Index to NASA Tech Briefs, 1975

This index contains abstracts and four indexes--subject, personal author, originating Center, and Tech Brief number--for 1975 Tech Briefs

Solving the More Difficult Aspects of Electric Motor Thermal Analysis in Small and Medium Size Industrial Induction Motors

With the ever-increasing pressure on electric motor manufacturers to develop smaller and more efficient electric motors, there is a need for more thermal analysis in parallel with the traditional electromagnetic design. Attention to the thermal design can be rewarded by major improvements in the overall performance. Technical papers published to date highlight a number of thermal design issues that are difficult to analyze. This paper reviews some of these issues and gives advice on how to deal with them when developing algorithms for inclusion in design software

Utilizing the Value of Smart Sensor Data in Motor Manufacturing

The topic of this master’s thesis was the utilizing of the value of smart sensor data in motor manufacturing at an electric motor factory in Vaasa. The target company has developed and manufactured smart sensors to customers for years and is now implementing them in its own production. In the thesis’s the possibilities of utilization of the data of smart sensor utilization in the Vaasa factory has been studied through a specified case study. The motors included in the pilot were selected by their usage in the process. The target was to identify improvement potentials for smart sensors in discrete industries and to create a plan for sensor data usage and further development. With the increased value of the efficient data usage, the target is to reduce unplanned stoppages, improve safety, and minimize the penalties and other costs paid because of delayed motors. An additional target was to improve the service and spare part activities with better utilization of data from the sensors as well as define the suitability of current motors in use to their current intended use. The concrete target of this thesis was to create reporting tools to the target company. First, a literature study was carried out for the basics in sensors, smart sensors, and electric motors. Special focus was on the target company’s smart motor sensors and their competitors on the market. With the information available the products were compared to each other. Conclusion were made on the basis of the pilot installation on the target factory’s premises on the value of the smart sensors on discrete production. Through the case study the additional value created to the target company of the smart sensor data was analyzed. A roadmap was created for the smart sensor data for further analyses, storing data and user experience. The outcome of this thesis was several Power BI templates, a fleet report and several recommendations for further development. Through a comparison it was noted that the ABB Ability Smart Sensor TM as a product is slightly more advanced than the smart sensors of the competitors. It was observed that only measuring the data does not bring value to the company, but the data has to be transformed into understandable and visual information and only after that it can bring real value to the company. In the case study it was also noted that actions based on the data created by the sensors can be performed in order to reduce unplanned outages in the motor manufacturing with the predictive data for timing of services and repairs. It was also observed that the data and information provided by the smart sensors can also be utilized in discrete manufacturing on motors that are not continuously used. This is additionally to the knowledge compared to the motors used in process industries where the value of the sensor data was already confirmed in earlier studies.Diplomityön aiheena on kohdeyrityksen älykkään anturin tuottama lisäarvo yhtiön Vaasan moottoritehtaan moottorivalmistuksessa. Kohdeyritys on valmistanut älykkäitä antureita asiakkaille myytäväksi jo useita vuosia ja on nyt käyttöönottamassa tuotteen omassa prosessissaan. Työssä tutkitaan älykkään anturin tuottaman datankäytön mahdollisuuksia kohdeyrityksen Vaasan yksikössä, määritellyn pilotin avulla. Pilottiin valittiin moottorit käyttötarkoituksen mukaan. Tavoitteena on tunnistaa kehittämiskohteita älykkäälle sensorille kappaletavaratuotannossa sekä luoda suunnitelma sensoridatan käytölle ja sen kehittämiseen. Datan tehokkaan käytön tavoitteina on pienentää suunnittelemattomia käyttökatkoksia, parantaa työturvallisuutta ja minimoida moottorien viivästyneiden toimitusten aiheuttamat lisääntyneet rahti ja muut ylimääräiset kustannukset. Lisäksi datankäytön tuomalla lisäarvolla pyritään kehittämään huolto- ja varaosatoimintaa, sekä määrittelemään käytössä olevien moottorien soveltuvuus nykyiseen käyttötarkoitukseensa. Konkreettisena tavoitteena on luoda toimeksiantoyritykselle raportointityökaluja. Työ alussa on kirjallisuuskatsaus anturien, älykkäiden anturien ja sähkömoottoreiden perusteisiin. Erityisesti tarkasteltiin kohdeyrityksen älykkäitä antureita ja sen kilpailijoita. Näitä vertailtiin toisiinsa saatavilla olevan tiedon avulla. Älykkään anturin pilottiasennuksen perusteella tehtiin johtopäätöksiä antureiden soveltuvuudesta kappaletavaratuotantoon esimerkkiyrityksen kautta. Pilotin perusteella pyrittiin analysoimaan tuotteen käyttöönoton kannattavuutta kohdeyritykselle. Lopuksi luotiin tiekartta antureista saatavan datan analysoinnille, tallettamiselle ja esittämiselle. Työn tuloksena syntyi Power BI raportointipohjia ja fleet report sekä kehitysehdotuksia jatkotoimenpiteille. Lisäksi työssä havaittiin, että ABB:n Ability Smart Sensor TM on tuotteena kilpailijoitaan hieman edellä tuotteen ominaisuuksien ja käytettävyyden osalta. Työssä havaittiin, että pelkkä datan mittaaminen sensoreilla ei itsessään tuo lisäarvoa yritykselle, vaan data pitää muuttaa ymmärrettäväksi informaatioksi ja vasta sen jälkeen se tuo lisäarvoa kohdeyritykselle. Edellisten lisäksi pilotissa havaittiin, että anturien tuottaman datan perusteella voidaan tehdä toimenpiteitä, jotta tuotannon suunnittelemattomia katkoksia pystyttäisiin vähentämään käyttämällä Smart Sensorin tuottamia tietoja ennakoivien huoltojen ja korjausten ajastamisessa. Ilmi tuli myös, että Smart Sensoreiden tuottamaa dataa voi käyttää myös kappaletavarateollisuudessa käytössä olevissa moottoreissa, jotka eivät ole jatkuvassa käytössä. Näin on siis prosessiteollisuudessa jatkuvassa käytössä olevien moottorien lisäksi, jossa sensorien tuotta-man datan hyöty on vahvistettu jo aikaisemmin

