@inproceedings{a577d1ec06ee4268b42b3ab44ea43aae,
title = "A Fault Prediction Method Based on IAALO-SVM and Similarity Measure",
abstract = "As an important part of electronic products, analog circuits are widely used in various fields. However, the fault prediction technology of analog circuit is still in its infancy because of its nonlinear characteristics such as nonlinearity and tolerance. According to the characteristics of small sample nonlinear data in analog circuits, the farther the prediction time distance of IAALO-SVM algorithm is from the initial training sample, the greater the prediction error is. Therefore, this article through the use of analog circuit fault parameters offline database, introduced the choice of time series similarity measure method is similar to database, according to the size of the similarity for failure prediction result, combining the measured data and offline data is put forward based on IAALO - SVM and similarity measure the failure prediction of new scheme to predict the residual service life of main amplifier circuit. The example shows that the new scheme can obtain high prediction accuracy in a long time and has practical application value.",
keywords = "Analog circuit, Fault prediction, IAALO-SVM, Similarity measure",
author = "Weiwei Hu and Hui Fan and Jiamin Liu and Yufeng Sun and Guangyan Zhao",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 10th Prognostics and System Health Management Conference, PHM-Qingdao 2019 ; Conference date: 25-10-2019 Through 27-10-2019",
year = "2019",
month = oct,
doi = "10.1109/PHM-Qingdao46334.2019.8942945",
language = "英语",
series = "2019 Prognostics and System Health Management Conference, PHM-Qingdao 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Wei Guo and Steven Li and Qiang Miao",
booktitle = "2019 Prognostics and System Health Management Conference, PHAI-Qingdao 2019",
address = "美国",
}