Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet

Feng, Kun; Jiang, Zhinong; Wei, He; Qin, Qiang

doi:10.1016/j.measurement.2011.06.011

Cited by 74 publications

(38 citation statements)

References 21 publications

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“…where m is the mass of the bearing vibration system, ξ is the damping ratio of the mechanical system and ω d is the damped natural frequency of the bearing structure [43].…”

Section: Fault Size Estimationmentioning

confidence: 99%

Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria

Deák¹,

Mankovits²,

Kocsis³

2017

SV-JME

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“…where m is the mass of the bearing vibration system, ξ is the damping ratio of the mechanical system and ω d is the damped natural frequency of the bearing structure [43].…”

Section: Fault Size Estimationmentioning

confidence: 99%

Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria

Deák¹,

Mankovits²,

Kocsis³

2017

SV-JME

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“…In order to indicate the failure mechanism, visual and experimental investigations were performed. The service life of journal bearings can be improved by using appropriate assembly with required clearance (Mehdizadeh, Khodabakhshi, 2014;Feng et al, 2011). Hydrodynamic bearings (HBs) are prone to initial wear due to contact friction between the bushing and shaft under the condition of insufficient hydrodynamic pressure (IHP).…”

Section: Introductionmentioning

confidence: 99%

Journal Bearing Fault Detection Based on Daubechies Wavelet

Narendiranath¹,

Himamshu²,

Prabin³

et al. 2017

Archives of Acoustics

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Journal bearings are widely used to support the shafts in industrial machinery involving heavy loads, such as compressors, turbines and centrifugal pumps. The major problem that could arise in journal bearings is catastrophic failure due to corrosion or erosion and fatigue, which results in economic loss and creates major safety risks. Thus, it is necessary to provide suitable condition monitoring technique to detect and diagnose failures, and achieve cost savings to the industry. Therefore, this paper focuses on fault diagnosis on journal bearing using Debauchies Wavelet-02 (DB-02). Nowadays, wavelet transformation is one of the most popular technique of the time-frequency-transformations. An experimental setup was used to diagnose the faults in the journal bearing. The accelerometer is used to collect vibration data, from the journal bearing in the form of time domain. This was then used as input for a MATLAB code that could plot the time domain signal. This signal was then decomposed based on the wavelet transform. The fast Fourier transform is then used to obtain the frequency domain, which gives us the frequency having the highest amplitude. To diagnose the faults various operating conditions are used in the journal bearing such as Full oil, half loose, half oil, fault 1, fault 2, fault 3 and full loose. Then the Artificial Neural Networks (ANN) is used to classify faults. The network is trained based on data already collected and then it is tested based on random data points. ANN was able to classify the faults with the classification rate of 85.7%. Thus, the test process for unseen vibration data of the trained ANN combined with ideal output target values indicates high success rate for automated bearing fault detection.

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“…The rolling bearing fault is one of the main causes of failures in rotating machinery [1]. Such failures can lead to catastrophic consequences and costly downtime [2].…”

Section: Introductionmentioning

confidence: 99%

“…In order to prevent bearing faults, various bearing fault diagnosis techniques have been developed. The vibration signal analysis is the main bearing fault monitoring method [1].…”

Section: Introductionmentioning

confidence: 99%

“…It is known that vibration sources emit high levels of noise due to complex surroundings [1]. In most cases, defectinduced impulses are weak at the incipient stage, and often buried in the background noise [1, An Investigation Into Fault Diagnosis in a Rotor-Bearing V. Vekteris, A. Trumpa, V. Turla, System with Dampers Used in Centrifugal Milk Separators N. Šešok, I. Iljin, V. Mokšin, A. Kilikevičius, A. Jakštas, J. Kleiza happen.…”

Section: Introductionmentioning

confidence: 99%

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An Investigation Into Fault Diagnosis in a Rotor-Bearing System with Dampers Used in Centrifugal Milk Separators

et al. 2017

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SummaryThis paper deals with the problems encountered in the fault diagnosis in damped rotorbearing systems used in centrifugal milk separators. It is shown that direct bearing vibration measurements are more reliable than indirect (through rotor housing) vibration measurements. However, in most cases it is not possible to measure bearing vibrations directly. The factors causing large diagnostic measurement errors, such as the influence of the vibration damping system, step-up gear and electric motor noise are discussed in the paper. It is established that vibration measurements of the damping system are noninformative and cannot be used to diagnose faults in bearings. It is proposed to use the vibration spectra correlation to predict bearing failures in rotor-bearing systems of this type.

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Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet

Cited by 74 publications

References 21 publications

Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria

Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria

Journal Bearing Fault Detection Based on Daubechies Wavelet

An Investigation Into Fault Diagnosis in a Rotor-Bearing System with Dampers Used in Centrifugal Milk Separators

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