电子学报 ›› 2018, Vol. 46 ›› Issue (3): 739-747.DOI: 10.3969/j.issn.0372-2112.2018.03.032

• 学术论文 • 上一篇    下一篇

基于加速因子不变原则的加速退化数据分析方法

王浩伟, 滕克难, 盖炳良   

  1. 海军航空大学, 山东烟台, 264001
  • 收稿日期:2016-07-21 修回日期:2017-01-19 出版日期:2018-03-25
    • 作者简介:
    • 王浩伟,男,1981年3月出生,山东莱州人.2014年12月毕业于海军航空工程学院兵器科学与技术系,现为海军航空工程学院军事装备学博士后,从事装备可靠性工程、加速试验技术、装备延寿技术等方面的研究工作.E-mail:13705355730@139.com;滕克难,男,1962年3月出生,山东济南人.教授、博士生导师、泰山学者、全军科技领军人才.2015年获南京理工大学工学博士学位,现为海军航空工程学院训练部部长,主要从事装备发展论证、装备综合保障理论与技术等方面的研究工作.E-mail:tkn001@126.com
    • 基金资助:
    • 山东省自然科学基金 (No.ZR2016FQ03); 国家自然科学基金 (No.51605487); 中国博士后科学基金 (No.2016M592965)

The Method of Analyzing Accelerated Degradation Data Based on Acceleration Factor Constant Principle

WANG Hao-wei, TENG Ke-nan, GAI Bing-liang   

  1. Naval Aeronautical University, Yantai, Shandong 264001, China
  • Received:2016-07-21 Revised:2017-01-19 Online:2018-03-25 Published:2018-03-25

摘要: 加速退化试验技术已经成为评估退化失效型产品可靠性的高效手段,然而,目前对加速退化数据分析时过多依据主观经验,容易造成可靠性评估结果不准.本文提出了基于加速因子不变原则较为客观分析加速退化数据的一种方法.首先,根据加速因子不变原则推导退化模型各参数在加速退化试验中应该满足的变化规律;然后,利用与加速应力无关的参数等式辨识各加应力水平下的加速退化数据是否有效,核心是构建t统计量检验参数估值是否满足等式关系;接下来,确定与加速应力相关的参数从而实现加速退化建模;最后,利用有效的加速退化数据估计出模型参数值,外推出产品在常规应力下的可靠度.以逆高斯退化模型为例对所提方法进行了具体阐述.仿真试验和实例应用表明,本文研究为基于加速退化数据的可靠性评估提供一种更客观、合理的技术途径.

关键词: 可靠性评估, 加速退化, 加速因子, 有效性辨识, 逆高斯

Abstract:

The technology of accelerated degradation testing has become an efficient approach to evaluating the reliability of the degrading product. However, the method of analyzing accelerated degradation data, which excessively dependents on subjective experience, results in the inaccuracy of the reliability evaluation. In the paper, a more objective method based on acceleration factor constant principle is proposed. First, the changing rules of the parameters of degradation models are deduced according to the acceleration factor constant principle. Next, the effectiveness of the degradation data under each accelerated stress is identified through the parameter equation independent of accelerated stress. The key is that a t statistic is constructed to verify whether the parameter estimates satisfy the parameter equation. Then, the acceleration models of the parameters dependent on accelerated stress are constructed. Last, the effective accelerated degradation data is utilized to estimate parameters, so the reliability under the normal stress level can be extraplolated. The proposed method is demonstrated by taking the inverse Gaussian process as an example. Both the simulation test and case application indicate that the study of the paper provides a more objective and reasonable technical approach to reliability evaluation based on accelerated degradation data.

Key words: reliability evaluation, accelerated degradation, acceleration factor, effectiveness identification, inverse Gaussian

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