Rotary Kiln Firing State Recognition Method Based on Flame Image Structural Similarity

Abstract

The invention relates to a rotary kiln firing state recognition method based on flame picture structure similarity. According to the technical scheme, the method includes the steps that a standard flame gray level image y, a normal flame gray level image storage FN and an abnormal flame gray level image storage FA are set; a to-be-monitored flame image P is obtained, and filtering and grey level transformation are carried out on the to-be-monitored flame image P to obtain a to-be-monitored flame gray level image x; average structural similarity coefficient calculation is carried out on the to-be-monitored flame gray level image x and all standard flame gray level images to obtain a+b MSSIM coefficients (x,y); the maximum value MAXssim of the MSSIM coefficients is selected, if the standard flame gray level image y corresponding to the maximum value MAXssim of the MSSIM coefficients belongs to the normal flame gray level image storage FN, the to-be-detected flame image P belongs to a normal state, and otherwise to-be-monitored flame image P belongs to an abnormal state. The method has the advantages of being high in precision, low in computation complexity, short in processing procedure and capable of achieving online real-time monitoring of flame state changes.

Description

technical field [0001] The invention belongs to the technical field of rotary kiln firing state recognition. In particular, it relates to a method for identifying the firing state of a rotary kiln based on the structural similarity of flame images. Background technique [0002] Rotary kiln is a thermal equipment used in calcination or roasting and other processing of various industrial raw materials. It is used for mechanical, physical or chemical treatment of input materials. It is widely used in building materials, chemical industry, metallurgy and other industries. Affected by the particularity of the structure of the rotary kiln and the complexity of the process, it is difficult to measure the quality indicators of the clinker obtained online, and it is also difficult to accurately identify the firing state of the clinker. In addition, the multi-variable strong coupling characteristics of the rotary kiln process and uncertain interference, etc. factors, the operation pr...

AI Technical Summary

Problems solved by technology

So far, many scholars have done a lot of in-depth research on each module of digital image processing. Although the recognition method of using digital image processing technology to judge the burning state of flame images has the advantages of high recognition accuracy, diverse and mature algorithms, but This kind of method inevitably has the defects of high computational complexity, long processing time, and the inability to monitor in real time online. It has not fundamentally changed the mode of "manual fire inspection", and affects the safety and reliability of the rotary kiln control system. Cause a series of problems such as unstable clinker quality index, low production capacity and high cost

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