Energy usage evaluation and condition monitoring for electric machines are important in industry for overall energy savings. Traditionally these functions are realized only for large motors in wired systems formed by communication cables and various types of sensors. The unique characteristics of the wireless sensor networks (WSN) make them the ideal wireless structure for low-cost energy management in industrial plants. This work focuses on developing nonintrusive motor-efficiency-estimation methods, which are essential in the wireless motor-energy-management systems in a WSN architecture that is capable of improving overall energy savings in U.S. industry. This work starts with an investigation of existing motor-efficiency-evaluation methods. Based on the findings, a general approach of developing nonintrusive efficiency-estimation methods is proposed, incorporating sensorless rotor-speed detection, stator-resistance estimation, and loss estimation techniques. Following this approach, two new methods are proposed for estimating the efficiencies of in-service induction motors, using air-gap torque estimation and a modified induction motor equivalent circuit, respectively. The experimental results show that both methods achieve accurate efficiency estimates within ¡À2-3% errors under normal load conditions, using only a few cycles of input voltages and currents. The analytical results obtained from error analysis agree well with the experimental results. Using the proposed efficiency-estimation methods, a closed-loop motor-energy-management scheme for industrial plants with a WSN architecture is proposed. Besides the energy-usage-evaluation algorithms, this scheme also incorporates various sensorless current-based motor-condition-monitoring algorithms. A uniform data interface is defined to seamlessly integrate these energy-evaluation and condition-monitoring algorithms. Prototype wireless sensor devices are designed and implemented to satisfy the specific needs of motor energy management. A WSN test bed is implemented. The applicability of the proposed scheme is validated from the experimental results using multiple motors with different physical configurations under various load conditions. To demonstrate the validity of the measured and estimated motor efficiencies in the experiments presented in this work, an in-depth error analysis on motor efficiency measurement and estimation is conducted, using maximum error estimation, worst-case error estimation, and realistic error estimation techniques. The conclusions, contributions, and recommendations are summarized at the end.

This master's thesis describes functionality and principle of the Hefaistos measurement system, which is fully automated and modular. Its purpose is to measure frequency responses of materials and its temperature dependence. The thesis describes all the necessary parts of the modular measurement system. Main part of this system is the control application programmed in LabVIEW software environment. Another necessary parts are impedance analyzers for acquiring frequency dependencies and heating chambers for heating measured materials. The control application ensures hardware synchronization between impedance analyzers and heating chambers. Together they create the Hefaistos system. Modularity of the system means that a user may choose which instrument combination will be used. The system offers choice between three impedance analyzers Agilent 4294A, Wayne Kerr 6520B and HIOKI 3532 LCR Hi-Tester and two heating chambers AOIP GEMINI 700 LRI and AOIP HYPERION. Possibilities of the Hefaistos system are demonstrated on the results of an example measurement.

The master theses deals with a detailed analysis of optical fiber sensors. Specifically, there are discussed optical fibers, various types of sensors and realization optical fiber senzor and senzor system that has been optimized and processed data in real time. In master theses also describes the LabView programming enviroment and uses components, including the entire sensor systém of a sensors system that sends measured data

This master's thesis focuses on the utilization of an artificially created weak magnetic field for navigation in 3D space. The theoretical part of this work deals with the general properties of the magnetic field and with its description. The next section of the theoretical part contains an overview of measuring principles for magnetic field measurements. Based on various types of measuring principles, the thesis elaborates on commercially available miniature sensors for magnetic field measurement with a measuring range up to 10 mT. The work focuses mainly on the magnetoresistive principle and fluxgate sensors. Furthermore, the theoretical part contains descriptions of methods for modeling the magnetic field of simple permanent magnets and various magnet assemblies. Lastly, the theoretical part involves a patent search of devices used for locating magnets that are installed in an intramedullary nail, which is used in intramedullary stabilization used on fractures of human bones. By locating the magnet in the nail, it is possible to precisely determine the position of the mounting holes. The practical part of the thesis deals with the analysis of magnetic field behavior in the vicinity of various magnetic assemblies, which were modeled in COMSOL Multiphysics using the finite element method. The models were created with the aim of analysing the behaviour of the magnetic field in the vicinity of the magnets and at the same time to find possible analytical functions that could be used to determine the position of the magnet in space relative to the probe. The result of this work is an analysis of various assemblies, which contains graphs of different dependencies and prescription of polynomial functions that approximate these dependencies. Another part of the thesis is the design of a probe that serves to locate the magnetic target. The work describes two possible methods of localization. For the differential method, a user interface in LabVIEW was created. The probe based on this method is fully capable of locating the magnet in the 2D plane. The state space search method is described only in theory.

