Helicopter Transmission System Fault Diagnosis And Health Management Method Based On Big Data

With its superior performance,helicopters have been widely used in modern military and civilian applications and have an irreplaceable position in some fields.However,since the birth of a helicopter,its failures have also emerged.Therefore,the history of the development of helicopters is also a history of the struggle between people and the failures of helicopter.With the aim of ensuring flight safety to the maximum extent,continuously improving the accuracy of helicopter fault diagnosis and reducing maintenance costs are people's constant pursuit goals.As one of the helicopter's three important components,the transmission system has the smallest safety margin and its reliability directly determines the safety of the helicopter.Today,the arrival of the era of big data has led to new breakthroughs and improved technology in helicopter fault diagnosis.In this paper,taking the helicopter transmission system as the research object,using data mining methods to apply some of the big data processing techniques for helicopter transmission fault diagnosis and remaining life prediction.Through experiments,these methods proved to be reliable,and solving some difficult problems in the helicopter transmission system.The research results of this paper are mainly as follows: 1.Through the study of affinity propagation(AP)clustering method,using it to the fault feature extraction of transmission system,and solving the problem of difficulty in dimension reduction and inaccurate feature extraction when applying the data analysis method to the transmission system.2.Aiming at the problems in the application of the AP algorithm in the transmission system process,a weighted AP algorithm is proposed to further improve the accuracy of the AP algorithm in extracting the transmission system features.3.The weighted AP algorithm is applied to the early fault diagnosis of transmission system and the multi-fault diagnosis of precision equipment.Through the experiments,good results have been achieved,solving the difficult problems of early fault diagnosis of transmission system and the difficulty of positioning in precision equipment.4.Proposing a hybrid hierarchical clustering method,which allows large data to be organized and segmented and served another idea for big data analysis.This method is applied to the complex fault diagnosis of the transmission system.Through the experiments,it can solve the troubles that different faults with the same features and the same faults with the different features in the helicopter transmission system.The fault diagnosis indicators have reached the specified requirements.5.By studying the Hidden Markov Model,combining it with the clustering method and applying it to the prediction of the remaining service life of the transmission system,the experiment verifies that this method can predict the remaining service life of the transmission system equipment.6.This paper also presents a solution for online,offline and overall health management of helicopter transmission system with big data.Through a series of studies,a helicopter transmission system health management system is established on data mining and big data analysis.