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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:
Possibility of defect detection by eddy current thermography in marine structures
Autorzy:
Świderski, W.
Powiązania:
https://bibliotekanauki.pl/articles/135253.pdf
Data publikacji:
2015
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
infrared thermography
non-destructive testing
marine structures
eddy current
steel
aluminum
Opis:
The main criterion for selecting materials for marine structures is the requirement of strength, which in shipbuilding is met by steels and high strength aluminum alloys. Internal and external forces acting on the hull of the ship have to be considered during the design process. There are also such factors as wave strength and sea conditions, waves hitting into the bow of the ship, vibrations, thermal differences, load displacement, loads caused by starting and landing aircraft on aircraft carriers, loads that occur upon the sudden immersion in and emerging from water in the case of submarines, effects of fatigue, corrosion cracking, etc. Eddy current thermography is a new non-destructive testing technique for detecting cracks in electro conductive materials. It combines the well-established inspection techniques of eddy current testing and thermography. The technique uses induced eddy currents to heat the sample being tested. Defects are then detected by changes in the flow(s) of induced eddy currents, which are revealed by thermal visualization and captured by an infrared (IR) camera. The paper discusses code for the numerical modeling of nondestructive testing by eddy current IR thermography and of IR testing of materials used in marine structures. The ThermoEdCur computer program developed by Vavilov was used to select suitable heating parameters of the tested metal sheet samples in order to detect subsurface defects.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2015, 44 (116); 43-46
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
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:
Dependence of Nanoelectronic-Structure Defect Detection by Cathodoluminescence on Electron Beam Current
Autorzy:
Pluska, M.
Czerwinski, A.
Ratajczak, J.
Szerling, A.
Kątcki, J.
Powiązania:
https://bibliotekanauki.pl/articles/1807514.pdf
Data publikacji:
2009-12
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
78.60.Hk
85.30.De
61.72.-y
Opis:
The dependence of defect detection by cathodoluminescence in a scanning electron microscope on the electron beam current is considered. The examined specimens are AlGaAs/GaAs laser heterostructures with InGaAs quantum well. It is shown that for low electron beam currents, which are typically used, the uniform cathodoluminescence is observed, while for the increasing high electron beam current the oval defects become more and more visible. The influence of electrical properties of the structure on the luminescence detection is explained.
Źródło:
Acta Physica Polonica A; 2009, 116, S; S-86-S-88
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
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:
Influence of thermal signal characteristics on defect detection in GFRP by active optical thermography
Autorzy:
Świderski, W.
Powiązania:
https://bibliotekanauki.pl/articles/247929.pdf
Data publikacji:
2018
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
non-destructive testing
composite material
IR thermography
badania nieniszczące
materiał kompozytowy
termografia IR
Opis:
Advances in technological development, since the 1990s, has been associated with the development of two basic domains of knowledge: information technology and material engineering. The development of material engineering is directly related to composite materials. One group of composite materials are fibre-reinforced composites. Due to their unique properties, they are used in various fields of engineering sectors. Composites reinforced with glass fibre (GFRP) are the second most commonly used composite after carbon fibre reinforced composites (CFRP). GFRP in many cases can replace traditional structural materials, which are usually made from metal. Of course, this material is exposed to damage both in production and operation phases. One method of non-destructive testing that effectively identifies defects in GFRP is active optical thermography. In this method, for thermal stimulation of the tested material, various types of heat sources are used for example: heating lamps, lasers etc. This article analyses the influence of the characteristics of the thermal optical sources on detection of typical defects in GFRP.
Źródło:
Journal of KONES; 2018, 25, 1; 379-383
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel data mining approach for defect detection in the printed circuit board manufacturing process
Autorzy:
Bártová, Blanka
Bína, Vladislav
Powiązania:
https://bibliotekanauki.pl/articles/2105321.pdf
Data publikacji:
2022
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
quality management
defect detection
AOI
PCA
PCB
SVM
zarządzanie jakością
wykrywanie defektów
Opis:
This research aims to propose an effective model for the detection of defective Printed Circuit Boards (PCBs) in the output stage of the Surface-Mount Technology (SMT) line. The emphasis is placed on increasing the classification accuracy, reducing the algorithm training time, and a further improvement of the final product quality. This approach combines a feature extraction technique, the Principal Component Analysis (PCA), and a classification algorithm, the Support Vector Machine (SVM), with previously applied Automated Optical Inspection (AOI). Different types of SVM algorithms (linear, kernels and weighted) were tuned to get the best accuracy of the resulting algorithm for separating good-quality and defective products. A novel automated defect detection approach for the PCB manufacturing process is proposed. The data from the real PCB manufacturing process were used for this experimental study. The resulting PCALWSVM model achieved 100 % accuracy in the PCB defect detection task. This article proposes a potentially unique model for accurate defect detection in the PCB industry. A combination of PCA and LWSVM methods with AOI technology is an original and effective solution. The proposed model can be used in various manufacturing companies as a postprocessing step for an SMT line with AOI, either for accurate defect detection or for preventing false calls.
