Fault diagnosis method of hydrometallurgical thickener based on reliability

Abstract

The invention provides a credibility-based fault diagnosis method for a hydrometallurgical thickener, which includes: obtaining online variables of the hydrometallurgical thickener; determining the fuzzy dimensions of each variable based on the online variables; the fuzzy dimensions are pre-established The dimension corresponding to the fuzzy concept included in the rule antecedent in the expert rule base; for each variable and the fuzzy dimension of the variable, the fuzzy membership function is used to obtain the credibility of the fuzzy dimension to which the variable belongs; uncertainty based on credibility The sexual reasoning model combines the rules in the expert rule base to conduct inference analysis on the credibility of each variable to obtain the credibility of the fault conclusion; compare the credibility of the fault conclusion with the preset threshold to obtain the fault result. The above method can obtain the rules corresponding to the diagnosis experience of experts or operators in advance, and perform fault diagnosis on the current online variables so that timely adjustments can be made based on the fault diagnosis results, thereby effectively reducing the accident rate and improving production safety.

Description

technical field [0001] The invention belongs to hydrometallurgy technology, in particular to a reliability-based fault diagnosis method for hydrometallurgical thickeners. Background technique [0002] With the development of our country's industrialization process, the problem of resources has become one of the main problems restricting our country's development. As the main source of industrial raw materials, mineral resources play a fundamental role in economic and social development. Due to the extensive utilization and massive consumption of mineral resources, my country is facing a serious shortage of mineral resources. The reserves of high-grade mineral resources are decreasing day by day, and the situation is very grim. my country is rich in reserves of low-grade mineral resources. Extracting mineral resources from poor, fine and miscellaneous ores has become an inevitable trend in future development. How to use low-grade mineral resources economically and efficientl...

AI Technical Summary

Problems solved by technology

The dense washing process is complicated in technology, harsh in the production environment, and has the characteristics of large inertia, large time lag, and many influencing factors. In addition to the influence of human subjective factors, it is difficult to achieve accurate fault diagnosis

In the actual process, many variables change in real time and have great randomness and frequent changes, which makes it more difficult to realize the fault diagnosis of the dense washing process

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