Electromechanics of an Ocean Current Turbine

The development of a numeric simulation for predicting the performance of an Ocean Current Energy Conversion System is presented in this thesis along with a control system development using a PID controller for the achievement of specified rotational velocity set-points. In the beginning, this numeric model is implemented in MATLAB/Simulink® and it is used to predict the performance of a three phase squirrel single-cage type induction motor/generator in two different cases. The first case is a small 3 meter rotor diameter, 20 kW ocean current turbine with fixed pitch blades, and the second case a 20 meter, 720 kW ocean current turbine with variable pitch blades. Furthermore, the second case is also used for the development of a Voltage Source Variable Frequency Drive for the induction motor/generator. Comparison among the Variable Frequency Drive and a simplified model is applied. Finally, the simulation is also used to estimate the average electric power generation from the 720 kW Ocean Current Energy Conversion System which consists of an induction generator and an ocean current turbine connected with a shaft which modeled as a mechanical vibration system

Model Identification, Updating, and Validation of an Active Magnetic Bearing High-Speed Machining Spindle for Precision Machining Operation

High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) are envisioned to be capable of autonomous self-identification and performance self-optimization for stable high-speed and high quality machining operation. High-speed machining requires carefully selected parameters for reliable and optimal machining performance. For this reason, the accuracy of the spindle model in terms of physical and dynamic properties is essential to substantiate confidence in its predictive aptitude for subsequent analyses.This dissertation addresses system identification, open-loop model development and updating, and closed-loop model validation. System identification was performed in situ utilizing the existing AMB hardware. A simplified, nominal open-loop rotor model was developed based on available geometrical and material information. The nominal rotor model demonstrated poor correlation when compared with open-loop system identification data. Since considerable model error was realized, the nominal rotor model was corrected by employing optimization methodology to minimize the error of resonance and antiresonance frequencies between the modeled and experimental data.Validity of the updated open-loop model was demonstrated through successful implementation of a MIMO u-controller. Since the u-controller is generated based on the spindle model, robust levitation of the real machining spindle is achieved only when the model is of high fidelity. Spindle performance characterization was carried out at the tool location through evaluations of the dynamic stiffness as well as orbits at various rotational speeds. Updated model simulations exhibited high fidelity correspondence to experimental data confirming the predictive aptitude of the updated model. Further, a case study is presented which illustrates the improved performance of the u-controller when designed with lower uncertainty of the model\u27s accurac

Smart Rotating Machines for Structural Health Monitoring

The objective of this thesis is to explore an innovative approach to the on-line health monitoring of rotating machinery in the presence of structural damage using active magnetic bearings (AMBs). First, the detailed model of the rotor with the breathing transverse crack is developed using finite element method. Next, the experimental data from the rotating magnetically levitated healthy and cracked shafts, under specially designed external excitation force, was collected, analyzed and compared with the computer simulation. The obtained results demonstrate that the presented on-line health monitoring technique is very effective for detection of the structural damage in rotating machinery, and it has a potential to be effectively applied in industr