Research on feature selection for rotating machinery based on Supervision Kernel Entropy Component Analysis with Whale Optimization Algorithm
Authors:
- Lili BaiLBLili Bai
- Zhennan HanZHZhennan Han
- Jiajun RenJRJiajun Ren
- Xiaofeng QinXQXiaofeng Qin
- 1 July 2020
- journal article
- research article
- Published by Elsevier in Applied Soft Computing
- Vol. 92
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (50775157,, 61805133)
This publication has 31 references indexed in Scilit:
- Research and application of improved adaptive MOMEDA fault diagnosis methodMeasurement, 2019
- A Novel Fault Diagnosis Method of Gearbox Based on Maximum Kurtosis Spectral Entropy DeconvolutionIEEE Access, 2019
- Self-adaptive bearing fault diagnosis based on permutation entropy and manifold-based dynamic time warpingMechanical Systems and Signal Processing, 2019
- Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimizationMechanical Systems and Signal Processing, 2019
- Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosisMechanical Systems and Signal Processing, 2018
- Adaptive parameterless empirical wavelet transform based time-frequency analysis method and its application to rotor rubbing fault diagnosisSignal Processing, 2017
- Knowledge extraction using data mining for multi-class fault diagnosis of induction motorNeurocomputing, 2015
- Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode DecompositionSensors, 2013
- Manifold subspace distance derived from kernel principal angles and its application to machinery structural damage assessmentSmart Materials and Structures, 2013
- Experimental Evaluation of a Unified Time-Scale-Frequency Technique for Bearing Defect Feature ExtractionJournal of Vibration and Acoustics, 2009