[comp] Sähkötekniikan korkeakoulu / ELEC

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7th GIM Scientific Workshop at Aalto University School of Electrical Engineering 19.-20.9.2013
(Aalto University, 2013) Älykkäiden koneiden huippuyksikkö GIM.; Halme, Aarne; Forsman, Pekka; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Surfing for Inspiration: digital inspirational material in design practice
(Design Research Society, 2018) Koch, Janin; Laszlo, Magda; Lucero Vera, Andres; Oulasvirta, Antti; Tietoliikenne- ja tietoverkkotekniikan laitos; Department of Communications and Networking; Median laitos; Department of Media; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Taiteiden ja suunnittelun korkeakoulu; School of Arts, Design and Architecture
Over the last decade, many new opportunities have emerged to support creativity and problem-solving in design by finding inspirational materials via the Internet. Online design communities such as those of Behance and Pinterest showcase portfolios and user-made artwork, and they offer support for designers’ day-to-day work to find and collect inspirational material. However, very little is known about how these communities affect inspiration-related practices of professional designers and how designers view them. This paper presents new data on the practices designers employ when seeking digital inspiration sources online and reflecting on, tracking, and managing them in today’s Web design. Current practice and views on sources of inspiration were described based on responses from 51 professional designers. The results suggest that the Internet has become a prevalent source for ideas in design, yet designers experience mounting issues of trust and relatedness with regard to online sources. Therefore, encouraging both should be considered a guiding principle for tools aimed at supporting designers within the realm of design practice.
Augmented Reality in Forest Machine Cabin
(Elsevier B.V., 2017) Palonen, Tuomo; Hyyti, Heikki; Visala, Arto; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Autonomous Systems; Autonomiset järjestelmät; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Augmented reality human machine interface is demonstrated in the cabin of a forest machine outdoors for the first time in real time. In this work, we propose a system setup and a real-time capable algorithm to augment the operator’s visual field with measurements from the forest machine and its environment. In the demonstration, an instrumented forestry crane and a lidar are used to model the pose of the crane and its surroundings. In our approach, a camera and an inertial measurement unit are used to estimate the pose of the operator’s head in difficult lighting conditions with the help of planar markers placed on the cabin structures. Using the estimate, a point cloud and a crane model are superimposed on the video feed to form an augmented reality view. Our system is tested to work outdoors using a forest machine research platform in real time with encouraging initial results.
Uncertainty analysis of intermodulation-based antenna measurements
(Institute of Electrical & Electronics Engineers (IEEE), 2016) Hannula, Jari-Matti; Viikari, Ville; Radiotieteen ja -tekniikan laitos; Department of Radio Science and Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Intermodulation measurement principle has been proposed for characterizing transponder antennas. Although the method seems to offer certain advantages compared to traditional antenna characterization methods, the measurement uncertainty has not yet been well characterized. We aim at identifying the main sources of measurement uncertainty and estimating the achievable accuracy in a certain case at 1 GHz.
Hybrid Microassembly in Environmental Scanning Electron Microscope Using Robotic Manipulator and Adhesives
(Micronano System Workshop, 2014) Liimatainen, Ville; Virta, Antti; Routa, Iiris; Zhou, Quan; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Micro- and Nanorobotics group; Mikro- ja nanorobotiikan ryhmä; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Automatic Speech Recognition for Northern Sámi with comparison to other Uralic Languages
(The Research Group on Artificial Intelligence (RGAI), 2016) Smit, Peter; Leinonen, Juho; Jokinen, Kristiina; Kurimo, Mikko; Signaalinkäsittelyn ja akustiikan laitos; Department of Signal Processing and Acoustics; Speech Recognition Research Group; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Speech technology applications for major languages are becoming widely available, but for many other languages there is no commercial interest in developing speech technology. As the lack of technology and applications will threaten the existence of these languages, it is important to study how to create speech recognizers with minimal effort and low resources. As a test case, we have developed a Large Vocabulary Continuous Speech Recognizer for Northern Sámi, an Finno-Ugric language that has little resources for speech technology available. Using only limited audio data, 2.5 hours, and the Northern Sámi Wikipedia for the language model we achieved 7.6% Letter Error Rate (LER). With a language model based on a higher quality language corpus we achieved 4.2% LER. To put this in perspective we also trained systems in other, better-resourced, Finno-Ugric languages (Finnish and Estonian) with the same amount of data and compared those to state-of-the-art systems in those languages.
Detection and species classification of young trees using machine perception for a semi-autonomous forest machine
(Institute of Electrical & Electronics Engineers (IEEE), 2015) Vihlman, Mikko; Hyyti, Heikki; Kalmari, Jouko; Visala, Arto; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Autonomous systems; Autonomiset järjestelmät; Sähkötekniikan korkeakoulu; School of Electrical Engineering
An approach to automatically detect and classify young spruce and birch trees in forest environment is presented. The method could be used in autonomous or semi-autonomous forest machines during tending operations. Detection is done by segmenting laser range images formed by a rotating laser scanner. Classification is done with a two-class Naive Bayes classifier based on image texture features. Multiple combinations of 99 features were tested and the best classifier included eight features from the co-occurrence matrix, local binary patterns, statistical geometrical features and Gabor filter. 79% of spruces and birches in the testing material were detected and 74% of these were correctly classified. Results suggest that the approach is suitable but there are still some challenges in each of the processing steps. Iteration between segmentation and classification is needed to increase reliability.
