The motion output accuracy of the mechanism has been significantly affected by the performance degradation of components. In this paper, the cumulative factor of wear degradation is considered. On the premise of small samples, an analysis method of time?varying reliability of mechanisms is proposed. This analysis method applies the cosimulation of ADAMS and MATLAB. Based on the Archard wear model, the pin radius degradation is calculated and considered as a time series problem. The mechanism function is established according to the RSM method, and the ARIMA method is used to predict the change of the mechanism response value under the subsequent wear cycle to expand the data samples. Based on the interference model of stress?strength,the limit state equation of mechanism is established and the time?varying reliability is calculated. The convenience and accuracy of this method are demonstrated with a crank?slider mechanism.

Initial defects and working environment will cause different degrees of cracks on the shaft. In order to analyze the effect of cracks on the rotor system, the finite element models of the cracked rotor were established through Jeffcott rotor dynamics model and fracture mechanics theory. The simulation analysis of different crack depths, crack angles and different speeds was carried out, and then a mechanical comprehensive failure table was used to carry out experimental research on part of the cracked rotors. The results show that: the appearance of cracks causes high?order frequency doubling components such as 2X in the vibration response of the system, and the phenomenon of depressions or even ferrules appeared in the axis track, and the vibration amplitude increases accordingly. As the crack deepens, the instability of the system gradually increases. The change of the crack inclination angle also affects the vibration characteristics of the system, and the 45?degree crack has the greatest impact on the system. When the speed starts to increase, the influence of the cracks on the system gradually decreases, the time?domain waveform tends to be stable, and the axis trajectory gradually changes back to an ellipse. Finally, the experimental results were compared with the simulation data to verify the conclusions of simulation and modeling.

In order to improve the accuracy of gasifier risk assessment, a safety assessment method that combines cloud model with catastrophe progression method was proposed. Through literature review and expert analysis, the risks of the gasifier are divided into mechanical systems, personnel, management and environmental risks, and a multi?level risk assessment system for the gasifier was established. The cloud model is an effective tool for qualitative and quantitative conversion. The entropy and hyper?entropy feature values of the cloud model were introduced, and the cloud entropy weight method was proposed to improve the traditional weight calculation method, and the weight calculation of all indicators was carried out to improve the accuracy of the ranking results. According to the normalization formula, the mutation membership value of each layer index and the total mutation membership value of the gasifier are calculated, and the risk level of the gasifier is judged according to the risk level evaluation table. The research results show that this method improves the comprehensiveness and objectivity of the weight ranking, and makes the gasifier risk assessment results consistent with the actual situation, which verifies the feasibility and effectiveness of the method.