Thermography has been shown to be a viable technique for inspection of composites. The quadrupole method is a valuable technique for rapidly simulating the thermal response of layered systems. Often, the effort has focused on a one-dimensional model, in particular for improved analysis of thermal data. For composites, the in-plane heat diffusion often significantly impacts the thermal response of defects of interest, therefore three-dimensional simulations are desirable. This paper discusses the extension of the quadrupole methodology to perform simulations of thermographic responses in three-dimensional configurations. This enables the more realistic simulations of the thermal response of delaminations in composites. The simulations are compared to finite element simulations of the same inspection configurations.
Thermography has been shown to be a viable technique for inspection of composites. Impact damage in composites typically contains multiple overlapping delaminations at different depths. Understanding the limitations of the thermographic inspection is enhanced by performing simulations of the technique. Most simulations of composite thermographic inspections have focused on simulations of a single delamination at a fixed depth. The quadrupole method has been shown as a viable technique for rapid three-dimensional thermographic simulations of a delamination. This method is expanded to enable rapid simulation of multiple overlapping delaminations at different depths. Quadrupole simulations are compared to finite element simulations of multiple delaminations at different depths. The simulations are also compared to the thermographic measurements on impacted composites where shape and depth of the delaminations are known from x-ray computed tomography data.
The application of the quadrupole method for simulating thermal responses of delaminations in carbon fiber reinforced epoxy composites materials is presented. The method solves for the flux at the interface containing the delamination. From the interface flux, the temperature at the surface is calculated. While the results presented are for single sided measurements, with ash heating, expansion of the technique to arbitrary temporal flux heating or through transmission measurements is simple. The quadrupole method is shown to have two distinct advantages relative to finite element or finite difference techniques. First, it is straight forward to incorporate arbitrary shaped delaminations into the simulation. Second, the quadrupole method enables calculation of the thermal response at only the times of interest. This, combined with a significant reduction in the number of degrees of freedom for the same simulation quality, results in a reduction of the computation time by at least an order of magnitude. Therefore, it is a more viable technique for model based inversion of thermographic data. Results for simulations of delaminations in composites are presented and compared to measurements and finite element method results.
Simple methods for reducing the pulsed thermographic responses of delaminations tend to overestimate the size of the delamination, since the heat diffuses in the plane parallel to the surface. The result is a temperature profile over the delamination which is larger than the delamination size. A variational approach is presented for reducing the thermographic data to produce an estimated size for a flaw that is much closer to the true size of the delamination. The method is based on an estimate for the thermal response that is a convolution of a Gaussian kernel with the shape of the flaw. The size is determined from both the temporal and spatial thermal response of the exterior surface above the delamination and constraints on the length of the contour surrounding the delamination. Examples of the application of the technique to simulation and experimental data are presented to investigate the limitations of the technique.
Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.
Flaw detection and characterization with thermographic techniques in graphite polymer composites are often limited by
localized variations in the thermographic response. Variations in properties such as acceptable porosity, fiber volume
content and surface polymer thickness result in variations in the thermal response that in general cause significant
variations in the initial thermal response. These result in a “noise” floor that increases the difficulty of detecting and
characterizing deeper flaws. A method is presented for computationally removing a significant amount of the “noise”
from near surface porosity by diffusing the early time response, then subtracting it from subsequent responses.
Simulations of the thermal response of a composite are utilized in defining the limitations of the technique. This method
for reducing the data is shown to give considerable improvement characterizing both the size and depth of damage.
Examples are shown for data acquired on specimens with fabricated delaminations and impact damage.
Impact damage in thin carbon fiber reinforced polymer composites often results in a relatively small region of damage at the front surface, with increasing damage near the back surface. Conventional methods for reducing the pulsed thermographic responses of the composite tend to underestimate the size of the back surface damage, since the smaller near surface damage gives the largest thermographic indication. A method is presented for reducing the thermographic data to produce an estimated size for the impact damage that is much closer to the size of the damage estimated from other NDE techniques such as microfocus x-ray computed tomography and pulse echo ultrasonics. Examples of the application of the technique to experimental data acquired on specimens with impact damage are presented. The method is also applied to the results of thermographic simulations to investigate the limitations of the technique.
