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Real-time reliability prediction for dynamic systems with both deteriorating and unreliable components

Science in china(Series F) 2009年第11期52卷 2234-2246页

作者： xu zhengguo1,2. ji yindong2.3.& zhou donghua1,{2., tsinghua university, Beijing 100084, china 2.tsinghua National Laboratory for Information Science and Technology, tsinghua university, Beijing 100084, china 3 Research Institute of Information Technology (RIIT), tsinghua university, Beijing 100084, china department of automation Tsinghua University Beijing China tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Research Institute of Information Technology (RIIT) Tsinghua University Beijing China

As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Considering a dynamic system that is composed of normal, deteriorating and unreliable components, this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems. For a deteriorating component, the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time. The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component. The whole proposed approach contains three algorithms. A modified interacting multiple model particle filter is adopted to estimate the dynamic system＇s state variables and the unmeasurable time-varying fault. An exponential smoothing algorithm named the Holt＇s method is used to predict the fault process. In the end, the system＇s reliability is predicted in real time by use of the Monte Carlo strategy. The proposed approach can effectively predict the impending failure of a dynamic system, which is verified by computer simulations based on a three-vessel water tank system.

关键词： reliability failure prognostics dynamic systems fault prediction particle filtering interacting multiple model exponential smoothing,predictive maintenance

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Approximating probability distribution of circuit performance function for parametric yield estimation using transferable belief model

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Science china(Information Sciences) 2013年第11期56卷 106-124页

作者： xu XiaoBin zhou {2. ji {2. WEN ChengLin School of automation and Institute of Systems Science and Control Engineering Hangzhou Dianzi University department of automation and {2. National Laboratory for Information Science and Technology Tsinghua University Research Institute of Information Technology (RIIT) Tsinghua University

This paper applies the transferable belief model(TBM)interpretation of the Dempster-Shafer theory of evidence to approximate distribution of circuit performance function for parametric yield *** input parameters of performance function as credal variables defned on a continuous frame of real numbers,the suggested approach constructs a random set-type evidence for these *** corresponding random set of the function output is obtained by extension principle of random *** the TBM framework,the random set of the function output in the credal state can be transformed to a pignistic state where it is represented by the pignistic cumulative *** an approximation to the actual cumulative distribution,it can be used to estimate yield according to circuit response *** advantage of the proposed method over Monte Carlo(MC)methods lies in its ability to implement just once simulation process to obtain an available approximate value of yield which has a deterministic estimation *** the same error,the new method needs less number of calculations than MC methods.A track circuit of high-speed railway and a numerical eight-dimensional quadratic function examples are included to demonstrate the efciency of this technique.

关键词： Dempster-Shafer theory of evidence Monte Carlo methods parametric yield random set transferable belief model

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H∞ Filtering for a Class of Networked Systems with Randomly Occurring Quantizations

H∞ Filtering for a Class of Networked Systems with Randomly...

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第三十届中国控制会议

作者： HE Xiao~1,WANG Zidong~(2.3),ji yindong~1,{2. {2.~2.1.Research Institute of Information Technology,tsinghua university,Beijing 100084,P.R.china 2.department of automation,tsinghua university,Beijing 100084,P.R.china 3.department of Information Systems and Computing,Brunei university,Uxbridge UB8 3PH,United Kingdom

In this paper,the H filtering problem is investigated for a class of discrete-time networked systems with random- ly occurring quantizations(ROQs).Logarithmic quantizers with different quantization laws are considered and a Bernoulli distributed stochastic sequence is utilized to determine which quantizer is used at a certain time *** converting the quantization effects into sector-bounded parameter uncertainties,a sufficient condition ensuring the existence of the desirable filters is proposed by using the Lyapunov function approach,and the parameters of the desired filters can further be obtained.A numerical example is employed to illustrate the applicability of the proposed technique.

关键词： H∞ Filtering Networked Systems(NSs) Randomly Occurring Quantizations(ROQs)

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