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CSME 2019/02
Volume 40 No.1
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63-72
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Working Performance Evaluation of Rolling Bearings Using Modern Statistics
Yongzhi Xua, Xintao Xiab and Xiang Nana
aSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
bSchool of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China；Collaborative Innovation Center of Machinery Equipment advanced Manufacturing of Henan Province, Luoyang 471003, China
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Abstract:
The performance assessment of time series with unknown distributions, which belongs to the category of problems with poor information, is a key challenge for modern statistics. On the basis of modern statistics, the fusion method of histograms and a normality test to judge the robustness and the direction of unsteady data of time series, and the fusion method combines the median estimate and Huber (M) estimate obtains robust data, unsteady data and the significance level of the time series. These methods are used in the vibration analysis of rolling bearings to verify their effectiveness, and the results show that unsteady data exist in time series at both ends of the order statistics. The reliability reflects the significance level of the rolling bearing vibration data and avoids error due to artificial factors. The intrinsic interval and the variation ratio accurately represent the working performance of rolling bearings, even in cases of complex and diverse running states. Additionally, the above fusion method provides a valuable solution to robustness problem for unknown distribution, the significance level test data and the boundary value of the Huber (M) estimate in modern statistical methods.
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Keywords: robust theory; significance level; variation ratio; intrinsic interval; working state
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*Corresponding author; e-mail: xiaxt1957@163.com
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©
2019
CSME , ISSN 0257-9731
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