Temperature Prediction of Aluminum Alloy Work-Pieces in Aging Furnaces Based on Improved Case-Based Reasoning

• 作者: Jianjun He Ling Shen Qi Zhu Weihua Gui
• 来源期刊: 有色冶金(英文)
• 学科: 医学
• 关键词: Prediction Model ALUMINUM Alloy Case-Based REASONING State Transition Algorithm AGING FURNACE
• 年，卷（期）: 2017,（4）
• 页码范围: 47-59
• 页数: 13页
• 分类号: R73

摘要

The temperature of aluminum alloy work-pieces in the aging furnace directly affects the quality of aluminum alloy products. Since the temperature of aluminum alloy work-pieces cannot be measured directly, a temperature prediction model based on improved case-based reasoning (CBR) method is established to realize the online measurement of the work-pieces temperature. More specifically, the model is constructed by an advanced case-based reasoning method in which a state transition algorithm (STA) is firstly used to optimize the weights of feature attributes. In other words, STA is utilized to find the suitable attribute weights of the CBR model that can improve the accuracy of the case retrieval process. Finally, the CBR model based on STA (STCBR) was applied to predict the temperature of aluminum alloy work-pieces in the aging furnace. The results of the experiments indicated that the developed model can realize high-accuracy prediction of work-pieces temperature and it has good application prospects in the industrial field.