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.
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.
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.
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.
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 deep drawing sheet metal were obtained by means of the traditionally carried out Erichsen cupping test and compared with the results obtained 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.