某些长期处于贮存状态的整机级、系统级装备具有测试数据复杂、相关性竞争失效、贮存环境动态变化的特点，使得预测其贮存寿命成为了理论研究和工程实践上的难题。. 本项目拟开展以下研究：(1)从概率统计的角度，提出基于t统计量的假设检验方法，辨识装备的哪些性能参数发生退化；(2)采用状态空间模型融合多元退化数据评估装备退化率，表征多元相关性退化的综合效果，在此基础上探索装备的突发失效概率随退化率的变化规律，构建相关性竞争失效模型；(3)研究动态环境信息采集和数学建模方法，利用环境因子不变原则与加速模型将动态环境信息有效融入竞争失效模型，实现动态贮存环境下的寿命预测。. 研究成果有助于解决某些长贮装备的寿命预测难题，并将推动相关性竞争失效建模、动态环境下寿命预测相关理论和方法的发展，在装备综合保障领域具有广阔的应用前景。

Due to the complex test data, dependent competing failure and dynamic storage environment of some machine or system level equipment that is in long-term storage, predicting the storage life of the equipment becomes a problem both in theoretical study and engineering application. . This project intends to carry out the following researches: (1) From the perspective of probability and statistics test data, a hypothesis test method based on t statistic is proposed to identify which of the performance indexes are being degraded; (2) The state space model is applied to evaluate the degradation rate of equipment by fusing multivariate degradation data, which is used to characterize the comprehensive effect of dependent multivariate degradation. On this basis, the changing rule between the traumatic failure probability and the degradation rate is explored, and then a dependent competing failure model is set up; (3) The methods of collecting and modeling the dynamic environment information are studied, and then the dynamic environment information is effectively integrated into the dependent competing failure model through environment factor constant principle and acceleration models, so the storage life in dynamic environment can be predicted.. Research achievement would not only help solve the problem of storage life prediction for some long-term storage equipment, but also promote the development of theory and method concerning dependent competing failure modeling and life prediction in dynamic storage environment. Furthermore, research achievement has a broad application prospect in the field of equipment integrated support.