The aim of this thesis was to develop user interface in LabVIEW to make typical measurements with spectral analyzer HP89410A There is introduced the theory of operation of an analogue heterodyne and a digital FFT spectral analyzer. It is explained the background of the Fast Fourier Transform. There are discussed the key settings in measuring with FTT analyzer, like window function, bandwidth, number of frequency points, or the averaging. Further is described the program, which was developed for measuring frequency characteristic by white noise and by stepped measurement. It was also made a module for measuring Signal to Noise Ratio and module for Total Harmonic Distortion. In the last part of this thesis are shown the results of processed exemplar measurements.

This project informs about the basic image processing on grayscale and binary images. The project deals with analyzing the data obtained. Acquaints with terms such as morphology and image segmentation. Acquired knowledge is applied to create a program to complete the processing of microscopic images in LabView programming environment with subsequent analysis and plotting of results into image. For a better idea supporting data about operation in progress are continuous images.

Improved fabrication of poly(vinylindenefluoride)-hexafluoropropylene (PVDF-HFP) thin films is of particular interest due to the high electric coercivity found in the beta-phase structure of the thin film. We show that it is possible to obtain high-quality, beta-phase dominant PVDF-HFP thin films using a direct approach to Langmuir-Blodgett deposition without the use of annealing or additives. To improve sample quality, an automated Langmuir-Blodgett thin film deposition system was developed; a custom dipping trough was fabricated, a sample dipping mechanism was designed and constructed, and the system was automated using custom LabVIEW software. Samples were fabricated in the form of ferroelectric capacitors on substrates of glass and silicon, and implement a unique step design with a bottom electrode of copper with an aluminum wetting layer and a top electrode of gold with an aluminum wetting layer. Samples were then characterized using a custom ferroelectric measurement program implemented in LabVIEW with a Keithley picoammeter/voltage supply to confirm electric coercivity properties. Further characterization using scanning electron microscopy and atomic force microscopy confirmed the improvement in thin film fabrication over previous methods.

This thesis aims to use vibration and acoustic noise analysis to help a production line of a certain motor type to ensure good quality. Noise from the gearbox is sometimes present and the way it is detected is with a human listening to it. This type of error detection is subjective, and it is possible for human error to be present. Therefore, an automatic test that pass or fail the produced Brush Less Direct Current (BLDC)-motors is wanted. Two measurement setups were used. One was based on an accelerometer which was used for vibration measurements, and the other based on a microphone for acoustic sound measurements. The acquisition and analysis of the measurements were implemented using the data acquisition device, compactDAQ NI 9171, and the graphical programming software, NI LabVIEW. Two methods, i.e., power spectrum analysis and machine learning, were used for the analyzing of vibration and acoustic signals, and identifying faults in the gearbox. The first method based on the Fast Fourier transform (FFT) was used to the recorded sound from the BLDC-motor with the integrated planetary gearbox to identify the peaks of the sound signals. The source of the acoustic sound is from a faulty planet gear, in which a flank of a tooth had an indentation. Which could be measured and analyzed. It sounded like noise, which can be used as the indications of faults in gears. The second method was based on the BLDC-motors vibration characteristics and uses supervised machine learning to separate healthy motors from the faulty ones. Support Vector Machine (SVM) is the suggested machine learning algorithm and 23 different features are used. The best performing model was a Coarse Gaussian SVM, with an overall accuracy of 92.25 % on the validation data.

Indiana University-Purdue University Indianapolis (IUPUI) / Improved fabrication of poly(vinylindenefluoride)-hexafluoropropylene (PVDF-HFP) thin films is of particular interest due to the high electric coercivity found in the beta-phase structure of the thin film. We show that it is possible to obtain high-quality, beta-phase dominant PVDF-HFP thin films using a direct approach to Langmuir-Blodgett deposition without the use of annealing or additives. To improve sample quality, an automated Langmuir-Blodgett thin film deposition system was developed; a custom dipping trough was fabricated, a sample dipping mechanism was designed and constructed, and the system was automated using custom LabVIEW software. Samples were fabricated in the form of ferroelectric capacitors on substrates of glass and silicon, and implement a unique step design with a bottom electrode of copper with an aluminum wetting layer and a top electrode of gold with an aluminum wetting layer. Samples were then characterized using a custom ferroelectric measurement program implemented in LabVIEW with a Keithley picoammeter/voltage supply to confirm electric coercivity properties. Further characterization using scanning electron microscopy and atomic force microscopy confirmed the improvement in thin film fabrication over previous methods.

The purpose of this thesis was to design and evaluate The ContexTable, a context-aware system built into a kitchen table. After establishing the current status of the field of context-aware systems and the hurdles and problems being faced, a functioning prototype system was designed and built. The prototype makes it possible to explore established, untested theory and novel solutions to problems faced in the field.