Abstract
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.
Highlights
The Aging Furnace (AF) is an important equipment for the thermal treatment of aluminum alloy work-pieces to enhance their comprehensive performance of anticorrosion property and mechanical properties, such as hardness and ultimate tensile strength [1]
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
state transition algorithm (STA) is utilized to find the suitable attribute weights of the CBR model that can improve the accuracy of the case retrieval process
Summary
The Aging Furnace (AF) is an important equipment for the thermal treatment of aluminum alloy work-pieces to enhance their comprehensive performance of anticorrosion property and mechanical properties, such as hardness and ultimate tensile strength [1]. The establishment of a reasonable temperature prediction model of aluminum alloy work-pieces is of practical significance to realize precise control of the work-pieces temperature during the aging process. The experimental results show that STCBR can realize high-accuracy prediction of work-pieces temperature and has strong robustness
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