Online process monitoring and quality assurance are highly favorable for composite manufacturing processes like automated tape layup (ATL), where the productivity is largely constrained by downtime consisting of quality inspection and error mitigation. The presented work details the use of thermography as an inspection tool for such a process, using thermoplastic based tape material. A new online monitoring system is developed containing Infrared camera integrated on a purpose build ATL test rig. Surface thermal history for the layup course over time is recorded, which is then extracted along the width of the tape. The end result is a single image containing sequence of images, detailing the temperature data over the length of a single tape. Temperature gradient throughout the layup is then used to recognize foreign bodies and defects. Variation in adhesion effects of ply to the tool, ply and ply and ply and foreign bodies can be detected and areas of weak bonding can be recognized.
For qualifying non-destructive inspection techniques, test blocks with reproducible cracks are necessary. Austenitic stainless steel samples with reference reflectors were created and compared with artificial fatigue cracks produced by a resonance testing machine. The samples were inspected by eddy current and ultrasonic testing to estimate their length and depth. Additionally, inductive thermography measurements were carried out. This method can be used to detect surface flaws in metallic materials. As the flaw depth influences the eddy current distribution and the heat diffusion, the temperature difference caused by a flaw correlates with its depth. The fatigue cracks become visible by evaluating the IR image sequence and by observing the typical ‘butterfly’ pattern. FEM simulations were used to model the thermography experiments. The signals of short and long cracks were compared to examine how the depth estimation derived for long cracks can also be applied for short fatigue cracks.
Carbon fiber reinforced plastic (CFRP) specimens, charged with defined loads in impact tests, have been examined with flash and inductive thermography from the front and the rear side. In the case of inductive thermography, eddy currents are induced in electrically conductive materials, usually in metals. But it can be also excellently used for inspection of CFRP, as eddy current can be induced in the carbon fibers. The fiber’s orientation regarding the magnetic field of the induction coil also has an influence on the detection results. The sequence of the temperature images, recorded during and after the short inductive heating pulse, is evaluated with a Fourier Transform, and the obtained phase image is used for localizing the impact damages. The flash thermography tests in transmission and reflection mode were evaluated using PPT and TSR methods. The results of the flash and inductive inspection techniques are compared for samples with different degrees of damage, in order to learn more about the capability of induction thermography for detecting impact damages.
Inductive thermography is a non-destructive technique, which can be excellently used for detection of surface cracks in electrically conductive materials. In ferro-magnetic steel even a single short pulse with duration of 50ms up to 1s is enough to induce a Joule heating which makes shallow cracks well detectable in the infrared image sequences. In the case of non-magnetic materials with high electrical and thermal conductivity, as e.g. aluminum, the situation is much more difficult: on the one hand a short heating pulse duration is necessary, otherwise the thermal signal diminishes too quickly due to the thermal diffusion. On the other hand with a short heating pulse it is not possible to induce enough heat in the material; therefore the signal-to-noise ratio becomes too low for defect detection. A possibility to overcome this problem is to apply a sequence of short pulses, as it is also done in the lock-in thermography. It is investigated, how many pulses and which pulse duration is necessary to detect surface cracks with different crack depths in non-magnetic materials, as in aluminum. It is also studied, how the heating power, that means the temperature increase during one heating pulse, influences the detectability. Experimental results are presented, obtained for an aluminum sample with artificial cracks and they are compared also with numerical simulations.
Inductive thermography has been proved to be an excellent method for detecting surface cracks in metallic materials. The Joule heating is generated directly in the workpiece due to the induced eddy current and its penetration depth is determined by material properties and by the excitation frequency. Whether an additional temperature increase or a colder area around the crack occurs, is determined by the ratio of the crack depth to the penetration depth. It is investigated how material parameters, excitation frequency, crack depth and its inclination angle affect the temperature distribution around a crack after a short heating pulse. With finite element simulations material independent results are calculated showing in which frequency and temporal range crack detection is possible. These results are analyzed more closely for four selected metals: ferro-magnetic and non-magnetic steel, aluminum and titanium.
Subsurface defects can be well detected by flash thermography evaluating the temperature response at the sample surface. In many cases flat bottom holes or air inclusions are investigated as typical defects. In contrast, in the current paper the main emphasis is placed on metal inclusions hidden in an insulator material. As the thermal effusivity of the metal is significantly higher than of the base material, the temperature decreases quicker above such a defect. Thermal quadrupole calculations and finite element simulations have been used to investigate more closely these temperature signals. Additionally, 3D printed samples have been created, where in the plastic material different metal plates, as steel, aluminum and copper have been introduced. The measurement results on these samples show very good agreement with theoretically calculated curves.
