Inertial Sensor Fault Diagnosis Based on an Improved Gain Principal Component Analysis Algorithm

Qing Hua Li; Yi Wang; Yang Pang

doi:10.4028/www.scientific.net/AMR.271-273.40

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273Inertial Sensor Fault Diagnosis Based on an...

Inertial Sensor Fault Diagnosis Based on an Improved Gain Principal Component Analysis Algorithm

Abstract:

An improved gain principle component analysis(PCA) algorithm is proposed for detecting the small deviation fault of the inertial sensor data. During calculating process of the Q and statistics, different gains are set to improve the small deviation fault detecting capability of some important variables. And the filtering technology is applied to reduce the noise of the sample data and emerge the misjudgment phenomenon. Numeric example result shows that the proposed algorithm can achieve fault diagnosis effectively compared with the conventional PCA algorithm.

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Periodical:

Advanced Materials Research (Volumes 271-273)

Pages:

40-44

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.40

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Online since:

July 2011

Authors:

Qing Hua Li, Yi Wang, Yang Pang

Keywords:

Improved Gain PCA, Inertial Sensor, Principal Component Analysis (PCA)

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