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Rolling bearing performance degradation condition recognition based on mathematical morphological fractal dimension and fuzzy C-means

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Abstract In allusion to performance degradation condition recognition issue for rolling bearing, a method based on mathematical morphological fractal dimension (MMFD as abbreviation) and fuzzy C-means algorithm (FCM as abbreviation)… Click to show full abstract

Abstract In allusion to performance degradation condition recognition issue for rolling bearing, a method based on mathematical morphological fractal dimension (MMFD as abbreviation) and fuzzy C-means algorithm (FCM as abbreviation) is proposed in this paper. MMFD of vibrating signal is able to describe the complexity and irregularity from the perspective of fractal, its effectiveness and stability is justified by means of signal simulation. On this basis, considering fuzzy character of performance degradation condition boundary, FCM is introduced in degradation condition recognition. Rolling bearing fatigue life enhancement testing was carried out in Hangzhou Bearing Test & Research Center, the whole life data was gathered and applied in this paper, the result shows that the proposed technique of MMFD-FCM has an excellent effect.

Keywords: degradation; rolling bearing; performance degradation; condition recognition; degradation condition

Journal Title: Measurement
Year Published: 2017

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