Data-mining based fault detection |
| |
Authors: | Hongguang Ma Chongzhao Han Guohua Wang Jianfeng Xu Xiaofei Zhu |
| |
Affiliation: | 1. Xi'an Jiaotong University,Xi'an 710049,China 2. Research Institute of High Technology,Xi'an 710025,China |
| |
Abstract: | This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and F-test, by which the quasi-optimal embedding dimension and time delay can be obtained. The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system. |
| |
Keywords: | Chaotic time series Phase space reconstruction Data mining Fault detection |
本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录! |
| 点击此处可从《电子科学学刊(英文版)》浏览原始摘要信息 |
|
点击此处可从《电子科学学刊(英文版)》下载全文 |