|
|
Involvement of vibrational spectroscopy in the in-situ analysis of PHA in bacterial biomass.
Kevélyová, Barbora ; Samek, Ota (referee) ; Sedláček, Petr (advisor)
The aim of this thesis was the study of polyhydroxyalkanoates in bacterial biomass using the ATR-FTIR method. Furthermore, the PCA method was chosen to evaluate the measured data and observe correlations or differences among the spectra of various biomass samples. The bacterial producents were Aneurinibacillus thermoaerophilus H1, AH30 and AFn2, Cupriavidus malaysiensis DSM 25816, DSM 19416 and DSM 19379 and three strains of Schlegelella thermodepolymerans M 15344, DSM 15264 and LMG 21645. Various heteropolymers with different monomer content and total PHA content were investigated. The monomers in the samples were 3-hydroxybutyrate, 4-hydroxybutyrate, 3-hydroxyvalerate, 4-hydroxyvalerate, 5-hydroxyvalerate and 4-hydroxyhexanoate. As the reference method for accurate quantitative and qualitative determination of polyhydroxyalkanoates in the samples, gas chromatography was performed. The spectra obtained by the FTIR method were compared and significant peaks related to the qualitative properties of PHA, namely monomer composition and crystallinity, were searched for. The PCA statistical method was successfully applied to the collected data from FTIR, with the help of which the qualitative differences between the samples were monitored. The most significant differences were observed in the presence of monomers 4-hydroxybutyrate and 4-hydroxyhexanoate, and they were related to the crystallinity of the samples. The analysis did not show potential for semi-quantitative determination of PHA in biomass. Differences between microorganisms were not observed. The procedure for evaluating FTIR spectra using PCA could in the future be used in the study of biomass containing various monomeric units, especially hydroxyvalerates in case of their higher content within the sample.
|
|
|
Automated tuning of drive controller
Adamec, Matúš ; Pohl, Lukáš (referee) ; Blaha, Petr (advisor)
This thesis deals with automated tuning of drive controller. To achieve this goal, system identification is needed. Therefore, the issue of identification is described at the beginning of this thesis. Spectral analysis was selected from many described methods. It was implemented in Matlab and also in C# language where was used averaging and Blackman-Tukey method. The C# application is linked to Beckhoff TwinCAT 3 and TwinCAT 2 runtime sytems that enable connections with real drive. Next, the problem of drive regulation is discussed and the results of using spectral analysis on real drives are shown. At the end of the thesis is described the algorithm of setting the speed controller with different types of frequency converters.
|
|
| |
|
|
Automatic classification of pronunciation of the letter „R“
Hrušovský, Enrik ; Vičar, Tomáš (referee) ; Harabiš, Vratislav (advisor)
This diploma thesis deals with automatic clasification of vowel R. Purpose of this thesis is to made program for detection of pronounciation of speech defects at vowel R in children. In thesis are processed parts as speech creation, speech therapy, dyslalia and subsequently speech signal processing and analysis methods. In the last part is designed software for automatic detection of pronounciation of vowel R. For recognition of pronounciation is used algorithm MFCC for extracting features. This features are subsequently classified by neural network to the group of correct or incorrect pronounciation and is evaluated classification success.
|
|
| |
|
|
Automatic classification of pronunciation of the letter „R“
Hrušovský, Enrik ; Vičar, Tomáš (referee) ; Harabiš, Vratislav (advisor)
This diploma thesis deals with automatic clasification of vowel R. Purpose of this thesis is to made program for detection of pronounciation of speech defects at vowel R in children. In thesis are processed parts as speech creation, speech therapy, dyslalia and subsequently speech signal processing and analysis methods. In the last part is designed software for automatic detection of pronounciation of vowel R. For recognition of pronounciation is used algorithm MFCC for extracting features. This features are subsequently classified by neural network to the group of correct or incorrect pronounciation and is evaluated classification success.
|
|
|
Automated tuning of drive controller
Adamec, Matúš ; Pohl, Lukáš (referee) ; Blaha, Petr (advisor)
This thesis deals with automated tuning of drive controller. To achieve this goal, system identification is needed. Therefore, the issue of identification is described at the beginning of this thesis. Spectral analysis was selected from many described methods. It was implemented in Matlab and also in C# language where was used averaging and Blackman-Tukey method. The C# application is linked to Beckhoff TwinCAT 3 and TwinCAT 2 runtime sytems that enable connections with real drive. Next, the problem of drive regulation is discussed and the results of using spectral analysis on real drives are shown. At the end of the thesis is described the algorithm of setting the speed controller with different types of frequency converters.
|
guest ::
