Time series prediction method of geometric characteristics of molten pool based on ARIMA model

Qiling Li; Zhenying Xu; Ziqian Wu; Mengyu Tang; Jinjin Yan; Jun Ling

doi:10.1117/12.2606686

24 November 2021 Time series prediction method of geometric characteristics of molten pool based on ARIMA model

Qiling Li, Zhenying Xu, Ziqian Wu, Mengyu Tang, Jinjin Yan, Jun Ling

Proceedings Volume 12060, AOPC 2021: Advanced Laser Technology and Applications; 1206017 (2021) https://doi.org/10.1117/12.2606686
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

A time-series prediction method for the geometric characteristics (length, length, area) of the molten pool in the laser cladding process is studied. This method uses the historical data of the change of the geometric characteristics of the molten pool to predict the geometric characteristics of the molten pool at the next moment, so as to promote the application in the control of the shape of the molten pool and the estimation of the state of the molten pool. In view of the time correlation shown by the time series of the geometric characteristics of the molten pool, a time series prediction method for the geometric characteristics of the molten pool was developed based on the Autoregressive Integrated Moving Average (ARIMA) model, and the dynamic stability index of the molten pool was proposed. The results show that the area of the molten pool has the best prediction accuracy, and the Mean Absolute Percentage Error (MAPE) is only 3.105, while the predicted MAPE of the width of the molten pool is 3.464 and the length of the predicted MAPE is 4.048. The dynamic stability index proposed can reflect the fluctuation of the molten pool.

Citation Download Citation

Qiling Li, Zhenying Xu, Ziqian Wu, Mengyu Tang, Jinjin Yan, and Jun Ling "Time series prediction method of geometric characteristics of molten pool based on ARIMA model", Proc. SPIE 12060, AOPC 2021: Advanced Laser Technology and Applications, 1206017 (24 November 2021); https://doi.org/10.1117/12.2606686

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KEYWORDS

Cladding

Data modeling

Image processing

Laser processing

Mathematical modeling

Autoregressive models

Lithium

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