Papers by Keyword: Infrared Nondestructive Testing

Abstract: Working in the corrosive environment for a long time, it is easy for metal pipes to produce stress corrosion cracks which will affect the use. An infrared detection method combining permeate treatment with heat-incentive steam is proposed to detect surface cracks, which then has been verified by simulations and experiments. For the simulation, pipe model including four cracks of different depth and width was constructed by ANSYS. Transient thermal analysis was made after convection incentive loaded on internal and external wall in the case of whether or not undergo surface infiltration processing. For the experiment, pipe including cracks were made the same as simulation parameters, then experiments were made using the thermal excitation system in two cases. Surface temperature distributions of the pipe were compared in two cases, the results of the study show that penetration treatment before heat incentive can significantly improve the surface crack detection sensitivity.

Abstract: The automatic identification of thermography defects is one of important targets of infrared nondestructive testing technology. The analysis of thermal images based on the principle of Hough transform not only can reduce the workload of identification through human beings' eyes, but also can improve the accuracy of defect identification and improve the work efficiency. The paper introduces the basic principle of Hough transform, realizes the testing for the linear defects in images through MATLAB simulation experiment, and describes the testing of other geometric figures under Hough transfer.

Abstract: This paper did quantitive flaw detection research to the defective parts of turnout point switch by using infrared thermal wave nondestructive testing based of the theory of infrared nondestructive testing. By using ANSYS, I made the numeric simulation test to parts of the inside known defection point switch, and made calculation and analysis for the result of this numeric simulation test. The result demonstrated that this method can achieve the quantitive infrared thermal wave nondestructive testing to defective parts of point switch.

Abstract: Abstract: The defect of concrete structures on material level can be expressed by defect depth and defect range. Infrared thermal imaging technology of concrete material defect detection is actually an inverse problem of heat transfer. On the basis of the current research achievements, infrared thermal imaging methods used in concrete structure defects was deduced to a multi-objective function optimization problem. Considering the traditional optimization algorithm slow convergence speed and local minima faults, this paper introduce particle swarm optimization algorithm (PSO) and the BP neural network to detect concrete material defect depth and range.PSO algorithm was used to optimize neural networks connection weights between layers and the network topology. The simulation test results are in good agreement with the experiment results and verify the validity of this method.