Moving sieve fault diagnosis method based on Weibull analysis model

Abstract

The invention discloses a moving sieve fault diagnosis method based on a Weibull analysis model. The method is characterized by collecting impact force of coal falling off from a moving sieve plate on a buffer board through an impact force sensor, and calculating proportion range of the coal falling off from the moving sieve plate in the total amount of a sample when the moving sieve plate is normal, that is, coal size distribution range; and analyzing the coal falling process in the time period t, and according to the total impact force P collected by the impact force sensor, calculating the proportion of the total quantity of the coal falling off from the moving sieve plate within the time period t in the total quantity of the sample, and making a comparison between the proportion and the proportion range obtained when the moving sieve plate is normal to measure the total quantity of the falling-off coal and realize moving sieve fault diagnosis. The method can realize moving sieve fault diagnosis only through the impact force of the coal on the buffer board, can roughly measure damage degree of the moving sieve plate, is simple to realize and high in precision, does not depend on application scenarios and improves economic benefit and intelligent supervision level of a coal preparation plant.

Description

technical field [0001] The invention relates to the field of dynamic screen fault diagnosis methods, in particular to a dynamic screen fault diagnosis method based on a Weibull analysis model. Background technique [0002] Dynamic sieve is an important equipment for separating coal particle size in coal preparation plant. Since coal preparation is a continuous flow operation process, the coupling between equipment is relatively large, and the equipment has strict requirements on the input parameters. Once a problem occurs, it will cause damage to subsequent machines in the production process, and even lead to shutdown in severe cases. Therefore, the problem of dynamic screen fault monitoring has become one of the important topics. The rapid and accurate fault diagnosis of dynamic screen is related to the efficiency and safety of coal preparation, and simplification, timeliness, and accuracy are the most important factors for the quality of dynamic screen diagnosis methods. ...

AI Technical Summary

Problems solved by technology

[0011] The technical problem to be solved by the present invention is to provide a dynamic sieve fault diagnosis method based on the Weibull analysis model to solve the shortcomings of various methods in the monitoring of the dynamic sieve and the long processing period in the actual coal preparation production, which is greatly affected by the environment and complicated high degree problem

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