| As an important strategic energy resource,coal plays a vital role in the economic and social development of China and the world,with rich reserves and wide application prospects.As an important part of coal industry production,coal processing plant is mainly engaged in screening and coal selection of coal.Many large equipment in the production process requires long-term high load operation,some important components of the equipment such as plates,pipes,columns,etc.due to their own existence or long-term load work factors will appear grooves,through holes and other defects,resulting in shortening the life of the components affect the overall performance of the equipment and may lead to safety accidents,so in the production process is particularly important to damage detection of equipment components.Ultrasonic nondestructive testing,as an advanced detection method that does not damage or affect the internal organization of objects or materials,is now widely used in industrial equipment damage detection.In the actual industrial inspection traditional ultrasonic NDT is mostly restricted,with low detection efficiency and defect detection rate,and the detection of defect information is not clear and intuitive,and is easily affected by interference factors.In order to improve the inspection efficiency of ultrasonic NDT and solve the problem of industrial inspection difficulties and interference,this project investigates the use of conventional pulse echo,ultrasonic phased array and ultrasonic TOFD inspection techniques for detecting defects in different types of equipment components according to their respective characteristics,and uses different defect reconstruction methods to complete the inversion of defects in2 D and 3D in components.Finally,we wrote the program in MATLAB platform and realized the 3D visualization of the defect inversion of coal processing plant equipment components through data processing.In this paper,we study the ultrasonic nondestructive testing techniques for the inversion of defects in different components of coal processing plant devices,adopt the methods that meet the actual workpiece testing conditions,and analyze and process the defect characteristic information obtained from the testing to finally complete the three-dimensional reconstructed inversion of defects in the components of coal processing plant devices.The research results show that the reconstruction method of eccentric through-hole defects in columnar components based on Born approximate approximation regime method,after defect amplitude correction,has significantly improved the reconstruction effect of 2D and 3D defects compared with Born approximate method;the ultrasonic phased array C-scan image body drawing method and the conventional pulse echo method of linear interpolation of detection data can be used to reconstruct notch defects in plate components,and the reconstruction The results match with the defect morphology and the data error is close,and the reconstruction results based on the C-scan image body drawing method are richer and more complete in pixels and information;the reconstruction method based on the B-scan image body drawing method can be used for the three-dimensional reconstruction of transverse hole defects in plate members,and the ultrasonic phased array method and the ultrasonic TOFD method can identify the depth location of defects exactly,and the cross-sectional images obtained by the ultrasonic TOFD method are reconstructed by the least squares method.The cross-sectional images obtained by the ultrasonic TOFD method can be reconstructed by the least squares method to obtain an accurate and intuitive 3D model of the cross-hole defects.The research method in this paper inverts defect reconstruction for different kinds of components,and the 2D and 3D reconstructed image features of the defects obtained are in accordance with the defect inversion information,which realizes the3 D reconstruction of the inversion defects of the components of the coal processing plant,and is of great significance for the use maintenance and safety warning of the coal processing plant.Figure [52] Table [10] Reference [89]... |