Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ming J"'
Publikováno v:
Journal of Sound and Vibration. 431:192-211
To achieve planetary gearbox fault classification, vibration signal analysis has been widely employed with rich information about the health status and easy measurement. It is critical to extract features with enough health status information for fau
Publikováno v:
Measurement. 158:107719
The rotating speed information is significant for condition-based monitoring of rotating machines which are often operated under varying speed conditions. To automatically extract rotating speed from vibration signals, a deep learning model named man
Publikováno v:
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 224:1759-1769
Empirical mode decomposition (EMD) has been widely applied to analyse signals for the detection of faults in rotating machinery. However, sometimes, it cannot reveal signal characteristics accurately because of the mode mixing problem. Ensemble empir
Publikováno v:
Journal of Sound and Vibration. 287:614-624
Principal component analysis (PCA) is a method that transforms multiple data series into uncorrelated data series. Independent component analysis (ICA) is a method that separates multiple data series into independent data series. Both methods have be
Autor:
Ming J. Zuo, Mohammad R. Hoseini
Publikováno v:
Lecture Notes in Mechanical Engineering ISBN: 9781447149927
In this paper, a novel technique for denoising gearbox vibration has been proposed. We first convert the vibration signal into a two-dimensional matrix such that each row of the resulting matrix contains exactly one revolution of the gear. This matri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3619a9d82ef2a5be845450d034bac5d
https://doi.org/10.1007/978-1-4471-4993-4_55
https://doi.org/10.1007/978-1-4471-4993-4_55
Publikováno v:
2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings.
Linear discriminant analysis (LDA) is a method of feature extraction that has demonstrated successful applications. The selection of the number of discriminant directions (r) is important to LDA, yet little attention is paid in the reported literatur
Publikováno v:
2010 International Conference on Wavelet Analysis and Pattern Recognition.
Matching pursuit is effective in matching the characteristic structure of signals and extracting the time-frequency features directly. It is employed to analyze the vibration signals of a gearbox under healthy and faulty statuses. Based on a compound
Publikováno v:
Volume 1: 22nd Biennial Conference on Mechanical Vibration and Noise, Parts A and B.
Ensemble empirical mode decomposition (EEMD) was developed to alleviate the mode-mixing problem in empirical mode decomposition (EMD). With EEMD, the components with physical meaning can be extracted from the signal. The bispectrum, a third-order sta
Autor:
Yaguo Lei, Ming J. Zuo
Publikováno v:
Measurement Science and Technology. 20:125701
A Hilbert–Huang transform (HHT) is a time–frequency technique and has been widely applied to analyzing vibration signals in the field of fault diagnosis of rotating machinery. It analyzes the vibration signals using intrinsic mode functions (IMFs
Publikováno v:
Journal of Testing and Evaluation. 35:100758
Vibration analysis has been widely used in machine fault feature extraction and diagnosis of rotating machinery. The effects of modulation and nonstationarity in vibration signals collected from a faulty gearbox present challenges for fault feature e