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Collection system design for multichannel spectrometer
Sovadina, Petr ; Buday, Jakub (referee) ; Novotný, Jan (advisor)
In laser-induced breakdown spectroscopy, the intensity of radiation that enters the spectrometer is crucial. Ideally, the collection of radiation is from a single point of plasma. The greater the intensity of radiation is, the more perspicuous the graph of wavelengths is. Therefore, it is necessary to have the best optimized optical collection system. The existing collection system was not designed for connection to a multichannel spectrometer. The use of the optical multifibre resulted in a collection of radiation from different spots in plasma. Therefore, there was a request for a new optical system designed to collect radiation from a single point of plasma and would be suited for the best collection of radiation. The designed and manufactured collection system was tested. During the test was discovered that the collection system can be calibrated well and allows collection from one point of plasma. The test is considered successful.
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Correction of laser-induced breakdown spectroscopy calibration models for changing ablation energies
Dvořák, Tomáš ; Vrábel, Jakub (referee) ; Képeš, Erik (advisor)
This bachelor thesis investigates transfer learning as a potential method for correcting calibration models based on multilayer perceptron neural networks in laser-induced breakdown spectroscopy due to changes in ablation energies. MLP calibration models for four elements (chromium, nickel, molybdenum and manganese) and six different ablation energies (40, 50, 60, 70, 80 and 90 mJ) were designed and trained. Models initially trained at an ablation energy of 50 mJ were then used to predict concentrations from spectra measured at the different ablation energies. Subsequent differences in the measurements were resolved by applying transfer learning. The results suggest that transfer learning could serve as a valid method for correcting inaccuracies due to differences in ablation energy, achieving comparable results to models trained from scratch in a fraction of the time and at significantly lower computational cost. However, this study could not clearly demonstrate consistent improvements in neural network performance using transfer learning in the context of LIBS. Likely contributing factors are the lack of optimization of the neural networks used, the limited complexity of the experimental dataset, or a combination of both. This research builds on and extends the literature and offers a deeper understanding of the capabilities and limitations of transfer learning in the context of LIBS.
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Collection system design for multichannel spectrometer
Sovadina, Petr ; Buday, Jakub (referee) ; Novotný, Jan (advisor)
In laser-induced breakdown spectroscopy, the intensity of radiation that enters the spectrometer is crucial. Ideally, the collection of radiation is from a single point of plasma. The greater the intensity of radiation is, the more perspicuous the graph of wavelengths is. Therefore, it is necessary to have the best optimized optical collection system. The existing collection system was not designed for connection to a multichannel spectrometer. The use of the optical multifibre resulted in a collection of radiation from different spots in plasma. Therefore, there was a request for a new optical system designed to collect radiation from a single point of plasma and would be suited for the best collection of radiation. The designed and manufactured collection system was tested. During the test was discovered that the collection system can be calibrated well and allows collection from one point of plasma. The test is considered successful.
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