Energy Conservation and Environmental Protection

Water vapor chemical supervision is an important means to ensure the safe and economic operation of the unit, and is an important guarantee to ensure the qualified water quality of the power plant thermal system and the safe and economic operation of the unit. The water vapor system of the thermal power plant is very unstable, and it is easy to generate all kinds of oxides, sulfides, hydroxide and other solid impurities in the equipment, which will seriously affect the safe and economic operation of the unit. Therefore, strict chemical supervision of water vapor system is an important means to ensure the safety and economic operation of boiler and thermal equipment. In the power station boiler and thermal system, water and steam are heat exchange media. Due to the chemical reaction of water and steam in the thermal system, the metal equipment in the thermal system is corroded, so it is necessary to ensure the quality of water and steam through chemical supervision. Therefore, it is of great significance to establish a perfect water vapor chemical supervision system for the safe and economic operation of the power plant.

This paper puts forward the overall idea of the prevention and control of urban forestry biological disasters in Xiamen during the "14th Five-Year Plan" period and formulates construction goals. The author focuses on setting the main tasks and key tasks of prevention and control of the urban forestry pest in Xiamen in the next 5 years, which is based on the actual occurrence of forestry biological disasters in Xiamen. Moreover, specific safeguard measures are proposed at the same time. This paper can be used as a reference for relevant departments to prepare the "14th Five-Year" urban forestry biological disaster prevention and control plan.

This article comprehensively analyzes the issues of soil pollution and soil remediation under ecological protection, and pays special attention to the application of information technology in this field. Through in-depth exploration of pollution sources, ecological impacts, and remediation methods, this article aims to propose more effective and sustainable solutions. Information technology, especially soil quality sensors, data analysis, remote sensing technology, and geographic information systems, has been proven to be powerful tools that can assist in monitoring, preventing, and repairing soil pollution.

This paper explores the automation control and optimization of intelligent knitting and weaving machinery with the aim of enhancing production efficiency, reducing costs, and improving product quality. The research encompasses control system architecture, PLC programming, intelligent control algorithms, data acquisition, and production process optimization. Key issues include the criteria for selecting control algorithms and the application of sensor technology in data acquisition. The paper emphasizes the suitability of different algorithms to meet various production requirements and provides a detailed insight into the importance of sensors in monitoring and adjusting production parameters. Through this study, manufacturers can monitor production processes in real-time, adjust parameters, and enhance product quality, thereby increasing market competitiveness. The conclusions of this study underscore the significance of intelligent control and optimization in the manufacturing industry, offering potential directions for future technological advancements and improvements.

In the development of food packaging, green environmental protection technology plays a very important role. In recent years, the application of green environmental protection technology in the food packaging industry has gradually increased, including the use of environmentally friendly materials, the development of degradability, easy recycling and other aspects. In the current environment of developing a green economy, the food packaging industry needs to apply green energy-saving and environmental protection technologies to its own production and development. This article introduces some common green energy-saving and environmental protection technologies, and analyzes and thinks about them, aiming to provide reference for the development of the food packaging industry and promote the sustainable development of enterprises.

This paper investigates automatic maintenance strategies for weather forecast systems based on big data and artificial intelligence (AI). Firstly, it delves into the collection and processing of weather data, including critical steps such as data source acquisition, data quality cleansing, and feature extraction and analysis. Secondly, it focuses on the application of AI in weather forecasting, including the utilization of machine learning and deep learning, improvements in weather models and prediction techniques, and algorithm optimization. Subsequently, it discusses automatic maintenance strategies in detail, encompassing the concepts and significance of maintenance, the design of automatic maintenance strategies, and the maintenance process and automation tools. Finally, it looks ahead to future trends in weather forecast systems, emphasizing research directions such as uncertainty modeling, explainable AI, handling extreme events, and climate change studies. This research is expected to drive continuous improvement in weather forecast systems, providing more accurate, real-time, and personalized weather information.