Research On Infrared Thermal Image Detection Technology Of Wind Turbine Blade Defects

Wind turbine blades are Glass Fiber Reinforced Plastics(GFRP),which are the key components for wind turbines to obtain wind energy.In the production process of blades,because of its special manufacturing process,the degree of automation is not high,resulting in surface or internal defects in the produced blades.These defects gradually expanded from the centimeter level under the effect of complex loads at high altitude,causing damage to the structural layer and causing major accidents.Therefore,the detection of internal defects in the blade is of great significance for ensuring the safety of the wind turbine,reducing maintenance costs and downtime losses.However,the infrared images of the wind turbine blades collected by the thermal imaging camera are not uniform.In addition,infrared images generally have low contrast,low signal-to-noise ratio,and edges that are easily blurred.The ability of infrared thermal imaging systems to detect and identify targets.First,the principle and method of continuous thermally excited infrared nondestructive testing technology are studied.Choose the appropriate excitation method and detection parameters.Build an infrared thermal imaging system.Designed and manufactured specimens containing common defects.Then the infrared thermal imaging experiment was carried out on the glass fiber epoxy resin composite specimen.Study the steps and methods of collecting the image sequence of the surface temperature field of the defective test piece.In order to solve the problem of uneven temperature field distribution on the surface of the test piece.Use polynomial fitting method to do non-uniformity correction.Makes too much light or dark parts suppressed.In order to improve the contrast of infrared images of wind turbine blades.This paper uses the method of Fourier transform and contrast-limited adaptive histogram equalization(CLAHE)to enhance the infrared image.First,the original heat map sequence is processed by fast Fourier transform to extract the phase information.Then the CLAHE algorithm is used to enhance the phase map with the best effect.This treatment method has solved the problems such as uneven heating and the influence of surface shape on detection.Avoid the influence of initial conditions and external factors.At the same time,it overcomes the shortcomings of traditional histogram equalization algorithm,such as excessive noise and sudden brightness change.The contrast of the infrared image is improved,and the purpose of image enhancement is realized.After enhanced processing,the contrast signal-to-noise ratio of infrared images is higher than other traditional methods.Improve the ability to identify the infrared thermal imaging defects of wind turbine blades.Finally,in order to further verify the effectiveness of the wind turbine blade infrared nondestructive testing method.On-site inspection of wind turbine blades.And analyze the test results.The existing infrared thermal image enhancement method is optimized under the premise of ensuring the effect and the calculation amount.And based on infrared images and human visual characteristics.Improve the final visual effect after image processing.Improve its performance and make it adaptive to a variety of scenarios.After on-site inspection of the blades,it was found that the non-destructive detection of infrared thermal images can effectively improve the ability to identify the infrared image defects of wind turbine blades.It is of great significance for ensuring the safety and efficiency of wind turbines,extending service life,reducing maintenance costs and downtime losses.