The Improved WNOFRFs Feature Extraction Method and Its Application to Quantitative Diagnosis for Cracked Rotor Systems

Liang, Haiying; Zhao, Chencheng; Chen, Yungao; Liu, Yang; Zhao, Yulai

doi:10.3390/s22051936

Cited by 7 publications

(3 citation statements)

References 38 publications

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“…However, for early bearing wear, the vibration signal of the bearing lacks obvious fault characteristics [ 25 , 26 ]. The bearing wear cannot be detected effectively only by the vibration signal [ 27 ]. Aiming at the insufficiency of a single type of sensor, the fault diagnosis method based on multi-sensors has been gradually developed [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis for Abnormal Wear of Rolling Element Bearing Fusing Oil Debris Monitoring

Zhao

Wang

Han

et al. 2023

Sensors

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The abnormal wear of a rolling element bearing caused by early failures, such as pitting and spalling, will deteriorate the running state and reduce the life. This paper demonstrates the importance of oil debris monitoring and its effective feature extraction for bearing health assessment. In this paper, a rolling bearing-rotor test rig with forced lubrication is set up and the nonferrous contaminants with higher hardness were introduced artificially to accelerate the occurrence of pitting and spalling. The early failure and abnormal wear of rolling bearings cannot be effectively detected only through the vibration signal; the temperature and oil debris monitoring data are also collected synchronously. Two features regarding the ferrous particle size distribution are extracted and fused with vibration based-features to form a feature set. The sensitive features are extracted from the features set using the Neighborhood Component Analysis method to avoid feature redundancy. Finally, the importance of the oil debris based-features for the diagnosis of abnormal bearing wear is analyzed with different machine learning algorithms. Taking SVM classifier as an example, the experiment results show that the introduction of oil debris based-features increases the diagnostic accuracy by 15.7%.

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Section: Introductionmentioning

confidence: 99%

Fault Diagnosis for Abnormal Wear of Rolling Element Bearing Fusing Oil Debris Monitoring

Zhao

Wang

Han

et al. 2023

Sensors

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“…The stability and effectiveness of index J were verified through numerical model and tests were conducted on the rotor with rub-impact. Liang et al 26,27 proposed the approach of improved WNOFRFs based on the KL divergence and the associated index KLRm to diagnose the rotor rub-impact and cracks. The results of numerical models and experiments indicate that KLRm can quantitatively diagnose crack faults of rotor systems.…”

Section: Introductionmentioning

confidence: 99%

Research on a quantitative fault diagnosis method for rotor rub-impact

Liang

Zhao

Liu

et al. 2023

Structural Health Monitoring

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The rotor system during its operation is susceptible to various faults such as unbalance, rub-impact, crack, and misalignment, which usually induce the rotor system to exhibit nonlinear behavior. Some linear diagnosis methods are unable to extract nonlinear characteristics of the faulty rotor system. However, existing nonlinear fault diagnosis methods can describe the nonlinear characteristics but cannot quantitatively indicate the severity of rub-impact faults. To address this issue, this study combines the nonlinear output frequency response functions weighted contribution rate (WNOFRFs) and JS divergence to develop an improved fault diagnosis approach, WNOFRFs based on the JS divergence (WNOFRFs-JS). And a superior NOFRFs-associated index JSRm is developed to indicate the severity of faults. In addition, a sensitive factor is defined to evaluate the sensitivity of the index. The performance of this approach is verified by an established dynamic model and a rotor rub-impact experimental rig. The results prove the effectiveness and merits of this approach for the identification of rotor rub-impact. JSRm is especially sensitive to rub-impact and can also quantitatively detect the severity of faults. The present approach can accurately and quantitatively identify the rub-impact rotor system. These advantages enable the improved WNOFRFs to be applied in the fault diagnosis and condition monitoring of rotating machinery and even other nonlinear systems.

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“…Changes in displacement and vibration frequency can be taken as defect indicators. To this end, many authors have suggested using indicators of the nonlinear behavior of the cracked shaft, such as the natural frequency and the orbits, in order to detect the presence of cracks [17][18][19][20][21][22][23][24]. The reduction of the the critical speed turns out to be a very good indicator of the presence of cracks [25] in rotating shafts.…”

Section: Introductionmentioning

confidence: 99%

Determination of the Critical Speed of a Cracked Shaft from Experimental Data

Muñoz-Abella

Montero

Rubio

et al. 2022

Sensors

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In this work, a procedure to obtain an accurate value of the critical speed of a cracked shaft is presented. The method is based on the transversal displacements of the cracked section when the shaft is rotating at submultiples of the critical speed. The SERR (Strain Energy Ralease Rate) theory and the CCL (Crack Closure Line) approach are used to analyse the proposed methodology for considering the behaviour of the crack. In order to obtain the best information and to define the procedure, the orbits and the frequency spectra at different subcritical rotational speed intervals are analyzed by means of the Fast Fourier Transform. The comparison of the maximum values of the FFT peaks within the intervals allows the subcritical speed to be determined, along with the value of the critical speed. When verified, the proposed procedure is applied to shafts with the same geometry and material and with cracks of increasing depth. The results show that the critical speed diminishes with the severity of the crack, as expected. A comparison is made between the critical speed obtained using the vertical and the horizontal displacements, finding no remarkable differences, meaning that in practical applications only one sensor for one of the displacements (in the vertical or horizontal direction) is needed to determine the critical speed. This is one of the main contributions of the paper, as it means that the orbits of the shaft are not needed. Finally, after this study we can conclude that the best results are achieved when the critical speed is obtained using data displacement in only one direction within the intervals around 12 or 13 of the critical speed.

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The Improved WNOFRFs Feature Extraction Method and Its Application to Quantitative Diagnosis for Cracked Rotor Systems

Cited by 7 publications

References 38 publications

Fault Diagnosis for Abnormal Wear of Rolling Element Bearing Fusing Oil Debris Monitoring

Fault Diagnosis for Abnormal Wear of Rolling Element Bearing Fusing Oil Debris Monitoring

Research on a quantitative fault diagnosis method for rotor rub-impact

Determination of the Critical Speed of a Cracked Shaft from Experimental Data

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