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Monitoring and Analysis of Corrosion of Reinforcing Steel in Reinforced Concrete Elements and Structures Using the Acoustic Methods
Timčaková, Kristýna ; Semerák,, Petr (referee) ; Medveď,, Igor (referee) ; Vaněrek, Jan (referee) ; Chobola, Zdeněk (advisor)
The dissertation thesis deals with the study of non-destructive acoustic methods as instruments for monitoring and analysing corrosion of reinforcing steel in reinforced concrete elements. Four acoustic methods were selected for this task - the impact-echo method, the nonlinear acoustic spectroscopy method, the acoustic emission method, and the ultrasonic pulse velocity method. To verify the functionality of these methods, testing was carried out on three sets of reinforced concrete samples that had been exposed to the effects of sodium chloride, which corroded the embedded steel reinforcement in these samples. Suitable parameters were proposed for individual acoustic methods to monitor corrosion of the reinforcements. In addition, experiments were designed to demonstrate the ability of the selected acoustic methods to reveal the corrosion of steel reinforcement and its influence on the concrete matrix and to assess the condition of the degraded elements and structures. The analysis of the measurement results based on their comparison shows the advantages and disadvantages of the individual methods and of their practical applications. To verify the results, correlation with common methods that are currently used for the study of corrosion was carried out and included for example the electrical resistivity measurement of the reinforcement and simultaneous monitoring of the sample surface using a confocal microscope to record the development of microcracks during the degradation.
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Automatic quality control of painted metal parts production using neural networks
Ježek, Štěpán ; Kolařík, Martin (referee) ; Burget, Radim (advisor)
This thesis is focused on the problem of visual quality control during painted metal parts fabrication. The main problem of the thesis is the design of automatic quality control method based on modern artificial intelligence and computer vision techniques. Quality control is an important part of a large number of industrial production processes, in which it is necessary to ensure compliance with a number of quality requirements for manufactured products. Until now, quality control is carried out mainly by specialized staff, who are subject to a number of expertise requirements. Currently known methods of visual quality control based on artificial intelligence are characterized by high demands on the size of the training data set and low tolerance for a significant change in position and rotation of the inspected objects relative to the scanning device. As a result of these shortcomings, the use of automated visual quality control in many current industrial applications is impossible. The main contribution of this thesis is the design of a new method for quality control, which shows a strong ability to function reliably even in cases where the above mentioned phenomena of change in position, rotation of objects and lack of training data occur during manufacturing. The accuracy of the method proposed in this thesis is experimentally verified on a data set based on the issue of quality control of painted metal parts. According to the measurement results of defect detection accuracy, the proposed method outperformed other, currently known methods by 10, 25 % using the AUROC metric.
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Non-destructive testing of gear-wheels
Krejčí, Martin ; Juliš, Martin (referee) ; Čech, Jaroslav (advisor)
This diploma thesis resolves aplication of particular non-destructive testing methods while producing castings of steel wheels and quality control of this process. There are described fundamentals of flaw detection, determination of flaw-generation cause and suggestions for optimalization of casting process and increasing of its quality.
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Modern trends in radiographic procedures and methods in defectoscopy
Skřivánková, Vendula ; Vlašic, František (referee) ; Juliš, Martin (advisor)
Presented thesis deals with modern trends and techniques in radiographic methods of crack detection which are recently used in engineering practice. In the first part, conventional (analogue) radiography principles based on creating a visible image of tested object to radiographic film are discussed. The next part is aimed to the digital radiography and radioscopy. To digitize existing X-ray film images, application of storage phosphor plates (CR), flat panels (DR) and computed tomography (CT).
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Locating welds defects on cranes.
Zíka, Luboš ; Hála, Michal (referee) ; Kubíček, Jaroslav (advisor)
The diploma thesis deals with the problematics of weld defects of cranes localisation and check. The aim is to analyse non-destructive methods, monitor the occurence of defects and their form and also to suggest the procedure of correction. The work is divided into a theoretical and practical part. In the theoretical part, there is an analysis of individual methods of non-destructive testing that are used for weld check on a particular girder. There is also an analysis of welding technologies used when making a crane girder. The practical part deals with evaluation of weld defects using two methods of non-destructive testing. Furthermore, statistics of defects is realised. In conclusion, the statistics outcome is resumed and evaluated.
