首页|Characteristics Prediction Method of Electro-hydraulic Servo Valve Based on Rough Set and Adaptive Neuro-fuzzy Inference System

Characteristics Prediction Method of Electro-hydraulic Servo Valve Based on Rough Set and Adaptive Neuro-fuzzy Inference System

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Synthesis characteristics of the electro-hydraulic servo valve are key factors to determine eligibility of the hydraulicproduction. Testing all synthesis characteristics of the electro-hydranlic servo valve after assembling leads to high repair rate and reject rate, so accurate prediction for the synthesis characteristics in the industrial production is particular important in decreasing the repair rate and the reject rate of the product. However, the research in forecasting synthesis characteristics of the electro-hydraulic servo valve is rare. In this work, a hybrid prediction method was proposed based on rough set(RS) and adaptive neuro-fuzzy inference system(ANFIS) in order to predict synthesis characteristics of electro-hydraulic servo valve. Since the geometric factors affecting the synthesis characteristics of the electro-hydraulic servo valve are from workers' experience, the inputs of the prediction method are uncertain. RS-based attributes reduction was used as the preprocessor, and then the exact geometric factors affecting the synthesis characteristics of the electro-hydraulic servo valve were obtained. On the basis of the exact geometric factors, ANFIS was used to build the final prediction model. A typical electro-hydranlic servo valve production was used to demonstrate the proposed prediction method.The prediction results showed that the proposed prediction method was more applicable than the artificial neural networks(ANN) in predicting the synthesis characteristics of electro-hydraulic servo valve, and the proposed prediction method was a powerful tool to predict synthesis characteristics of the electro-hydraulic servo valve. Moreover, with the use of the advantages of RS and ANFIS, the highly effective forecasting framework in this study can also be applied to other problems involving synthesis characteristics forecasting.

characteristics predictionrough setadaptive neuro-fuzzy inference systemelectro-hydraulic servo valveartificial neural networks

JIA Zhenyuan、MA Jianwei、WANG Fuji、LIU Wei

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Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education,Dalian University of Technology, Dalian 116024, China

国家自然科学基金Research and Innovation Teams Foundation Project of Ministry of Education of ChinaLiaoning Provincial Key Laboratory Foundation Project of China

50835001IRT061020060132

2010

10.3901/CJME.2010.02.200

中国机械工程学报
中国机械工程学会

中国机械工程学报

CSCDSCIEI
影响因子：0.765
ISSN：1000-9345
年,卷(期)：2010.23(2)
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