Sähköverkkotiedonsiirtomenetelmän kehittäminen taajuusmuuttajaohjattuihin sähkökäyttöihin

Sähkömoottorin jatkuva-aikainen kunnonvalvonta vaatii tiedonsiirtoa moottorilta ylemmälle tietojärjestelmätasolle, kuten taajuusmuuttajalle. Uusien kaapeleiden asennus on työlästä ja kallista. Moottorin ja taajuusmuuttajan välillä on kuitenkin aina kaapeli, jota käytetään moottorin tehonsyöttöön. Tätä kaapelia on mahdollista käyttää myös tiedonsiirtokanavana. Tässä diplomityössä käsitellään ja tutkitaan sähköverkkotiedonsiirtomenetelmää, jonka avulla voidaan muodostaa Ethernet-yhteys moottorilta taajuusmuuttajalle tai toisinpäin. Työssä kehitetään simulointimalli tiedonsiirtokanavan taajuusriippuvan vaimennuksen simuloimiseen. Lisäksi kehitetään kytkentärajapinta, joka mahdollistaa tiedonsiirron kolmivaiheisessa taajuusmuuttajan syöttämässä moottorikaapelissa. Työssä suunnitellaan ja toteutetaan tiedonsiirtoa varten pilot-laitteisto, jolla tehdään laboratoriotestit. Laboratoriotesteillä varmistetaan menetelmän soveltuvuus. Laboratoriotestien avulla etsitään myös reunaehdot tiedonsiirron toiminnalle ja tiedonsiirtonopeuteen vaikuttavia tekijöitä taajuusmuuttajakäytössä. Lisäksi tarkastellaan menetelmän aiheuttamaa viivettä, joka on tärkeäsäätösovellusten kannalta. Lopuksi arvioidaan menetelmän soveltuvuus käytännön sovelluksiin.

Hybrid du/dt-filter in frequency converter applications

The aim of the thesis is to investigate the hybrid LC filter behavior in modern power drives; to analyze the influence of such a du/dt filter on the control system stability. With the implementation of the inverter output RLC filter the motor control becomes more complicated. And during the design process the influence of the filter on the motor should be considered and the filter RLC parameters should be constrained.

Cognitive Auditory Evoked Potentials in Investigation of Hearing Discrimination

Preattentive perception of occasional deviating stimuli in the stream of standard stimuli can be recorded with cognitive event-related potential (ERP) mismatch negativity (MMN). The earlier detection of stimuli at the auditory cortex can be examined with N1 and P2 ERPs. The MMN recording does not require co-operation, it correlates with perceptual threshold, and even complex sounds can be used as stimuli. The aim of this study was to examine different aspects that should be considered when measuring discrimination of hearing with ERPs. The MMN was found to be stimulusintensity- dependent. As the intensity of sine wave stimuli was increased from 40 to 80 dB HL, MMN mean amplitudes increased. The effect of stimulus frequency on the MMN was studied so that the pitch difference would be equal in each stimulus block according to the psychophysiological mel scale or the difference limen of frequency (DLF). However, the blocks differed from each other. The contralateral white noise masking (50 dB EML) was found to attenuate the MMN amplitude when the right ear was stimulated. The N1 amplitude was attenuated and, in contrast, P2 amplitude was not affected by contralateral white noise masking. The perception and production of vowels by four postlingually deafened patients with a cochlear implant were studied. The MMN response could be elicited in the patient with the best vowel perception abilities. The results of the studies show that concerning the MMN recordings, the stimulus parameters and recording procedure design have a great influence on the results.