Źródło:
Engineering Management in Production and Services; 2022, 14, 2; 13--25
2543-6597
2543-912X
Pojawia się w:
Engineering Management in Production and Services
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:
Industrial Application of Deep Neural Network for Aluminum Casting Defect Detection in Case of Unbalanced Dataset
Autorzy:
Awtoniuk, Michał
Majerek, Dariusz
Myziak, Artur
Gajda, Cyprian
Powiązania:
https://bibliotekanauki.pl/articles/2204946.pdf
Data publikacji:
2022
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
machine learning
deep neural network
classification
casting defect
casting defect detection
Opis:
We have developed a deep neural network for casting defect detection. The approach is original because it assumes the use of data related to the casting manufacturing process, i.e. measurement signals from the casting machine, rather than data describing the finished casting, e.g. images. The defects are related to the production of car engine heads made of silumin. In the current research we focused on the detection of defects related to the leakage of the casting. The data came from production plant in Poland. The dataset was unbalanced. It included nearly 38,500 observations, of which only 4% described a leak event. The work resulted in a deep network consisting of 22 layers. We assessed the classification accuracy using a ROC curve, an AUC index and a confusion matrix. The AUC value was 0.97 and 0.949 for the learning and testing dataset, respectively. The model allowed for an ex-post analysis of the casting process. The analysis was based on Shapley values. This makes it possible not only to detect the occurrence of a defect but also to give potential reasons for the appearance of a casting leak.
Źródło:
Advances in Science and Technology. Research Journal; 2022, 16, 5; 120--128
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
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:
Fabric Defect Detection Using the Sensitive Plant Segmentation Algorithm
Wykrywanie defektów tkaniny za pomocą czułego algorytmu segmentacji roślin (SPSA)
Autorzy:
Nisha, M. Fathu
Vasuki, P.
Roomi, S. Mohamed Mansoor
Powiązania:
https://bibliotekanauki.pl/articles/234459.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Tematy:
external stimulation
fabric pattern
sensitive behaviour
texture
zewnętrzna stymulacja
wzór tkaniny
wrażliwe zachowanie
tekstura
Opis:
Fabric quality control and defect detection are playing a crucial role in the textile industry with the development of high customer demand in the fashion market. This work presents fabric defect detection using a sensitive plant segmentation algorithm (SPSA) which, is developed with the sensitive behaviour of the sensitive plant biologically named “mimosa pudica”. This method consists of two stages: The first stage enhances the contrast of the defective fabric image and the second stage segments the fabric defects with the aid of the SPSA. The SPSA proposed was developed for defective pixel identification in non-uniform patterns of fabrics. In this paper, the SPSA was built through checking with devised conditions, correlation and error probability. Every pixel was checked with the algorithm developed to be marked either a defective or non-defective pixel. The SPSA proposed was tested on different types of fabric defect databases, showing a much improved performance over existing methods.
Wraz z rozwojem zapotrzebowania klientów na rynku mody kontrola jakości tkanin i wykrywanie defektów odgrywa kluczową rolę w przemyśle tekstylnym. W pracy przedstawiono wykrywanie defektów tkanin przy użyciu czułego algorytmu segmentacji roślin (SPSA), który został opracowany na podstawie rośliny o nazwie biologicznej „mimosa pudica”. Ta metoda składa się z dwóch etapów. Pierwszy etap to wzmocnienie kontrastu wadliwego obrazu tkaniny, a drugi etap segmentował defekty tkaniny za pomocą SPSA. Proponowana metoda z użyciem SPSA została opracowana do identyfikacji wadliwych pikseli w niejednorodnych wzorach tkanin. W artykule przedstawiono wyniki SPSA, a także dokonano ich weryfikacji pod kątem korelacji i prawdopodobieństwa błędu. Każdy piksel został sprawdzony za pomocą opracowanego algorytmu, tak aby został zaznaczony piksel wadliwy lub nieuszkodzony. Proponowany algorytm SPSA został przetestowany na różnych typach baz danych defektów tkanin i wykazał niezwykłą wydajność w stosunku do istniejących metod.
Źródło:
Fibres & Textiles in Eastern Europe; 2020, 3 (141); 84-87
1230-3666
2300-7354
Pojawia się w:
Fibres & Textiles in Eastern Europe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wykorzystanie badań nieniszczących do wykrywania defektów w skórach naturalnych
Using the non-destructive testing to defect detection in leathers
Autorzy:
Dudzik, S.
Chudzik, S.
