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Diagnosis temperature is one of the most important disciplines. We meet it in everyday life, but it is very important for all sectors of industry. This is a measurement providing an immediate state of the measured object. Contact measurement of different temperature sensors and contactless measurement using thermal imagers. The important part is the measurement of temperature rise of induction motor. Part of the work deals with losses in the electric motor. These losses are converted into heat, which affects from various parts of the machine. Correct identification of the temperature field is important in helping to design the cooling system of the instrument. Virtually the data obtained are compared with theoretical data. We will capture part of the device and realize thermal simulations in a suitable simulation program. We propose modifying the cooling machine and the resulting data from the simulation compares.

This thesis is concerned with thermodiagnostics in industrial practise, which is very important for the assessment of technical condition of object on the basis of temperature, in today's time. It includes summary of contact and contact-free methods and their principle, advantages and disadvantages for aplication in industrial practise. Because of thesis it was carried out measurement in company Daikin Device Czech republic with the use of contact thermometer and two available thermocameras for solving of topical tasks relating to production.

Diese Arbeit betrachtet die Wechselwirkung von solarer Einstrahlung mit Wolken in der Atmosphäre. Diese wird insbesondere repräsentiert durch den Wolkenstrahlungseffekt. Hierbei wurde vor allem auf die Auswirkungen von kleinskaliger Variabilität von Wolken und Wolkenfeldern auf die Genauigkeit des Wolkenstrahlungseffektes am Oberrand der Atmosphäre und am Boden Rücksicht genommen. Mit einer Schliessungsstudie ist der modellierte Wolkenstrahlungseffekt mit Schiffsmessungen verglichen worden. Hierbei wurden die Wolkeneigenschaften in dem Modell durch Schiffs- und Satellitendaten als Eingangsdatensatz beschrieben. Ein Zugewinn in der Genauigkeit konnte durch die kombinierte Nutzung beider Datenquellen erzielt werden, konkret durch die Kombination des Flüssigwasserpfads aus Schiffsmessungen und des effektiven Radius aus Satellitenbeobachtungen. Durch die Schliessungsstudie sind zwei Probleme in der Auflösung kleinskaliger Bewölkung und deren Auswirkung auf abgeleitete Wolkeneigenschaften identifiziert worden, die im weiteren Verlauf der Arbeit genauer betrachtet wurden. Ein Vergleich zweier Methoden zur Erkennung des Bedeckungsgrades, jeweils eine vom Boden und eine vom Oberrand der Atmosphäre, hat insgesamt eine gute Übereinstimmung ergeben. Jedoch zeigten sich Abweichungen bei geringer Bedeckung. So wurde bei einem Bedeckungsgrad von ca. 40% in der Hälfte der Fälle den Satellitenbildpunkt als bewölkt klassifiziert. Diese Unsicherheiten in der Klassifikation konnten auf die abgeleitete reflektierte solare Einstrahlung übertragen werden. Für als unbewölkt erkannte, tatsächlich aber bewölkte, Bildpunkte wurde eine mittlere Überschätzung der reflektierte solare Einstrahlung von ca. 30 W/m−2 gefunden. Ebenfalls wurde der Einfluss der zeitlichen Variabilität in der solaren Einstrahlung auf die Bestimmung des Wolkenstrahlungseffektes einer Wolke untersucht. Hierfür wurde ein lineares Modell entwickelt und präsentiert, das die diffuse Einstrahlung mit dem Bedeckungsgrad in Zusammenhang stellt. Das Modell liefert zwei Koeffizienten, die die Variation der diffusen Einstrahlung durch eine Wolke unter der Annahme, dass die beobachtete Wolke den ganzen Himmel bedeckt, beschreiben. Dies ermöglicht einen direkten Vergleich des Wolkenstrahlungseffektes einer beobachteten Wolke mit Modellergebnissen und die Entkopplung von der zeitlich variablen direkten Einstrahlung.

This dissertation revisits, develops, and documents methods that can be used to calibrate spaceborne microwave radiometers once in orbit. The on-orbit calibration methods discussed within this dissertation can provide accurate and early results by utilizing Calibration Attitude Maneuvers (CAM), which encompasses Deep Space Calibration (DSC) and a new use of the Second Stokes (SS) analysis that can provide early and much needed insight on the performance of the instrument. This dissertation describes pre-existing and new methods of using DSC maneuvers as well as a simplified use of the SS procedure. Over TRMM's 17 years of operation it has provided invaluable data and has performed multiple CAMs over its lifetime. These maneuvers are analyzed to implement on-orbit calibration procedures that will be applied for future missions. In addition, this research focuses on the radiometric calibration of TMI that will be incorporated in the final processing (Archive/Legacy of the NASA TMI 1B11 brightness temperature data product). This is of importance since TMI's 17-year sensor data record must be vetted of all known calibration errors so to provide the final stable data for science users, specifically, climatological data records.

