NDLI: A study on time series models and criterion rules based on condition monitoring of the tracking test system

Content Provider	IEEE Xplore Digital Library
Author	Wang Feng Li Xia Zhang Bing Wang Xiang-yu
Copyright Year	2013
Description	Author affiliation: Sch. of Distance & Further Educ., Southwest Jiaotong Univ., Chengdu, China (Wang Xiang-yu) \|\| State Key Lab. of Traction Power, Southwest Jiaotong Univ., Chengdu, China (Wang Feng; Li Xia; Zhang Bing)
Abstract	Due to lots of measuring positions, long duration, complex test objects and various data types in the tracking test system, there is a badly need to find a simple, effective and convenient analysis method to process the test data and figure out the potential rules. This paper finds a method of identifying the optimal time-series model automatically, through studying different models and criterion rules. This method doesn't need to do any artificial hypothesis to the evolution rules of parameters, but estimates the changing rules of parameters from data adhering to the thought of “let the data speak for themselves”, so it achieves the self-explanatory of the data. As a conclusion, the accuracy of the method introduced in this paper is verified through simulating to the gear acceleration data measured from EMU tracking test and the method is effective and convenient.
Starting Page	663
Ending Page	667
File Size	219343
Page Count	5
File Format	PDF
ISBN	9781479925643
e-ISBN	9781479925650
DOI	10.1109/MEC.2013.6885146
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Condition monitoring Tracking test system Time series analysis Estimation Self-explanatory Time series Predictive models Data models Acceleration Data mining Vehicle dynamics Autoregressive processes
Content Type	Text
Resource Type	Article

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