Modelling of multiple failure mechanisms for system reliability prediction
Helicopters are highly dependent on their transmission systems, which provide the vital links from the engines to the rotor and ancillary systems. Components are highly loaded and must be manufactured to a high degree of accuracy; the lack of redundancy implies that this is a 'series-chain' system. Existing techniques for calculating expected life are based upon historical data from different gearbox and helicopter types, thus limiting the confidence of the results. Design techniques may be conservative in some areas, whilst neglecting to consider different load patterns, usage, maintenance and environmental factors. This work describes the development of probabilistic models that represent damage accumulated by fatigue, wear and corrosion of the key components with an Intermediate gearbox (IGB). The parameters of these models represent geometrical, load and material data at the design stage, and produce an output in terms of failure probability against operating hours. This allows the influential parameters to be identified before building a prototype helicopter gearbox. The results from these models are then used to predict the upper and lower bounds of system reliability. This enables the combination of diverse failure mechanisms to be viewed to determine the relevant significance of each failure mechanisms. The effectiveness of the gearbox monitoring systems has been incorporated in the computer model by considering the probability of detection (POD) of each failure mechanism. The work to develop models found that there is a large body of work available to describe damage accumulation due to fatigue, but far less in regard to wear and corrosion. Fatigue models are very sensitive to load and material variability, particularly tooth root bending fatigue, for which many loads are considered 'non-damaging'. Wear models are mostly affected by changes in material hardness, wear coefficient and slip amplitude; changes in load are less influential on the predicted time to failure. The results for galvanic corrosion are dominated by the corrosion rate and time to initiate. In the system reliability model, reducing gear load appears to be the simplest means to increase life; increases in material strength and reduction in material variability are less achievable without significant improvements in manufacture and/or material technology.