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Remaining useful life prediction of aero-engines based on random-coefficient regression model considering random failure threshold 被引量:1
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作者 WANG Fengfei TANG Shengjin +3 位作者 LI Liang SUN Xiaoyan YU Chuanqiang SI Xiaosheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第2期530-542,共13页
Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomne... Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed. 展开更多
关键词 AERO-ENGINE remaining useful life(RUL) random failure threshold(RFT) random-coefficient regression(RCR) parameters estimation
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Remaining useful life estimation based on Wiener degradation processes with random failure threshold 被引量:15
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作者 TANG Sheng-jin YU Chuan-qiang +3 位作者 FENG Yong-bao XIE Jian GAO Qin-he SI Xiao-sheng 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第9期2230-2241,共12页
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 fail... 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. 展开更多
关键词 condition based maintenance remaining useful life wiener process random failure threshold BAYESIAN EM algorithm
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Fault-tolerant topology in the wireless sensor networks for energy depletion and random failure
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作者 刘彬 董明如 +1 位作者 尹荣荣 尹文晓 《Chinese Physics B》 SCIE EI CAS CSCD 2014年第7期343-349,共7页
Nodes in the wireless sensor networks (WSNs) are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this probl... Nodes in the wireless sensor networks (WSNs) are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this problem, in this paper, we build a fault-tolerant topology which can effectively tolerate energy depletion and random failure. Firstly, a comprehensive failure model about energy depletion and random failure is established. Then an improved evolution model is presented to generate a fault-tolerant topology, and the degree distribution of the topology can be adjusted. Finally, the relation between the degree distribution and the topological fault tolerance is analyzed, and the optimal value of evolution model parameter is obtained. Then the target fault-tolerant topology which can effectively tolerate energy depletion and random failure is obtained. The performances of the new fault tolerant topology are verified by simulation experiments. The results show that the new fault tolerant topology effectively prolongs the network lifetime and has strong fault tolerance. 展开更多
关键词 wireless sensor networks fault tolerant topology energy depletion random failure
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Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data 被引量:2
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作者 伍雪冬 王耀南 +1 位作者 刘维亭 朱志宇 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第6期546-551,共6页
On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random in... On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering (EKF) and the unscented Kalman filtering (UKF), which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network (RBFNN) prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent. 展开更多
关键词 prediction of time series with missing data random interruption failures in the observation neural network approximation
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Bayesian Reliability Assessment and Degradation Modeling with Calibrations and Random Failure Threshold 被引量:4
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作者 黄金波 孔德景 崔利荣 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第4期478-483,共6页
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-... 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. 展开更多
关键词 Bayesian method reliability assessment degradation modeling CALIBRATIONS random failure thresh-old multi-stage system
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Structural Fault Tolerance of Scale-Free Networks
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作者 蒿敬波 殷建平 张波云 《Tsinghua Science and Technology》 SCIE EI CAS 2007年第S1期246-249,共4页
The fault tolerance of scale-free networks is examined in this paper. Through the simulation on the changes of the average path length and network fragmentation of the Barabasi-Albert model when faults happen, it can ... The fault tolerance of scale-free networks is examined in this paper. Through the simulation on the changes of the average path length and network fragmentation of the Barabasi-Albert model when faults happen, it can be observed that generic scale-free networks are quite robust to random failures, but are very vulnerable to targeted attacks at the same time. Therefore, an existing optimization strategy for the robustness of scale-free networks to failures and attacks is also introduced. The simulation similar with the above proved that the so-called (1,0) network has potentially interconnectedness closer to that of a scale-free network and robustness to targeted attacks closer to that of an exponential network. Furthermore, its resistance to random failures is better than that of either of them. 展开更多
关键词 scale-free network random failure targeted attack optimization strategy
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