Artificial intelligence technology has been widely used in many fields and has attracted the attention of more and more people in the industrial field. At this stage, in order to further improve the steel metallurgical effect and metallurgical quality, the steel and metallurgical industry has strengthened the research on artificial intelligence technology, integrated it into the steel and metallurgical industry, realized the automation and intelligence of steel and metallurgical production, and accelerated the steel and metallurgical production. efficiency, reducing the labour intensity of workers, improving the economic benefits of industrial enterprises, and providing broad space for the further development of the steel industry.
1. Application of metallurgical intelligent robots
In the context of the optimization and innovation of artificial intelligence technology, through in-depth research on artificial intelligence robots, the goal of intelligent robots has been achieved, and robots have been applied to the industrial field, bringing new development opportunities to the further development of the industrial field. At this stage, industrial intelligent robots have been effectively used in the steel and metallurgical industry, and have replaced manual labour in high-risk environments such as high temperatures and toxic environments.
However, the use of robots in the steel and metallurgical industry is still not widespread, mainly because although intelligent robots can replace manual labour in completing many dangerous tasks in actual work, the cost is relatively high. In addition to the use of intelligent robots in steel forging, material handling and other tasks, the rest of the management work and production control of the steel rolling heating furnace are all done manually. However, the realization of intelligent robots still brings new opportunities to the steel and metallurgical industry. It is believed that intelligent robots will be widely used in the steel and metallurgical industry in the future, laying a good foundation for the further development of the steel and metallurgical industry.
2. Application of expert control and network neural control
Expert control is an important part of the artificial intelligence system. It is an intelligent control technology based on expert system theory and combined with control theory. In the iron and steel metallurgical industry, through the effective use of expert systems, the temperature of the steel rolling heating furnace can be comprehensively controlled, and a three-network neural network can be constructed to calculate the heating state of the steel billet, the gas composition of the steel rolling heating furnace and the heat balance in the furnace, and finally obtain The calculated value index and furnace heat loss vector data information can be obtained to ensure the quality of steel metallurgical production. It can also effectively improve the control effect of steel metallurgical production and improve the operation safety and efficiency of the steel rolling heating furnace.
Network neural control is a form of control achieved by simulating the activity of human brain neurons. In the steel and metallurgical industry, through the effective use of network neural control systems, the entire process of steel production can be controlled to ensure the quality and effect of steel production.
3. Application of self-organizing neural network
During the development of iron and steel metallurgical production, testing and production control work are fully implemented to ensure that the quality of iron and steel metallurgical forging production is effectively improved. In order to obtain data information about the entire steel and metallurgical production process, the steel and metallurgical industry has begun to use artificial intelligence self-organizing neural networks.
Self-organizing neural networks can automatically complete classification automatically retrieve data features and detect and collect various data information in the production process. To this end, we should take advantage of the self-organizing neural network and integrate it into the iron and steel metallurgical production detection system to ensure that the temperature of the molten iron, the temperature of the molten steel and the temperature of the slag can be detected in real-time during the smelting process of iron and steel metallurgy. At the same time, the purity of the molten steel or the molten iron can be measured. Comprehensive testing lays a good foundation for improving the quality of steel production.
In addition, in the application of a self-organizing neural network, the operating temperature of the steel rolling heating furnace and the exhaust gas and smoke generated by the operation can be comprehensively detected. In order to improve the closed-loop effect of automated control, relevant personnel need to control metallurgical automation technology in actual development, maximize the advantages of self-organizing neural networks, and improve the detection effect of key variables in the smelting process.
In addition, in the application process of self-organizing neural network, production technicians in the steel and metallurgical industry can conduct comparative analysis of the detected data information, thereby achieving quantitative analysis of steel metallurgy, and quantification of data information during the entire operation of the rolling heating furnace. , understand the existing problems and take corresponding measures in a timely manner to lay a good foundation for ensuring the quality of steel production.
4. Application of artificial intelligence fault diagnosis technology
Artificial intelligence fault diagnosis technology involves relatively many intelligence and automation technologies, including control systems, neural networks and fuzzy theory. In the steel and metallurgical industry, through the effective use of artificial intelligence fault diagnosis technology, electrical faults can be comprehensively inspected at every step of production.
Due to the relatively harsh steel and metallurgical production environment, many production equipment are easily affected by external factors, causing various dangerous accidents. It will also have a serious impact on the quality of steel and metallurgical production and cause economic losses to steel and metallurgical industry enterprises. In the traditional steel and metallurgical production process, the fault diagnosis methods used are too cumbersome, and the diagnosis accuracy is relatively low. It requires a lot of time and energy, and it is difficult to meet the requirements of modern steel and metallurgical production.
In order to effectively transform the traditional steel and metallurgical production diagnosis methods and diagnostic models, through the effective use of artificial intelligence fault diagnosis technology, the steel production process and production temperature can be controlled through neural networks, and the expert system can also control the overall production process and detect in time The faulty equipment existing in the steel and metallurgical production can be eliminated. The overall detection accuracy and detection efficiency are relatively high, which improves the efficiency and quality of steel production and creates more economic benefits for the steel and metallurgical industry. It also provides further development in the field of steel and metallurgical industry. The development brings opportunities.
To sum up, the steel and metallurgical industry should further strengthen the effective use of artificial intelligence technology, strengthen the control of every steel and metallurgical link, actively improve and optimize the steel and metallurgical production technology, realize the intelligence and automation of steel and metallurgical production, and further meet the needs of the steel and metallurgical industry. production needs in the steel and metallurgical industry, ensuring that the quality of steel and metallurgical production is comprehensively improved, and providing help for the steel and metallurgical industry to achieve sustainable development goals.
Source of article: Cheng Cheng. Application of artificial intelligence in the steel and metallurgical industry. Standardization of engineering construction