Reliability Assessment of Aircraft Commutators

Abstract

The article describes the method of predicting the reliability and durability of an aircraft commutator, which is a primary source of electric energy in helicopters. Tests were conducted for 10 starter-generators. From this research it follows that the technical condition of brushes and bearings has a significant impact on the reliability of starter-generators. The reliability of starter-generators was determined based on the method consisting of two stages that was adopted: the first stage involved determining the density function of changes in diagnostic parameter depending on the operating time, but the second stage included the assessment of the reliability of bearings of the starter-generator taking into account the real flight profile. The first stage of the adopted method consisted of defining the dynamic model of changing the length of the starter-generator’s brush, which became the probabilistic model. Subsequently, based on differential equations, Fokker–Planck partial differential equation was derived, which describes the process of increasing the brush wear in a probabilistic way. This method enables the prediction of the residual durability of the helicopter’s starter-generator due to the change in a diagnostic parameter which is the wear of brushes during starter-generator operation. The second stage of this method allows determining the durability of starter-generator’s bearings building upon the average helicopter’s flight profile. Owing to the difficulty in measuring the wear of bearings, the relation between the durability of bearings and the temperature of surroundings can be applied by replacing the flight altitude with temperature. The reliability of the helicopter’s starter-generator was determined based on the serial-type reliability structure.

Service Life Prediction for Rotating Electrical Machines on Aircraft in Terms of Temperature Loads

“…Thus, a full model was developed to analyze the risk of a failure. In preparing these models, parameters such as temperature, speed, and engine type were taken into account [1,22,23].…”

“…As a result of the above circumstances, these machines require greater attention during maintenance, as well as proper monitoring of their conditions. This article is a continuation of the topic undertaken in the paper [1] in which the authors determined the reliability of an aircraft electrical machine. The reliability of the electric starter was determined by the wear of its brushes and starter bearings using the ambient temperature on the example of one type of aircraft.…”

Semi-Markov approach for reliability modelling of light utility vehicles

“…Next, using an original indicator, they selected a Generalized Gamma distribution as the best fitting of the empirical distribution function. In turn, Wawrzyński et al [53] used statistical methods to develop a reliability model for aircraft commutators, under the assumption of a serial reliability structure of a tested object.…”

“…Statistical methods Generalized Gamma distribution Cabin door lock on rail vehicles [43] Reliability series structure model Aircraft commutators [53] Statistical methods and fuzzy logic Weibull and fuzzy models Light combat aircraft [60] Statistical methods and neural networks Exponential, Weibull and MLP models Light utility vehicles [34] Weibull, Non-Homogeneous Poisson Process and Adaptive Neuro-Fuzzy Inference System models Fluid filling equipment in automotive manufacturing industry [45] Neural networks Neural models (MLP) Vehicles [25] Neural model of reliability allocation Machine tools [11] Neural networks and partial swarm optimization Hybrid model Industrial robot systems [2] Ordered weighted averaging aggregation operator Reliability allocation model Thin-film transistor liquid-crystal display [7] Probabilistic methods Reliability models including hard and soft failures Micro-electro-mechanical systems devices [46][37]…”