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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Multistate Reliability Analysis of Recessive Fault of Mechanical Meta-Action Unit Based on Markov Process
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Multistate Reliability Analysis of Recessive Fault of Mechanical Meta-Action Unit Based on Markov Process

机译:Multistate Reliability Analysis of Recessive Fault of Mechanical Meta-Action Unit Based on Markov Process

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摘要

In order to clearly express the reliability dynamic change process of mechanical meta-action units with recessive fault on continuous time series, this paper proposes a reliability analysis method for multistate systems with recessive failures of mechanical meta-action units based on the fusion of vibration signal analysis and Markov process. By analyzing the vibration signal, five major recessive fault types of mechanical meta-action units are determined. By analyzing the experimental data and based on the average time of the first occurrence of five major recessive faults, a performance level state representation model of mechanical meta-action unit based on fault importance weight is established. Then, based on the repairable characteristics of the mechanical element action unit, the two-way state transition model and state probability differential equation of mechanical meta-action units are established, and the state probability of each state is obtained. Next, under the condition of determining the initial state, the change process curves of the instantaneous availability, instantaneous average performance, and instantaneous average performance deficit of the mechanical meta-action unit are obtained by solving the reliability index calculation formula. Finally, this paper takes the worm rotation meta-action unit as an example to verify the law and probability of the state transition of the mechanical meta-action unit, and the performance level change accompanying the state transition process, by analyzing the failure modes and causes of recessive faults, the corresponding reliability control measures are formulated, and the control effects before and after reliability control are analyzed. The research results show that this method can effectively improve the accuracy of the state probability when calculating the state probability of each state, and compared with the discrete Markov model, when studying the reliability of complex multistate systems, this method can dynamically describe the change process of state probability, instantaneous availability, instantaneous average performance, and instantaneous average performance deficit in real time under the condition of continuous time-dependent variables. It has certain guiding significance for the reliability analysis of mechanical element action units in the long-term range.

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