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Time-Variant Reliability Analysis Method for Uncertain Motion Mechanisms Based on Stochastic Process Discretization

IEEE ACCESS(2022)

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Abstract
The reliability of a motion mechanism is affected by corrosion, wear, aging and other components' performance degradations with the extension of service time. This paper tackles this problem by proposing a time-varying reliability analysis method for uncertain motion mechanisms. First, a model of motion mechanism error is constructed by assessing the difference between actual and expected motion. A time-varying reliability analysis method for a motion mechanism is proposed. The time-varying performance function is discretized into several static performance functions, which are further approximated with several normal variables. Then, the correlation coefficient matrix and probability density function of these normal variables are calculated, and the time-varying reliability of a motion mechanism is obtained via high-dimensional Gaussian integration. The study demonstrates that the proposed method successfully transforms the time-varying reliability problem into several time-invariant reliability problems for analysis, and handles the time-varying reliability problem of a nonlinear motion mechanism involving random variables and stochastic processes, and significantly increases the computational efficiency. Finally, the proposed method's effectiveness is verified by two numerical examples and one practical engineering problem.
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Key words
Reliability, Uncertainty, Autocorrelation, Stochastic processes, Reliability theory, Random processes, Reliability engineering, Process discretization, uncertain mechanism, time-varying reliability, first-order reliability method
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