TY - JOUR A1 - Ahmadi, Samim A1 - Burgholzer, P. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Super resolution laser line scanning thermography N2 - In this paper we propose super resolution measurement and post-processing strategies that can be applied in thermography using laser line scanning. The implementation of these techniques facilitates the separation of two closely spaced defects and avoids the expected deterioration of spatial resolution due to heat diffusion. The experimental studies were performed using a high-power laser as heat source in combination with pulsed thermography measurements (step scanning) or with continuous heating measurements (continuous scanning). Our work shows that laser line step scanning as well as continuous scanning both can be used within our developed super resolution (SR) techniques. Our SR techniques make use of a compressed sensing based algorithm in post- processing, the so-called iterative joint sparsity (IJOSP) approach. The IJOSP method benefits from both - the sparse nature of defects in space as well as from the similarity of each measurement. In addition, we show further methods to improve the reconstruction quality e.g. by simple manipulations in thermal image processing such as by considering the effect of the scanning motion or by using different optimization algorithms within the IJOSP approach. These super resolution image processing methods are discussed so that the advantages and disadvantages of each method can be extracted. Our contribution thus provides new approaches for the implementation of super resolution techniques in laser line scanning thermography and informs about which experimental and post-processing parameters should be chosen to better separate two closely spaced defects. KW - Super resolution KW - Laser thermography KW - Compressed sensing KW - Laser scanning KW - Joint sparsity PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-509796 DO - https://doi.org/10.1016/j.optlaseng.2020.106279 SN - 0143-8166 VL - 134 SP - 106279 PB - Elsevier Ltd. AN - OPUS4-50979 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Rus, J. A1 - Gustschin, A. A1 - Mooshofer, H. A1 - Grager, J.-C. A1 - Bente, Klaas A1 - Gaal, Mate A1 - Pfeiffer, F. A1 - Grosse, C. U. T1 - Qualitative comparison of non-destructive methods for inspection of carbon fiber-reinforced polymer laminates N2 - In the rapidly expanding composite industry, novel inspection methods have been developed in recent years. Particularly promising for air-coupled testing are cellular polypropylene transducers which offer better impedance matching to air than piezoelectric transducers. Furthermore, broadband transmitters (laser-induced ultrasound and thermoacoustic emitters) and receivers (optical microphones) have opened a completely new chapter for advanced contact-free ultra-sound inspection. X-ray dark-field radiography offers a different approach to detect porosity and microcracks, employing small angle X-ray scattering. These innovative ultrasonic and radiographic alternatives were evaluated in comparison with well-established inspection techniques. We applied thirteen different non-destructive methods to inspect the same specimen (a carbon fiber-reinforced polymer laminate with induced impact damage): air-coupled ultrasound testing (using piezoelectric transducers, broadband optical microphones, cellular polypropylene transducers, and a thermoa- coustic emitter), laser-induced ultrasound testing, ultrasonic immersion testing, phased array ultrasonic testing, optically excited lock-in thermography, and X-ray radiography (projectional absorption and dark-field, tomosynthesis, and micro-computed tomography). The inspection methods were qualitatively characterized by comparing the scan results. The conclusions are advantageous for a decision on the optimal method for certain testing constraints. KW - Carbon fiber-reinforced polymer KW - Air-coupled ultrasound KW - Optically excited lock-in thermography KW - X-ray micro-computed tomography KW - X-ray dark-field radiography PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-509473 DO - https://doi.org/10.1177/0021998320931162 SN - 0021-9983 VL - 54 IS - 27 SP - 4325 EP - 4337 PB - SAGE AN - OPUS4-50947 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Tiitta, M. A1 - Tiitta, V. A1 - Gaal, Mate A1 - Heikkinen, J. A1 - Lappalainen, R. A1 - Tomppo, L. T1 - Air-coupled ultrasound detection of natural defects in wood using ferroelectret and piezoelectric sensors N2 - Air-coupled ultrasound was used for assessing natural defects in wood boards by through-transmission scanning measurements. Gas matrix piezoelectric (GMP) and ferroelectret (FE) transducers were studied. The study also included tests with additional bias voltage with the ferroelectret receivers. Signal analyses, analyses of the measurement dynamics and statistical analyses of the signal parameters were conducted. After the measurement series, the samples were cut from the measurement regions and the defects were analyzed visually from the cross sections. The ultrasound responses were compared with the results of the visual examination of the cross sections. With the additional bias voltage, the ferroelectret measurement showed increased signal-to-noise ratio, which is especially important for air-coupled measurement of high-attenuation materials like wood. When comparing the defect response of GMP and FE sensors, it was found that FE sensors had more sensitive dynamic range, resulting from better s/n ratio and short response pulse. Classification test was made to test the possibility of detecting defects in sound wood. Machine learning methods including decision trees, k-nearest neighbor and support vector machine were used. The classification accuracy varied between 72 and 77% in the tests. All