Life on Earth is strongly related to the Sun, which makes it a vital star to study and understand. To improve our knowledge of the way the Sun works, many satellites have been launched into space to monitor the Sun‟s activities where the one of main focus is the effect of these activities on the Earth‟s climate; PICARD is one such satellite. Due to the noise associated with SODISM images, the clarity of these images and the appearance of solar features are affected. Image denoising and enhancement are the main techniques to improve the visual appearance of SODISM images. Affective de-noising algorithm methods depend on a proper detecting of noise present in the image. The aim is to identify which type of noise is present in the image. To reach this point, supervised machine-learning (ML) classifier is used to classify the type of noise present in the image. Furthermore, this work introduces a novel technique developed to enhance the quality of SODISM images. In this thesis, the Modified Undecimated Discrete Wavelet Transform (M-UDWT) technique is used to de-noise and enhance the quality of SODISM images. The proposed method is robust and effectively improves the quality of SODISM images, and produces more precise information and clear feature are brought out. In addition, the non wavelet enhancement is developed as well in this thesis. The results of this algorithm is discussed. The new methods are also assessed using two different methods: subjective (by human observation) and objective (by calculation)

<p>The compressive sensing (CS) paradigm provides an efficient image acquisition technique through simultaneous sensing and compression. Since the imaging philosophy in CS imagers is different from conventional imaging systems, new physical structures are required to design cameras suitable for CS imaging.</p> <p>While this work is focused on the hardware implementation of CS encoding for CMOS sensors, the image reconstruction problem of CS is also studied. The energy compaction properties of the image in different domains are exploited to modify conventional reconstruction problems. Experimental results show that the modified methods outperform the 1-norm and TV (total variation) reconstruction algorithms by up to 2.5dB in PSNR.</p> <p>Also, we have designed, fabricated and measured the performance of two real-time and area-efficient implementations of the CS encoding for CMOS imagers. In the first implementation, the idea of active pixel sensor (APS) with an integrator and in-pixel current switches are used to develop a compact, current-mode implementation of CS encoding in analog domain. In another implementation, the conventional three-transistor APS structure and switched capacitor (SC) circuits are exploited to develop the analog, voltage-mode implementation of the CS encoding. With the analog and block-based implementation, the sensing and encoding are performed in the same time interval, thus making a real-time encoding process. The proposed structures are designed and fabricated in 130nm technology. The experimental results confirm the scalability, the functionality of the block read-out, and the validity of the design in making monotonic and appropriate CS measurements.</p> <p>This work also discusses the CS-CMOS sensors for high frame rate CS video coding. The method of multiple-camera with coded exposure video coding is discussed and a new pixel and array structure for hardware implementation of the method is presented.</p> / Doctor of Philosophy (PhD)

For the X-ray astronomy project Advanced Telescope for High ENergy Astrophysics (Athena) wafer-scale DEpleted P-channel Field Effect Transistor (DEPFET) detectors are proposed as Focal Plane Array (FPA) for the Wide Field Imager (WFI). Prototype structures with different pixel layouts, each consisting of 64 x 64 pixels, were fabricated to study four different DEPFET designs. This thesis reports on the results of the electrical and spectroscopic characterization of the different DEPFET designs. With the electrical qualification measurements the transistor properties of the DEPFET structures are investigated in order to determine whether the design intentions are reflected in the transistor characteristics. In addition, yield and homogeneity of the prototypes can be studied on die, wafer and batch level for further improvement of the production technology with regard to wafer-scale devices. These electrical characterization measurements prove to be a reliable tool to preselect the best detector dies for further integration into full detector systems. The spectroscopic measurements test the dynamic behavior of the designs as well as their spectroscopic performance. In addition, it is revealed how the transistor behavior translates into the detector performance. This thesis, as the first systematic study of different DEPFET designs on die and detector level, shows the limitations of the current DEPFET assessment methods. Thus, it suggests a new concise characterization procedure for DEPFET detectors as well as guidelines for expanded testing in order to increase the general knowledge of the DEPFET. With this study of four different DEPFET variants not only designs suitable for Athena mission have been found but also improvement impulses for the starting wafer-scale device production are provided.

