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Ultrasonic Power Load Forecasting Based on BP Neural Network

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Abstract

The use of power load forecasting in aluminum alloy ultrasonic-assisted casting systems can improve its working efficiency and stability and simultaneously improve the casting quality of the aluminum alloy as well. A power load forecasting model based on a back-propagation neural network was designed and embedded in an ultrasonic power supply, referred to as the new ultrasonic power supply; the ultrasonic power supply without power load forecasting was referred to as the traditional ultrasonic power supply. Both these power supplies were used in an experimental process of 7085 aluminum alloy ultrasonic-assisted casting. The power load range and harmonic frequency range were 953.01–1194.02 W and 16.03–19.1 kHz for the traditional ultrasonic power supply with an average grain size of 179.93 µm and 1073.1–1213.02 W and 17.94–20.04 kHz for the new ultrasonic power supply with an average grain size of 139.41 µm, respectively. The results of the ultrasonic-assisted alloy casting experiment showed that the design of the proposed power load forecasting model could improve the work efficiency of the assisted casting system as well as the quality of the aluminum alloy casting.

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Acknowledgements

This work is partially supported by the National Basic Research Development Program of China (Grants No. 2012CB619504),the National natural Science Foundation of China(Grant Nos. 51575539 and 51475480), the Excellent Scientific and technological innovation team of Central South University, and National Key Laboratory for manufacturing aluminum alloy components and Light Alloy Research Institute Central South University, the People’s Republic of China, The authors also thank Academician of the Chinese Academy of Engineering Professor Weihua Gui for helpful comments.

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  1. Light Alloy Research Institute, Central South University, Changsha, 410083, China

    Xiwen Chen, Xiaoqian Li & Ruiqing Li

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  1. Xiwen Chen
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  2. Xiaoqian Li
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Correspondence to Xiwen Chen.

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Chen, X., Li, X. & Li, R. Ultrasonic Power Load Forecasting Based on BP Neural Network. J. Inst. Eng. India Ser. C 101, 383–390 (2020). https://doi.org/10.1007/s40032-019-00549-3

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  • DOI: https://doi.org/10.1007/s40032-019-00549-3

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