噪声与振动控制2026，Vol.46Issue(3)：97-103,7.DOI:10.3969/j.issn.1006-1355.2026.03.015
信息重构融合深度学习的泵机组故障诊断方法
Fault Diagnosis Method of Pump Units Based on Information Reconstruction and Deep Learning
摘要
Abstract
Aiming at the problems of noise interference and low diagnostic accuracy of pump unit in actual operation,a fault diagnosis method of pump unit based on information reconstruction and deep learning was proposed.Firstly,the Red-billed blue magpie optimizer(RBMO)was used to optimize Variational mode decomposition(VMD),to decompose the vibration signal into a series of subsequences.Secondly,the vibration signal was reconstructed using Permutation Entropy(PE)and filtering algorithm.Finally,the generated image was input into a neural network based on the EfficientNet network to output the diagnostic results,and the Motif difference field(MDF)was used to convert the reconstructed signal into a two-dimensional image.This method was verified by experiments.Experimental results show that the proposed method can accurately classify faults,and has better noise resistance and higher accuracy than other methods under the condition of strong noise interference.关键词
故障诊断/红嘴蓝鹊优化算法/变分模态分解/信息重构/图形差分场Key words
fault diagnosis/red-billed blue magpie optimizer/variational mode decomposition/information reconstruction/graph difference field分类
信息技术与安全科学引用本文复制引用
巫庆辉,许皓远,魏宇晨..信息重构融合深度学习的泵机组故障诊断方法[J].噪声与振动控制,2026,46(3):97-103,7.基金项目
国家自然科学基金(52177047) （52177047）
2024年度辽宁省教育科学规划课题项目(JG24DB234) （JG24DB234）
