چکیده مقاله
This paper presents an optimized gear fault identification system using Genetic Algorithm GA to investigate the type of gear failure of a gearbox system using Artificial Neural Networks ANN with a well designed structure suited for practical implementations due to its short training duration and high accuracy Slight worn, medium worn, and broken teeth of gears are categorized as gear faults Wavelet analysis which is implemented for non stationary signals, is capable of providing both time domain and frequency domain information simultaneously and therefore recognized in this research as the most reliable signal analysis method to extract a feature vector to train ANN using normalized wavelet packet energy rate index of the vibration signal GA was exploited to settle on an optimized system by determination of best values for wavelet function type, decomposition level and number of neurons of hidden layer leading to a high speed, meticulous two layer ANN with a particularly small size
کلیدواژهها
نویسندگان
J Rafiee
M Sc student in Manufacturing Engineering
F Arvani
B Sc graduate in Manufacturing Engineering
A Harifi
Ph D student in Control Engineering
M.H Sadeghi
Assistant Prof in Mechanical Engineering
شیوه ارجاع
Rafiee, J and Arvani, F and Harifi, A and Sadeghi, M.H,1384,A GA-Based Optimized Fault Identification System Using Neural Networks,01st Tehran International Congress on Manufacturing Engineering (TICME2005),Tehran
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی و هفتمین کنفرانس ملی مهندسی ساخت و تولید1 فروردین 1384 · تهران