Intelligent monitoring system for AIPFIMS plasma furnace

By configuring an intelligent monitoring system with sensors and data processing modules, the problem of traditional plasma furnaces being unable to monitor in real time has been solved, enabling real-time control and optimization of parameters within the plasma furnace, thereby improving production safety and efficiency.

CN121994038APending Publication Date: 2026-05-08郑州勒普特生态科技有限公司
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Patent Information

Application Number
CN202411560960.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-04
Publication Date
2026-05-08

AI Technical Summary

Technical Problem

Traditional plasma furnaces lack intelligent monitoring systems, making it impossible to monitor key parameters such as furnace temperature, pressure, and gas content in real time, leading to safety hazards and low production efficiency.

Method used

It is equipped with temperature, pressure and gas sensors, and transmits data to the data processing module through a high-speed data transmission interface for real-time analysis and report generation. It can also be remotely monitored and controlled via the Internet or local area network, with automatic early warning and alarm, and timely adjustment of plasma power and gas intake to optimize the process.

Benefits of technology

It enables real-time monitoring and control of parameters within the plasma furnace, improving production safety and efficiency, ensuring that operators can respond to abnormal situations in a timely manner, and enhancing product quality.

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Abstract

The invention discloses an intelligent monitoring system for an AIPFIMS plasma furnace. The intelligent monitoring system comprises the following steps: step 1, configuring a corresponding sensor; step 2, data analysis and processing; step 3, remote monitoring and control; 4, intelligent early warning and alarming are carried out; and 5, automatically adjusting and optimizing. In addition, trend analysis and prediction can be carried out according to historical data and real-time data through the data processing module, and the performance change and possible faults of the plasma furnace can be predicted in advance.
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