【摘要】 由于现代装备长寿命、高可靠的特点,较短时间内很难获得足够的失效数据,使得基于失效数据的寿命评估方法难以应用。相对于失效数据来说,产品的性能退化数据包含了更多的信息,而且通过产品的性能退化数据进行可靠性和寿命评估可以更加节约试验时间和费用,因此基于性能退化数据的寿命分析是解决长寿命、高可靠产品寿命评估问题的有效途径之一。本文以某型伺服系统为对象,根据自然贮存和加速贮存试验数据建立关键性能参数的退化模型,利用退化模型求解失效概率分布函数或贮存可靠度函数,进而得到基于关键性能参数的贮存寿命评估结果,最终实现对伺服系统贮存寿命的综合评估。更多还原

【Abstract】 Due to the long life and high reliability of modern equipment, it is difficult to obtain enough failure data in a short time, which makes the life assessment method based on failure data difficult to apply. Compared to the failure data, the performance degradation data of the product contains more information, and the reliability and life assessment of the degraded data by the product can save the test time and cost more, so the life analysis based on the performance degradation data is solved long life, high reliability product life assessment of one of the effective ways. In this paper, a degenerate model of key performance parameters is established based on the natural storage and accelerated storage test data. The failure probability model is used to solve the failure probability distribution function or the storage reliability function, and then we can get the storage performance evaluation results based on the key performance parameters. Finally, servo system storage life can be comprehensively evaluated.更多还原