Submerged arc furnace intelligent inspection system based on cloud side end cooperation

Through the cloud-edge-end intelligent inspection system for the intelligent inspection of mineral furnaces, the dynamic sparse LSTM model and security constraint PPO reinforcement learning algorithm are used to solve the problem of rigid resource allocation and insufficient multi-source data fusion in the intelligent inspection system of mineral furnaces, and efficient and reliable fault identification and response are achieved, improving the real-time and reliability of the system.

CN120455402APending Publication Date: 2025-08-08HARBIN BOSHI AUTOMATION CO LTD
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Patent Information

Application Number
CN202510788934.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-13
Publication Date
2025-08-08

AI Technical Summary

Technical Problem

There are problems in the intelligent inspection system of mine hot furnaces, such as insufficient utilization rate of cloud edge detection and poor real-time performance due to rigid resource allocation strategies, poor reliability of intelligent inspection systems in harsh environments, and insufficient fusion of multi-source data, resulting in poor fault identification accuracy.

Method used

The intelligent inspection system of mineral hot furnace based on cloud edge and end collaboration is adopted. Through the cross-layer collaborative processing module, a dynamic sparse LSTM model and a security constraint PPO reinforcement learning algorithm is used to realize the intelligent allocation of global resources of end-side devices, edge-side platforms and cloud platforms, dynamically adjust the computing power allocation ratio, and perform data collection, preprocessing and deep learning analysis.

Benefits of technology

The dynamic allocation strategy of resources is realized, load balancing is improved, high-priority task response delay is reduced, system reliability and fault identification accuracy are improved, and the efficient, reliable and adaptive operation of the mine furnace is ensured.

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Abstract

A submerged arc furnace intelligent inspection system based on cloud side-end cooperation belongs to the technical field of submerged arc furnace intelligent robot inspection, and comprises an end side device, an edge side platform, a cloud platform and a cross-layer cooperative processing module, the end side device is in communication connection with the edge side platform, and the edge side platform is in communication connection with the cloud platform; and the cross-layer cooperative processing module is used for intelligently deploying global resources of the end-side equipment, the edge-side platform and the cloud platform, predicting a future load trend by adopting a dynamic sparse LSTM model algorithm, inputting a prediction result into a security constraint PPO reinforcement learning algorithm to adaptively adjust a task and a computing power allocation proportion, and carrying out dynamic resource allocation according to an output result. According to the invention, the cross-layer cooperative processing module interacts and communicates with the cloud side, the edge side and the end side, so that a dynamic allocation strategy of resources is realized, and the problems of low resource utilization rate and poor real-time performance caused by a rigid resource allocation strategy during routing inspection are avoided.
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