Buratto William Gouvêa, Muniz Rafael Ninno, Nied Ademir, Barros Carlos Frederico de Oliveira, Cardoso Rodolfo, Gonzalez Gabriel Villarrubia
Electrical Engineering Graduate Program, Department of Electrical Engineering, Santa Catarina State University (UDESC), Joinville 89219-710, Brazil.
Electrical Engineering Graduate Program, Department of Electrical Engineering, Federal University of Pará (UFPA), Belém 66075-110, Brazil.
Sensors (Basel). 2024 Feb 1;24(3):967. doi: 10.3390/s24030967.
This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.
本综述深入探讨了自动化和传感器技术在优化发电过程中热处理参数方面的关键作用。对高效可持续发电的需求导致发电厂对热处理的严重依赖。然而，确保对这些处理进行精确控制仍然具有挑战性，因此需要集成先进的自动化和传感器系统。本文评估了自动化的关键方面，强调其在简化操作、提高安全性以及优化热处理过程中的能源效率方面的能力。此外，它突出了传感器在监测和调节关键参数（如温度、压力和流速）方面不可或缺的作用。这些传感器能够进行实时数据采集，便于立即进行调整以维持最佳运行条件并防止系统故障。它探讨了最近的技术进步，包括机器学习算法和物联网集成，这些技术革新了热处理控制中的自动化和传感器能力。融入这些创新显著提高了控制系统的精度和适应性，从而提高了性能并减少了环境影响。本综述强调了自动化和传感器技术在发电热处理中的必要性，强调了它们在提高运营效率、确保可靠性以及推动发电过程可持续性方面的关键作用。