Powiązania:
https://bibliotekanauki.pl/articles/266357.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
garbowanie skór
aktywna termografia w podczerwieni
lokalne progowanie adaptacyjne
leather tanning
active infrared thermography
locally adaptive thresholding
Opis:
W pracy zaprezentowano wyniki badań, mających na celu ocenę możliwości wykrywania defektów w skórach naturalnych, z wykorzystaniem aktywnej termografii w podczerwieni. W badaniach użyto czterech próbek skór zawierających wady powstałe w procesie garbowania. Próbki skóry nagrzewano z wykorzystaniem lampy halogenowej i jednocześnie prowadzono rejestrację sekwencji termogramów ich powierzchni. Zarejestrowane termogramy poddano następnie analizie z wykorzystaniem zaawansowanych algorytmów przetwarzania obrazów. W wyniku badań stwierdzono, że aktywna termografia w podczerwieni pozwala na wykrywanie defektów w skórach naturalnych, które nie byłyby możliwe do wykrycia metodami stosowanymi dotychczas. Dodatkowo, zastosowanie zaawansowanych metod przetwarzania obrazów pozwoliło na zautomatyzowanie procesu wykrywania wad.
Natural leathers usually have different defects, resulting from them during the life of the animal, or due to improper skin removal and preservation of leathers. Recognition of defects allows you to assess the quality and determine the suitability of the leathers for particular purposes as well as. In the most commonly used method, the examined leather is spread on a table or a hanger and a subjective evaluation of the defects affecting the homogeneous structure of the hulled natural leather is made by means of the human senses (i.e. the human eye or the human touch). In this paper an experimental study was carried out to evaluate the possibility of detecting defects, arising from tanning, and further processing of natural leather. In experiments, the investigated leather sample was heated and the transient temperature field was recorded by an infrared camera. Finally, the thermograms of the leather surface were processed and the diagnostic information about the defect presence was obtained. In the paper it was found the active thermography is very useful for detection of defects in leathers. Furthermore, the application of advanced image processing methods allowed to fully automate the detection process.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2017, 54; 39-42
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie metod progowania lokalnego do wykrywania defektów z użyciem termografii aktywnej
Application of local thresholding algorithms for defect detection using active thermography
Autorzy:
Dudzik, S.
Sochacka, O.
Powiązania:
https://bibliotekanauki.pl/articles/267010.pdf
Data publikacji:
2018
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
termografia aktywna
badania nieniszczące
wykrywanie defektów
progowanie lokalne
active thermography
non-destructive testing
defect detection
local thresholding
Opis:
W pracy zaprezentowano zastosowanie metod progowania lokalnego do wykrywania defektów z użyciem termografii aktywnej. Przeprowadzono badania eksperymentalne polegające na rejestracji sekwencji termogramów powierzchni badanej próbki materiału dla dwóch wymuszeń cieplnych oraz dwóch faz procesu wymiany ciepła (faza nagrzewania i faza stygnięcia). Sekwencje termogramów uzyskane w badaniach eksperymentalnych zostały poddane binaryzacji z wykorzystaniem lokalnych metod progowania. Do oszacowania efektywności wykrywania defektów za pomocą zaproponowanych metod, zastosowano kryteria oparte na pojęciu błędu klasyfikacji w obszarze defektów i obszarze tła. Na podstawie badań stwierdzono, że największą dokładność uzyskuje się z stosując zmodyfikowaną metodę Bradleya.
The paper presents the application of local thresholding methods for defect detection using active thermography. Experimental studies were performed involving the recording of the sequence of thermograms of the surface of the tested material sample. Experiments were conducted for two different thermal excitations and two phases of the heat transfer process (i.e. heating phase and cooling phase). The thermograms from sequences obtained in experimental studies were then binarized using local thresholding methods. Three following methods were employed: modified Bradley method, median method and Gaussian weighted mean method. To assess the accuracy of defect detection using the proposed algorithms, the criteria based on the concept of classification error in the defected and non-defected areas were applied. In this work it was found that the most accurate method is the modified Bradley method.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2018, 59; 43-46
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Detection of inner defects in industrial pipelines using transient IR thermography
Autorzy:
Kopeć, M.
Chatzipanagiotou, P.
De Mey, G.
Więcek, B.
Powiązania:
https://bibliotekanauki.pl/articles/114312.pdf
Data publikacji:
2017
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
infrared thermography
transient thermal testing
defect detection
polypropylene pipe
Opis:
A long time operation of pipelines can lead to the reduction of their wall thickness. This process is accelerated by high temperature and variable pressure of the transported medium and can finally cause mechanical failures along with leaks and danger of explosion. The aim of this paper is to present a new method for the detection of abraded walls in industrial pipelines using the time-frequency analysis. The results of transient temperature measurements are used for the calculation of the thermal time constants corresponding - as demonstrated - to the pipeline wall thickness.
Źródło:
Measurement Automation Monitoring; 2017, 63, 3; 115-118
2450-2855
Pojawia się w:
Measurement Automation Monitoring
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
Wyświetlanie 1-15 z 43

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