基于Bayes法的电主轴极小子样可靠性研究

蒋 喜;刘宏昭;訾佼佼;原大宁;刘丽兰

振动与冲击 ›› 2015, Vol. 34 ›› Issue (4) : 121-127.

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PDF(1329 KB)
振动与冲击 ›› 2015, Vol. 34 ›› Issue (4) : 121-127.
论文

基于Bayes法的电主轴极小子样可靠性研究

  • 蒋 喜,刘宏昭,訾佼佼,原大宁,刘丽兰
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Research on Extremely Small-Scale Sample’s Reliability of Motorized Spindle Based on Bayes Method

  • JIANG Xi,LIU Hong-zhao,ZI Jiao-jiao,YUAN Da-ning,LIU Li-lan
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摘要

针对长寿命的磨削电主轴极小子样的可靠性评估问题,提出了Bayes结合虚拟增广样本的分析方法。首先,在Bayes法基本流程的指导下,研究了基于Bayes法的磨削电主轴可靠性评估方法。根据定时截尾试验的原则对电主轴进行可靠性试验,应用Bayes法结合磨削电主轴试验样本的可靠性试验数据,综合虚拟增广样本法对其可靠性进行评估,最终获得电主轴的可靠性评估结果。最后,将基于Bayes法与基于伪寿命分布法的磨削电主轴极小子样可靠性评估结果进行比较,以验证基于Bayes法可靠性评估理论的合理性。

Abstract

In view of the problem that the reliability evaluation of long life grinding motorized spindle’s extremely small sample is difficult, the analysis method of Bayes combined with virtual augmented sample is proposed. First of all, under the guidance of the basic process of the Bayes method, theoretical research of the reliability evaluation method of grinding motorized spindle based on Bayes method is done. Based on the principle of timing truncation test, the reliability test of motorized spindle is done. Then, the Bayes method combined with the reliability testing data of the grinding motorized spindle’s testing sample and integrated virtual augmented sample method was applied to assess the reliability of electric spindle. Eventually, the reliability evaluation results of the motorized spindle are got. Finally, the reliability evaluation results of grinding motorized spindle based on Bayes method and based on false life’s distribution method are compared, so that the rationality of the reliability evaluation theory Based on Bayes method is verified.

关键词

电主轴 / 极小子样 / Bayes / 虚拟增广 / 可靠性

Key words

Motorized Spindle / Extremely Small Sample / Bayes / Virtual Augmented / Reliability

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导出引用
蒋 喜;刘宏昭;訾佼佼;原大宁;刘丽兰. 基于Bayes法的电主轴极小子样可靠性研究[J]. 振动与冲击, 2015, 34(4): 121-127
JIANG Xi;LIU Hong-zhao;ZI Jiao-jiao;YUAN Da-ning;LIU Li-lan. Research on Extremely Small-Scale Sample’s Reliability of Motorized Spindle Based on Bayes Method[J]. Journal of Vibration and Shock, 2015, 34(4): 121-127

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