the tested machine learning methods could be used efficiently for the classification. KW - Air-coupled transducers KW - Wood KW - Ultrasound KW - Ultrasonic imaging KW - Ferroelectret KW - Machine learning PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-509503 DO - https://doi.org/10.1007/s00226-020-01189-y SP - 1 EP - 14 PB - Springer AN - OPUS4-50950 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Haller, T. A1 - Völker, Christoph A1 - Hartmann, T. T1 - Machine learning based multi-sensor fusion for the nondestructive testing of corrosion in concrete N2 - Half-cell potential mapping (HP) is the most popular non-destructive testing method (NDT) for locating corrosion damage in concrete. It is generally accepted that HP is susceptible to environmental factors caused by salt-related deterioration, such as different moisture and chloride gradients. Additional NDT methods are able to identify distinctive areas but are not yet used to estimate more accurate test results. We present a Supervised Machine Learning (SML) based approach to data fusion of seven different signal features to obtain higher quality information. SMLs are methods that explore (or learn) relationships between different (sensor) data from predefined data labels. To obtain a representative, labelled data set we conducted a comprehensive experiment simulating the deterioration cycle of a chloride exposed device in the laboratory. Our data set consists of 18 measurement campaigns, each containing HP, Ground Penetrating- Radar, Microwave Moisture and Wenner resistivity data. We compare the performance of different ML approaches. Many outperform the best single method, HP. We describe the intrinsic challenges posed by a data-driven approach in NDT and show how future work can help overcome them. T2 - SMAR2019 - 5th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures CY - Potsdam, Germany DA - 27.08.2019 KW - Machine Learning KW - NDT KW - Half-Cell Potential Mapping KW - Corrosion KW - Reinforced Concrete KW - Data Fusion PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-498563 UR - http://www.ndt.net/?id=24890 VL - 25 IS - 1 SP - 24890-1 EP - 24890-8 PB - NDT.net CY - Kirchwald AN - OPUS4-49856 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ehlers, Henrik A1 - Pelkner, Matthias A1 - Thewes, R. T1 - Heterodyne Eddy Current Testing Using Magnetoresistive Sensors for Additive Manufacturing Purposes N2 - In recent years additive manufacturing technologies have become widely popular. For complex functional components or low volume production of workpieces, laser powder bed fusion can be used. High safety requirements, e.g. in the aerospace sector, demand extensive quality control. Therefore, offline non-destructive testing methods like computed tomography are used after manufacturing. Recently, for enhanced profitability and practicality online non-destructive testing methods, like optical tomography have been developed. This paper discusses the applicability of eddy current testing with magnetoresistive sensors for laser powder bed fusion parts. For this purpose, high spatial resolution giant magnetoresistance arrays are utilized for testing in combination with a single wire excitation coil. A heterodyne principle minimizes metrology efforts. This principle is compared to conventional signal processing in an eddy current testing setup using an aluminum test sample with artificial surface defects. To evaluate the influence of the powder used in the manufacturing process on eddy current testing and vice versa, a laser powder bed fusion mock-up made from stainless steel powder (316L) is used with artificial surface defects down to 100 µm. This laser powder bed fusion specimen was then examined using eddy current testing and the underlying principles. KW - Eddy current testing KW - Heterodyning KW - Laser powder bed fusion KW - Giant magnetoresistance KW - Additive manufacturing KW - 316L PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-506140 DO - https://doi.org/10.1109/JSEN.2020.2973547 SN - 1530-437X VL - 20 IS - 11 SP - 5793 EP - 5800 PB - IEEE AN - OPUS4-50614 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thummerer, G. A1 - Mayr, G. A1 - Hirsch, Philipp Daniel A1 - Ziegler, Mathias A1 - Burgholzer, P. T1 - Photothermal Image Reconstruction in Opaque Media with Virtual Wave Backpropagation N2 - Thermographic reconstruction of defects that lie in the bulk of a sample is a difficult task because entropy production during heat diffusion leads to information loss. To reconstruct defects one has to solve an inverse heat conduction problem. The quality of the reconstruction is closely related to the information content of the observed data set that is reflected by the decreasing ability to spatially resolve a defect with growing defect depth. In this work we show a 2D reconstruction of rectangular slots with different width-to-depth ratios in a metallic sample. For this purpose, we apply the virtual wave concept and incorporate positivity and sparsity as prior information to overcome the diffusion-based information loss partially. The reconstruction is based on simulated and experimental pulse thermography data. In the first reconstruction step, we compute a virtual wave field from the surface temperature data. This allows us, in the second step, to use ultrasonic backpropagation methods for image reconstruction. KW - Virtual wave concept KW - Thermography KW - Photothermal Technique KW - Image reconstruction PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-506166 DO - https://doi.org/10.1016/j.ndteint.2020.102239 VL - 112 SP - 102239 PB - Elsevier Ltd. CY - Netherlands AN - OPUS4-50616 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ahmadi, Samim A1 - Burgholzer, P. A1 - Mayr, G. A1 - Jung, P. A1 - Caire, G. A1 - Ziegler, Mathias