Study On Boiler Combustion State Detection Method Based On Computer Vision

As the modem thermal energy generating set develops toward to large capacity and high parameter,the enquipment is getting more and more complex,and it requires higher controlling quality of production process.The detection technique based on computer vision for boiler combustion status is very meaningful to monitor and diagnosis the combustion status of power plant pulverized-coal boiler for security,economic and environmental protection.Flame images are the most direct reflection of the boiler furnace's burning states and playing a more and more important role in combustion monitoring.Using the CCD camera and the application of computer vision technology,the visual combustion monitoring is studied to the complete and reliable detection information of the boiler combustion state.The main purpose of this paper is the boiler combustion state detection method based on computer vision,to achieve the the boiler combustion visualization and combustion state intelligent detection,the main results and conclusions of paper are listed as follows:(1)Burning image pretreatment and its feature extraction are achieved using image preprocessing algorithm;(2)The boiler combustion state is analyzed using the characteristic parameters of burning image;(3)The detection method of boiler combustion state is established on the basis of computer vision.Analysis composition of combustion state detection system of pulverized-coal boiler and pimage acquisition;researches image processing technology for image noise removal and image segmentation and compares the results of image processing methods by experiment test.The results show that Canny algorithm is a multi-stage optimization operator with filtering,enhancement and detection,Strong antinoise ability,and eventually get the accurate edges of the targe.Compared with the other edge detection operator,Canny is more suitable for boiler furnace flame edge extraction,and obtain the satisfactory image segmentation,which will lay a good foundation for subsequent feature extraction of flame image.On the basis of image processing technology,for the flame has features of changing fastly and flashing continuously,the experimental results of the flame motion region extracted from the background estimation method and the three difference method are analyzed.Result shows that three difference method can separate the flame region more accurately and adequately.So it's more suitable for flame region segmentation;And it can be found that the Ohta color space is most suitable for dividing flame color.For different scenarios with different flame color range and the hole problem in motion area exacted from three difference method,Otsu algorithm is applied to select the flame color segmentation threshold automatically in Ohta color space.And the region growing algorithm is used to make up the hole problem.So the area with flame color can be segmented accurately.Finally,combined with the motion area exacted from three difference method,the motion area only with flame color is obtained.This method proposed can eliminate the stationary object with flame color and reduce the target region effectively.Based on analyzing pulverized-coal boiler combustion process,the boiler's combustion stste and usual characteristic parameters reflected the combustion stste and calculation methods are defined.Extracted characteristic parameters of flame image from the multiple flame images,the simulation results show that the relationship between the flame image characteristic parameters and combustion state.The comprehensive features of flame(such as the Wavelet energy,stroboscopic,contour and the number of connected regions features)are combined to further determine whether there is fire or not.And according to the ability of each feature to identify flame,a weight is set to each feature.And whether there is a flame or not in suspicious areas can be determined.Contrary to the fire detection method based on flame features proposed in this paper,some simulation experiments have been done.The experimental results show that the fire detection method can be applied to complex background environment with a good anti-interference ability and high recognition accuracy.