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Jianshe Kang
Mechanical Engineering College, Shijiazhuang

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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.
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 Lishan Hao Ruifeng Yang Ruifeng Zhang Xinghui Zhang