A new method for computing the failure probability of the fatigue life is proposed, dealing with uncertain problems with both random and interval variables. Using a Taylor expansion and the concept of statistical moment, the first four central moments of the structural fatigue life performance function are obtained. Then, using a second Taylor expansion, the first four central moments are expanded at the midpoint of the interval variable, and the intervals of the statistical moments of the performance function are calculated. The obtained moment information is applied into an Edgeworth series expansion expression, giving the cumulative distribution function of the structural fatigue life performance function and getting its interval of the failure probability. Two numerical examples of growing complexity are employed to demonstrate the feasibility of the proposed approach.

In order to solve the problems of high energy consumption and serious waste of heat energy in the cooling of traditional oil cooler in hydraulic system, the author proposed the reliability optimization design of intelligent mechanical structure for waste heat recovery. The author has built a waste heat recovery test platform for hydraulic system, the influence of electrical load, oil flow rate and working medium flow rate on system operation and energy characteristics is studied. The experimental results show that: under the same working condition, compared with the oil cooler of the same specification, the maximum thermal efficiency of the proposed organic Rankine cycle waste heat recovery system is increased to 2.56%. The expander pressure ratio and system thermal efficiency increase with the increase of electric load and oil flow rate. With the increase of the flow rate of the working medium, the superheat of the working medium at the inlet of the expander decreases significantly, while the heat exchange of the evaporator and the output power of the expander increase. Under the test condition, the maximum heat exchange of evaporator is 4.18 kW, and the maximum output power of expander is 356 W. The energy saving effect of waste heat recovery system of hydraulic system is obtained, and the influence law of operation parameters on system performance is obtained.

In order to solve the problem of design efficiency of the digital assembly process, the author proposes a research using ultrasonic transducer technology. The main content of this research is to study the ultrasonic transducer elements according to the basic structure of the ultrasonic transducer.Through the study of equivalent circuit of ultrasonic transducer, the model of impedance matching design is constructed. Finally, the feasibility of ultrasonic transducer technology is obtained through experiments. Experimental results show that the transducer multichip structure of the ultrasonic transducer system and the LC matching network circuit can make the AOTF system achieve better results, and the diffraction efficiency is up to more than 70%, which is of great significance to the research and development of the current digital assembly process system. Conclusion. It is proven that the research of ultrasonic transducer technology can meet the needs of digital assembly process design efficiency.

In order to extend the actual service life of mechanical equipment components and realize the reasonable protection of applied structural components, the reliability optimization design of mechanical structure based on computational intelligence is studied. With the help of wavelet neural network, the established reliability and reliability index are obtained, and then the basic theory of reliability and computational intelligence technology are studied through the reliability optimization of mechanical zero structure. On this basis, the application concepts of reliability design method are defined, and the final calculation result of reliability optimization value is obtained by combining fuzzy set and level cut set, so as to realize the reliability optimization design of mechanical structure based on computational intelligence. The experimental results show that, compared with the traditional design method, the optimization design method supported by computational intelligence technology can better improve the disadvantages of mechanical structure object, and has strong practical application value in extending the reliability application time.