Subsurface defects can be detected by flash thermography by evaluating the temperature response at the surface. Many techniques have been developed in the past to localize a defect and also to estimate its depth and size. Two of the most established methods are TSR and PPT, whereby TSR analyzes the data in the time domain, and PPT evaluates the signal in the frequency domain. In order to get the data in the frequency domain, Fourier transformation, especially FFT is used to calculate the phase shift for the different frequencies. The usage of FFT assumes a periodical signal or a temporal signal which is limited in the time. As this is not the case for the temperature signal after a short pulse heating, the transformation to the frequency domain generates some errors. Therefore parameters as sampling frequency and duration of evaluation have to be selected carefully. Even if many publications have been already dealing with this topic, in this paper a new approach is attempted by comparing the temporal behavior as it is handled by the TSR technique with the frequency behavior calculated by PPT. The results are interpreted with the help of simulation models of flat bottom hole samples.
Castings, forgings and other steel products are nowadays usually tested with magnetic particle inspection, in order to detect surface cracks. An alternative method is active thermography with inductive heating, which is quicker, it can be well automated and as in this paper presented, even the depth of a crack can be estimated. The induced eddy current, due to its very small penetration depth in ferro-magnetic materials, flows around a surface crack, heating this selectively. The surface temperature is recorded during and after the short inductive heating pulse with an infrared camera. Using Fourier transformation the whole IR image sequence is evaluated and the phase image is processed to detect surface cracks. The level and the local distribution of the phase around a crack correspond to its depth. Analytical calculations were used to model the signal distribution around cracks with different depth and a relationship has been derived between the depth of a crack and its phase value. Additionally, also the influence of the heating pulse duration has been investigated. Samples with artificial and with natural cracks have been tested. Results are presented comparing the calculated and measured phase values depending on the crack depth. Keywords: inductive heating, eddy current, infrared
Active thermography data for nondestructive testing has traditionally been evaluated by either visual or numerical identification of anomalous surface temperature contrast in the IR image sequence obtained as the target sample cools in response to thermal stimulation. However, in recent years, it has been demonstrated that considerably more information about the subsurface condition of a sample can be obtained by evaluating the time history of each pixel independently. In this paper, we evaluate the capabilities of two such analysis techniques, Pulse Phase Thermography (PPT) and Thermographic Signal Reconstruction (TSR) using induction and optical flash excitation. Data sequences from optical pulse and scanned induction heating are analyzed with both methods. Results are evaluated in terms of signal-tobackground ratio for a given subsurface feature. In addition to the experimental data, we present finite element simulation models with varying flaw diameter and depth, and discuss size measurement accuracy and the effect of noise on detection limits and sensitivity for both methods.
Many workpieces produced in large numbers with a large variety of sizes and geometries, e.g. castings and forgings, have to be 100% inspected. In addition to geometric tolerances, material defects, e.g. surface cracks, also have to be detected. We present a fully automated nondestructive testing technique for both types of defects. The workpiece is subject to continuous motion, and during this motion two measurements are performed. In the first step, after applying a short inductive heating, a thermographic measurement is carried out. An infrared camera records the surface temperature of the workpiece enabling the localization of material defects and surface cracks. In the second step, a light sectioning measurement is performed to measure the three-dimensional geometry of the piece. With the help of feature-based registration the data from the two different sources are fused and evaluated together. The advantage of this technique is that a more reliable decision can be made about the nature of the failures and their possible causes. The same registration technique also can be used for the comparison of different pieces and therefore to localize different failure types, via comparison with a "golden," defect-free piece. The registration technique can be applied to any part that has unique geometric features, around which moments can be computed. Consequently, the inspection technique can be applied to many different parts. The efficacy of the method is demonstrated with measurements on three parts having different geometries.
Many workpieces produced in large numbers and having a large variety of sizes and geometries, e.g. castings and forgings,
have to be 100% inspected; on the one side, geometric tolerances need to be examined, and on the other side material
defects, surface cracks have to be detected. In the paper a fully automated non-destructive testing technique is presented,
whereby the workpiece is continuously moved and during this movement two measurements are carried out: first a thermographical
measurement combined with inductive heating, where an infrared camera records the temperature distribution at
the surface of the workpiece in order to localize material defects and surface cracks. In the second step a light sectioning
measurement is carried out, to measure the 3d geometry of the piece. With help of registration the data from the two different
sources are fused (merged) and evaluated together. The advantage of this technique is, that a more reliable decision can
be made about the failures and their possible causes. The same registration technique can also be used for the comparison
of different pieces and therefore to localize different failure types, compared to a 'golden', defect-free piece.
