A fault diagnosis method for hydrometallurgical leaching process based on dcd

Abstract

The invention belongs to the technical field of fault diagnosis of the hydrometallurgical leaching process, and in particular relates to a DCD-based fault diagnosis method of the hydrometallurgical leaching process. The fault diagnosis method of the leaching process based on DCD is mainly oriented to the leaching process of hydrometallurgy. It establishes a dynamic cause-and-effect graph knowledge base by extracting expert knowledge and information in process data as prior information, and enters the inference diagnosis mechanism after observing abnormal conditions. , use the abnormal situation as evidence to calculate the posterior probability of each possible failure cause, and compare the posterior probability to obtain the diagnosis result. This algorithm mainly includes the steps of DCD event determination, DCD structure learning, DCD parameter learning and DCD online process fault diagnosis in the leaching process. The present invention uses DCD fault diagnosis technology to deal with the uncertainty of information in the leaching process, which reduces the dependence of the diagnostic technology on a large amount of data to a certain extent, can bring more accurate diagnosis results, and ensure the economic and production benefits of the enterprise.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of hydrometallurgical leaching process, and in particular relates to a method for fault diagnosis of hydrometallurgical leaching process based on DCD. Background technique [0002] With the gradual reduction of high-grade ore, the hydrometallurgical industry has begun to be highly valued by countries all over the world. Compared with traditional pyrometallurgy, hydrometallurgy technology has the advantages of high efficiency, cleanliness, and is suitable for the recovery of low-grade complex metal mineral resources. Especially in view of the low grade, complex symbiosis, and high impurity content of gold mines in my country, the industrialization of hydrometallurgical processes is of great significance for improving the comprehensive utilization rate of gold mines, reducing solid waste production, and reducing environmental pollution. Facing such a complex industrial process as hydrometal...

AI Technical Summary

Problems solved by technology

However, the hydrometallurgical process is relatively complex, with many process parameters and many variables that are difficult to measure directly. In this context, it is difficult to use data-based methods for fault diagnosis.

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