Abstract
A new load-share reliability model of systems under the changeable load is proposed in the paper. It is assumed that the load is a piecewise smooth function which can be regarded as an extension of the piecewise constant and continuous functions. The condition of the residual lifetime conservation, which means continuity of a cumulative distribution function of time to failure, is accepted in the proposed model. A general algorithm for computing reliability measures is provided. Simple expressions for determining the survivor functions under assumption of the Weibull probability distribution of time to failure are given. Various numerical examples illustrate the proposed model by different forms of the system load and different probability distributions of time to failure.
Highlights
A lot of available methods and models of the system reliability do not take into account a very important factor which impacts on the real system reliability behavior and takes place in most applications
The reliability analysis of systems under the changeable piecewise smooth load as a special case of the piecewise constant load and continuous load has been provided in the paper
The main feature of the considered models is applying the condition of the residual lifetime conservation to reliability analysis which is crucial in the reliability models
Summary
Received 11 May 2014; Revised 27 August 2014; Accepted 1 September 2014; Published 11 September 2014. A new load-share reliability model of systems under the changeable load is proposed in the paper. It is assumed that the load is a piecewise smooth function which can be regarded as an extension of the piecewise constant and continuous functions. The condition of the residual lifetime conservation, which means continuity of a cumulative distribution function of time to failure, is accepted in the proposed model. A general algorithm for computing reliability measures is provided. Simple expressions for determining the survivor functions under assumption of the Weibull probability distribution of time to failure are given. Various numerical examples illustrate the proposed model by different forms of the system load and different probability distributions of time to failure
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