Flaw detection and characterization with thermographic techniques in graphite polymer composites is often
limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity,
variations in fiber volume content and surface polymer thickness result in variations in the thermal response that
in general cause significant variations in the initial thermal response. These variations result in a noise floor
that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing
thermographic responses taken before and after a change in state in a composite to improve the detection
of subsurface flaws. A method is presented for registration of the responses before finding the difference. A
significant improvement in the detectability is achieved by comparing the differences in response. Examples of
changes in state due to application of a load and impact are presented.
Designed to fulfill a critical inspection need for the Space Shuttle Program, the EVA IR Camera System can detect crack and subsurface defects in the Reinforced Carbon-Carbon (RCC) sections of the Space Shuttle's Thermal Protection System (TPS). The EVA IR Camera performs this detection by taking advantage of the natural thermal gradients induced in the RCC by solar flux and thermal emission from the Earth.
This instrument is a compact, low-mass, low-power solution (1.2cm3, 1.5kg, 5.0W) for TPS inspection that exceeds existing requirements for feature detection. Taking advantage of ground-based IR thermography techniques, the EVA IR Camera System provides the Space Shuttle program with a solution that can be accommodated by the existing inspection system. The EVA IR Camera System augments the visible and laser inspection systems and finds cracks and subsurface damage that is not measurable by the other sensors, and thus fills a critical gap in the Space Shuttle's inspection needs. This paper discusses the on-orbit RCC inspection measurement concept and requirements, and then presents a detailed description of the EVA IR Camera System design.
Thermographic nondestructive inspection techniques have been shown to provide quantitative, large area damage detection capabilities for the ground inspection of the reinforced carbon-carbon (RCC) used for the wing leading edge of the Shuttle orbiter. The method is non-contacting and able to inspect large areas in a relatively short inspection time. Thermal nondestructive evaluation (NDE) inspections have been shown to be applicable for several applications to the Shuttle in preparation for return to flight, including for inspection of RCC panels during impact testing, and for between-flight orbiter inspections. The focus of this work is to expand the capabilities of the thermal NDE methodology to enable inspection by an astronaut during orbital conditions. The significant limitations of available resources, such as weight and power, and the impact of these limitations on the inspection technique are discussed, as well as the resultant impact on data analysis and processing algorithms. Of particular interest is the impact to the inspection technique resulting from the use of solar energy as a heat source, the effect on the measurements due to working in the vacuum of space, and the effect of changes in boundary conditions, such as radiation losses seen by the material, on the response of the RCC. The resultant effects on detectability limits are discussed.
KEYWORDS: Signal to noise ratio, Principal component analysis, Image compression, Data modeling, Image processing, Composites, Inspection, Nondestructive evaluation, Data processing, Temperature metrology
Analysis of thermal data requires the processing of large amounts of temporal image data. The processing of the data for quantitative information can be time intensive especially out in the field where large areas are inspected resulting in numerous data sets. By applying a temporal compression technique, improved algorithm peformance can be obtained. In this study, analysis techniques are applied to compressed and non-compressed thermal data. A comparison is made based on computational speed and defect signal to noise.
Nondestructive Evaluation (NDE) is an important tool for ensuring the inspectability of a structural design and assessing the integrity of the structure during fabrication and service. NDE test results are typically examined by an inspector to determine the location and size of damage. There is significant potential for reducing the human effort involved in this procedure by digitally processing this data to enhance the signatures of flaws and to perform automated identification of suspected flaws. Computational NDE focuses on the development of methods for the simulation of NDE techniques and reduction of NDE data for an assessment of the integrity of the structure. This paper examines a technique that enhances the contrast between damaged and undamaged regions to improve the quality and reliability of flaw identification. An anisotropic diffusion algorithm is applied to the data. Anisotropic diffusion techniques are shown to significantly reduce image noise while maintaining defect contrast and preserving the important features of a flaw. The use of this algorithm is shown to improve detectability levels for thermal NDE data for both standard array imaging infrared cameras as well as the cheaper, more portable microbolometers of interest today. By increasing and automating detectability, significant advances can be made in the use of thermal NDE tools.
