FORECASTING THE REMAINING USEFUL LIFE OF MECHANICAL OBJECTS BASED ON THEIR FAILURE STATISTICS

Abstract

The article is devoted to the problem of determining the residual life of mechanical objects based on the analysis of their failure statistics using a probabilistic-physical approach. The feasibility of applying the diffusion monotonic distribution (DM-distribution) as a theoretical reliability model is substantiated. This model differs from traditional strictly probabilistic distributions in that its parameters have a clear physical interpretation: the coefficient of variation of the generalized degradation process and the average rate of change of the determining parameter. Such an approach makes it possible to combine mathematical rigor with the physical essence of wear and degradation processes.The article considers the main characteristics of residual life-mean value and gamma-percent life and provides the formulas for their calculation using the DM-distribution. The method is shown to be convenient both in cases where the dynamics of the determining parameter are known and when long-term failure statistics are available.An example is given using experimental data from fatigue tests of V-95 alloy samples, widely employed by different researchers, which confirms the adequacy of the chosen model.The comparison of empirical and calculated estimates demonstrates their closeness, with the error not exceeding 5 %, which is a high level of accuracy for statistical estimation practice. The practical significance of the research lies in enabling effective planning of replacement intervals and preventive maintenance for long-life objects such as nuclear power plants, pipelines, bridges, and aircraft.