Q
Qian Chen
Researcher at Nanjing University of Aeronautics and Astronautics
Publications - 64
Citations - 1828
Qian Chen is an academic researcher from Nanjing University of Aeronautics and Astronautics. The author has contributed to research in topics: Vibration isolation & Isolator. The author has an hindex of 21, co-authored 58 publications receiving 1578 citations. Previous affiliations of Qian Chen include Applied Materials & Nanjing University.
Papers
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Journal ArticleDOI
The application of principal component analysis and kernel density estimation to enhance process monitoring
TL;DR: The application of kernel density estimation (KDE) and principal component analysis (PCA) to provide enhanced monitoring of multivariate processes to demonstrate the power and advantages of the KDE approach over parametric density estimation which is still widely used.
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Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data
TL;DR: In this paper, the concept of cointegration is introduced for the analysis of non-stationary time series, as a promising new approach for dealing with the problem of environmental variation in monitored features.
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Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion
TL;DR: In this paper, a novel method for fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis (MF-DFA) and Mahalanobis distance criterion (MDC) was proposed.
Proceedings Article
Fault diagnosis of rolling bearings using multifractal detrended fluctuation analysis and Mahalanobis distance criterion
TL;DR: In this article, the multifractal detrended fluctuation analysis (MF-DFA) is applied to uncover the multifractality buried in nonstationary time series for exploring rolling bearing fault data.
Journal ArticleDOI
Cointegration Testing Method for Monitoring Nonstationary Processes
TL;DR: An application case study to an industrial distillation unit with a nonstatioanry process shows that a tidy cointegration model can describe the dynamic equilibruim state of the unit and correctly detect abnormal behavior of the process.