Error characteristics associated with satellite-derived precipitation products are important for atmospheric and hydrological model data assimilation, forecasting, and climate diagnostic applications. This information also aids in the refinement of physical assumptions within algorithms by identifying geographical regions and seasons where existing algorithm physics may be incorrect or incomplete. Examination of relative errors between independent estimates derived from satellite microwave data is particularly important over regions with limited surface-based equipments for measuring rain rate such as the global oceans and tropical continents. In this context, analysis of microwave based satellite datasets from the Tropical Rainfall Measuring Mission (TRMM) enables to not only provide information regarding the inherent uncertainty within the current TRMM products, but also serves as an opportunity to prototype error characterization methodologies for the TRMM follow-on program, the Global Precipitation Measurement (GPM) . Most of the TRMM uncertainty evaluation studies focus on the accuracy of rainfall accumulated over time (e.g., season/year). Evaluation of instantaneous rainfall intensities from TRMM orbital data products is relatively rare. These instantaneous products are known to potentially cause large uncertainties during real time flood forecasting studies at the watershed scale. This is more so over land regions, where the highly varying land surface emissivity offers a myriad of complications, hindering accurate rainfall estimation. The error components of orbital data products also tend to interact nonlinearly with hydrologic modeling uncertainty. Keeping these in mind, the present thesis fosters the development of uncertainty analysis using instantaneous satellite orbital data products (latest version 7 of 1B11, 2A25, 2A23, 2B31, 2A12) derived from the passive and active microwave sensors onboard TRMM satellite, namely TRMM Microwave Imager (TMI) and precipitation radar (PR). The study utilizes 11 years of orbital data from 2002 to 2012 over the Indian subcontinent and examines the influence of various error sources on the convective and stratiform precipitation types. Two approaches are taken up to examine uncertainty. While the first approach analyses independent contribution of error from these orbital data products, the second approach examines their combined effect. Based on the first approach, analysis conducted over the land regions of Mahanadi basin, India investigates three sources of uncertainty in detail. These include 1) errors due to improper delineation of rainfall signature within microwave footprint (rain/no rain classification), 2) uncertainty offered by the transfer function linking rainfall with TMI low frequency channels and 3) sampling errors owing to the narrow swath and infrequent visits of TRMM sensors. The second approach is hinged on evaluating the performance of rainfall estimates from each of these orbital data products by accumulating them within a spatial domain and using error decomposition methodologies. Microwave radiometers have taken unprecedented satellite images of earth’s weather, proving to be a valuable tool for quantitative estimation of precipitation from space. However, as mentioned earlier, with the widespread acceptance of microwave based precipitation products, it has also been recognized that they contain large uncertainties. One such source of uncertainty is contributed by improper detection of rainfall signature within radiometer footprints. To date, the most-advanced passive microwave retrieval algorithms make use of databases constructed by cloud or numerical weather model simulations that associate calculated microwave brightness temperature to physically plausible sample rain events. Delineation of rainfall signature from microwave footprints, also known as rain/norain classification (RNC) is an essential step without which the succeeding retrieval technique (using the database) gets corrupted easily. Although tremendous advances have been made to catapult RNC algorithms from simple empirical relations formulated for computational expedience to elaborate computer intensive schemes which effectively discriminate rainfall, a number of challenges remain to be addressed. Most of the algorithms that are globally developed for land, ocean and coastal regions may not perform well for regional catchments of small areal extent. Motivated by this fact, the present work develops a regional rainfall detection algorithm based on scattering index methodology for the land regions of study area. Performance evaluation of this algorithm, developed using low frequency channels (of 19 GHz, 22 GHz), are statistically tested for individual case study events during 2011 and 2012 Indian summer monsoonal months. Contingency table statistics and performance diagram show superior performance of the algorithm for land regions of the study region with accurate rain detection observed in 95% of the case studies. However, an important limitation of this approach is comparatively poor detection of low intensity stratiform rainfall. The second source of uncertainty which is addressed by the present thesis, involves prediction of overland rainfall using TMI low frequency channels. Land, being a radiometrically warm and highly variable background, offers a myriad of complications for overland rain retrieval using microwave radiometer (like TMI). Hence, land rainfall algorithms of TRMM TMI have traditionally incorporated empirical relations of microwave brightness temperature (Tb) with rain rate, rather than relying on physically based radiative transfer modeling of rainfall (as implemented in TMI ocean algorithm). In the present study, sensitivity analysis is conducted using spearman rank correlation coefficient as the indicator, to estimate the best combination of TMI low frequency channels that are highly sensitive to near surface rainfall rate (NSR) from PR. Results indicate that, the TMI channel combinations not only contain information about rainfall wherein liquid water drops are the dominant hydrometeors, but also aids in surface noise reduction over a predominantly vegetative land surface background. Further, the variations of rainfall signature in these channel combinations were seldom assessed properly due to their inherent uncertainties and highly non linear relationship with rainfall. Copula theory is a powerful tool to characterize dependency between complex hydrological variables as well as aid in uncertainty modeling by ensemble generation. Hence, this work proposes a regional model using Archimedean copulas, to study dependency of TMI channel combinations with respect to precipitation, over the land regions of Mahanadi basin, India, using version 7 orbital data from TMI and PR. Studies conducted for different rainfall regimes over the study area show suitability of Clayton and Gumbel copula for modeling convective and stratiform rainfall types for majority of the intraseasonal months. Further, large ensembles of TMI Tb (from the highly sensitive TMI channel combination) were generated conditional on various quantiles (25th, 50th, 75th, 95th) of both convective and stratiform rainfall types. Comparatively greater ambiguity was observed in modeling extreme values of convective rain type. Finally, the efficiency of the proposed model was tested by comparing the results with traditionally employed linear and quadratic models. Results reveal superior performance of the proposed copula based technique. Another persistent source of uncertainty inherent in low earth orbiting satellites like TRMM arise due to sampling errors of non negligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. This study investigates sampling uncertainty of seasonal rainfall estimates from PR, based on 11 years of PR 2A25 data product over the Indian subcontinent. A statistical bootstrap technique is employed to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall was found to exhibit seasonal variations. To give a practical demonstration of the implications of bootstrap technique, PR relative sampling errors over the sub tropical river basin of Mahanadi, India were examined. Results revealed that bootstrap technique incurred relative sampling errors of <30% (for 20 grid), <35% (for 10 grid), <40% (for 0.50 grid) and <50% (for 0.250 grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. In order to study the effect of sampling type on relative sampling uncertainty, the study compares the resulting error estimates with those obtained from latin hypercube sampling. Based on this study, it may be concluded that bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in in-situ validation data. One of the important goals of TRMM Ground Validation Program has been to estimate the random and systematic uncertainty associated with TRMM rainfall estimates. Disentangling uncertainty in seasonal rainfall offered by independent observations of TMI and PR enables to identify errors and inconsistencies in the measurements by these instruments. Motivated by this thought, the present work examines the spatial error structure of daily precipitation derived from the version 7 TRMM instantaneous orbital data products through comparison with the APHRODITE data over a subtropical region namely Mahanadi river basin of the Indian subcontinent for the seasonal rainfall of 6 years from June 2002 to September 2007. The instantaneous products examined include TMI and PR data products of 2A12, 2A25 and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products was quantified based on the performance metrics derived from the contingency table. For the seasonal daily precipitation over 10x10 grids, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition technique, performed to disentangle systematic and random errors, testified that the multiplicative error model representing rainfall from 2A12 algorithm, successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results indicate that even though the radiometer derived 2A12 is known to suffer from many sources of uncertainties, spatial and temporal analysis over the case study region testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered. These findings clearly document that proper characterization of error structure offered by TMI and PR has wider implications in decision making, prior to incorporating the resulting orbital products for basin scale hydrologic modeling. The current missions of GPM envision a constellation of microwave sensors that can provide instantaneous products with a relatively negligible sampling error at daily or higher time scales. This study due to its simplicity and physical approach offers the ideal basis for future improvements in uncertainty modeling in precipitation.

