A Recognition Method of Rotary Kiln Sequential Working Conditions Based on Convolution-Recurrent Neural Network

Abstract

The invention provides a rotary kiln sequential working condition recognition method based on a convolution-cyclic neural network, and relates to the technical fields of image classification and pattern recognition. This method first preprocesses the continuous time video sequence information of the rotary kiln firing zone collected under different working conditions; and uses the PCA principal component analysis method to perform preliminary feature extraction and dimensionality reduction for the region of interest; and then designs the CNN-RNN volume Convolutional cyclic neural network to further extract image features and dynamic information between image sequences; use random search hyperparameter optimization method to select the optimal hyperparameters of convolution-cyclic neural network, so as to obtain the optimal CNN-RNN neural network classifier model , to realize the working condition recognition of the rotary kiln image sequence. The rotary kiln sequence operating condition recognition method based on the convolution-cyclic neural network provided by the present invention can not only use image space features but also use the correlation information and dynamic features between image sequences, and can solve the problem of rotary kiln image sequence operating condition identification. achieve better classification results.

Description

technical field [0001] The invention relates to the technical field of image classification and pattern recognition, in particular to a method for recognizing sequential operating conditions of a rotary kiln based on a convolutional-cyclic neural network. Background technique [0002] The rotary kiln is up to 100 meters long and is in continuous rotation. The particularity of its structure and the complexity of the process make the sintering process of the rotary kiln complex, including the physical and chemical reactions of materials, fuel combustion, heat transfer between gases, materials, and linings. Multiple coupled processes such as gas and material movement. Due to the difficulties in the sintering process of the rotary kiln, such as the difficulty of online measurement of the clinker quality index and the difficulty of accurately identifying the firing state of key process parameters closely related to the quality of the clinker, the existing sintering process of the...

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Problems solved by technology

However, the research object of this method is only the flame grayscale image, and the multi-channel encoding problem of the image is not considered, nor is the timing relationship of the clinker sintering condition of the rotary kiln considered.

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