DCD-based hydrometallurgical leaching process fault diagnosis method

Abstract

The invention belongs to the technical field of fault diagnosis of hydrometallurgical leaching processes, and in particular relates to a DCD-based hydrometallurgical leaching process fault diagnosis method. The DCD-based leaching process fault diagnosis method is mainly used for a hydrometallurgical leaching process and is characterized by extracting information in expert knowledge and process data as the prior information to establish a dynamic causality diagram knowledge base; activating an inference diagnosis mechanism after an abnormal situation is observed; calculating the posterior probability of each possible fault cause by using the abnormal situation as an evidence; and obtaining a diagnostic result by comparing the posterior probabilities. The algorithm mainly includes the stepsof leaching process DCD event determination, DCD structure learning, DCD parameter learning and DCD online process fault diagnosis. The method processes the uncertainty of information in the leachingprocess by using the DCD fault diagnosis technology, reduces the dependence of the diagnostic technology on a large amount of data to a certain extent, can bring more accurate diagnosis results, and ensures the economic benefit and the production benefit of enterprises.

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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