TY - GEN
T1 - A Comparative Analysis of Supervised/unsupervised Algorithms in PHM Application
AU - Zhang, Chenguang
AU - Dong, Run
AU - Zhang, Xiaobin
AU - Li, Weilin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Intelligent learning algorithms, as one of the most currently remarkable data-driven approaches, have achieved great success in many applications, such as fault diagnosis, state evaluation and life prognosis of airborne equipment. This paper mainly introduces the classification and typical principles of supervised and unsupervised learning algorithms, and compares their differences in the application of system health status assessment. Through the establishment of K-means clustering model and artificial neural network model, the data obtained from Monte Carlo analysis are processed and classified, and then the health state of the system is estimated. This paper verifies the superiority of the supervised algorithm in evaluation accuracy through the experimental data, and analyzes its essential reason. The conclusion can provide guidance for the engineering application of supervised and unsupervised learning algorithm.
AB - Intelligent learning algorithms, as one of the most currently remarkable data-driven approaches, have achieved great success in many applications, such as fault diagnosis, state evaluation and life prognosis of airborne equipment. This paper mainly introduces the classification and typical principles of supervised and unsupervised learning algorithms, and compares their differences in the application of system health status assessment. Through the establishment of K-means clustering model and artificial neural network model, the data obtained from Monte Carlo analysis are processed and classified, and then the health state of the system is estimated. This paper verifies the superiority of the supervised algorithm in evaluation accuracy through the experimental data, and analyzes its essential reason. The conclusion can provide guidance for the engineering application of supervised and unsupervised learning algorithm.
KW - Artificial neural network
KW - K-means clustering
KW - Supervised learning
KW - Unsupervised learning
UR - http://www.scopus.com/inward/record.url?scp=85143158847&partnerID=8YFLogxK
U2 - 10.1109/PHM-Yantai55411.2022.9942049
DO - 10.1109/PHM-Yantai55411.2022.9942049
M3 - 会议稿件
AN - SCOPUS:85143158847
T3 - 2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022
BT - 2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022
A2 - Guo, Wei
A2 - Li, Steven
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022
Y2 - 13 October 2022 through 16 October 2022
ER -