摘要
In this paper,negative selection and genetic algorithms are combined and an improved bi-objective optimization scheme is presented to achieve optimized negative selection algorithm detectors.The main aim of the optimal detector generation technique is maximal nonself space coverage with reduced number of diversified detectors.Conventionally,researchers opted clonal selection based optimization methods to achieve the maximal nonself coverage milestone;however,detectors cloning process results in generation of redundant similar detectors and inefficient detector distribution in nonself space.In approach proposed in the present paper,the maximal nonself space coverage is associated with bi-objective optimization criteria including minimization of the detector overlap and maximization of the diversity factor of the detectors.In the proposed methodology,a novel diversity factorbased approach is presented to obtain diversified detector distribution in the nonself space.The concept of diversified detector distribution is studied for detector coverage with 2-dimensional pentagram and spiral self-patterns.Furthermore,the feasibility of the developed fault detection methodology is tested the fault detection of induction motor inner race and outer race bearings.
作者简介
Anam ABID received her Bachelor,s degree in electrical engineering from the University of Engineering and Technology Peshawar,Pakistan,and the Master's degree in electrical engineering from the National University of Sciences and Technology Pakistan.She is currently pursuing her Ph.D.degree in Mechatronics and holds a faculty position with the Department of Mechatronics Engineering at the University of Engineering and Technology,Peshawar.Her research interests include fault detection,control systems,machine learning,and signal processing;Zia UI HAQ received his BachelorJ s degree in agricultui'al engineering and Master's degree in soil and water engineering from NWFP University of Engineering and Technology,Peshawar Pakistan,and Ph.D.degree from the University of Southampton,UK,in 1996,2003,and 2009,respectively.Currently,he is an Assistant Professor with the Department of Agriculture at the University of Engineering and Technology,Peshawar,Pakistan.His research interests include soil and water engineering,irrigation and intelligent computing methods;Muhammad Tahir KHAN received his Bachelor's degree in mechanical engineering from NW.FP University of Engineering&:Technology,Peshawar,Pakistan,Master's degree in mechatron-ics from University of New South Wales,Sydney,Australia,and Ph.D.degree from the University of British Columbia,Vancouver BC,Canada,in 1997,1999,and 2010,respectively.He was a postdoctoral fellow with the Industrial Automation Laboratory at the University of British Columbia,Vancouver,BC,Canada for 2 years until January 2012.Currently,he is a Professor with the Department of Mechatronics at the University of Engineering and Technology,Peshawar,Pakistan.His research interests include robotics,and intelligent control systems.