Surface transformation hardening of carbon steel with high power fiber laser

This study investigated the surface hardening of steels via experimental tests using a multi-kilowatt fiber laser as the laser source. The influence of laser power and laser power density on the hardening effect was investigated. The microhardness analysis of various laser hardened steels was done. A thermodynamic model was developed to evaluate the thermal process of the surface treatment of a wide thin steel plate with a Gaussian laser beam. The effect of laser linear oscillation hardening (LLOS) of steel was examined. An as-rolled ferritic-pearlitic steel and a tempered martensitic steel with 0.37 wt% C content were hardened under various laser power levels and laser power densities. The optimum power density that produced the maximum hardness was found to be dependent on the laser power. The effect of laser power density on the produced hardness was revealed. The surface hardness, hardened depth and required laser power density were compared between the samples. Fiber laser was briefly compared with high power diode laser in hardening medium-carbon steel. Microhardness (HV0.01) test was done on seven different laser hardened steels, including rolled steel, quenched and tempered steel, soft annealed alloyed steel and conventionally through-hardened steel consisting of different carbon and alloy contents. The surface hardness and hardened depth were compared among the samples. The effect of grain size on surface hardness of ferritic-pearlitic steel and pearlitic-cementite steel was evaluated. In-grain indentation was done to measure the hardness of pearlitic and cementite structures. The macrohardness of the base material was found to be related to the microhardness of the softer phase structure. The measured microhardness values were compared with the conventional macrohardness (HV5) results. A thermodynamic model was developed to calculate the temperature cycle, Ac1 and Ac3 boundaries, homogenization time and cooling rate. The equations were numerically solved with an error of less than 10-8. The temperature distributions for various thicknesses were compared under different laser traverse speed. The lag of the was verified by experiments done on six different steels. The calculated thermal cycle and hardened depth were compared with measured data. Correction coefficients were applied to the model for AISI 4340 steel. AISI 4340 steel was hardened by laser linear oscillation hardening (LLOS). Equations were derived to calculate the overlapped width of adjacent tracks and the number of overlapped scans in the center of the scanned track. The effect of oscillation frequency on the hardened depth was investigated by microscopic evaluation and hardness measurement. The homogeneity of hardness and hardened depth with different processing parameters were investigated. The hardness profiles were compared with the results obtained with conventional single-track hardening. LLOS was proved to be well suitable for surface hardening in a relatively large rectangular area with considerable depth of hardening. Compared with conventional single-track scanning, LLOS produced notably smaller hardened depths while at 40 and 100 Hz LLOS resulted in higher hardness within a depth of about 0.6 mm.

Radio-frequency-based measurement methods for bearing current analysis in induction motors

The most common reason for a low-voltage induction motor breakdown is a bearing failure. Along with the increasing popularity of modern frequency converters, bearing failures have become the most important motor fault type. Conditions in which bearing currents are likely to occur are generated as a side effect of fast du/dt switching transients. Once present, different types of bearing currents can accelerate the mechanical wear of bearings by causing deformation of metal parts in the bearing and degradation of the lubricating oil properties.The bearing current phenomena are well known, and several bearing current measurement and mitigation methods have been proposed. Nevertheless, in order to develop more feasible methods to measure and mitigate bearing currents, better knowledge of the phenomena is required. When mechanical wear is caused by bearing currents, the resulting aging impact has to be monitored and dealt with. Moreover, because of the stepwise aging mechanism, periodically executed condition monitoring measurements have been found ineffective. Thus, there is a need for feasible bearing current measurement methods that can be applied in parallel with the normal operation of series production drive systems. In order to reach the objectives of feasibility and applicability, nonintrusive measurement methods are preferred. In this doctoral dissertation, the characteristics and conditions of bearings that are related to the occurrence of different kinds of bearing currents are studied. Further, the study introduces some nonintrusive radio-frequency-signal-based approaches to detect and measure parameters that are associated with the accelerated bearing wear caused by bearing currents.

Effects of Fin Parameters on Gas-Side Heat Transfer Performance of H-Type Finned Tube Bundle in a Waste Heat Recovery Boiler

Alfa Laval Aalborg Oy designs and manufactures waste heat recovery systems utilizing extended surfaces. The waste heat recovery boiler considered in this thesis is a water-tube boiler where exhaust gas is used as the convective heat transfer medium and water or steam flowing inside the tubes is subject to cross-flow. This thesis aims to contribute to the design of waste heat recovery boiler unit by developing a numerical model of the H-type finned tube bundle currently used by Alfa Laval Aalborg Oy to evaluate the gas-side heat transfer performance. The main objective is to identify weaknesses and potential areas of development in the current H-type finned tube design. In addition, numerical simulations for a total of 15 cases with varying geometric parameters are conducted to investigate the heat transfer and pressure drop performance dependent on H-type fin geometry. The investigated geometric parameters include fin width and height, fin spacing, and fin thickness. Comparison between single and double tube type configuration is also conducted. Based on the simulation results, the local heat transfer and flow behaviour of the H-type finned tube is presented including boundary layer development between the fins, the formation of recirculation zone behind the tubes, and the local variations of flow velocity and temperature within the tube bundle and on the fin surface. Moreover, an evaluation of the effects of various fin parameters on heat transfer and pressure drop performance of H-type finned tube bundle has been provided. It was concluded that from the studied parameters fin spacing and fin width had the most significant effect on tube bundle performance and the effect of fin thickness was the least important. Furthermore, the results suggested that the heat transfer performance would increase due to enhanced turbulence if the current double tube configuration is replaced with single tube configuration, but further investigation and experimental measurements are required in order to validate the results.

IoT Based Pain Management using Physiological Parameters

The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.