Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2356 Research Paper of Special Issue

Assessment of Health of Friction Pair in Sliding Bearing Using Vibration Sensor and Continuous Wavelet Transform Time–Frequency Images

Chaoming Huang, Yongtao Liao, Qingtao Li, Hongliang Yu, Jianbin Liao, and Chih-Cheng Chen

(Received April 29, 2020; Accepted August 18, 2020)

Keywords: frictional vibration, feature extraction, time–frequency image, image segmentation, sliding bearing

A new method was proposed to find the characteristic parameters of the vibration induced by friction and wear of a sliding bearing. The parameters were obtained from the data of vibration signals using vibration sensors and processed with the continuous wavelet transform (CWT) and image technology. We collected the vibration signal of a ZCHSnSb8-8 bearing alloy and drew three-dimensional images with the time–frequency spectrum. Then, the important features were extracted by image segmentation technology. The parameters corresponding to the features were calculated with an algorithm to find the relationship between the parameters and the vibration characteristics. The results in this study revealed that the parameters of the vibration signal quantitatively represented the vibration characteristics of the sliding bearing caused by friction and wear. The new method is useful for assessing the health of a sliding bearing that has been deteriorated by friction and wear of its friction pair.

Corresponding author: Hongliang Yu, Chih-Cheng Chen

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