广义概率分布能够更加准确地描述性能退化数据的特性，降低奇异点和概率分 布选择错误时带来的影响，为此，文中引入Ⅱ型广义 logistic 分布( Ⅱ-GLD) 进行退化可靠 性评估． 通过加入位置参数和尺度参数对时变退化量建模，根据各时刻分布的分位数和对 应试验数据之间的均方误差建立目标函数，结合粒子群优化( PSO) 算法实现对目标函数 中多个参数的同时估计． 运用所提方法对实例进行退化可靠性评估、验证和对比，结果表 明:该模型计算得到的退化数据均值和标准差与实际值的相对误差在 8%以内，不同失效 阈值下的可靠性评估结果与试验数据吻合良好;对比分析表明，与正态分布和威布尔分布 相比，Ⅱ-GLD 能够有效挖掘退化数据的尾部特性，真实反映产品的初期退化． 

As the generalized probabilistic distribution can describe the characteristics of performance degradation data with high precision and reduce the impacts caused by the outliers and the fault selection of probabilistic distribution，the type-Ⅱ generalized logistic distribution ( Ⅱ-GLD) is applied to the degradation reliability evaluation in this paper． In the investigation，the parameters of location and scale are introduced in the modeling of time-dependent degradation data，the objective function is established according to the meansquare error ( MSE) between the quantiles of Ⅱ-GLD and the experiment data，and particle swarm optimization ( PSO) algorithm is utilized to estimate parameters simultaneously． Then，the proposed approach is applied to a practical example for the evaluation of degradation reliability，followed with a verification and comparison． The results show that the relative errors between the mean and the standard deviation are below 8%，and that the reliability evaluation results match well with the pseudolifetime data in different failure thresholds． Moreover，it is indicated that，as compared with the normal distribution and the Weibull distribution，Ⅱ-GLD can explore the tail characteristics of degradation data more effectively and represent the initial degradation of the product faithfully．