Reliability Analysis for the Dependent Competing Failure With Wear Model and its Application to the Turbine and Worm System

Many systems are usually subjected to the combined effects of degradation and random shocks at the same time. Their failures are the competitive result of soft failure caused by degradation and hard failure caused by shocks. For operating machinery, wear failure is the main failure mechanism, and the machine is also subject to shock during the wear process. This paper proposes a new generalized surface wear model in combination with dependent competing failure processes; this proposed model is different from the other wear model with independent wear increments. As a typical mechanical structure, worm gears and worms are subjected to the combined effect of two failure mechanisms: soft failure caused by performance degradation, and hard failure caused by shocks. Meanwhile, it is necessary to consider the competitiveness and correlation of these two failure mechanisms. The interdependent competitive failure model is used to describe the failure of operating machinery. In this study, the extended Archard model is used to calculate the wear depth of the tooth surface, and the wear model is established through the wear threshold. The relationship between tooth surface wear depth and duty cycle, sliding speed, and contact stress is analyzed. An iterative algorithm is used to derive a nonlinear time-varying wear degradation model considering contact stress and sliding velocity. Comparing the calculation results with the Monte Carlo simulation method, the model has high accuracy and describes the mechanism of soft and hard failures, and the mutual dependence of the two failure mechanisms has an important effect on reliability. Numerical examples are presented to illustrate the developed reliability models, along with sensitivity analysis.

Automated summary

This study examines the failure mechanisms of operating machinery, proposing a new generalized surface wear model that accounts for the competitive effects of degradation and random shocks. The model demonstrates high accuracy in describing the mechanisms of soft and hard failures, emphasizing the importance of considering the mutual dependence between these two failure mechanisms in reliability analysis.