Iowa Crop Progress & Condition, March 5, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, April 18, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, April 11, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, April 25, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, May 2, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, May 9, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Governor Branstad's 2015 Condition of the State Address, January 13, 2015

Speech by Governor Branstad

Iowa Crop Progress & Condition, May 15, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Iowa Crop Progress & Condition, May 23, 2016

Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

Vessel centerline tracking and boundary sgementation in coronary MRA with minimal manual interaction.

Magnetic resonance angiography (MRA) provides a noninvasive means to detect the presence, location and severity of atherosclerosis throughout the vascular system. In such studies, and especially those in the coronary arteries, the vessel luminal area is typically measured at multiple cross-sectional locations along the course of the artery. The advent of fast volumetric imaging techniques covering proximal to mid segments of coronary arteries necessitates automatic analysis tools requiring minimal manual interactions to robustly measure cross-sectional area along the three-dimensional track of the arteries in under-sampled and non-isotropic datasets. In this work, we present a modular approach based on level set methods to track the vessel centerline, segment the vessel boundaries, and measure transversal area using two user-selected endpoints in each coronary of interest. Arterial area and vessel length are measured using our method and compared to the standard Soap-Bubble reformatting and analysis tool in in-vivo non-contrast enhanced coronary MRA images.

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

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.

Control hardware and Condition Monitoring System for Intersector Weld/Cut Robot

Työ sisältää ohjaislaitteiston vertailun ja valinnan rinnakkaisrakenteista robottia varten sekä kunnonvalvontajärjestelmän periaatteiden laadinnan kyseistä robottia varten. Ohjauslaitteisto sisältää teollisuustietokoneen sekä kenttäväylän. Sekä tietokoneesta että väylästä on teoriaosuus ja yksityiskohtaisempi valintaosuus. Teoriaosuudessa selitetään tarkemmin laitteiden toimintaperiaatteista. Valintaosuudessa kerrotaanmiksi jokin tietty laite on valittu käytettäväksi robotin ohjauksessa. Kunnonvalvontateoria ja rinnakkaisrakenteisen robotin kunnonvalvonnan keinot ovat työn toinen osa. Teoriaosa sisältää yleisluonteisen selvityksen vikaantumisesta ja valvonnasta. Erikoisrobotin kunnonvalvonnan keinot esitetään työssä tietyssä järjestyksessä. Ensin esitetään mahdolliset vikatilanteet. Toisessa kohdassa havainnollistetaan vikojen havaitseminen.