Infrared Detection Of Paste Residues On The Aero-engine Turbine Blade Surface

Aero-engine turbine blades are the key components of the aviation aircraft, have a direct impact on the quality and safety of the engine. Special turbine blade materials and manufacturing process is complex, expensive, and therefore commonly used in the production and maintenance process, nondestructive testing, defect detection. Traditional non-destructive testing methods, such as radiographic testing, ultrasonic testing, magnetic particle testing, penetrant testing and turbo detection, because of certain deficiencies and can not get a good application in the defect inspection of turbine blades.In order to meet the security requirements in the defect inspection of turbine blades to improve the detection efficiency and accuracy, using infrared thermal wave nondestructive testing technology to detect the surface of turbine blades paste residues. Infrared thermal wave nondestructive testing technology is different from the passive infrared detection by active control of the excitation source and measuring the surface temperature field changes to the surface and internal structure, so as to achieve the purpose of detection. This detection method has a non-contact, safe operation, high sensitivity, high detection efficiency, and apply a wide area of observation, measurement results are intuitive, quantitative measurement.In this paper, paste residue infrared thermal wave nondestructive detection system hardware, software, experimental results and image processing and other key issues around the turbine blade surface to elaborate. The innovation of the paper is as follows:1. A proposed aero-engine turbine blade surface paste residue infrared thermal wave nondestructive testing program, complete the design of the detection system; and complete the specific experiment, collected the different thermal image of the location of the untreated and the surface of the turbine blades paste residues.2. Matlab image processing on the thermal image, using a custom image enhancement method to achieve defect image extraction.