Glass fiber manufacturing industrial equipment fault sequence determination method and system

Abstract

The invention discloses a glass fiber manufacturing industrial equipment fault sequence determination method and system. The method comprises the steps that fault information of glass fiber manufacturing industrial equipment is acquired; the concept of an intelligent set in a language is introduced, relevant language variables are utilized to describe decision expert assessment information, and the complicated equipment fault information is expressed through corresponding fuzzy numbers; and expert weights and criterion weights are calculated, decision information is expressed in the form of "triangular interval fuzzy numbers", a compromise solution is obtained through binary relationship numbers in combination with a VIKOR method, and an optimal alternative scheme in case of an industrialequipment fault is selected under the action of multiple criteria. The method is applied to industrial equipment fault diagnosis for expressing the fault information, which is difficult to describe, by the adoption of the fuzzy numbers, a clear mathematical model is established, a sequencing mode is adopted to select the optimal alternative scheme, and the problem which cannot be solved through atraditional fault diagnosis method is solved.

Description

technical field [0001] The invention belongs to the field of industrial equipment, in particular to a method and system for determining the fault sequence of industrial equipment in the glass fiber manufacturing industry. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] The industrial equipment in the glass fiber manufacturing industry is constantly developing towards intelligence and large-scale. With the increasingly complex and diverse equipment faults, how to quickly and accurately diagnose faults has become a difficult problem; traditional equipment fault diagnosis methods cannot be effectively diagnosed due to limitations. , and complex fault information is difficult to express with numerical values. [0004] Multi-criteria group decision-making refers to inviting multiple decision-making experts to evaluate the optimal plan among m...

AI Technical Summary

Problems solved by technology

However, this method is mainly for fault diagnosis of some relatively simple systems, and it cannot be applied to more complex systems.

Traditional diagnostic methods are no longer suitable for modern intelligent and large-scale equipment. There are many multi-criteria group decision-making methods, and accurate mathematical models can be established to solve the shortcomings and difficulties of traditional fault diagnosis methods. Therefore, this paper proposes the industrial equipment fault diagnosis Combining with multi-criteria group decision-making is a very novel topic

Images