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The Appliances Immunity to Short Voltage Dips and Interruptions
Bok, Jaromír ; Beláň, Anton (referee) ; Santarius, Pavel (referee) ; Drápela, Jiří (advisor)
This Ph.D. thesis deals with problems about voltage dips and short voltage interruptions, generally named as voltage events, which origin in power supply networks and have a negative influence for all connected electric appliances. In this thesis single phase appliances are considered. These problems closely relate with area of electromagnetic compatibility which solve all questions about correct operation of different types of electric appliances during electromagnetic disturbances impact. Voltage events are ones of the many types of electromagnetic disturbances. The connection between disturbance sources and sensitive electric appliances is created by power supply lines. The immunity of electric appliances to voltage dips and short interruptions is currently tested via voltage dips with strictly defined parameters which are intended by class of electromagnetic environment in which the usage of electric appliance is recommended. During immunity tests the rectangular shape of voltage dips is preferred. The main descriptive parameters of testing voltage events are the residual voltage and the event time duration. But voltage dips and short interruptions defined by this way do not closely relate with parameters of real voltage dips and interruptions occurred in public supply system where parameters of voltage dips are variable. Moreover in the power supply system there are many of others voltage parameters which can have a significant influence to immunity level of connected electric appliances. This Ph.D. thesis also deals with finding more voltage event parameters. Although the voltage events occurrence in the power supply system is not limited and voltage events are considered only as informative voltage parameter it is important to monitor voltage events occurrence. The monitoring device has to be able to operate for ling time period and it has to detect parameters of voltage events with adequate accuracy. The accuracy of detected event parameters and the detection delay depends on the detection algorithm characteristics. That is why the part of this thesis relates with a comparison of several detection algorithms and their abilities to correct detection of voltage event parameters. The main purpose of this thesis is the proposal of connection between classification of voltage dips and short interruptions occurred in power supply system with the classification of electric appliances immunity to these voltage events. On the base of many of provided electric appliances immunity tests and also on the base of long time period voltage events monitoring the special compatibility levels are proposed in this thesis. The observation of proposed compatibility levels will bring the increasing level of reliable operation of all connected electric appliances.
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Deep learning based QRS delineator
Malina, Ondřej ; Hejč, Jakub (referee) ; Smíšek, Radovan (advisor)
This thesis deals with the issue of automatic measurement of the duration of QRS complexes in ECG signals. Special emphasis is then placed on the possibility of automatic detection of QRS complexes while exciting cardiac tissue with a pacemaker. The content of this work is divided into four logical units, where the first part deals with the heart as an organ. It describes the origin and spread of excitement in the heart, its possible pathologies and their manifestations in ECG recording, it also deals with pacing and measuring ECG recording during simultaneous pacing. The second part of the thesis contains a brief introduction to the topic of machine and deep learning. The third part of the thesis contains a search of current approaches using methods based on deep learning to solve the detection of QRSd. The fourth part deals with the design and implementation of its own model of deep learning, able to detect the beginnings and ends of QRS complexes from ECG recordings. It describes the data preprocessing implemented in the MATLAB programming environment. The actual implementation of the model was performed in the Python using the PyTorch and NumPy moduls.
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Modern methods of QRS detection
Fajkus, Jiří ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This bachelor’s thesis deals with methods, which are used for processing of ECG signals, specifically for the detection of QRS complexes. The QRS detection is an essential part of every ECG analysis because it is a source of points with timing information, which are used for classification and measurement of other waves and intervals required for diagnostics. Some ways of QRS detection are described in this work and there is also a description of detector implemented in programming environment MATLAB, which is based on zero crossing counts. This QRS detector was then tested CSE database and signals from Holter examination.
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Diagnosis of Ventricular Tachycardias from Electrocardiogram
Šrutová, Martina ; Hrubeš, Jan (referee) ; Kolářová, Jana (advisor)
The aim of this thesis is a diagnosis of ventricular tachycardias, fibrillations and flutters from electrocardiogram. These disturbances of heart rate are ranked among the life threatening arrhytmias. This work presents own method of the automatic detection, which is created for the ECG holter monitoring system. The proposed algorithm is based on the detection in the spectral domain, which is supported by the detection in the time domain. The results show the discrimination of arrhytmias from the normal sinus rhythm and the discrimination from the noise. The method is tested with ECG records from the The AHA Database (American Heart Association) and from The MIT-BIH Malignant Ventricular Arrhythmia Database.
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Deep learning based QRS delineator
Malina, Ondřej ; Ronzhina, Marina (referee) ; Smíšek, Radovan (advisor)
This thesis deals with the issue of automatic measurement of the duration of QRS complexes in ECG signals. Special emphasis is then placed on the possibility of automatic detection of QRS complexes while exciting cardiac tissue with a pacemaker. The content of this work is divided into four logical units, where the first part deals with the heart as an organ. It describes the origin and spread of excitement in the heart, its possible pathologies and their manifestations in ECG recording, it also deals with pacing and measuring ECG recording during simultaneous pacing. The second part of the thesis contains a brief introduction to the topic of machine and deep learning. The third part of the thesis contains a search of current approaches using methods based on deep learning to solve the detection of QRSd. The fourth part deals with the design and implementation of its own model of deep learning, able to detect the beginnings and ends of QRS complexes from ECG recordings. It describes the data preprocessing implemented in the MATLAB programming environment. The actual implementation of the model was performed in the Python using the PyTorch and NumPy moduls.
