdpi.com/2075-1702/10/2/155

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https://www.mdpi.com/2075-1702/10/2/155

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