Research On The Visual Inspection Method For Vibration And Stoma Of The Machined Surface Of Motorcycle Wheel Hub

With the substantial improvement of the level of intelligent science and technology,intelligent manufacturing industry is experiencing rapid development.Quality inspection is an important part of the development of manufacturing industry.The defects on the surface of motorcycle wheels are the main reason for wheel scrapping.If the quality of motorcycle wheels is not up to standard,it is easy to cause traffic accidents.If it is serious,it will also endanger the personal safety of drivers.Therefore,it is necessary to carry out quality inspection on motorcycle wheels.The processing procedure of motorcycle wheels is cumbersome.If it is not processed properly,the wheels will produce defects such as shock and air holes.Nowadays,the main method for motorcycle wheel manufacturers to detect wheel surface defects is manual inspection,which not only consumes energy,but also is difficult to guarantee the inspection efficiency and quality.In view of the above objective problems,this paper studies the algorithm of vibration and air hole defects on the machining surface of motorcycle wheel rim,completes the image acquisition by designing an imaging system,and gives the test results and analysis of the algorithm.(1)For the seismogenic defects,it is found that the traditional Gaussian line detection algorithm cannot completely extract the seismogenic lines.Therefore,this paper proposes a seismogenic defect detection algorithm based on relative amplitude,which can completely extract the seismogenic lines.Measure the spacing of the seismogenic lines,compare with the normal grain spacing,and complete the judgment of the seismogenic defects.Test results show that the proposed method is obviously superior to Gaussian line detection method in extracting the continuity of vibration lines.(2)For stomatal defects,it is found that the traditional global threshold and local dynamic threshold methods are not accurate for the extraction of stomatal defects.Therefore,this paper proposes a stomatal defect detection algorithm based on relative amplitude histogram,which can achieve accurate extraction of stomatal defects and has certain adaptive ability.The minimum circumscribed rectangle method is used to extract the characteristics of stomatal defects.Test results show that the proposed method is superior to global threshold and local dynamic threshold methods.(3)The imaging system of the wheel is designed in this paper,according to the different positions of the wheel,the wheel machining surface is divided into five parts: outer edge surface,outer edge end surface,central end surface,drum bottom and brake ring,and the imaging scheme is designed according to the structural characteristics of each part.By debugging the parameters of cameras,light sources and other equipment,the best shot picture is obtained.The highlight of this paper is that the seismogenic defect detection algorithm based on relative amplitude and the porosity defect detection algorithm based on relative amplitude histogram do not filter the image,retain the details of the image,and ensure the integrity of the detection results.Experiments show that the seismic and pore defect detection methods adopted in this paper can accurately detect defects and have certain practical value.