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Research On NC Scanning System Of Immersion Ultrasonic Testing And Flaw Classification

Posted on:2010-08-28Degree:MasterType:Thesis
Country:ChinaCandidate:H T ZhangFull Text:PDF
GTID:2132360278981282Subject:Mechanical Manufacturing and Automation
Abstract/Summary:PDF Full Text Request
As an effective mean to achieve intelligent ultrasonic testing ,automatic immersion ultrasonic testing technology is of great significance to improve the efficiency and quality of ultrasonic testing. The development of high-speed, high precision CN scanning system can improve ultrasonic testing automatic level. The flaw classification in ultrasonic testing technology is a difficult issue. To design and machine the specimen with artificial flaws, and then to collect and process data are of important significance for picking up eigenvalues and achieving flaw classification.According to the requirements of immersion ultrasonic testing scanning system for scanning NC unit and the characteristics of immersion ultrasonic testing, a scanning NC unit with framework is designed. The fast scan axis uses AC servo motor driving ball screw, and step axis and the probe positioning axis use step motors driving ball screw. The system probe scanning speed is 300mm / s and accuracy is 0.02mm / p. In order to ensure system dependability and optimize structure, the types and parameters of the main components have been selected. The model of scanning NC unit is built by the PRO / E software, then the model is led into ADAMS to do the simulation of the motion and the analysis of kinematic and dynamics.In flaw classification, the artificial flaw specimens with pores, inclusions and cracks are designed and machined. The ultrasonic flaw signal acquisition system is set up by the CTS-4020 digital ultrasonic flaw detector, US4020 computer communication and data processing software, data storage software based on VC6.0, IPC800A Tiangong industrial computer and ultrasonic probes. The signal of artificial flaw specimens is collected by ultrasonic signal acquisition system, and flaws are classified by neural network method based on wavelet decomposition, and the method is of high accurate rate. A good foundation is laid for ultrasonic flaw classification.
Keywords/Search Tags:Ultrasonic Testing, Immersion Scan, Simulation Analysis, Specimen, Flaw Classification
PDF Full Text Request
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