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Deep Neural Networks for Defect Detection
Juřica, Tomáš ; Herout, Adam (referee) ; Hradiš, Michal (advisor)
The goal of this work is to bring automatic defect detection to the manufacturing process of plastic cards. A card is considered defective when it is contaminated with a dust particle or a hair. The main challenges I am facing to accomplish this task are a very few training data samples (214 images), small area of target defects in context of an entire card (average defect area is 0.0068 \% of the card) and also very complex background the detection task is performed on. In order to accomplish the task, I decided to use Mask R-CNN detection algorithm combined with augmentation techniques such as synthetic dataset generation. I trained the model on the synthetic dataset consisting of 20 000 images. This way I was able to create a model performing 0.83 AP at 0.1 IoU on the original data test set.
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Inovation of system for electroluminiscence defect detection of solar cells
Lepík, Pavel ; Křivík, Petr (referee) ; Vaněk, Jiří (advisor)
This master thesis analyses the existing methods both practically and theoretically used to detect defected surface area in solar cells. Various methods were used but by using an upgraded CMOS camera without IR filter to implement the electroluminescence method, this has proven to have a very crucial impact on the results. Given the overall results and the acquired information, a procedure with a simple parameter can be setup to carry out the measurements. In addition to this a catalog was formed showing the defects occurring in mono and polycrystalline solar cells.
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Thermovision of photovoltaic modules automatic analysis
Repko, Ilia ; Křivík, Petr (referee) ; Vaněk, Jiří (advisor)
This work deals with the automatic evaluation of thermographic images of photovoltaic modules. In theoretical part of work described main principles of sun's battery work and methods for detection defects, that affecting the quality work, including method thermography, which is based on principle of contactless measuring the surface temperature the observed object. Practical part dedicated to creation of algorithms for detection defects, result is a source code for the program MATLAB.
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Diagnostic Method Used to a Location of Solar Cells Defects
Jandová, Kristýna ; Vaněk, Jiří (advisor)
This doctoral thesis deals with analysis of existing area defect detection methods in solar cells and with concept of its innovation and of the development of faster detection method. Results of measurement is analyzing in practical and theoretical part. The most important is LBIC (Light Beam Induced Current) method innovated of different wavelength light source usage and Electroluminescence method. On the bases of this knowledge is created Fast LBIC method and then is created catalog of defects in monocrystalline silicon solar cells.
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Analyse of photovoltaic solar cells by the photoluminescence method
Baura, Tomáš ; Bača, Petr (referee) ; Vaněk, Jiří (advisor)
This thesis deals with the analysis of solar cells by photoluminescence method. Photoluminescence method is based on the excitation of luminescence radiation of the solar cell material by an external excitation light source. This method can detect various types of defects in the material solar cells. The main objective is the design and realization of a measuring system defects of solar cells, which is based on this method. For excitation of luminescence is used LED array. For the detection of luminescence is used CCD camera with IR optical filter. To filter out the excitation light radiation is used disc screen and optical interrupter. The parameters and options of this measuring system are verified and characterized by test measuring for example the achievable rotation speed of screen and response of optical interrupter. At the end is tested detection of luminescence radiation of solar cells in the measuring system. The measured images are compared with the method of electroluminescence.
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