@article{f9ebc3f2ef7b4a1aa8130c6fc973f987,
title = "A novel diagnostic and prognostic framework for incipient fault detection and remaining service life prediction with application to industrial rotating machines",
keywords = "Canonical variable analysis, Condition monitoring, Diagnosis and prognosis, Grey forecasting model, Particle filter",
author = "Xiaochuan Li and Xiaoyu Yang and Yingjie Yang and Ian Bennett and David Mba",
note = "Funding Information: This work was supported by the National Natural Science Foundation of China (No. 71671091 , 71701098 ), the China Scholarship council , Postgraduate Research & Practice Innovation Program of Jiangsu Province, China ( KYCX18_0233 ), and the Leverhulme Trust International Research Network project ( IN-2014-020 ). Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",
year = "2019",
month = sep,
doi = "10.1016/j.asoc.2019.105564",
language = "English",
volume = "82",
journal = "Applied Soft Computing",
issn = "1568-4946",
publisher = "Elsevier",
}