Multisensor Information Fusion for Fault Diagnosis of Axial Piston Pump Based on Improved WPD and SSA-KSTTM-Reference-Cited by-同舟云学术

Multisensor Information Fusion for Fault Diagnosis of Axial Piston Pump Based on Improved WPD and SSA-KSTTM

Published:2023-10-01 Issue:19 Volume:23 Page:22998-23010
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Chen Dong-Ning¹^ORCID,Zhou Zi-Yu¹^ORCID,Hu Dong-Bo¹^ORCID,Liu Wen-Ping²^ORCID,Liu Ji-Tao¹^ORCID,Chen Ya-Nan³^ORCID

Affiliation:

1. Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control and the Key Laboratory of Advanced Forging and Stamping Technology and Science, Yanshan University, Qinhuangdao, China

2. Xuzhou Xugong Excavation Machinery Company Ltd., Xuzhou, China

3. Qinglong County Power Supply Branch and State Grid Jibei Electric Power Company Ltd., Qinhuangdao, China

Funder

National Natural Science Foundation of China

Hebei Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10269339/10233232.pdf?arnumber=10233232

Reference47 articles.

1. A Bearing Fault Diagnosis Method Based on Improved Mutual Dimensionless and Deep Learning

2. A fusion feature and its improvement based on locality preserving projections for rolling element bearing fault classification

3. Fault Feature Selection and Diagnosis of Rolling Bearings Based on EEMD and Optimized Elman_AdaBoost Algorithm

4. Kernelized support tensor train machines

5. A Fault Feature Extraction Method for the Fluid Pressure Signal of Hydraulic Pumps Based on Autogram

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