Hangzhou City University

Xuxia Zhang

Jun Wu

Anping Wan

Weipeng Liu

Tao Peng

Ting Chen

Luoke Hu

A data mining-based method for real-time production quality prediction of aluminum alloy casting, includes: (1) based on mold flow analysis results, installing sensors on a casting mold; wherein the sensors include at least one temperature sensor, at least one pressure sensor, at least one contact sensor, and a multi-functional gas sensor; (2) during casting production, real-time collecting temperatures, pressures, and contact times of the aluminum liquid at a plurality of locations of the casting mold, and pressure, composition, humidity, and temperature of gas in a mold cavity, by the installed sensors, for constructing an aluminum alloy casting process parameter set; and (3) inputting the process parameter set to a production quality prediction model; wherein the production quality prediction model is used to judge whether the production quality is qualified, which is obtained by mining a relationship between history casting process parameters and casting quality data.

Data mining-based method for real-time production quality prediction of aluminum alloy casting, electronic device, and computer-readable storage medium

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HANGZHOU, China

Xuxia Zhang