Alpha Stable Distribution Based Morphological Filter for Bearing and Gear Fault Diagnosis in Nuclear Power Plant. (23rd April 2015)

• Record Type: Journal Article
• Authors: Zhang, Xinghui; Kang, Jianshe; Xiao, Lei; Zhao, Jianmin
• Other Names: Serikov Arkady Academic Editor.
• Is Part Of: Science and technology of nuclear installations. Volume 2015(2015)
• Publication Date: 2015-04-23
• Subjects: Nuclear engineering -- Periodicals; Nuclear facilities -- Periodicals; Nuclear engineering; Nuclear facilities; Electronic journals; Periodicals; 621.48
• DOI: 10.1155/2015/460131
• Languages: English
• ISSNs: 1687-6075

Abstract

Abstract : Gear and bearing play an important role as key components of rotating machinery power transmission systems in nuclear power plants. Their state conditions are very important for safety and normal operation of entire nuclear power plant. Vibration based condition monitoring is more complicated for the gear and bearing of planetary gearbox than those of fixed-axis gearbox. Many theoretical and engineering challenges in planetary gearbox fault diagnosis have not yet been resolved which are of great importance for nuclear power plants. A detailed vibration condition monitoring review of planetary gearbox used in nuclear power plants is conducted in this paper. A new fault diagnosis method of planetary gearbox gears is proposed. Bearing fault data, bearing simulation data, and gear fault data are used to test the new method. Signals preprocessed using dilation-erosion gradient filter and fast Fourier transform for fault information extraction. The length of structuring element (SE) of dilation-erosion gradient filter is optimized by alpha stable distribution. Method experimental verification confirmed that parameter alpha is superior compared to kurtosis since it can reflect the form of entire signal and it cannot be influenced by noise similar to impulse.