Sensors 2013, 13(1), 274-291; doi:10.3390/s130100274

Health Assessment of Cooling Fan Bearings Using Wavelet-Based Filtering

1 School of Mechanical, Electronic and Industrial Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China 2 Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA
* Author to whom correspondence should be addressed.
Received: 30 October 2012; in revised form: 14 December 2012 / Accepted: 18 December 2012 / Published: 24 December 2012
(This article belongs to the Section Physical Sensors)
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Abstract: As commonly used forced convection air cooling devices in electronics, cooling fans are crucial for guaranteeing the reliability of electronic systems. In a cooling fan assembly, fan bearing failure is a major failure mode that causes excessive vibration, noise, reduction in rotation speed, locked rotor, failure to start, and other problems; therefore, it is necessary to conduct research on the health assessment of cooling fan bearings. This paper presents a vibration-based fan bearing health evaluation method using comblet filtering and exponentially weighted moving average. A new health condition indicator (HCI) for fan bearing degradation assessment is proposed. In order to collect the vibration data for validation of the proposed method, a cooling fan accelerated life test was conducted to simulate the lubricant starvation of fan bearings. A comparison between the proposed method and methods in previous studies (i.e., root mean square, kurtosis, and fault growth parameter) was carried out to assess the performance of the HCI. The analysis results suggest that the HCI can identify incipient fan bearing failures and describe the bearing degradation process. Overall, the work presented in this paper provides a promising method for fan bearing health evaluation and prognosis.
Keywords: cooling fan; health assessment; prognostics and health management; comblet filtering; exponentially weighted moving average; health condition indicator

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MDPI and ACS Style

Miao, Q.; Tang, C.; Liang, W.; Pecht, M. Health Assessment of Cooling Fan Bearings Using Wavelet-Based Filtering. Sensors 2013, 13, 274-291.

AMA Style

Miao Q, Tang C, Liang W, Pecht M. Health Assessment of Cooling Fan Bearings Using Wavelet-Based Filtering. Sensors. 2013; 13(1):274-291.

Chicago/Turabian Style

Miao, Qiang; Tang, Chao; Liang, Wei; Pecht, Michael. 2013. "Health Assessment of Cooling Fan Bearings Using Wavelet-Based Filtering." Sensors 13, no. 1: 274-291.

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