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Applied Methods for Transparent Materials Inspection
Horák, Karel ; Honec, Jozef (advisor)
A lot of production lines contain camera inspection systems that increase quality of production. Therefore this presented work deals with applications of computer image processing methods in defectoscopy. Concretely the thesis is concerned with defects evaluation of glass bottles in food operations by the help of visual system BTCAM612, which is in existing configuration installed inland and in several foreign countries. The system is developed in conjunction with developer company CAMEA Ltd. from Brno and it is its sole ownership. The whole process of bottles inspection is described in sequence. First of all it is the hardware acquisition of images of three main controlled parts of bottles – neck, bottom and side. Next chapters are concentrated on image processing and features classification. The features are obtained from image by methods based on detection of in-homogeneities on glass material. Essential part of work is focused on filtration of synthetic patterns from bottles bottoms using function of complex invariants. These patterns are occurred especially in many plants in eastern countries, where marketplace with inspection systems and generally with quality inspection of industrial lines is expanded lately.
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Ultrasound in material diagnostics
Kristek, Michal ; Frk, Martin (referee) ; Kazelle, Jiří (advisor)
Objectives of the semestral project are to study the physical basis of ultra acoustic and comprehend the basics of ultrasound usage in diagnostic of materials. I should also become familiar with functions and usage of ultrasound device EPOCH LT made by OLYMPUS and perform measurement of thickness and speed of ultrasound spreading in selected materials.
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Modern diagnostic methods use in defectoscopy
Vítámvás, Zdeněk ; Stránský, Lubomír (referee) ; Juliš, Martin (advisor)
Nowadays non-destructive testing offers various ways to detection defects in material. By selecting of suitable method or suitable combination of tests we can locate the defect and determine size of defect with sufficient accuracy. For higher probability of detect defects and for easier operation and evaluation are still evolve new ways of inspection. There are summarizes both ordinarily and modern methods using in defectoscopy in this work. There are describe its principles, courses of testing, suitability of use and there are drop next general information.
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Detection of infill defects in 3D printed structures using the DIC method
Doležal, Tomáš ; Halabuk, Dávid (referee) ; Ščerba, Bořek (advisor)
Additive manufacturing offers wide range of advantages. However various internal defects are likely to be formed during the manufacturing process which negatively affect mechanical properties. Detection of those defects is critical to ensure that the manufactured component stays reliable and maintains its dependability throughout its whole life. The potential of the digital image correlation (DIC) method for detect detection in components manufactured using additive technologies has not yet been investigated in the literature. In this master thesis a novel non-destructive defectoscopic method for the internal defect detection in 3D printed structures is presented, based on the evaluation of the strain field obtained by the DIC method. The method was experimentally evaluated on samples with artificial internal defects fabricated by FDM technology. The samples containing defects were successfully visually detected. A convolutional neural network was then used for the defect detection and achieved a classification accuracy of 94,5 %. This methodology has a potential to provide cheap and fast detection of internal defects formed in additive manufactured components in the future although future research is still required.
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Automatic quality control of painted metal parts production using neural networks
Ježek, Štěpán ; Kolařík, Martin (referee) ; Burget, Radim (advisor)
This thesis is focused on the problem of visual quality control during painted metal parts fabrication. The main problem of the thesis is the design of automatic quality control method based on modern artificial intelligence and computer vision techniques. Quality control is an important part of a large number of industrial production processes, in which it is necessary to ensure compliance with a number of quality requirements for manufactured products. Until now, quality control is carried out mainly by specialized staff, who are subject to a number of expertise requirements. Currently known methods of visual quality control based on artificial intelligence are characterized by high demands on the size of the training data set and low tolerance for a significant change in position and rotation of the inspected objects relative to the scanning device. As a result of these shortcomings, the use of automated visual quality control in many current industrial applications is impossible. The main contribution of this thesis is the design of a new method for quality control, which shows a strong ability to function reliably even in cases where the above mentioned phenomena of change in position, rotation of objects and lack of training data occur during manufacturing. The accuracy of the method proposed in this thesis is experimentally verified on a data set based on the issue of quality control of painted metal parts. According to the measurement results of defect detection accuracy, the proposed method outperformed other, currently known methods by 10, 25 % using the AUROC metric.
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