Liao, Y.S.Y.S.LiaoYan, M.T.M.T.YanChang, C.C.C.C.ChangLiaoYS2008-11-262018-06-282008-11-262018-06-28200209240136http://ntur.lib.ntu.edu.tw//handle/246246/86988https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037186768&doi=10.1016%2fS0924-0136%2801%2901252-3&partnerID=40&md5=90e90bdc3249cc6df9778dd184ed90a9In this paper, a feed-forward neural network is used to estimate the workpiece height and distinguish the machining condition in wire electrical discharge machining (WEDM). Some experiments have been carried out to verify the effectiveness of this approach. Based on the on-line estimated workpiece height, a rule-based strategy is proposed to maintain optimal and stable machining. According to the rule-based strategy, servo voltage and power settings can be adjusted correctly to suit the workpiece profile. Experimental results demonstrate that high machining efficiency and stable machining can be achieved by means of the rule-based control strategy. © 2002 Elsevier Science B.V. All rights reserved.application/pdf234085 bytesapplication/pdfen-USEstimation; Neural network; Wire electrical discharge machining; Workpiece heightControl system analysis; Feedforward neural networks; Knowledge based systems; Online systems; Parameter estimation; Wire electrical discharge machining (WEDM); Electric discharge machiningjournal article2-s2.0-0037186768http://ntur.lib.ntu.edu.tw/bitstream/246246/86988/1/20.pdf