Aeroengine Performance Deterioration Evaluation Using Clustering and Multi-Scaling Optimal Hyper Sphere Kernel Distance Assessment
Dong Li · Journal of Propulsion Technology · 2013
Aiming at repeated linearity and excessiveness of engine performance evaluating parameter,a cluster method according to variation and distance judgement was presented.Similar individuals were grouped,mean of every group was adopted as analysis objective,which reduced dimension greatly.On the basis of Support Vector Data Description,hyper sphere kernel distance metric was introduced while multiparameter was converted to single parameter,and contradiction leaded by parameter overfull was settled.Distance between a point in the character space and core of hyper sphere denotes performance deterioration.Valve curve of beginning deterioration and worsening was obtained.Considering contribution of parameter after clustering to performance evaluation,multi-scaling kernel parameter and punish coefficient C are optimized by improved Particle Swarm Optimization algorithm.Results indicate that engine performance can be consistent to factual condition after considering multi-scaling parameter.Evaluating results of multi-scaling parameter after clustering are consistent with original parameter.