环氧树脂耐电子辐照性能

研究了电子辐照对几种4,4’-二氨基二苯甲烷固化的环氧树脂造成的破坏效应.结果表明:在1.4 MeV电子辐照时,环氧树脂会变色、失重、开裂,同时力学性能下降.实验结果表明:双酚A二缩水甘油醚(DGEBA),N,N,N’,N’-四缩水甘油基-4,4’-二氨基二苯甲烷(TGDDM),对氨基苯酚三缩水甘油环氧树脂(TGPAP),DGEBA/TGDDM和DGEBA/TGPAP共混物均能承受106 Gy的吸收剂量.而DGEBA/TGPAP共混物,能承受107 Gy的吸收剂量.环氧树脂抗辐照性能的次序为DGEBA/TGPAP＞ DGEBA/TGDDM ＞TGPAP≈TGDDM＞DGEBA.环氧树脂经电子辐照后压缩模量增加,表明在辐照效应中交联机理占主导,DMA和DSC分析也证实了这一点.     

Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

High-cost equipment is often reused after maintenance, and whether the information before the maintenance can be used for the Remaining Useful Life (RUL) prediction after the maintenance is directly determined by the consistency of the degradation pattern before and after the maintenance. Aiming at this problem, an RUL prediction method based on the consistency test of a Wiener process is proposed. Firstly, the parameters of the Wiener process estimated by Maximum Likelihood Estimation (MLE) are proved to be biased, and a modified unbiased estimation method is proposed and verified by derivation and simulations. Then, the h statistic is constructed according to the reciprocal of the variation coefficient of the Wiener process, and the sampling distribution is derived. Meanwhile, a universal method for the consistency test is proposed based on the sampling distribution theorem, which is verified by simulation data and classical crack degradation data. Finally, based on the consistency test of the degradation model, a weighted fusion RUL prediction method is presented for the fuel pump of an airplane, and the validity of the presented method is verified by accurate computation results of real data, which provides a theoretical and practical guidance for engineers to predict the RUL of equipment after maintenance.     

Remaining useful life prognostics for aeroengine based on superstatistics and information fusion

Remaining useful life（RUL） prognostics is a fundamental premise to perform conditionbased maintenance（CBM） for a system subject to performance degradation. Over the past decades,research has been conducted in RUL prognostics for aeroengine. However, most of the prognostics technologies and methods simply base on single parameter, making it hard to demonstrate the specific characteristics of its degradation. To solve such problems, this paper proposes a novel approach to predict RUL by means of superstatistics and information fusion. The performance degradation evolution of the engine is modeled by fusing multiple monitoring parameters, which manifest non-stationary characteristics while degrading. With the obtained degradation curve,prognostics model can be established by state-space method, and then RUL can be estimated when the time-varying parameters of the model are predicted and updated through Kalman filtering algorithm. By this method, the non-stationary degradation of each parameter is represented, and multiple monitoring parameters are incorporated, both contributing to the final prognostics. A case study shows that this approach enables satisfactory prediction evolution and achieves a markedly better prognosis of RUL.     

基于退化信息融合理论的可靠性预测研究

传统的可靠性评估方法一般基于失效寿命数据,而目前对于高可靠长寿命的电子产品,很难通过加速试验获得其失效寿命时间。为解决这一矛盾,将性能退化理论、信息融合技术与传统可靠性评估方法相结合,提出基于退化信息融合理论的可靠性预测的新方法,并应用某型雷达24V/2A稳压电源板的加速性能退化试验进行验证,结果表明方法用于高可靠长寿命电子产品的可靠性评估是正确有效的。