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Detection of gunshots from small arms
Nesvadba, Ondřej ; Malucha, Jan (referee) ; Sigmund, Milan (advisor)
This thesis deals with acoustical gunshot detection from small arms, typically of the calibre up to 10 mm, primarily in urban areas. Thesis includes initial research of methods, which are usually used for gunshot detection. The key part of this work is examination of typical values of gunshot signal. Based on the values obtained, decisive parameters in time and frequency domains are determined and detection algorithms are proposed. Function of these algorithms is tested and evaluated. The possible influence of various features of recordings on detection success rate was discussed.
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Deep learning based QRS delineator
Malina, Ondřej ; Ronzhina, Marina (referee) ; Smíšek, Radovan (advisor)
This thesis deals with the issue of automatic measurement of the duration of QRS complexes in ECG signals. Special emphasis is then placed on the possibility of automatic detection of QRS complexes while exciting cardiac tissue with a pacemaker. The content of this work is divided into four logical units, where the first part deals with the heart as an organ. It describes the origin and spread of excitement in the heart, its possible pathologies and their manifestations in ECG recording, it also deals with pacing and measuring ECG recording during simultaneous pacing. The second part of the thesis contains a brief introduction to the topic of machine and deep learning. The third part of the thesis contains a search of current approaches using methods based on deep learning to solve the detection of QRSd. The fourth part deals with the design and implementation of its own model of deep learning, able to detect the beginnings and ends of QRS complexes from ECG recordings. It describes the data preprocessing implemented in the MATLAB programming environment. The actual implementation of the model was performed in the Python using the PyTorch and NumPy moduls.
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Deep learning based QRS delineator
Malina, Ondřej ; Hejč, Jakub (referee) ; Smíšek, Radovan (advisor)
This thesis deals with the issue of automatic measurement of the duration of QRS complexes in ECG signals. Special emphasis is then placed on the possibility of automatic detection of QRS complexes while exciting cardiac tissue with a pacemaker. The content of this work is divided into four logical units, where the first part deals with the heart as an organ. It describes the origin and spread of excitement in the heart, its possible pathologies and their manifestations in ECG recording, it also deals with pacing and measuring ECG recording during simultaneous pacing. The second part of the thesis contains a brief introduction to the topic of machine and deep learning. The third part of the thesis contains a search of current approaches using methods based on deep learning to solve the detection of QRSd. The fourth part deals with the design and implementation of its own model of deep learning, able to detect the beginnings and ends of QRS complexes from ECG recordings. It describes the data preprocessing implemented in the MATLAB programming environment. The actual implementation of the model was performed in the Python using the PyTorch and NumPy moduls.
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The Appliances Immunity to Short Voltage Dips and Interruptions
Bok, Jaromír ; Beláň, Anton (referee) ; Santarius, Pavel (referee) ; Drápela, Jiří (advisor)
This Ph.D. thesis deals with problems about voltage dips and short voltage interruptions, generally named as voltage events, which origin in power supply networks and have a negative influence for all connected electric appliances. In this thesis single phase appliances are considered. These problems closely relate with area of electromagnetic compatibility which solve all questions about correct operation of different types of electric appliances during electromagnetic disturbances impact. Voltage events are ones of the many types of electromagnetic disturbances. The connection between disturbance sources and sensitive electric appliances is created by power supply lines. The immunity of electric appliances to voltage dips and short interruptions is currently tested via voltage dips with strictly defined parameters which are intended by class of electromagnetic environment in which the usage of electric appliance is recommended. During immunity tests the rectangular shape of voltage dips is preferred. The main descriptive parameters of testing voltage events are the residual voltage and the event time duration. But voltage dips and short interruptions defined by this way do not closely relate with parameters of real voltage dips and interruptions occurred in public supply system where parameters of voltage dips are variable. Moreover in the power supply system there are many of others voltage parameters which can have a significant influence to immunity level of connected electric appliances. This Ph.D. thesis also deals with finding more voltage event parameters. Although the voltage events occurrence in the power supply system is not limited and voltage events are considered only as informative voltage parameter it is important to monitor voltage events occurrence. The monitoring device has to be able to operate for ling time period and it has to detect parameters of voltage events with adequate accuracy. The accuracy of detected event parameters and the detection delay depends on the detection algorithm characteristics. That is why the part of this thesis relates with a comparison of several detection algorithms and their abilities to correct detection of voltage event parameters. The main purpose of this thesis is the proposal of connection between classification of voltage dips and short interruptions occurred in power supply system with the classification of electric appliances immunity to these voltage events. On the base of many of provided electric appliances immunity tests and also on the base of long time period voltage events monitoring the special compatibility levels are proposed in this thesis. The observation of proposed compatibility levels will bring the increasing level of reliable operation of all connected electric appliances.
|
|
|
Modern methods of QRS detection
Fajkus, Jiří ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This bachelor’s thesis deals with methods, which are used for processing of ECG signals, specifically for the detection of QRS complexes. The QRS detection is an essential part of every ECG analysis because it is a source of points with timing information, which are used for classification and measurement of other waves and intervals required for diagnostics. Some ways of QRS detection are described in this work and there is also a description of detector implemented in programming environment MATLAB, which is based on zero crossing counts. This QRS detector was then tested CSE database and signals from Holter examination.
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