Aircraft structural integrity is a major concern for airlines and airframe manufacturers. To remain economically competitive, airlines are looking at ways to retire older aircraft, not when some fixed number of flight hours or cycles has been reached, but when true structural need dictates. This philosophy is known as `retirement for cause.' The need to extend the life of commercial aircraft has increased the desire to develop nondestructive evaluation (NDE) techniques capable of detecting critical flaws such as disbonding and corrosion. These subsurface flaws are of major concern in bonded lap joints. Disbonding in such a joint can provide an avenue for moisture to enter the structure leading to corrosion. Significant material loss due to corrosion can substantially reduce the structural strength, load bearing capacity and ultimately reduce the life of the structure. The National Aeronautics and Space Administration's Langley Research Center has developed a thermal NDE system designed for application to disbonding and corrosion detection in aircraft skins. By injecting a small amount of heat into the front surface of an aircraft skin, and recording the time history of the resulting surface temperature variations using an infrared camera, quantitative images of both bond integrity and material loss due to corrosion can be produced. This paper presents a discussion of the development of the thermal imaging system as well as the techniques used to analyze the resulting thermal images. The analysis techniques presented represent a significant improvement in the information available over conventional thermal imaging due to the inclusion of data from both the heating and cooling portion of the thermal cycle. Results of laboratory experiments on fabricated disbond and material loss samples are presented to determine the limitations of the system. Additionally, the results of actual aircraft inspections are shown, which help to establish the field applicability for this technique. A recent application of this technology to aircraft repairs using boron/epoxy patches is shown illustrating the flexibility of the technology.
A thermal technique is presented for imaging subsurface damage and computing the depth of damaged areas for low diffusivity materials. The measurement technique presented uses uniform heating with quartz lamps over a large area. The surface temperature of the sample is collected using a scanning IR radiometer and a real time image processor during the cooling of the sample after heating. Flaw depths are computed by performing a numeric approximation to the surface Laplacian on each temperature image in the time series. The depth of the damage is then calculated from the time required for the amplitude of the surface Laplacian to reach a minimum in the region over the damage. Experimental results from the application of the technique to low diffusivity materials with surface and subsurface defects at various depths are presented showing the technique's ability to give quantitative depth of damage information. Additionally, the effects of variations in defect size on the time for flux minimum, and thus on the calculated depth, is also investigated. Finally, finite element simulations are compared with experimental results.
The presence of cracks significantly decreases the structural integrity of thin metal sheets used in aerospace applications. Thermographic detection of surface temperature variations due to these cracks is possible after external heating. An approximate line source of heat is used to produce an inplane flow of heat in the sheet. A crack in the sheet perturbs the inplane flow of heat and can be seen in an image of the surface temperature of the sheet. An effective technique for locating these perturbations is presented which reduces the surface temperature image to an image of variations in the inplane heat flow. This technique is shown to greatly increase the detectability of the cracks. This thermographic method has advantages over other techniques in that it is able to remotely inspect a large area in a short period of time. The effectiveness of this technique depends on the shape, position and orientation of the heat source with respect to the cracks as well as the extent to which the crack perturbs the surface heat flow. The relationship between these parameters and the variation in the heat flow is determined both by experimental and computational techniques. Experimental data is presented for through-the-thickness, subsurface and surface EDM notches. Data for through-the-thickness fatigue cracks are also presented.
Post-processing of infrared thermal image thta is a technique which finds many uses in a laboratory devoted to
non-destructhe evaluation (NDE) of materials. Among these are determination ofmaterial pmperty values and
detection/location of delaminations. Exanples are shown in which thermal diffusivity is measured for technique verification,
as a verification of the tensor nature of diffusivity measurements and as a proxy for porosity in a test sample of a material
under developmenL Another example is given in which the coefficient of thennal expansion is determined through the
phenomenon of thermoelasticity. A final example is given in which post-processing extrts the thermal signature of a
delamination from an image dominated by an unwanted feature. Following these examples of materials evaluation using
post-processing, a set of procedures common to the data analysis in the examples is extracted. Generic requirements are
given so that each procedure can operate consistently within the entire process to produce appropriate values of the material