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    Wyświetlanie 1-9 z 9
    Tytuł:
    Application of Artificial Neural Networks for Defect Detection in Ceramic Materials
    Autorzy:
    Akinci, T. C.
    Nogay, H. S.
    Yilmaz, O.
    Powiązania:
    https://bibliotekanauki.pl/articles/176701.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    impulse noise
    artificial neural network
    ANN
    defect detection
    ceramic materials
    Opis:
    In this study, an artificial neural network application was performed to tell if 18 plates of the same material in different shapes and sizes were cracked or not. The cracks in the cracked plates were of different depth and sizes and were non-identical deformations. This ANN model was developed to detect whether the plates under test are cracked or not, when four plates have been selected randomly from among a total of 18 ones. The ANN model used in the study is a model uniquely tailored for this study, but it can be applied to all systems by changing the weight values and without changing the architecture of the model. The developed model was tested using experimental data conducted with 18 plates and the results obtained mainly correspond to this particular case. But the algorithm can be easily generalized for an arbitrary number of items.
    Źródło:
    Archives of Acoustics; 2012, 37, 3; 279-286
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics
    Autorzy:
    Rawashdeh, Nathir
    Hazaveh, Paniz
    Altarazi, Safwan
    Powiązania:
    https://bibliotekanauki.pl/articles/2201189.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    industrial inspection
    quality control
    defect detection
    polymer film
    vision
    Opis:
    Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be imple mented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.
    Źródło:
    Management and Production Engineering Review; 2023, 14, 1; 61--71
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automatic defect detection and characterization by thermographic images based on damage classifiers evaluation
    Autorzy:
    Dinardo, Giuseppe
    Fabbiano, Laura
    Tamborrino, Rosanna
    Vacca, Gaetano
    Powiązania:
    https://bibliotekanauki.pl/articles/221850.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    thermography
    non-destructive testing
    thermal barrier coatings
    image segmentation
    uncertainty analysis
    Opis:
    In the framework of non-destructive evaluation (NDE), an accurate and precise characterization of defects is fundamental. This paper proposes a novel method for characterization of partial detachment of thermal barrier coatings from metallic surfaces, using the long pulsed thermography (LPT). There exist many applications, in which the LPT technique provides clear and intelligible thermograms. The introduced method comprises a series of post-processing operations of the thermal images. The purpose is to improve the linear fit of the cooling stage of the surface under investigation in the logarithmic scale. To this end, additional fit parameters are introduced. Such parameters, defined as damage classifiers, are represented as image maps, allowing for a straightforward localization of the defects. The defect size information provided by each classifier is, then, obtained by means of an automatic segmentation of the images. The main advantages of the proposed technique are the automaticity (due to the image segmentation procedures) and relatively limited uncertainties in the estimation of the defect size.
    Źródło:
    Metrology and Measurement Systems; 2020, 27, 2; 219-242
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Defect Detection Using Deep Learning-Based YOLOv3 in Cross-Sectional Image of Additive Manufacturing
    Autorzy:
    Choi, Byungjoo
    Choi, Yongjun
    Lee, Moon-Gu
    Kim, Jung-Sub
    Lee, Sang-Won
    Jeon, Yongho
    Powiązania:
    https://bibliotekanauki.pl/articles/2048889.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    additive manufacturing
    deposition defect
    data augmentation
    YOLOv3
    object detection
    Opis:
    Deposition defects like porosity, crack and lack of fusion in additive manufacturing process is a major obstacle to commercialization of the process. Thus, metallurgical microscopy analysis has been mainly conducted to optimize process conditions by detecting and investigating the defects. However, these defect detection methods indicate a deviation from the operator’s experience. In this study, artificial intelligence based YOLOv3 of object detection algorithm was applied to avoid the human dependency. The algorithm aims to automatically find and label the defects. To enable the aim, 80 training images and 20 verification images were prepared, and they were amplified into 640 training images and 160 verification images using augmentation algorithm of rotation, movement and scale down, randomly. To evaluate the performance of the algorithm, total loss was derived as the sum of localization loss, confidence loss, and classification loss. In the training process, the total loss was 8.672 for the initial 100 sample images. However, the total loss was reduced to 5.841 after training with additional 800 images. For the verification of the proposed method, new defect images were input and then the mean Average Precision (mAP) in terms of precision and recall was 0.3795. Therefore, the detection performance with high accuracy can be applied to industry for avoiding human errors.
    Źródło:
    Archives of Metallurgy and Materials; 2021, 66, 4; 1037-1041
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Defect Detection in Ceramic Materials Based on Time-Frequency Analysis by Using the Method of Impulse Noise
    Autorzy:
    Akinci, T. C.
    Powiązania:
    https://bibliotekanauki.pl/articles/177471.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    impulse noise
    time-frequency analysis
    defect detection in ceramic materials
    Opis:
    In this study, it was achieved by using the method of impulse noise to detect internal or surface cracks that can occur in the production of ceramic plates. Ceramic materials are often used in the industry, especially as kitchenware and in areas such as the construction sector. Many different methods are used in the quality assurance processes of ceramic materials. In this study, the impact noise method was examined. This method is a test technique that was not used in applications. The method is presented as an examination technique based on whether there is a deformation on the material according to the sound coming from it as a result of a plastic bit hammer impact on the ceramic material. The application of the study was performed on plates made of ceramic materials. Here, it was made with the same type of model plates manufactured from the same material. The noise that would occur as a result of the impact applied on a point determined on the materials to be tested has been examined by the method of time-frequency analysis. The method applied gives pretty good results for distinguishing ceramic plates in good condition from those which are cracked.
