Key Technologies for Health Management and Applications of Aero-Engine Based on Principal Component Analysis

2014 ◽  
Vol 538 ◽  
pp. 218-221
Author(s):  
Jian Guo Cui ◽  
Xu Zhao ◽  
Jun Li ◽  
Bo Cui ◽  
Li Ying Jiang ◽  
...  

Aero-Engine health management generally involves a series of activities over the period from the aerospace breaking down until it returning to normal, including signal processing, monitoring, health assessment, decision supporting, human-computer interaction, and so on. As one of the key technology of Aero-Engine health management, fault diagnosis plays a very important role on the safe operation of Aero-Engine. Currently, for effective challenging Aero-Engine health management, a fault diagnosis of Aero-Engine based on Principal Component Analysis (PCA) s proposed. Firstly, based on a variety of significant parameters of the collected information, principal component analysis model is established. Secondly, the fault diagnosis of engine operating conditions is realized by comparing the T2 statistic and Squared Prediction Error (SPE) statistic as an engine running in good condition threshold limits. Finally, through the variable's cumulative contributions diagram with the behavior of SPE overrun, the fault variables are effectively worked out. Experimental results show that the proposed PCA method can efficiently come true Aero-Engine health management o and has some engineering applications values.

2014 ◽  
Vol 644-650 ◽  
pp. 2556-2561
Author(s):  
Ning Lv ◽  
Guang Yuan Bai ◽  
Yuan Jian Fu ◽  
Lu Qi Yan

Aiming at the limitation of the application of principal component analysis model for fault diagnosis in nonlinear time-varying process, kernel transformation theory is introduced into the data feature extraction of nonlinear space, on the basis of the periodic characteristics of the batch process, putting forward a kind of improved multi-way kernel principal component analysis fault diagnosis model, which effectively solves the nonlinear problem of process data and ensures integrity of data and information extraction. By comparing with other methods in experiment, the results show that the proposed method has good real-timing and accuracy to slow time-varying of batch process.


2011 ◽  
Vol 50-51 ◽  
pp. 728-732
Author(s):  
Ping Li ◽  
Ming Ying Zhuo ◽  
Li Chao Feng ◽  
Rui Zhang

Non-performance loan ratio is one of the important assessment criteria of the security of credit assets. It is also an important financial indicator to evaluate the general strength of commercial banks. Using principal component analysis method and statistical software SPSS16.0 and based on the non-performance loan ratio and relative data of some commercial banks in China in 2007, this paper provided a principal component analysis model for the non-performance loan ratio of China’s commercial banks. The factors that affect the non-performance loan ratio were refined in this paper. Finally, the characteristics of effect factors of each bank were analyzed and compared in detail.


2017 ◽  
Vol 128 ◽  
pp. 05015
Author(s):  
Juan-Juan Li ◽  
Liang Hu ◽  
Guo-Ying Meng ◽  
Guang-Ming Xie ◽  
Ai-Ming Wang ◽  
...  

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