Method and system for identifying raw materials running in kiln

Abstract

The invention relates to the field of machine learning of an artificial intelligence technology, in particular to a method and a system for identifying raw materials in a kiln, which are mainly used for improving the identification rate of raw materials in the kiln and identifying risks in advance. The method comprises the following steps that S1, a feature model M of the raw material running in the kiln is determined, a plurality of sets of data corresponding to the feature model in off-line data in the kiln are collected to serve as samples, and the feature model M comprises a plurality of feature parameters and data ranges corresponding to the feature parameters; s2, establishing a multilayer perceptron (MLP) model for the feature model M; s3, training and testing a multilayer perceptron (MLP) model according to the sample to obtain an optimal training model; and S4, detecting data corresponding to the characteristic parameters in the kiln condition in real time, inputting the data into the optimal training model, and determining the raw material running condition according to the output of the optimal training model. The method solves the influence of human subjective factors, reduces the consumption of manpower, and improves the judgment rate.

Description

technical field [0001] The invention relates to the field of machine learning of artificial intelligence technology, in particular to a method and system for identifying running raw meal in a kiln, which is mainly used for improving the identification rate of running raw meal in a kiln and identifying risks in advance, so as to have more sufficient time to take countermeasures measure. Background technique [0002] At present, in the cement production process of the new dry kiln, the raw meal enters the rotary kiln for calcination, and clinker is obtained after calcination. However, in the actual production process, often due to some reasons, the raw meal is not fully calcined. The raw meal is still raw, and the phenomenon of running raw meal in the kiln occurs. This phenomenon will seriously affect the calcination quality of cement products. Therefore, it is very important to always pay attention to the status of the calcination system, and to be able to dynamically observ...

AI Technical Summary

Problems solved by technology

In this patent, various on-line detectors and on-line analyzers are used to conduct online real-time detection of raw material ratio, raw meal grinding, homogenization, calcination, clinker grinding, etc. in the cement production process, thereby realizing the quality control of cement production. Real-time detection, and through integration with DCS system and expert system, it can effectively control the cement production process in real time. On-line real-time detection of clinker mills, etc., the amount of data detected is large, and the post-analysis process of each set of data requires a more complicated calculation process, which takes a long analysis process and slow response speed

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