A data indicator-based deep belief networks to detect multiple faults in axial piston pumps-Reference-Cited by-同舟云学术

A data indicator-based deep belief networks to detect multiple faults in axial piston pumps

Published:2018-11 Issue: Volume:112 Page:154-170
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Wang Shuhui,Xiang Jiawei,Zhong Yongteng,Tang Hesheng

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference45 articles.

1. Predicting the behavior of slipper pads in swash plate-type axial piston pumps;Harris;J. Dyn. Syst. Meas. Control.,1996

2. Vibration analysis with lifting scheme and generalized cross validation in fault diagnosis of water hydraulic system;Chen;J. Sound. Vib.,2007

3. Adaptive wavelet transform for vibration signal modelling and application in fault diagnosis of water hydraulic motor;Chen;Mech. Syst. Signal Process.,2006

4. A novel model for predicting thermoelastohydrodynamic lubrication characteristics of slipper pair in axial piston pump;Tang;Int. J. Mech. Sci.,2013

5. A combined method for triplex pump fault diagnosis based on wavelet transform, fuzzy logic and neuro-networks;Kong;Mech. Syst. Signal Process.,2004

Cited by 129 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An in-situ measurement approach for the oil film characteristics of the spherical valve plate pair in axial piston pumps;Measurement;2024-02

2. Fault Diagnosis in Centrifugal Pumps: A Dual-Scalogram Approach with Convolution Autoencoder and Artificial Neural Network;Sensors;2024-01-28

3. A Soft Sensor Model for Predicting the Flow of a Hydraulic Pump Based on Graph Convolutional Network–Long Short-Term Memory;Actuators;2024-01-17

4. Denoising graph neural network based hydraulic component fault diagnosis method;Mechanical Systems and Signal Processing;2023-12

5. Latest innovations in the field of condition-based maintenance of rotatory machinery: a review;Measurement Science and Technology;2023-11-30