Vibration response mechanism of faulty outer race rolling element bearings for quantitative analysis

Cui, Lingli; Zhang, Yu; Zhang, Feibin; Zhang, Jianyu; Lee, Seung−Chul

doi:10.1016/j.jsv.2015.10.015

Cited by 151 publications

(90 citation statements)

References 22 publications

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“…The mathematical morphological gradient spectrum is obtained according to Formula (14); the results are shown in Figure 3.…”

Section: Analysis Of Vibration Signals Of Motors With No-loadmentioning

confidence: 99%

“…The algorithm was tested against measurement noise and found to be robust. Cui et al [14] established a nonlinear vibration model for fault severity assessment of rolling element bearings, and proposed a quantitative fault diagnosis method. For difficult diagnostic problems focused on bearing damage size, Zhao et al [15] proposed a quantitative diagnosis method based on empirical mode decomposition (EMD) and approximate entropy for the fault severity of rolling bearing.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Study on a Novel Fault Damage Degree Identification Method Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy

Zhao

Yao

et al. 2018

Entropy

101

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A damage degree identification method based on high-order difference mathematical morphology gradient spectrum entropy (HMGSEDI) is proposed in this paper to solve the problem that fault signal of rolling bearings are weak and difficult to be quantitatively measured. In the HMGSEDI method, on the basis of mathematical morphology gradient spectrum and spectrum entropy, the changing scale influence of structure elements to damage degree identification is thoroughly analyzed to determine its optimal scale range. The high-order difference mathematical morphology gradient spectrum entropy is then defined in order to quantitatively describe the fault damage degree of bearing. The discrimination concept of fault damage degree is defined to quantitatively describe the difference between the high-order differential mathematical entropy and the general mathematical morphology entropy in order to propose a fault damage degree identification method. The vibration signal of motors under no-load and load states are used to testify the effectiveness of the proposed HMGSEDI method. The experiment shows that high-order differential mathematical morphology entropy can more effectively identify the fault damage degree of bearings and the identification accuracy of fault damage degree can be greatly improved. Therefore, the HMGSEDI method is an effective quantitative fault damage degree identification method, and provides a new way to identify fault damage degree and fault prediction of rotating machinery.

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“…The mathematical morphological gradient spectrum is obtained according to Formula (14); the results are shown in Figure 3.…”

Section: Analysis Of Vibration Signals Of Motors With No-loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study on a Novel Fault Damage Degree Identification Method Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy

Zhao

Yao

et al. 2018

Entropy

101

View full text Add to dashboard Cite

show abstract

“…Rolling bearings manufacturers strive to produce their products characterized by low vibration emission. Excessive vibration value may indicate micro damages of rolling elements and raceways (Cui et al, 2016), lubrication contamination or bearings construction defects (Petersen et al, 2015). Manufacturers usually do not present detailed values of internal clearance of rolling bearings.…”

Section: Introductionmentioning

confidence: 99%

Influence of the internal clearance of ball bearings on the vibration level

2018

Engineering Mechanics

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The paper presents research of the influence of the radial internal clearance of the rolling ball bearings on the basic exploitation parameter which is the level of vibration. The measuring method of radial internal clearance of rolling bearings and measuring device are described. The 6304 type ball rolling bearings were used in research. The experimental research consisted of measurements of radial internal clearance and vibration level. The vibration analysis was divided into three basic frequency bands: low (50-300 Hz), medium (300-1800 Hz) and high (1800-10 000 Hz). The research was carried out in Laboratory of Rolling-Elements Bearings located in Kielce University of Technology. The research results showed that the increase of the radial clearance values affect the level of vibration generated by rolling bearings. The biggest influence was noted in the medium vibration frequency band.

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“…Bearing plays an important role in ensuring the normal operation of mechanical components [1][2][3]. According to statistics, approximately 30% of rotary machine faults are caused by bearing failure.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Bearing Fault Detection Using Step-Varying Vibrational Resonance Based on Duffing Oscillator Nonlinear System

Liu

Dai

et al. 2017

Shock and Vibration

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Bearing is a key part of rotary machines, and its working condition is critical in normal operation of rotary machines. Vibrational signals are usually analyzed to monitor the status of bearing. However, information on the status of bearing is always buried in heavy background noise; that is, status information of bearing is weaker than the background noise. Extracting the status features of bearing from signals buried in noise is difficult. Given this, a step-varying vibrational resonance (SVVR) method based on Duffing oscillator nonlinear system is proposed to enhance the weak status feature of bearing by tuning different parameters. Extraction ability of SVVR was verified by analyzing simulation signal and practical bearing signal. Experimental results show that SVVR is more effective in extracting weak characteristic information than other methods, including multiscale noise tuning stochastic resonance (SR), Woods-Saxon potential-based SR, and joint Woods-Saxon and Gaussian potential-based SR. Two evaluation indices are investigated to qualitatively and quantitatively assess the fault detection capability of the SVVR method. The results show that the SVVR can effectively identify the weak status information of bearing.

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Vibration response mechanism of faulty outer race rolling element bearings for quantitative analysis

Cited by 151 publications

References 22 publications

Study on a Novel Fault Damage Degree Identification Method Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy

Study on a Novel Fault Damage Degree Identification Method Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy

Influence of the internal clearance of ball bearings on the vibration level

Enhanced Bearing Fault Detection Using Step-Varying Vibrational Resonance Based on Duffing Oscillator Nonlinear System

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