Research on steam meter calibration in cigarette factory based on machine learning

Yuanli Qin; Ningning Zhao; Yulong Feng; Shaolin Zhao

doi:10.1117/12.3015679

15 March 2024 Research on steam meter calibration in cigarette factory based on machine learning

Yuanli Qin, Ningning Zhao, Yulong Feng, Shaolin Zhao

Proceedings Volume 13079, Third International Conference on Testing Technology and Automation Engineering (TTAE 2023); 1307905 (2024) https://doi.org/10.1117/12.3015679
Event: 3rd International Conference of Testing Technology and Automation Engineering (TTAE 2023), 2023, Xi-an, China

Abstract

In the current industrial environment, electronic instruments have been widely used, but at the same time, electronic instruments also face many problems, such as zero temperature drift and sensitivity temperature drift caused by temperature changes. This article proposes an algorithm based on software proofreading that combines anomaly detection algorithms with neural networks. It is concluded that this method can indeed proofread instruments and maintain errors within an acceptable range. This method can further improve the accuracy and reliability of the current industry, ensuring process optimization and efficiency improvement.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuanli Qin, Ningning Zhao, Yulong Feng, and Shaolin Zhao "Research on steam meter calibration in cigarette factory based on machine learning", Proc. SPIE 13079, Third International Conference on Testing Technology and Automation Engineering (TTAE 2023), 1307905 (15 March 2024); https://doi.org/10.1117/12.3015679

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