Fault diagnosis method of hydrometallurgical thickener based on reliability

Abstract

The invention provides a fault diagnosis method of a hydrometallurgy thickener based on credibility. The method includes obtaining on-line variables of a hydrometallurgy thickener; determining fuzzy dimensionality of each variable according to on-line variables, wherein the fuzzy dimensionality is dimensionality corresponding to fuzzy concepts included in rule antecedents in a pre-established expert rule base; aiming at each variable and the fuzzy dimensionality of the variable, adopting a fuzzy membership degree function to obtain the credibility of the fuzzy dimensionality to which the variable belongs; based on an uncertainty reasoning model based on credibility and rules in the expert rule base, performing rational analysis on the credibility of each variable, and obtaining fault conclusion credibility; and comparing the fault conclusion credibility with a preset threshold value, and obtaining a fault result. The abovementioned method can obtain rules corresponding to diagnosis experience of experts or operating personnel in advance, and perform fault diagnosis on current on-line variables, so as to perform timely adjustment according to a fault diagnosis result, thereby effectively reducing an 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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