@inproceedings{f5985ac3ff6242c5921062a68518c2e4,
title = "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 T 2 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.",
keywords = "Improved gain PCA, Inertial sensor, Principal component analysis",
author = "Qinghua Li and Wang Yi and Pang Yang",
year = "2011",
doi = "10.4028/www.scientific.net/AMR.271-273.40",
language = "英语",
isbn = "9783037851579",
series = "Advanced Materials Research",
pages = "40--44",
booktitle = "Advanced Materials and Information Technology Processing, AMITP 2011",
note = "2011 International Conference on Advanced Materials and Information Technology Processing, AMITP 2011 ; Conference date: 17-04-2011 Through 18-04-2011",
}