Research And Implementation Of Screw Thread Feature And Geometric Defect Detection Based On Ordered Point Cloud

As a clean and low-carbon new energy,nuclear energy is playing a more and more important role in modern social life.However,there are radioactive substances inside the nuclear power plant.To ensure normal and safe operation,the nuclear power plant needs to carry out regular maintenance.The pressure vessel in the nuclear reactor is the core equipment in the nuclear power plant,which is composed of the vessel,the top cover,and the fastening seal.The pressure vessel adopts a number of flange threads to connect the vessel to the top cover and is sealed by a metal seal ring.The connection quality of the screw thread directly affects the safety of the reactor.In this paper,the main bolt hole of the nuclear power plant pressure vessel is taken as the detection target.A series of data processing works,such as data calibration,extraction of screw thread’s characteristic parameters,extraction of screw thread defects and their parameters,and visualization of testing data,is completed for the measurement data of the screw thread hole scanning measurement system as one of the independent detection software.The main work includes:1.Measurement data calibrated.For the detection system,a mathematical model is established,and the unknown parameters of its transformation matrix are given.To solve the unknown parameters,a method combining simulated annealing particle swarm and iterative nearest point combination algorithm was adopted,and the measurement data of cylinder samples were used as the standard for the calibration solution.2.The characteristic parameters of the screw thread extracted.According to the definition of screw thread’s characteristic parameters and defects,mathematical methods are adopted to process the collected point cloud data,including central axis correction based on linear least square method,cross-section acquisition based on projection,crosssection data denoising based on Fourier transform low-pass filtering.On this basis,the extraction algorithm of six main screw thread parameters is realized: small diameter,middle diameter,large diameter,pitch,half Angle of tooth profile,and coaxiality.3.Screw thread defects and their parameters extracted.The average fitting method is used to obtain the ideal screw thread shape based on the data of the collection point cloud.Then the point in the collection point cloud that has a certain difference from the ideal curve of the screw thread is signed as the point cloud group of screw thread defect.Then the Euclidean clustering algorithm is used to extract the defect.Finally,the dimensional parameters of the defect are measured,including the non-axial defect length,axial defect length,and radial defect length.4.Screw thread surface visualized.The collection point cloud homogenized and interpolated.Then,a fast triangular surface was generated for the interpolated point cloud to obtain the screw thread surface.Finally,combining with the deviation value obtained during defect extraction,the colored screw thread surface was obtained by assigning the gradient color of the surface.5.Pressure vessel main bolt hole inspection data processing system realized and applied.The construction of the development environment and software framework,software interface design is completed.The main function modules,such as data calibration,extraction of screw thread characteristic parameters,extraction of screw thread defect,and its characteristic parameters,are tested.The application experiments are designed for the main functions,and the experimental data is analyzed to verify the effectiveness of the system.