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西安交通大学 [16]

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限定条件	专题：西安交通大学第一署名单位第一作者单位通讯作者单位

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	Optimal swarm decomposition with whale optimization algorithm for weak feature extraction from multicomponent modulation signal 期刊论文 Mechanical Systems and Signal Processing, 2019, 卷号: 122, 页码: 673-691 作者: Miao, Yonghao; Zhao, Ming; Makis, Viliam; Lin, Jing 收藏 \| 浏览/下载：19/0 \| 提交时间：2019/11/19 Bearing fault diagnosis Compound fault diagnosis Individual components Machinery condition monitoring Meta-heuristic optimizations Mode decomposition Numerical validations Optimization algorithms
	Order spectrogram visualization for rolling bearing fault detection under speed variation conditions 期刊论文 Mechanical Systems and Signal Processing, 2019, 卷号: 122, 页码: 580-596 作者: Wang, Yi; Tse, Peter W.; Tang, Baoping; Qin, Yi; Deng, Lei 收藏 \| 浏览/下载：17/0 \| 提交时间：2019/11/19 Bearing fault diagnosis Machinery condition monitoring Non-stationary vibration signals Operating condition Order tracking Rolling bearing vibration Spectrograms Time-frequency distributions
	Application of unsupervised linear discriminant analysis for condition monitoring of rotating machinery 会议论文作者: Khandaker, Noman; Zhang, Ruxin; Dong, Shuzhi; Xu, Bin; Zhang, Zhifeng 收藏 \| 浏览/下载：9/0 \| 提交时间：2019/11/19 Feature extraction methods K - means clustering K-nearest neighbors Linear discriminant analyses (LDA) Linear discriminant analysis Online condition monitoring Principle component analysis Unsupervised method
	Sparse filtering with the generalized l(p)/l(q) norm and its applications to the condition monitoring of rotating machinery 期刊论文 MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 卷号: 102, 页码: 198-213 作者: Jia, Xiaodong; Zhao, Ming; Di, Yuan; Li, Pin; Lee, Jay 收藏 \| 浏览/下载：9/0 \| 提交时间：2019/11/26 Deep learning Sparse filtering Incipient fault detection Rotating machinery Minimum entropy deconvolution
	A LOF-based method for abnormal segment detection in machinery condition monitoring 会议论文作者: Xu, Xuefang; Lei, Yaguo; Zhou, Xin 收藏 \| 浏览/下载：9/0 \| 提交时间：2019/11/26 abnormal segment detection machinery condition monitoring local outlier factor big data outlier
	A Dirty Data Recognition Method for Machinery Condition Monitoring in Big Data Era 会议论文作者: Lei, Yaguo; Zhou, Xin; Xu, Xuefang; Jia, Feng 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/11/26 volatility dirty data recognition heteroskedasticity big data condition monitoring
	2131. Nonlinear factor analysis and its application to acoustical source separation and identification 期刊论文 Journal of Vibroengineering, 2016, 卷号: 18, 页码: 3397-3411 作者: Cheng, Wei; Gao, Lin; Zhang, Jie; Lu, Jiantao 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/11/26 Acoustical sources Correlation analysis Machinery condition monitoring Noise monitoring Nonlinear factor analysis Operating condition Separation and identification Separation performance
	Speed Condition Monitoring of Rotating Machinery Using Electrostatic Method 会议论文作者: Li, Lin; Wang, Xiaoxin; Hu, Hongli; Yang, Xingyue 收藏 \| 浏览/下载：4/0 \| 提交时间：2019/12/02 electrostatic sensor auto-correlation function rotational speed measurement cross-correlation function
	A deep learning-based method for machinery health monitoring with big data 期刊论文 Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2015, 卷号: 51, 期号: [db:dc_citation_issue], 页码: 49-56 作者: Lei, Yaguo; Jia, Feng; Zhou, Xin; Lin, Jing 收藏 \| 浏览/下载：4/0 \| 提交时间：2019/12/02 Condition monitoring systems Fault diagnosis method Gear transmission system Identification accuracy Intelligent diagnosis methods Learning Theory Machinery Health Monitoring Signal processing technique
	Research progress and prospects on machinery monitoring under varying working condition 期刊论文中国工程科学(英文版), 2013, 期号: [db:dc_citation_issue], 页码: 29-34 作者: Lin Jing; Zhao Ming 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/12/10

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