Digital implementation of full-order flux observers for induction motors
(European Power Electronics and Drives Association, 2002) Hinkkanen, Marko; Luomi, Jorma; Electric Drives; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Sähkötekniikan korkeakoulu; School of Electrical Engineering
This paper deals with flux estimation for induction motor drives by using a full-order flux observer. A problem of full-order flux observers is their need for computationally demanding discretization methods in order to work stably and accurately at high speeds. An implementation of the full-order flux observer using the stator and rotor fluxes as state variables in the stator reference frame and in the rotor reference frame, respectively, was recently proposed. This paper describes how an observer gain can be included in this structure. It is shown that discretization errors of the proposed implementation are small and that there is more freedom to choose an observer gain, even if the simple forward Euler discretization is used.
Minimizing losses of a synchronous reluctance motor drive taking into account core losses and magnetic saturation
(Institute of Electrical & Electronics Engineers (IEEE), 2014) Qu, Zengcai; Tuovinen, Toni; Hinkkanen, Marko; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
This paper proposes a loss-minimizing controller for synchronous reluctance motor drives. The proposed method takes core losses and magnetic saturation effects into account. The core-loss model consists of hysteresis losses and eddy-current losses. Magnetic saturation is modeled using two-dimensional power functions considering cross coupling between the d- and q-axes. The efficiency optimal d-axis current is calculated offline using the loss model and motor parameters. Instead of generating a look-up table, an approximate function was fitted to the loss-minimizing results. The loss-minimizing method is applied in a motion-sensorless drive and the results are validated by measurements.
Signal-injection assisted full-order observer with parameter adaptation for synchronous reluctance motor drives
(Institute of Electrical & Electronics Engineers (IEEE), 2013) Tuovinen, Toni; Hinkkanen, Marko; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
A back-EMF-based position observer for motion-sensorless synchronous reluctance motor (SyRM) drives is augmented with parameter-adaptation laws for improved low, medium, and high speed operation. The augmented observer is experimentally evaluated using a 6.7-kW SyRM drive under various speeds and load conditions. The analysis and experimental results indicate that the stator-resistance adaptation should be enabled only at low speeds, the d-axis inductance adaptation should be enabled only at medium and high speeds near no load, and the q-axis inductance adaptation should be enabled only at high speeds under high load.
Loss-minimizing control of synchronous reluctance motors — A review
(Institute of Electrical & Electronics Engineers (IEEE), 2013) Qu, Zengcai; Hinkkanen, Marko; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Sähkötekniikan korkeakoulu; School of Electrical Engineering
This paper reviews state-of-the-art loss-minimizing control strategies for synchronous reluctance motors. Methods can be categorized as loss-model controllers (LMCs) and search controllers (SCs). For LMCs, different loss models and the corresponding optimal solutions are summarized. The effects of the core losses and magnetic saturation on the optimal stator current are investigated; magnetic saturation is a more important factor than the core losses. For SCs, different search algorithms are presented and compared. The SCs are evaluated based on their convergence speed, parameter sensitivity, accuracy, and the torque ripple caused by the search process.
Online identification of parameters defining the saturation characteristics of induction machines
(Institute of Electrical & Electronics Engineers (IEEE), 2012) Ranta, Mikaela; Hinkkanen, Marko; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
The induction machine model parameters need to be estimated with good accuracy to ensure a good performance of the drive. Due to the magnetic saturation, the inductances vary as a function of the flux level. The magnetizing curve can be identified at standstill, but more accurate results are obtained if the identification is performed as the machine is running. In this paper, the magnetic saturation is modelled using a power function, and adaptation laws for the function parameters are proposed. The adaptation method is implemented in the control system of a sensorless drive. Experimental results on a 2.2-kW machine show that the identification of the stator inductance is rapid and the accuracy is good.
Inclusion of hysteresis and eddy current losses in nonlinear time-domain inductance models
(Institute of Electrical & Electronics Engineers (IEEE), 2011) Ranta, Mikaela; Hinkkanen, Marko; Belahcen, Anouar; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
A time-domain model including the core losses of a nonlinear inductor is proposed. The model can be seen as a parallel combination of a nonlinear inductance modelling the saturation and a nonlinear resistance modelling the core losses. The desired steady-state core-loss profile is used to determine the resistance function. The model is easy to implement and can be used in many different applications. The hysteresis loop of an electrical steel sample is measured at several frequencies in order to experimentally validate the model. It is shown that the model is able to predict both major and minor hysteresis loops very well.