    Źródło:
    Archives of Acoustics; 2011, 36, 1; 77-85
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of Two Advanced Vision Methods Based on Structural and Surface Analyses to Detect Defects in the Erichsen Cupping Test
    Autorzy:
    Jasiński, C.
    Świłło, S.
    Kocańda, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/353647.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    defect detection
    Erichsen cupping test
    laser speckle
    vision system
    Opis:
    Due to the wide range of various sheet metal grades and the need to verify the material properties, there are numerous methods to determine the material formability. One of them, that allows quick determination of sheet metal formability, is the Erichsen cupping test described in the ISO 20482: 2003 standard. In the presented work, the results of formability assessment for DC04 deepdrawing sheet metal were obtained by means of the traditionally carried out Erichsen cupping test and compared with the resultsobtained by using two advanced methods based on vision analysis. Application of these methods allows extending the traditional scope of analysis during Erichsen cupping test by determination of the necking and strain localization before fracture. The proposed methods were compared in order to dedicate appropriate solution for the industrial application and laboratory tests respectively, where the simplicity and reliability are the mean aspects need to be considered when applied to the Erichsen cupping test.
    Źródło:
    Archives of Metallurgy and Materials; 2019, 64, 3; 1041-1049
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A New Approach to Experimental Testing of Sheet Metal Formability for Automotive Industry
    Autorzy:
    Jasiński, C.
    Kocańda, A.
    Morawiński, Ł.
    Świłło, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/350906.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    vision system
    defect detection
    Erichsen cupping test
    laser speckle
    Opis:
    Advanced vision method of analysis of the Erichsen cupping test based on laser speckle is presented in this work. This method proved to be useful for expanding the range of information on material formability for two commonly used grades of steel sheets: DC04 and DC01. The authors present a complex methodology and experimental procedure that allows not only to determine the standard Erichsen index but also to follow the material deformation stages immediately preceding the occurrence of the crack. Accurate determination of these characteristics in the sheet metal forming would be an important application, especially for automotive industry. However, the sheet metal forming is a very complex manufacturing process and its success depends on many factors. Therefore, attention is focused in this study on better understanding of the Erichsen index in combination with the material deformation history.
    Źródło:
    Archives of Metallurgy and Materials; 2019, 64, 4; 1231-1238
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Detection of thinning of homogeneous material using active thermography and classification trees
    Autorzy:
    Dudzik, Sebastian
    Dudek, Grzegorz
    Powiązania:
    https://bibliotekanauki.pl/articles/1848987.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    active thermography
    classification tree
    defect detection and characterization
    material thinning detection
    Opis:
    Active thermography is an efficient tool for defect detection and characterization as it does not change the properties of tested materials. The detection and characterization process involves heating a sample and then analysing the thermal response. In this paper, a long heating pulse was used on samples with a low thermal diffusivity and artificially created holes of various depths. As a result of the experiments, heating and cooling curves were obtained. These curves, which describe local characteristics of the material, are recognized using a classification tree and divided into categories depending on the material thickness (hole depths). Two advantages of the proposed use of classification trees are: an in-built mechanism for feature selection and a strong reduction in the dimensions of the pattern. Based on the experimental study, it can be concluded that classification trees are a useful tool for the thinning detection of homogeneous material.
    Źródło:
    Metrology and Measurement Systems; 2021, 28, 1; 89-105
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Defect recognition of buried pipeline based on approximate entropy and variational mode decomposition
    Autorzy:
    Ju, Haiyang
    Wang, Xinhua
    Zhang, Tao
    Zhao, Yizhen
    Ullah, Zia
    Powiązania:
    https://bibliotekanauki.pl/articles/221572.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Buried Pipeline
    Defect Recognition
    Geomagnetic Anomaly Detection
    Variational Mode Decomposition
    Approximate Entropy
    Opis:
    The study aimed to examine the use of Geomagnetic Anomaly Detection (GAD) to locate the buried ferromagnetic pipeline defects without exposing them. However, the accuracy of GAD is limited by the background noise. In the present work, we propose an approximate entropy noise suppression (AENS) method based on Variational Mode Decomposition (VMD) for detection of pipeline defects. The proposed method is capable of reconstructing the magnetic field signals and extracting weak anomaly signals that are submerged in the background noise, which was employed to construct an effective detector of anomalous signals. The internal parameters of VMD were optimized by the Scale–Space algorithm, and their anti-noise performance was compared. The results show that the proposed method can remove the background noise in high-noise background geomagnetic field environments. Experiments were carried out in our laboratory and evaluation results of inspection data were analysed; the feasibility of GAD is validated when used in the application to detection of buried pipeline defects.
    Źródło:
    Metrology and Measurement Systems; 2019, 26, 4; 739-755
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

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