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Xinghui Zhang
Mechanical Engineering College, Shijiazhuang

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Bearing Fault Diagnosis Method Using Envelope Analysis and Euclidean Distance Haiping Li; Jianmin Zhao; Xinghui Zhang; Hongzhi Teng; Ruifeng Yang; Lishan Hao
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Bearings are widely used in rotating machines. Its health status is a significant index to indicate whether machines run continually or not. Detecting the bearing faults timely is very important for the maintenance decision making. In this paper, a new fault diagnosis method based on envelope analysis and Euclidean Distance is developed. Envelope analysis is used to enable the fault frequencies clearly. Then, amplitudes of fault frequencies are used as the fault features. Finally, Euclidean Distance is used to identify the different fault types. This method can identify the fault locations intelligently even if the bearings are under different fault levels. The effectiveness of this methodology is demonstrated using the bearing data sets of Case Western Reserve Univerity. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4186
Research on Operating Condition Effect on the Shock Pulse Method Ruifeng Zhang; Jianshe Kang; Lishan Hao; Xinghui Zhang; Hongzhi Teng; Haiping Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5392-5398

Abstract

Rolling bearings are one of the most widely used elements in industrial applications. Shock pulse method (SPM) has proven successfully as a diagnostic tool in determining bearing health. On the basis of illustrating the principle of SPM, this paper mainly concentrates on investigating the effect of different operating conditions on SPM. The shock pulse signals are derived from the wind turbine gearbox test rig by SPM instrument. Through comparing the slope of dB values when the rotating speed or load changes, effect of operating conditions on SPM is analyzed. The analysis results show that SPM is more sensitive to the rotating speed in contrast with the load.
Gear Fault Diagnosis and Classification Based on Fisher Discriminant Analysis Haiping Li; Jianmin Zhao; Xinghui Zhang; Hongzhi Teng; Ruifeng Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp6198-6204

Abstract

Gears are the most essential parts in rotating machinery. So gear fault modes diagnosis and levels classification are very important in engineering practice. This paper present a novel method in gear fault recognition and identification using Fisher discriminant analysis (FDA) due to FDA can reduct dimension when analyse signal. The real data collected from a gearbox test rig is used to validate the method this paper proposed. And the effectiveness of the methodology was demonstrated by the results obtained from the analysis. Three kinds of fault modes and levels were identified. And energy was selected as feature parameter. The fault modes (normal, breaktooth and crack) were diagnosed at first, then the fault levels of breaktooth and crack are classified. The accurate rate of the method is approximate 89%.
Application of SPM to Detect the Wind Turbine Bearing Fault Ruifeng Yang; Jianshe Kang; Xinghui Zhang; Hongzhi Teng; Haiping Li
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

With the widespread application of wind turbines, the Maintenance issue gets growing concern. Bearings play a critical role in industrial applications. It is necessary to effectively monitor their health status. The shock pulse method (SPM) can detect the incipient fault of bearings and prevent the fault consequence effectively. However, many researchers used laboratory data to validate the SPM. This paper mainly concentrates on the SPM application on bearing fault detection of wind turbines. Shock pulse signals are derived from the gearbox of industrial wind turbine test rig by SPM instrument. According to frequency spectrum analysis, the bearing fault has been accurately detected and located. The analysis results demonstrate that the SPM technology is potentially effective for detecting the bearing faults of industrial wind turbines. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4122
Co-Authors Haiping Li Hongzhi Teng Hongzhi Teng Hongzhi Teng Jianmin Zhao Jianshe Kang Lishan Hao Lishan Hao Ruifeng Yang Ruifeng Zhang