Centrifugal Pump Fault Diagnosis Methods Based on Dislocation Superposition Methods and Improved Probabilistic Neural Networks

被引：0
|
作者：
Chen J. [1 ,2 ]
Xu C. [1 ,2 ]
Xu T. [1 ,2 ]
机构：
[1] Institute of Noise and Vibration Engineering, Hefei University of Technology, Hefei
[2] Automotive NVH Engineering & Technology Research Center, Anhui Province, Hefei
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2023年 / 34卷 / 23期
关键词：
centrifugal pump; dislocation superposition method; fault diagnosis; Harris hawk optimization algorithm; probabilistic neural network;
D O I：
10.3969/j.issn.1004-132X.2023.23.009
中图分类号：
学科分类号：
摘要：
Based on dislocation superposition method and improved probabilistic neural network, a fault diagnosis method of centrifugal pumps was proposed to solve the problems of online fault diagnosis using acoustic radiation signals of centrifugal pumps under strong background noise. Firstly, the acoustic radiation signals of centrifugal pumps were denoised by dislocation superposition method to enhance the fault information in acoustic radiation signals and improve the signal-to-noisc ratio. The time domain features of acoustic signals were extracted to construct the time domain feature matrix. After dimensionality reduction of the obtained time domain feature matrix through principal component analysis, which was used as the inputs of machine learning probabilistic neural network. At the same time, Harris hawk optimization algorithm was used to optimize the parameters of the probabilistic neural network to get the diagnosis model, and then the improved probabilistic neural network was used to recognize the patterns of the centrifugal pump faults, and compared with a variety of diagnostic methods. The experimental results show that the dislocation superposition method may highlight the signal characteristics and realize signal enhancement, and the improved probabilistic neural network has a good ability of online fault diagnosis of centrifugal pump acoustic radiation signals. © 2023 China Mechanical Engineering Magazine Office. All rights reserved.
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页码：2854 / 2861
页数：7
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共 20 条
  • [1] HOU Jiaoyi, SUN Hongyu, XU Aoyu, Et al., Fault Diagnosis of Synchronous Hydraulic Motor Based on Acoustic Signals[J], Advances in Mechanical Engineering, 12, 4, (2020)
  • [2] ZHAO Yike, WANG Jiaxu, ZHANG Xin, Et al., Aero-engine Fault Diagnosis Based on an Enhanced Minimum Entropy Deconvolution [J], China Mechanical Engineering, 34, 2, pp. 193-200, (2023)
  • [3] WU Lei, WANG Jiaxu, ZHANG Xin, Et al., Blind Deconvolution Based on Reweighted-kurtosis Maximization for Wind Turbine Fault Diagnosis, China Mechanical Engineering, 33, 19, pp. 2356-2363, (2022)
  • [4] YAO Jiachi, LIU Chao, SONG Keyu, Fault Diagnosis of Planetary Gearbox Based on Acoustic Signals[J], Applied Acoustics, 181, (2021)
  • [5] LIU Zhong, ZOU Shuyun, LI Zhipeng, Et al., Wavelet Energy Features of Acoustic Emission Signals under Centrifugal Pump Cavitation Conditions [J], Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 31, 8, pp. 99-103, (2015)
  • [6] YANG Bo, HUANG Qian, FU QIANG, Et al., Fault Diagnosis Method for Horizontal Centrifugal Pump Based Oil CEEMD and Optimized KNN[J], Mechanical & Electrical Engineering Magazine, 39, 11, pp. 1502-1509, (2022)
  • [7] ZHOU Yunlong, LYU Yuanzheng, Incipient Cavitations Fault Diagnosis for a Centrifugal Pump Based on Multi-position Noise Analysis[J], Journal of Vibration and Shock, 36, 7, pp. 39-44, (2017)
  • [8] TAN Yi, Research on Pump Fault Diagnosis and Location Method Based on Sound[D], (2022)
  • [9] YAO KE, WANC Qi, MIAO Yuzhou, Et al., Fault Diagnosis Method for Centrifugal Pumps Based on PARAFAC Analysis and SVM[J], Noise and Vibration Control, pp. 106-111, (2022)
  • [10] CHEN Daibing, YUAN Shouqi, PEI Ji, Et al., Identification Method for Centrifugal Pump Working Condition Based on Improved Binary Tree Support Vector Machine [J], Journal of Drainage and Irrigation Machinery Engineering, 41, 1, pp. 8-15, (2023)
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