A Data and Model Hybrid Driven Method for Machining Energy Consumption Prediction of Boxy Parts

doi:10.3901/JME.2023.12.097

Abstract

Abstract: Boxy parts are the carrier and installation base of mechanical products and components, and their manufacturing process consumes a lot of resources and energy. As a leading technology for energy efficiency assessment and optimization, it is of great significance to predict the energy consumption in machining process. However, due to the various features and their complicated relationship of boxy parts, it is difficult to predict the machining energy consumption accurately. In order to fill this gap, a data and model hybrid driven method for machining energy consumption prediction of boxy parts is proposed. Firstly, the structure of boxy parts is analyzed, on this basis, the machining energy consumption characteristics of machining features and their coupling relationship are analyzed. Then, according to the intersecting and non-intersecting relationship of boxy parts, in order to realize the machining energy consumption prediction of boxy parts, a data-driven energy consumption prediction model for non-intersecting feature and a model-driven energy consumption prediction model for intersecting feature are established respectively. Finally, the validity of the proposed model and method are verified by an example of machining a boxy part, at the same time, compared with the energy consumption prediction method of pure data-driven and pure model-driven, the superiority of the proposed method is illustrated.

Key words: boxy part, energy consumption prediction, data and model hybrid driven, features, coupling feature

CLC Number:

TG501

ZHANG Hua, LI Shuguang, YAN Wei, JIANG Zhigang, ZHU Shuo, MA Feng. A Data and Model Hybrid Driven Method for Machining Energy Consumption Prediction of Boxy Parts[J]. Journal of Mechanical Engineering, 2023, 59(12): 97-108.

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