@inproceedings{8963daa5349e4472aa06063e228dada5,
title = "Application of Pearson Diversity Entropy as Prognostic Measure of Rotating Machinery",
abstract = "As a novel nonlinear measure, diversity entropy (DE) is a promising tool for prognosis of rotating machinery health. Being a core procedure in DE algorithm, cosine similarity (CS) focuses on the difference between the direction of two vectors instead of their distance or length. However, the direction difference can be easily affected by unwanted signal noise components, which will lead to low accuracy in DE-based signal complexity estimation. As a result, under heavy noise, DE not only fails to detect the incipient fault at the earliest stage of inception but also fails to trace the development of the fault. Aiming to solve the aforementioned problems, this paper incorporates the concept of Pearson similarity (PS) into DE calculation, instead of CS. PS measures the decentralized linear correlation between two vectors. Due to the involvement of PS, the newly proposed measure is termed as Pearson diversity entropy (PDE). Bearing run-to-failure data has been utilized to verify the performance of the proposed PDE. Result shows that the proposed PDE not only overcomes the limitations of original DE but also demonstrates better performance than conventional entropy algorithms such as permutation entropy (PE) and improved version of DE, namely multiscale diversity entropy (MDE).",
keywords = "Cosine similarity, Diversity entropy, Early fault detection, Pearson similarity, Rotating machinery",
author = "Wang Xinyue and Khandaker Noman and Hui Li and Yinchao Chen and Chenggang Tao and Yongbo Li",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023 ; Conference date: 22-08-2023 Through 23-08-2023",
year = "2024",
doi = "10.1007/978-981-99-8498-5_43",
language = "英语",
isbn = "9789819984978",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "519--527",
editor = "Andrew Tan and Fan Zhu and Haochuan Jiang and Kazi Mostafa and Yap, {Eng Hwa} and Leo Chen and Olule, {Lillian J. A.} and Hyun Myung",
booktitle = "Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023",
}