For the X-ray astronomy project Advanced Telescope for High ENergy Astrophysics (Athena) wafer-scale DEpleted P-channel Field Effect Transistor (DEPFET) detectors are proposed as Focal Plane Array (FPA) for the Wide Field Imager (WFI). Prototype structures with different pixel layouts, each consisting of 64 x 64 pixels, were fabricated to study four different DEPFET designs. This thesis reports on the results of the electrical and spectroscopic characterization of the different DEPFET designs. With the electrical qualification measurements the transistor properties of the DEPFET structures are investigated in order to determine whether the design intentions are reflected in the transistor characteristics. In addition, yield and homogeneity of the prototypes can be studied on die, wafer and batch level for further improvement of the production technology with regard to wafer-scale devices. These electrical characterization measurements prove to be a reliable tool to preselect the best detector dies for further integration into full detector systems. The spectroscopic measurements test the dynamic behavior of the designs as well as their spectroscopic performance. In addition, it is revealed how the transistor behavior translates into the detector performance. This thesis, as the first systematic study of different DEPFET designs on die and detector level, shows the limitations of the current DEPFET assessment methods. Thus, it suggests a new concise characterization procedure for DEPFET detectors as well as guidelines for expanded testing in order to increase the general knowledge of the DEPFET. With this study of four different DEPFET variants not only designs suitable for Athena mission have been found but also improvement impulses for the starting wafer-scale device production are provided.