Characteristics forecasting of hydraulic valve based on grey correlation and ANFIS

Authors:
Zhen-Yuan Jia;Jian-Wei Ma;Fu-Ji Wang;Wei Liu
Affiliations:
Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, Dalian 116024, China;Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, Dalian 116024, China;Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, Dalian 116024, China;Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, Dalian 116024, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

Accurate prediction is crucial for the synthesis characteristics of the hydraulic valve in industrial production. A prediction method (G-ANFIS for short) based on grey correlation and adaptive neuro-fuzzy system (ANFIS) to forecast synthesis characteristics of hydraulic valve is devised and the utilizing of the method can help enterprises to decrease the repair rate and reject rate of the product. Grey correlation model is used first to get the main geometric elements affecting the synthesis characteristics of the hydraulic valve and thus simplifies the system forecasting model. Then use ANFIS to build a prediction model based on the above mentioned main geometric elements. To illustrate the applicability and capability of the devised prediction method, a specific hydraulic valve production was used as a case study. The results demonstrate that the prediction method was applied successfully and could provide high accuracy. The method performed better than artificial neural networks (ANN) to forecast the synthesis characteristics of hydraulic valve.