Active thermography can be well used to detect subsurface defects like buried cavities in materials. For metallic materials
induction heating is the most efficient technique, because the heat is generated directly in the material and therefore
the usually low emissivity and absorption coefficient of the metallic surface does not affect the heating process. Short
inductive heating pulses (0.5-2 s) have been used to detect holes with a diameter of 2 mm in a depth of 2-4 mm below the
surface in aluminum samples. Some of the defects were generated during the production process; other ones were created
artificially. The size and the depth of these defects were determined with the help of computer tomography. Additionally
to the experimental data, also finite element simulations and analytical calculations have been carried out in order to
model the heat distribution for different defect sizes and defect depths. The calculations have been used to optimize the
heating pulse duration. Based on the modelling results, an evaluation algorithm has been developed, which allows an
automatically localization of the defects with help of image processing techniques. In order to test the stability of the
automated evaluation, noise has been added to the calculated temperature distribution. The same processing technique has
been used for the evaluation of the experimental data to localize subsurface defects and very good detection results could
In the case of thermographic inspection, the workpiece is heated in a particular manner followed by the observation of the resulting temperature increase at the material surface by means of an infrared camera. Inhomogeneities such as surface cracks cause a nonuniform distribution of the temperature; consequently, they can be localized in the infrared images. For metallic pieces, the most efficient way is inductive heating, whereby the induced eddy current generates heat directly in the surface skin of the sample. Experiments have been carried out on how steel workpieces, especially castings, can be thermographically inspected to detect cracks. The testing is a nondestructive and contact-free method. The goal is to develop a fully automated testing equipment with high throughput, where the flawed pieces are identified by evaluation and classification of the infrared images. The classification task is to distinguish between temperature increase around a crack and additional heating at the edges of the workpieces. Neural network has been used to train and to classify about 750 images, and good results have been achieved.
Thermo-inductive investigations can be well used for the detection of surface cracks in metallic materials. The workpiece
is heated by a short inductive pulse and an infrared camera is recording the temperature distribution of the surface.
Irregularities and failures in the surface cause anomalies in the temperature distribution, making the failures visible and
detectable in the infrared images. Results of experiments show that magnetic and non-magnetic materials have very
different behavior: surface cracks in magnetic materials are heated stronger than the failure-free surface. On the other
hand, in non-magnetic materials cracks are less heated than the surface itself and become visible through lower
temperature values. These different behaviors can be well explained by the different penetration depth of the eddy
current, mainly influenced by the magnetic permeability of the material. Model calculations have been carried out in
order to describe the distribution of the eddy current around a surface crack and to calculate the resulting temperature
profile around it. The time-dependent evaluation of the temperature changes provides results which are independent of
the emissivity differences and therefore shows also very well-defined results in the case of grinded or scratched surfaces.
This technique has been used for a couple of different work-pieces presenting its advantages. The experimental and
calculated results are compared, showing a very good agreement.
For thermo-inductive crack detection, a metallic work-piece is placed in a high frequency magnetic field which induces eddy currents in a very thin layer of the surface. This eddy current heats up the sample and the emitted infrared radiation is viewed by an infrared sensitive camera. An inhomogeneous temperature distribution on the surface corresponds to inhomogeneities and cracks in the material. The main goal of the thermo-inductive crack detection is on the one side to find cracks and on the other side to determine their depths. For this purpose an examination of all parameters affecting the result of the measurements has to be made.
In previous publications it has been shown how the thermal quotient Tcrack/Tsurf depends on several parameters (i.e.: time, pulse length, penetration depth of the eddy current and crack depth). All these investigations were made for rectangular shaped cracks. But metallographic cross-sections show that real cracks have different shapes and different angles depending on the circumstances of the origin of the crack. In this paper results of finite element simulations are presented demonstrating what kind of influence the different shapes have to the thermal contrast. It is also shown in which way the crack geometry affects the temperature distribution on the crack near surface. The calculations take into consideration the distribution of the eddy currents around the crack for both magnetic and non-magnetic materials. The simulations are based on coupled modeling of magnetic and thermal phenomena. The calculated results are in very good agreement with the measurements.
In the case of thermo-inductive probing the material is heated by HF-induced eddy currents and the emission from the material surface is detected by an infrared camera. Anomalies in the surface temperature correspond to in-homogeneities in the material. Due to the high excitation frequency (200 kHz) and the magnetic properties of the material, the penetration depth of the current is very small (about 0.03 mm). Therefore the eddy current 'flows around' surface cracks with a depth of 0.1-1 mm. This causes a higher current density and higher temperature around the failures, which are made visible by the infrared camera. Experiments have been carried out on steel wires with a diameter of 4.5-10 mm and with longitudinal surface cracks with a depth of 0.1-0.2 mm. Due to the high heat conductivity of the material, the temperature difference diminishes very quickly. Therefore short heating pulses with duration of 0.1-0.5 sec have been applied. The measurement result shows, that the thermo-inductive method is well suited to detect such shallow flaws. An analytical model has been derived, to calculate the temperature distribution in the wire and around the failure. The model also shows the dependence of the temperature distribution on the parameters of the experiments, as e.g. the length of the heating pulse, which helps to optimize the measurement setup. Additionally, finite element simulations have been carried out. The results of the model-calculations and the simulations are successfully compared with the experimental results.