After-rolling cooling is a crucial technology for regulating the structure and properties of hot-rolled products, providing vital support for the production and quality improvement of hot-rolled strip products. The after-rolling cooling control system is a core factor limiting the development of after-rolling cooling technology. Therefore, conducting research on the after-rolling cooling control system is of significant importance. This paper first analyzes the basic principles of after-rolling cooling and summarizes the current state of research and applications for after-rolling cooling systems. It provides a comprehensive analysis and summarizes the research status and development trends of the after-rolling cooling control system from two aspects: control strategies and heat transfer mathematical models. Temperature control, as a key component of the after-rolling cooling control system, is essential. Precise control of cooling water pressure, flow rate, and the impact of strip speed fluctuations during the cooling process is an effective control strategy to improve the high-precision temperature control of the after-rolling cooling system. A comprehensive analysis of the application of traditional heat transfer models in strip steel heat transfer processes is presented. A comparative analysis of traditional temperature control models and temperature control models with the addition of intelligent algorithms indicates that conventional afterr-olling cooling control models can no longer meet the requirements of new after-rolling cooling systems under complex conditions. Therefore, it is necessary to develop more practical and intelligent adaptive control models that align with the characteristics of the new after-rolling cooling systems.
KEYWORDS: Control systems, Cooling systems, Data modeling, Temperature control, Mathematical modeling, HVAC controls, Systems modeling, Process control, Deep learning, Performance modeling
Post-rolling cooling is a critical step in the hot rolling production process, and it has a significant impact on the microstructure and mechanical properties of the final product. This paper first introduces three main modules of research on advanced post-rolling cooling system models. Secondly, it analyzes how to establish high-precision predictive models for post-rolling cooling systems and improve temperature control accuracy. The paper summarizes some strategies and solutions proposed by scholars to address identified issues. By utilizing advanced control theory and deep learning, a post-rolling control and cooling predictive model is developed to effectively mine production big data and provide accurate forecasts for the cooling system. In terms of improving temperature control accuracy, scholars have optimized existing self-learning models, resulting in a dual-model parallel system known as VSG+DNN. This system significantly enhances the stability and robustness of the post-rolling cooling system.
This paper proposes an improved RRT algorithm based on the cellular decomposition method. In the constructed two-dimensional plane, the space is decomposed into traversable regions and obstacle regions. Subsequently, based on the relationships between adjacent regions, random sampling points are constrained within neighboring regions until expansion reaches the region containing the target node. The planned route is then optimized to effectively address the issue of excessive turning points. Simulation results demonstrate that the improved RRT algorithm enhances path planning accuracy and efficiency in the application of two-dimensional mobile robot navigation, reducing travel distances and lowering cost consumption.
KEYWORDS: Control systems, Environmental monitoring, Agriculture, Crop monitoring, Internet of things, Environmental sensing, Data processing, Temperature control, Sensors, Yield improvement
With the development of society and the progress of technology, the traditional agricultural production mode can no longer meet the needs of today's development. In recent years, China has vigorously promoted and supported the development of agriculture, with the development of agricultural greenhouses tending towards informatization, networking, and intelligence. Traditional agricultural greenhouses generally manage greenhouses based on user experience, wasting a lot of manpower and resources. Due to the gap between user experience and crop growth needs, it has a significant impact on crop yield and quality, making it difficult to further improve the development of agriculture. Based on the above issues, a monitoring system has been designed using Internet of Things technology on greenhouse greenhouses to achieve intelligent online visual monitoring, improve the quality and yield of crops more effectively, enhance the utilization rate of greenhouse greenhouses, improve user labor efficiency, and promote the stability of agricultural production development.
KEYWORDS: Internet of things, Agriculture, Control systems, Internet technology, Environmental monitoring, Sensors, Humidity, Data transmission, Environmental sensing, Internet
The Internet of Things is the product of the information technology revolution and has a broad application prospect in all walks of life. The intelligent hydroponic greenhouse is not only the product of scientific and technological development, but also the development trend of future agriculture. The intelligent hydroponic greenhouse using Internet of Things technology can not only realize automatic monitoring, intelligent control, remote control and other functions, but also make the development of agriculture more intelligent and modern. Two monitoring networks of nutrient solution and greenhouse environment are respectively built through the Internet of Things to realize real-time monitoring and control of nutrient solution and greenhouse internal environment, truly liberate productivity, greatly reduce the labor intensity of users, not only make agricultural development more accurate and intelligent, but also make agriculture more integrated and industrialized.
For the boring bar’s chatter, based on the built-in damping boring bar, a type of magnetorheological semi-active dynamic vibration absorbing boring bar component was proposed. And a nonlinear dynamical model of absorbing boring bar was established. An analytical solution for the system's dynamical response is obtained by the multi-scale method, which is verified by the numerical solution, and the changes in the boring bar system parameters on the effect of dynamic characteristic was explored, the results provide the basis for the monitored control of the boring bar’s cutting chatter.
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