Research On Focal Plane Blind Cluster Problem Under The Background Of Infrared Diagnosis Of Power Equipment

Infrared detection technology is widely used in condition monitoring and fault location of power equipment such as generators,transformers,and overhead lines because of its advantages of non-contact,high safety,and power detection.The infrared image is an important basis for judging the operating state of the device in the detection system,and the imaging quality has a direct impact on the accuracy of the detection.Due to factors such as manufacturing process and materials,the infrared focal plane array(IRFPA)of the infrared imaging system inevitably has problems such as blind elements and non-uniformity,which seriously affects the imaging quality and causes false detection and missed judgment of the detection system.In order to improve the imaging quality,it is necessary to study fast and effective blind element detection and compensation algorithms..In recent years,under the continuous research efforts of researchers,the blind element detection and compensation algorithms have been continuously improved,and the imaging quality of infrared images has been improved to some extent.However,with the development of integration technology,the specifications of infrared focal plane arrays are constantly expanding,and new problems are constantly emerging.For example,the occurrence of blind clusters,that is,the blind elements appear larger than the blind point,the size of the blind element,and the sheet is too bright or too dark on the image,which has a much greater impact on the quality of the infrared image than the general blind element form.Based on the MATLAB image processing module,this paper designs and implements a set of blind element cluster detection and compensation algorithm for the traditional blind element processing algorithm.Feasibility and effectiveness.It has certain reference value for improving the imaging quality of infrared systems,especially the images of blind clusters.The main research work of this paper is as follows:(1)Introduced the background of the research,introduced the principle of infrared imaging in detail,and introduced the basic structure of the infrared imaging system.Review a large number of literatures and related standards,analyze the characteristics of blind elements and detail the mechanism of blind element generation,the classification of blind elements,and the expression of blind elements in infrared images.(2)Analysis of the causes of blind cluster generation,research on several commonly used blind element detection and compensation methods,and found that the commonmethods lack the adaptability to blind clusters.In order to solve the problem of blind clusters in images,this paper proposes a blind element detection algorithm based on improved gray histogram and a blind element cluster compensation algorithm based on temperature gradient.The principle and process of the algorithm are introduced in detail.(3)The above processing algorithm is simulated by MATLAB,and the feasibility and effectiveness of the algorithm are verified.For the detection accuracy,after consulting a large amount of literature,it is proposed that in addition to the blind element rate as the evaluation standard,the blind element distribution,the number of blind element types,etc.should also be used as evaluation criteria,and the detection algorithm and tradition of this paper are based on this standard.The detection algorithm was compared.For the compensation effect,the peak signal-to-noise ratio and structural similarity are introduced as the evaluation criteria,and the compensation algorithm and the traditional compensation algorithm are compared.The experimental results show that the detection and compensation algorithm is feasible and effective,and it has good adaptability to blind clusters.