The On-line Detecting System Of Blast Furnace Burden Surface Temperature Field Based On Multi-source Information Fusion And Its Application

As the foundation of our national economy, steel industry plays an important role in the economic and social development respecting its extensive connection with other industries. Blast furnace (BF), the most critical equipment in steel industry and the major energy-consumer as well as the great producer of environmental pollution, has a great influence on the economic benefits of the steel company and even the whole country.The gas flow distribution in the throat is one of the major influences on BF production situation, which keeps it running stablely and provides a direction for its optimization operation. While the gas flow distribution in BF throat could be truly reflected by BF burden surface temperature field. In view of the deficiency of singular detecting information in reflecting BF burden surface temperature field, this dissertation develops an "on-line detecting system for BF burden surface temperature field based on multi-source information fusion" by employing the technique of information fusion, image processing, artificial intelligence and soft sensor. The industrial application to a 2200mj BF of some steel company shows the efficiency of the system in truly reflecting the distribution status of BF burden surface temperature field and in providing a real-time and accurate guidance for the operation of BF burden distribution and the diagnose of BF status, which ensure BF a smooth running and the company a great benefit as well.The main focuses of study and innovations are included in the following four aspects:1. The detecting plan for burden surface temperature field based on heterogeneous information extraction and multi-source information fusion.Based on the comprehensive investigation on BF production process and the principle of gas flow formation and distribution, this dissertation builds a grey correlation model for relating burden surface temperature field with multi-source detecting information, such as infrared image, cross temperature, ratio of ore to coke (OCR), stock line etc. so as to obtained the parameters of process detection and characteristic quantity which are closely related to the burden surface temperature field. And then, the on-line detecting plan for BF burden surface temperature field is settled with the courses of multi-source information collection in the process of BF production, feature extraction of multi-scale heterogeneous information and multi-source information fusion. This plan can make full use of all the detecting devices and facilities on hand, calculate and extract multi-scale heterogeneous information efficiently and generalize all the reliable feature information reasonably, which offers a new idea for the state detection in BF production.2. The technology of feature extraction for BF burden surface temperature field based on multi-scale heterogeneous information.First, to solve the disagreement of multi-source detecting information in spatial dimension and in temporal dimension, spatial registration method based on spatial geometric relation and temporal registration method based on least square are employed for the purpose of conforming the multi-scale information spatially and temporally. Then, the feature of multi-scale heterogeneous information is extracted, which includes a) the geometrical relation between pixel points and burden surface coming from the optical calibration of infrared camera, the binary feature of images based on genetic algorithm and maximum fuzzy-entropy, furnace heart calibration and gray contour in the image based on the expert rules; b) the temperature distribution of gas flow around cross-thermocouple concerning the method of spatial interpolation; c) the OCR related to the distribution of burden surface temperature field based on the model of BF burden distribution.3. The technology of multi-source information fusion for BF burden surface temperature field based on reliability theory and Kalman filter.On the basis of the feature extraction of multi-source heterogeneous information, firstly, the burden surface temperature is estimated respectively according to all kinds of singular heterogeneous information, including:cross-thermocouple based on thermodynamic principle, the infrared images based on multipoint dynamic calibration, OCR based on fuzzy reasoning and thermocouple in furnace wall based on heat conduction. Secondly, the center part of the temperature field and its edge part are respectively calculated with reliability theory and Kalman filter.4. Online detecting system of BF burden surface temperature field and its application to a typical BF.The software of VC++6.0 and the hardware including infrared photography instrument, image acquisition card, industrial Ethernet communication equipment and industrial control computer are employed to realize the collection of multi-source information, feature extraction, information fusion and to build the online detecting system of BF burden surface temperature field featuring the friendly man-machine interface and interconnection. The application of this system to a 2200m3 BF in some steel company achieves the goal of low-cost and high-precision in the detection of BF burden surface temperature field.