| 摘要: |
| 针对非导电工程陶瓷双电极同步伺服放电加工工艺参数与加工效果间的高度非线性，提出了一种既能充分利 用神经网络的自学习能力，又能利用小波良好的时频局部化特性的非导电工程陶瓷双电极同步伺服放电加工效果预测的小波神经网络方法，并建立了预测模型,同时将预测结果与传统神经网络模型的预测结果进行了比较。结果 表明,小波网络模型的收敛速度和预测精度均优于传统神经网络模型。 |
| 关键词: 小波网络 人工神经网络 非导电工程陶瓷 放电加工 双电极同步伺服 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金项目(50675225);山东省科技攻关项目(2006GG22_1) |
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| Prediction for electrical discharge machining process with synchronous servo double electrodes based on wavelet neural network |
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YU Li-li1,LIU Yong-hong1,CAI Bao-ping1,ZHU Lian-zhang2,JI Ren-jie1,DONG Xin1
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(1. College of Mechanical and Electronic Engineering in China University of Petroleum, Dongying 257061,Shandong Province，China ;2. College of Computer and Communication Engineering in China University of Petroleum，Dongying 257061，Shandong Province, China)
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| Abstract: |
| According to the hicgh nonlinear feature and complex nature of electrical discharge machining process with synchronous servo double electrodes for non-conducti^e engineering ceramics, a forecast method based on wavelet neutral network which can make full use of part characteristics of wavelet time-frequent and self-study ability of neutral network was presented and the forecast model was set up. The forecast results by wavelet neural network model were compared with those of traditional neural network model. The results show that the model based on wavelet neural network is better than that based on traditional neural network in both convergence rate and prediction accuracy. |
| Key words: wavelet neural network artificial neural network non-conductive engineering ceramics electrical discharge machining synchronous servo double electrodes |
