A Neural Network Approach for the On-line Estimation of Workpiece Height in WEDM
Resource
Journal of Materials Processing Technology 121 (2-3): 252-258
Journal
Journal of Materials Processing Technology
Journal Issue
121
Pages
252-258
Date Issued
2002
Date
2002
Author(s)
Liao, Y.S.
Yan, M.T.
Chang, C.C.
Abstract
In 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.
Subjects
Estimation; Neural network; Wire electrical discharge machining; Workpiece height
Other Subjects
Control system analysis; Feedforward neural networks; Knowledge based systems; Online systems; Parameter estimation; Wire electrical discharge machining (WEDM); Electric discharge machining
Type
journal article
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