Analysis and design of a position observer with resistance adaptation for synchronous reluctance motor drives
(Institute of Electrical & Electronics Engineers (IEEE), 2011) Tuovinen, Toni; Hinkkanen, Marko; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
A back-EMF-based reduced-order position observer with stator-resistance adaptation is analyzed for motion-sensorless synchronous reluctance motor drives. Analytical equations for steady-state estimation errors and stability conditions are derived (with and without resistance adaptation), taking into account errors in the parameter estimates. The effect of the observer gain on the noise reduction is studied by means of eigenvector analysis. A robust gain selection is proposed, which maximizes the allowed uncertainties in the parameter estimates. The proposed observer design is experimentally evaluated using a 6.7-kW synchronous reluctance motor drive; stable operation is demonstrated at low speeds under various parameter errors.
A comparison of an adaptive full-order observer and a reduced-order observer for synchronous reluctance motor drives
(Institute of Electrical & Electronics Engineers (IEEE), 2011) Tuovinen, Toni; Hinkkanen, Marko; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
Two back-EMF-based position observers are compared for motion-sensorless synchronous reluctance motor drives. The reduced-order observer is of the second order, and the adaptive full-order observer is of the fourth order. The proposed design rules guarantee the stability of the adaptive full-order observer, if the parameter estimates are accurate. The observers are experimentally evaluated using a 6.7-kW synchronous reluctance motor drive in low-speed operation and under parameter errors. The gain selection of the second-order observer is easier, but the adaptive full-order observer is more robust against parameter variations and spatial harmonics.
A reduced-order position observer with stator-resistance adaptation for synchronous reluctance motor drives
(Institute of Electrical & Electronics Engineers (IEEE), 2010) Tuovinen, Toni; Hinkkanen, Marko; Harnefors, Lennart; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
A reduced-order position observer with stator-resistance adaptation is applied for motion-sensorless synchronous reluctance motor drives. A general analytical solution for the stabilizing observer gain and stability conditions for the stator-resistance adaptation are given. The local stability of the position and stator-resistance estimation is guaranteed at every operating point except the zero frequency, if inductances are known accurately. The observer design is experimentally tested using a 6.7-kW synchronous reluctance motor drive; stable operation at low speeds under various loading conditions is demonstrated.
Analysis and design of a position observer with stator-resistance adaptation for PMSM drives
(Institute of Electrical & Electronics Engineers (IEEE), 2010) Hinkkanen, Marko; Tuovinen, Toni; Harnefors, Lennart; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
This paper deals with reduced-order observers with stator-resistance adaptation for motion-sensorless permanent-magnet synchronous motor drives. An analytical solution for the stabilizing observer gain and stability conditions for the stator-resistance adaptation are derived. The proposed observer design is experimentally tested using a 2.2-kW motor drive; stable operation at very low speeds under different loading conditions is demonstrated.
A reduced-order position observer with stator-resistance adaptation for PMSM drives
(Institute of Electrical & Electronics Engineers (IEEE), 2010) Hinkkanen, Marko; Tuovinen, Toni; Harnefors, Lennart; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
A reduced-order position observer with stator-resistance adaptation is proposed for motion-sensorless permanent-magnet synchronous motor drives. A general analytical solution for the stabilizing observer gain and stability conditions for the stator-resistance adaptation are derived. Under these conditions, the local stability of the position and stator-resistance estimation is guaranteed at every operating point except the zero frequency, if other motor parameters are known. The proposed observer design is experimentally tested using a 2.2-kW motor drive; stable operation at very low speeds under different loading conditions is demonstrated.
Rotor parameter identification of saturated induction machines
(Institute of Electrical & Electronics Engineers (IEEE), 2009) Ranta, Mikaela; Hinkkanen, Marko; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
An induction machine model is proposed for the identification of rotor parameters using high-frequency signal injection. The model includes both the magnetic saturation caused by the fundamental-wave components and the frequency dependence encountered in the signal injection method. Both the skin effect in the rotor winding and the eddy current losses in the rotor core are taken into account. Sinusoidal signal injection is used at several frequencies, and the model parameters are fitted to the results. The rotor leakage inductance and the rotor resistance valid at low slip frequencies are also obtained from the model directly. Experimental results for a 45-kW machine are presented. It is shown that the model fits well to the measured data in various operating points, and the accuracy of the identified parameters is good.
Inclusion of hysteresis and eddy current losses in dynamic induction machine models
(Institute of Electrical & Electronics Engineers (IEEE), 2009) Ranta, Mikaela; Hinkkanen, Marko; Dlala, Emad; Repo, Anna-Kaisa; Luomi, Jorma; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electric Drives; Sähkötekniikan korkeakoulu; School of Electrical Engineering
This paper proposes a method for including both hysteresis losses and eddy current losses in the dynamic space vector model of induction machines. The losses caused by the rotation and magnitude changes of the flux vector are taken into account. The model can be applied, for example, to time-domain simulations and real-time applications such as drive control. Finite element analysis, simulations, and laboratory experiments of a 45-kW motor are used for the investigation. It is shown that the model can predict the iron losses in a wide frequency range. The accuracy is significantly improved as compared to earlier models.

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