政治信任阈失的社会机理及其时代表征

全球化背景下,政治信任的嬗变抑或阈失是一种普遍现象,其社会机理首先来源于现代复杂社会的风险叠加与政治体系的应对失效;其次,全球化的深度扩展和民主政治危机导致了公民民族国家政治共同体认同基础的消解和对政治体系信任的弱化;最后,批判性公民的成长和官僚机构的消极腐败,意味着公民与国家之间关系的失衡以及权利与责任关系的断裂,并直接淡化了公民的政治信任情感,加速了公民政治信任的流失。

大间隙环流中单圆盘弹支转子系统失稳阈分析

分析了大间隙环流中弹支单圆盘转子系统的失稳阈 .首次定义了大间隙环流中转子系统界限失稳频率修正量 ΔΩ和大间隙环流综合影响因子Im.结果表明 ,大间隙环流对弹支单圆盘转子系统的失稳阈有较大的影响 ,大间隙环流产生的流体动力质量ma 是导致这种影响的根本原因 .

大间隙环流中Jeffcott转子系统失稳阈的研究

采用 Routh- Hurwitz稳定性准则 ,研究了大间隙环流中 Jeffcott转子系统的失稳阈 .结果表明 :大间隙环流对 Jeffcott转子系统的失稳阈有较大的影响 ,大间隙环流产生的流体动力质量 ma

倾斜转子-滑动轴承系统周期解稳定性研究

针对倾斜转子-滑动轴承系统的周期解稳定性问题,考虑倾斜状态下滑动轴承径向载荷的变化,基于有限元法建立了系统的动力学方程。使用Newmark方法仿真得到了倾斜转子-轴承系统的动力学响应,并分析了倾斜角度变化对转子周期解失稳阈速和失稳区宽度的影响。仿真结果表明,转子倾斜角度增大会导致转子失稳阈速减小,失稳区宽度增大,但对周期解失稳区域上边界影响不大。倾斜转子的升速实验验证了仿真结果。

Remaining useful life estimation based on Wiener degradation processes with random failure threshold

Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

Bayesian Reliability Assessment and Degradation Modeling with Calibrations and Random Failure Threshold

A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-specified periodical calibrations. And here a random threshold distribution instead of a constant threshold which is difficult to determine in practice is used. The system reliability is defined as the probability that the degradation signals do not exceed the random threshold. Based on the posterior distribution estimates of degradation performance, two models for Bayesian reliability assessments are presented in terms of the degradation performance and the distribution of random failure threshold. The methods proposed in this paper are very useful and practical for multi-stage system with uncertain failure threshold. This study perfects the degradation modeling approaches and plays an important role in the remaining useful life estimation and maintenance decision making.