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A Review of Automation and Sensors: Parameter Control of Thermal Treatments for Electrical Power Generation.
Buratto, William Gouvêa; Muniz, Rafael Ninno; Nied, Ademir; Barros, Carlos Frederico de Oliveira; Cardoso, Rodolfo; Gonzalez, Gabriel Villarrubia.
Afiliação
  • Buratto WG; Electrical Engineering Graduate Program, Department of Electrical Engineering, Santa Catarina State University (UDESC), Joinville 89219-710, Brazil.
  • Muniz RN; Electrical Engineering Graduate Program, Department of Electrical Engineering, Federal University of Pará (UFPA), Belém 66075-110, Brazil.
  • Nied A; Production Engineering Graduate Program, Department of Science and Technology, Federal Fluminense University (UFF), Rio das Ostras 28895-532, Brazil.
  • Barros CFO; Electrical Engineering Graduate Program, Department of Electrical Engineering, Santa Catarina State University (UDESC), Joinville 89219-710, Brazil.
  • Cardoso R; Production Engineering Graduate Program, Department of Science and Technology, Federal Fluminense University (UFF), Rio das Ostras 28895-532, Brazil.
  • Gonzalez GV; Production Engineering Graduate Program, Department of Science and Technology, Federal Fluminense University (UFF), Rio das Ostras 28895-532, Brazil.
Sensors (Basel) ; 24(3)2024 Feb 01.
Article em En | MEDLINE | ID: mdl-38339684
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Brasil

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Brasil