Transformer-based Drum-level Prediction in a Boiler Plant with Delayed Relations among Multivariates

التفاصيل البيبلوغرافية
العنوان: Transformer-based Drum-level Prediction in a Boiler Plant with Delayed Relations among Multivariates
المؤلفون: Su, Gang, Yang, Sun, Li, Zhishuai
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Machine Learning
الوصف: The steam drum water level is a critical parameter that directly impacts the safety and efficiency of power plant operations. However, predicting the drum water level in boilers is challenging due to complex non-linear process dynamics originating from long-time delays and interrelations, as well as measurement noise. This paper investigates the application of Transformer-based models for predicting drum water levels in a steam boiler plant. Leveraging the capabilities of Transformer architectures, this study aims to develop an accurate and robust predictive framework to anticipate water level fluctuations and facilitate proactive control strategies. To this end, a prudent pipeline is proposed, including 1) data preprocess, 2) causal relation analysis, 3) delay inference, 4) variable augmentation, and 5) prediction. Through extensive experimentation and analysis, the effectiveness of Transformer-based approaches in steam drum water level prediction is evaluated, highlighting their potential to enhance operational stability and optimize plant performance.
Comment: under review of IEEE PES ISGT Europe 2024 conference
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.11180
رقم الأكسشن: edsarx.2407.11180
قاعدة البيانات: arXiv