This thesis deals with detection of the natural frequencies in the material structures using algorithms working in real-time. It is used for detection of material damage. Is described physic of material, issue of discrete signals and their spectrums and methods for the calculation of the spectral components of the signal. These metods are implemented to Matlab programming environment. Methods are tested with simulated data and real signal.

Ο Έλεγχος Δομικής Ακεραιότητας (ΕΔΤ) μέσω Ακουστικής Εκπομπής, αποτελεί ένα σημαντικό εργαλείο της μηχανικής στην έγκαιρη διάγνωση δομικών σφαλμάτων και στην αύξηση της διάρκειας ζωής κτηρίων. Οι σύγχρονες εφαρμογές συστημάτων ΕΔΤ χαρακτηρίζονται από μεγάλο κόστος εφαρμογής και συντήρησης. Χρησιμοποιώντας νέες τεχνολογίες ολοκληρωμένων συστημάτων χαμηλής κατανάλωσης ισχύος, ασύρματης επικοινωνίας, καθώς επίσης και τεχνικών ψηφιακής επεξεργασίας σημάτων και αναγνώρισης προτύπων, μπορεί να δημιουργηθεί ένα σύστημα ΕΔΤ φθηνό και αποδοτικό. Στόχος μας σε αυτή την διπλωματική είναι η υλοποίηση ενός συστήματος ασύρματων αισθητήρων, ικανών να επιτελέσουν έλεγχο δομικής ακεραιότητας μέσω ακουστικής εκπομπής, χρησιμοποιώντας μικροελεγκτές LPC2148 και πομποδέκτες nRF24L01. / Structural health monitoring with acoustic emission techniques is an important engineering tool in the diagnosis of structural faults. Modern applications of SHM systems are difficult to implement and cost inefficient. By using new integrated systems technologies, wireless communications, coupled with better techniques in signal processing and pattern recognition, a much more cheap and efficient SHM system may be build. Our target in this thesis, is to implement a wireless sensor system, capable of SHM with acoustic emission, by using LPC2148 microcontrollers and nRF24L01 transceivers.

The organic materials used for stator winding insulation are subject to deterioration from thermal, electrical, and mechanical stresses. Stator winding insulation breakdown due to excessive thermal stress is one of the major causes of electric machine failures; therefore, prevention of such a failure is crucial for increasing machine reliability and minimizing financial loss due to motor failure. This work focuses on the development of an efficient and reliable stator winding temperature estimation scheme for small to medium size mains-fed induction machines. The motivation for the stator winding temperature estimation is to develop a sensorless temperature monitoring scheme and provide an accurate temperature estimate that is capable of responding to the changes in the motors cooling capability. A discussion on the two major types of temperature estimation techniques, thermal model-based and parameter-based temperature techniques, reveals that neither method can protect motors without sacrificing the estimation accuracy or motor performance. Based on the evaluation of the advantages and disadvantages of these two types of temperature estimation techniques, a new online stator winding temperature estimation scheme for small to medium size mains-fed induction machines is proposed in this work. The new stator winding temperature estimation scheme is based on a hybrid thermal model. By correlating the rotor temperature with the stator temperature, the hybrid thermal model unifies the thermal model-based and the parameter-based temperature estimation techniques. Experimental results validate the proposed scheme for stator winding temperature monitoring. The entire algorithm is fast, efficient and reliable, making it suitable for implementation in real time stator winding temperature monitoring.

Dizertační práce je zaměřena na softwarově definované přijímače určené k úzkopásmové družicové komunikaci. Komunikační kanály družicových spojů zahrnujících komunikaci s hlubokým vesmírem jsou zatíženy vysokými úrovněmi šumu, typicky modelovaného AWGN, a silným Dopplerovým posuvem signálu způsobeným mimořádnou rychlostí pohybu objektu. Dizertační práce představuje možné postupy řešení výpočetně efektivní digitální downkonverze úzkopásmových signálů a systému odhadu kmitočtu nosné úzkopásmových signálů zatížených Dopplerovým posuvem v řádu násobků šířky pásma signálu. Popis navrhovaných algoritmů zahrnuje analytický postup jejich vývoje a tam, kde je to možné, i analytické hodnocení jejich chování. Algoritmy jsou modelovány v prostředí MATLAB Simulink a tyto modely jsou využity pro ověření vlastností simulacemi. Modely byly také využity k experimentálním testům na reálném signálu přijatém z družice PSAT v laboratoři experimentálních družic na ústavu radioelektroniky.

This diploma thesis deals with the design and implementation of an electronic module for acoustic detection. The module has the task of detecting a predetermined acoustic signals through them learned classification model. The module is used mainly for security purposes. To identify and classify the proposed model using machine learning techniques. Given the possibility of retraining for a different set of sounds, the module becomes a universal sound detector. With acoustic sound using the digital MEMS microphone, for which it is designed and implemented conversion filter. The resulting system is implemented into firmware microcontroller with real time operating system. The various functions of the system are realized with regard to the possible optimization (less powerful MCU or battery power). The module transmits the detection results of the master station via Ethernet network. In the case of multiple modules connected to the network to create a distributed system, which is designed for precise time synchronization using PTP protocol defined by the IEEE-1588 standard.