Research On Fault Feature Extraction For Critical Components Of Helicopter Transmission Chain

Helicopter usually works in severe condition, and its structure is very complicated.Transmission chain is the only channel for power transmission which can t beredundantly designed, so the damage/fault in transmission system will threaten thesafety of helicopter greatly. Therefore, it is particularly important to carry out conditionmonitoring and fault diagnosis for transmission chain in order to detect early damage intime. As is the basis of condition monitoring and fault diagnosis, it is of greatsignificance to extract fault feature information effectively from the vibration signalacquired from critical components of transmission chain.Funded by the project supported by National Natural Science Foundation of China“Research on methods of overcomplete sparse representation and reconstruction ofdamage feature information for moving components” and “Research on accumulatingdamage tracking and prognosis methods based on phase space warping for helicopterdrive train” and Ministerial-level project “Health management and fault prognosistechnology of rotor wing and transmission system of XXX”, fault feature extraction forcritical components of helicopter transmission chain based on vibration analysis isstudied in this thesis. The main contents include:(1) The fault simulation modes of bearing and gear are built, and the signal oftypical fault of bearing and gear is simulated so as to provide available data for thefollowing fault diagnosis methods;(2) Several types of signal pre-processing techniques are researched, such as timesynchronous average and singular value decomposition, and these techniques arevalidated with simulated and experimental data;(3) The parameter feature extraction techniques based on raw vibration signal, timesynchronous average signal, residual signal, and difference signal are researched;(4) The typical traditional spectrum analysis techniques are analyzed with rawvibration signal from damage seeded test of bearing and gear, and the technique offeature extraction based on EMD is especially focused.Following the research plan of theory study→simulation analysis→experimentverification, this thesis is based on comprehensive summery of feature extractiontechniques for critical components of transmission chain and focuses on part of them. The techniques introduced in this thesis is validated with simulation signal andexperiment data of damage seeded test, which is the basis of further research oncondition monitoring and fault diagnosis.