Vibration Forces Produced by Waviness of the Rolling Surfaces of Thrust Loaded Ball Bearings Part 1: Theory

Wardle, Frank

doi:10.1243/pime_proc_1988_202_127_02

Cited by 140 publications

(115 citation statements)

References 4 publications

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“…The 435 former observation was also reported by Tiwari et al [105,106], and the latter by Tandon et al [46]. 436 Sopanen et al [54,55] ignored the slippage of the rolling elements (balls) [49] and neglected the centrifugal 437 forces acting on them, although it was shown that the modelled defect-related frequencies agree well with 438 the earlier results published in the literature [46,97,98,103,[105][106][107].…”

supporting

confidence: 53%

“…While Sopanen et al [54,55] did not conduct any experimental work, they 429 compared their modelling results with those of similar studies available in the literature. For example, for 430 the localised raceway defects, the predicted results were compared with the results in reference [46], and for 431 the waviness, the modelling results were compared with the results reported in references [97,98,103,107].…”

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An extensive review of vibration modelling of rolling element bearings with localised and extended defects

Singh

Howard

Hansen

2015

Journal of Sound and Vibration

124

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This paper presents a review of literature concerned with the vibration modelling of rolling element bearings that have localised and extended defects. An overview is provided of contact fatigue, which initiates subsurface and surface fatigue spalling, and subsequently leads to reducing the useful life of rolling element bearings. A review is described of the development of all analytical and finite element (FE) models available in the literature for predicting the vibration response of rolling element bearings with localised and extended defects. Low-and high-frequency vibration signals are generated at the entry and exit of the rolling elements into and out of a bearing defect, respectively. The development of this finding is described along with analytical models to approximate these vibration signals. Algorithms to estimate the size of bearing defects are reviewed and their limitations are discussed. A summary of the literature is presented followed by recommendations for future research.

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confidence: 53%

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confidence: 99%

An extensive review of vibration modelling of rolling element bearings with localised and extended defects

Singh

Howard

Hansen

2015

Journal of Sound and Vibration

124

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“…When the number of balls and waves are equal there would be severing vibrations. Wardle [9] showed that ball waviness produced vibrations in the axial and radial directions at different frequencies and also pointed out that only even orders of ball waviness produced vibrations.…”

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confidence: 99%

Stability analysis of a rotor bearing system due to surface waviness and number of balls

Harsha

Kankar

2004

International Journal of Mechanical Sciences

100

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“…When faults occur in the rolling element bearing, impulse-type vibration behavior appears [3]. There are many sources of vibration of bearings [4,5], some are inherent, such as the variable compliance effect, which cannot be guarded against but can be minimized with proper preloading and interference fitting; some are simply period repetitions, such as cage frequency. Others are due to unbalances in assembly and yet others are due to the waviness of rolling surfaces (no surface is perfectly smooth).…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC

Ge¹,

Wang²,

Ren³

2017

Entropy

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This study proposes a novel fault diagnosis method that is based on empirical wavelet transform (EWT) and kernel density estimation classifier (KDEC), which can well diagnose fault type of the rolling element bearings. With the proposed fault diagnosis method, the vibration signal of rolling element bearing was firstly decomposed into a series of F modes by EWT, and the root mean square, kurtosis, and skewness of the F modes were computed and combined into the feature vector. According to the characteristics of kernel density estimation, a classifier based on kernel density estimation and mutual information was proposed. Then, the feature vectors were input into the KDEC for training and testing. The experimental results indicated that the proposed method can effectively identify three different operative conditions of rolling element bearings, and the accuracy rates was higher than support vector machine (SVM) classifier and back-propagation (BP) neural network classifier.

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Vibration Forces Produced by Waviness of the Rolling Surfaces of Thrust Loaded Ball Bearings Part 1: Theory

Abstract: Theoretical expressions are derived relating amplitude and wavelength of surface imperfections in thrust loaded ball bearings to vibration forces and frequencies produced under constant-speed operating conditions.

Cited by 140 publications

References 4 publications

An extensive review of vibration modelling of rolling element bearings with localised and extended defects

An extensive review of vibration modelling of rolling element bearings with localised and extended defects

Stability analysis of a rotor bearing system due to surface waviness and number of balls

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC

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