T1 - Photothermal super resolution imaging: A comparison of different thermographic reconstruction techniques N2 - This paper presents different super resolution reconstruction techniques to overcome the spatial resolution limits in thermography. Pseudo-random blind structured illumination from a onedimensional laser array is used as heat source for super resolution thermography. Pulsed thermography measurements using an infrared camera with a high frame rate sampling lead to a huge amount of data. To handle this large data set, thermographic reconstruction techniques are an essential step of the overall reconstruction process. Four different thermographic reconstruction techniques are analyzed based on the Fourier transform amplitude, principal component analysis, virtual wave reconstruction and the maximum thermogram. The application of those methods results in a sparse basis representation of the measured data and serves as input for a compressed sensing based algorithm called iterative joint sparsity (IJOSP). Since the thermographic reconstruction techniques have a high influence on the result of the IJOSP algorithm, this paper Highlights their Advantages and disadvantages. KW - Super resolution KW - Compressed sensing KW - Laser thermography KW - Virtual wave KW - Defect reconstruction PY - 2020 DO - https://doi.org/10.1016/j.ndteint.2020.102228 VL - 111 SP - 2228 PB - Elsevier Ltd. CY - Netherlands AN - OPUS4-50419 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kondo, M. A1 - Melzer, Michael A1 - Karnaushenko, D. A1 - Uemura, T. A1 - Yoshimoto, S. A1 - Aklyama, M. A1 - Noda, Y. A1 - Araki, T. A1 - Schmidt, O. G. A1 - Sekitani, T. T1 - Imperceptible magnetic sensor matrix system integrated with organic driver and amplifier circuits N2 - Artificial electronic skins (e-skins) comprise an integrated matrix of flexible devices arranged on a soft, reconfigurable surface. These sensors must perceive physical interaction spaces between external objects and robots or humans. Among various types of sensors, flexible magnetic sensors and the matrix configuration are preferable for such position sensing. However, sensor matrices must efficiently map the magnetic field with real-time encoding of the positions and motions of magnetic objects. This paper reports an ultrathin magnetic sensor matrix system comprising a 2 × 4 array of magnetoresistance sensors, a bootstrap organic shift register driving the sensor matrix, and organic signal amplifiers integrated within a single imperceptible platform. The system demonstrates high magnetic sensitivity owing to the use of organic amplifiers. Moreover, the shift register enabled real-time mapping of 2D magnetic field distribution. KW - Imperceptible electronics KW - Magnetic sensor system KW - Electronic skin KW - Organic electronics KW - Giant magnetoresistance PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-503855 DO - https://doi.org/10.1126/sciadv.aay6094 SN - 2375-2548 VL - 6 IS - 4 SP - Paper eaay6094, 1 EP - 10 PB - American Association for the Advancement of Science AN - OPUS4-50385 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moosavi, Robabeh A1 - Grunwald, Marcel A1 - Redmer, Bernhard T1 - Crack detection in reinforced concrete N2 - Automatic segmentation of cracks using crack detection methods fails when applied on concrete with embedded reinforcements; it results in artifacts called false-detected cracks. We present a two-step approach to trace the cracks which reduces significantly detecting the false ones. In the first step, the reinforcements were found and removed from the 3D data set, and in the second step, the cracks were detected in the 3D data set free from reinforcements. To visualize and determine the structure and the degree of damages nondestructively, planar tomography as a special case of laminography was used. KW - 3D imaging KW - Laminography KW - Crack detection KW - Reinforced concrete PY - 2020 DO - https://doi.org/10.1016/j.ndteint.2019.102190 VL - 109 SP - 102190 PB - Elsevier Ltd. AN - OPUS4-49520 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eckel, S. A1 - Zscherpel, Uwe A1 - Huthwaite, P. A1 - Paul, N. A1 - Schumm, A. T1 - Radiographic film system classification and noise characterisation by a camera-based digitisation procedure N2 - Extracting statistical characteristics from radiographic films is vital for film system classification and contrast sensitivity evaluation and serves as a basis for film noise simulation. A new method for digitising radiographic films in order to extract these characteristics is presented. The method consists of a camera-based setup and image processing procedure to digitise films. Correct optical density values and granularity can be extracted from the digitised images, which are equal to results obtained by standardised measurement procedures. Specific statistical characteristics of film noise are theoretically derived and subsequently verified by the obtained data, including characteristics such as Gaussianity and spatial spectral characteristics of the optical density fluctuations. It is shown that the presented method correctly measures the granularity of film noise and can therefore replace time-consuming microdensitometer measurements traditionally required for film system classifications. Additionally, the inherent unsharpness of film systems was investigated and compared with literature data. This comparison serves as another validation approach of the presented method. KW - Radiography KW - Image processing KW - Film noise KW - Film system classification KW - Digitisation PY - 2020 DO - https://doi.org/10.1016/j.ndteint.2020.102241 SN - 0963-8695 VL - 111 IS - 4 SP - 102241 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-50517 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -