<p>PolyTech AB in Malmköping manufactures gyro stabilized camera systems or helicopter applications. In this Master´s Thesis a shaker test rig for vibration testing of these systems is designed, implemented and evaluated. The shaker is required to have an adjustable frequency and displacement and different shakers that meet these requirements are treated in a literature study.</p><p>The shaker chosen in the test rig is based on a mechanical solution that is described in detail. Additionally all components used in the test rig are described and modelled. The test rig is identified and evaluated from different experiments carried out at PolyTech, where the major part of the identification is based on data collected from accelerometers.</p><p>The test rig model is used to develop a controller that controls the frequency and the displacement of the shaker. A three-phase motor is used to control the frequency of the shaker and a linear actuator with a servo is used to control the displacement. The servo controller is designed using observer and state feedback techniques.</p><p>Additionally, the mount in which the camera system is hanging is modelled and identified, where the identification method is based on nonlinear least squares (NLS) curve fitting technique.</p>

Background Excess adipose tissue and low physical activity are two major determinants for chronic diseases such as type 2 diabetes and cardiovascular disease.  Understanding these relationships requires accurate and precise measures of body composition and physical activity, and most existing observational studies lack such measures. Paper I to III in this thesis addresses the validity of measures of physical activity and abdominal adipose mass. In paper IV and V, we explore the relationships between obesity and physical activity on metabolic health in non-pregnant and pregnant women and their offspring. Methods and Results Two hundred men and women representative of the Northern Sweden EPIC cohort were recruited for Paper I. A questionnaire on physical activity (PAQ) was validated against objectively measured physical activity energy expenditure (PAEE). A categorical physical activity index (Cambridge index) calculated from PAQ showed strongest correlation with PAEE (r=0.33 p&lt;0.05). In Paper II, abdominal adiposity were assessed in 29 adult men and women using anthropometric measurements, dual energy x-ray absorptiometry (DXA) and ultrasound and were compared to computed tomography (CT). Waist circumference showed the highest correlation with CT-assessed visceral (r=0.85, p&lt;0.0001) and subcutaneous adipose tissue (r=0.86, p&lt;0.0001). Adipose thickness was best assessed with ultrasound. In Paper III, the validity of a wrist-worn triaxial accelerometer was assessed in 32 pregnant and 74 non-pregnant women using double-labeled water method (DLW) as the criterion measure. The output from the accelerometer explained 24% (p &lt;0.001) of the variation in PAEE in non-pregnant and 11% (p&lt;0.05) in the pregnant women. In Paper IV, 35 pregnant and 73 non-pregnant women underwent a 75g oral glucose tolerance test and habitual energy expenditure and physical activity was assessed objectively. Total physical activity was inversely associated with early insulin response in both pregnant (r=-0.47, p=0.007) and non-pregnant (r=-0.36, p=0.004) women. In, Paper V, 32 women and their offspring (n=33) were studied 4 months post-partum. Body composition was quantified using DXA in the women and air-displacement plethysmography  in the infants. Mid-pregnancy weight gain was significantly associated with infant fat mass (r=0.41, p=0.022), whereas late-pregnancy weight gain associated to infant fat-free mass (r=0.37, p=0.04). Conclusion This work describes new methods as well as conventional anthropometric estimates and a questionnaire, that provide relatively strong estimates of body composition and physical activity which could be used in larger studies. Pregnant women were shown to have more sedentary behavior than non-pregnant but physical activity appeared to have equal effect on glucose homeostasis in both groups, which may help guide lifestyle interventions in pregnancy. The impact of weight gain during the different trimesters seems to differentially affect the offspring’s body composition in early infancy, which might give us clues to when different aspects of fetal development and growth occur and how modifiable lifestyle behaviors might be intervened upon to improve long-term health. / Embargo

A Wearable Mobility Monitoring System (WMMS) can be an advantageous device for rehabilitation decision-making. This thesis presents the design and evaluation of a proof-of-concept WMMS that uses the BlackBerry Smartphone platform. A Java program was developed for the BlackBerry 9550, using the integrated tri-axial accelerometer, Global Positioning System sensor (GPS), CMOS digital video camera, and timer to identify change-of-state (CoS) among static states, dynamic states, small activity of daily living (ADL) movements, and car riding. Static states included sitting, lying, standing, and taking an elevator. Dynamic states included walking on level ground, walking on stairs, and walking on a ramp. Small activity of daily living movements included bathroom activities, working in the kitchen, and meal preparation. Following feature extraction from the sensor data, two decision trees were used to distinguish CoS and mobility activities. CoS identification subsequently triggered video recording for improved mobility context analysis during post-processing.

This thesis work designs and implements a wearable system to recognize physical activities and detect fall in real time. Recognizing peoples physical activity has a broad range of applications. These include helping people maintaining their energy balance by developing health assessment and intervention tools, investigating the links between common diseases and levels of physical activity, and providing feedback to motivate individuals to exercise. In addition, fall detection has become a hot research topic due to the increasing population over 65 throughout the world, as well as the serious effects and problems caused by fall.<p> In this work, the Sun SPOT wireless sensor system is used as the hardware platform to recognize physical activity and detect fall. The sensors with tri-axis accelerometers are used to collect acceleration data, which are further processed and extracted with useful information. The evaluation results from various algorithms indicate that Naive Bayes algorithm works better than other popular algorithms both in accuracy and implementation in this particular application.<p> This wearable system works in two modes: indoor and outdoor, depending on users demand. Naive Bayes classifier is successfully implemented in the Sun SPOT sensor. The results of evaluating sampling rate denote that 20 Hz is an optimal sampling frequency in this application. If only one sensor is available to recognize physical activity, the best location is attaching it to the thigh. If two sensors are available, the combination at the left thigh and the right thigh is the best option, 90.52% overall accuracy in the experiment.<p> For fall detection, a master sensor is attached to the chest, and a slave sensor is attached to the thigh to collect acceleration data. The results show that all falls are successfully detected. Forward, backward, leftward and rightward falls have been distinguished from standing and walking using the fall detection algorithm. Normal physical activities are not misclassified as fall, and there is no false alarm in fall detection while the user is wearing the system in daily life.

A Wearable Mobility Monitoring System (WMMS) can be an advantageous device for rehabilitation decision-making. This thesis presents the design and evaluation of a proof-of-concept WMMS that uses the BlackBerry Smartphone platform. A Java program was developed for the BlackBerry 9550, using the integrated tri-axial accelerometer, Global Positioning System sensor (GPS), CMOS digital video camera, and timer to identify change-of-state (CoS) among static states, dynamic states, small activity of daily living (ADL) movements, and car riding. Static states included sitting, lying, standing, and taking an elevator. Dynamic states included walking on level ground, walking on stairs, and walking on a ramp. Small activity of daily living movements included bathroom activities, working in the kitchen, and meal preparation. Following feature extraction from the sensor data, two decision trees were used to distinguish CoS and mobility activities. CoS identification subsequently triggered video recording for improved mobility context analysis during post-processing.

In order to detect movements and vibrations on different appliance, especially robots and self-going devices are used different sensors. One of the most used movement sensors are accelerometers. They are three different types of accelerometers one-axes, two-axes and three-axes. They can be analogue or digital. Husqvarna AB uses an accelerometer to detect movements of their self-going lawnmower Automower. Since it begins to turn up others sensors on the market and the sensor which today uses in Husqvarna’s lawnmower don’t fulfils all functions there is a need to find other solutions. What sensors can be found on a market and which new has come? How can they be used best and which difference is between them? How can they use to detect movements in x, y and z direction and how can they read different movements to detect collision, inclination and lift? Sensor analysis will be done to find out how they can be used in this matter and an big analysis will be done to find out how a sensor witch already is in a lawnmower can be use on the better ways? / För att kunna detektera rörelse och vibrationer på olika anordningar och framförallt robotar och självgående maskiner används olika sensorer. En av de mest använda rörelsesensorer är accelerometer. Det finns en uppsjö av olika utföringar som kan vara med en axel, två axlar eller tre axlar. Accelerometrar finns som digitala eller analoga. Husqvarna AB använder en sådan sensor för att detektera rörelse på sin självgående gräsklippare Automower. Eftersom det börjar dyka upp andra sensorer på marknaden och den sensor som används idag uppfyller inte alla funktioner finns det behov av att lägga tid på att se vad kan åstadkommas med en sådan sensor. Vilka sensorer kan hittas på marknaden och vilka nya har dykt upp? Hur kan de användas på bästa sätt och vad skiljer de åt? Hur kan de användas för att detektera rörelse i x, y, z-led och hur kan de läsa av olika rörelse för att detektera krock, lutning och lyft? Det skall göras analys för att se hur olika sensorer reagerar och hur kan de användas på bästa sätt. Det skall utforskas hur den sensor som redan sitter kan användas på ett bättre sätt.

This thesis approaches the problem of estimating the arm angles of an industrial robot with flexibilities in joints and links. Due to cost-cutting efforts in the industrial robots industry, weaker components and more cost-effective structures have been introduced which in turn has led to problems with flexibilities, nonlinearities and friction. In order to handle these challenging dynamic problems and achieve high accuracy this study introduces state observers to estimate the tool position.The observers use measurements of the motor angles and an accelerometer and the different evaluated observers are based on an Extended Kalman Filter and a deterministic variant. They have been evaluated in experiments on an industrial robot with two degrees of freedom. The experimental verification shows that the state estimates can be highly accurate for medium frequency motions, ranging from 3-30Hz. For this interval the estimate were also robust to model inaccuracies.The estimation of low-frequency motions was relatively poor, due to problemswith drift for the accelerometer, and it also showed a significant dependence on the accuracy of the model. For industrial robots it is mainly the medium frequency motions which are hard to estimate with existing techniques and these observers therefore carries great potential for increased precision.

Volvo Powertrain i Köping tillverkar växellådor till tunga fordon, som lastbilar och bussar. Varje tillverkad växellåda provkörs innan den levereras till kund, det vill säga till något av de bolag inom koncernen som slutmonterar växellådan i fordonet. Provkörningen innehåller ett antal olika automatiserade funktionstester, exempelvis test av oljetryck och test av mjukvaran i växellådans styrbox. Förutom dessa genomförs även ett manuellt kvalitetstest. Den person som provkör växellådan försöker höra eventuella missljud. Ett typiskt fel som upptäcks på detta sätt är ojämnheter på kugghjulen, exempelvis att en av kuggarna har blivit skadad under tillverkningen. En nackdel med att manuellt lyssna efter fel är att nivån för vad som är acceptabelt blir subjektiv. Det är dessutom svårt att på detta sätt avgöra exakt var i växellådan felet sitter, vilket kan leda till att fel komponent byts ut och kasseras vid justering. Efter varje justering krävs en ny provkörning och växellådan kan inte godkännas förrän rätt komponenten är utbytt. Målet med examensarbetet har varit att utveckla ett system som kan detektera fel automatiskt genom att mäta ljud och vibrationer i växellådan. Det är också önskvärt att direkt kunna isolera felkällan till en specifik del av växellådan. Genom att veta på vilket kugghjul felet sitter underlättas justeringen av växellådan, vilket både sparar tid och minskar kassationskostnader. Arbetet har delats in tre huvuddelar: analys, utveckling av mjukvara och utveckling av mätsystem. Första delen var en matematisk analys av hur bidraget från olika rörliga delar i växellådan kan isoleras ur ljud- och vibrationssignaler. För att åstadkomma detta beräknas ett antal tidsmedelvärden på sensorsignalen. Andra delen innebar att utveckla den programvara som sköter felanalysen och validera den. Den tredje delen var att bygga och testa själva mätsystemet och ta fram programvara som styr mätningen och kommunicera med växellådans datorsystem. Feldetekteringssystemet behöver vara snabbt och kunna diagnostisera fel från korta mätserier. Det innebär en extra utmaning eftersom långa mätserier är att föredra speciellt om felen som ska detekteras är små. Resultaten från försöken är lovande och möjligheterna för att utveckla ett komplett system är goda. I undersökningen har felaktiga lådor detekterats och en god felisolering har uppnåtts. I det nuvarande utvecklingsfasen detekterar och isolerar diagnosprogrammet kuggfel på alla axlar. Ytterligare provkörning av växellådor med samma typ av fel behövs dock för att verifiera metoden. Analysprogrammet bör också byggas ut till att omfatta fler typer av fel än de som hittills varit möjligt att arbeta med. Även lagerfel kan detekteras med den utvecklade metoden men det har inte kunnat utvärderas på grund av bristande data. Vi rekommenderar att företaget färdigställer testsystemet då utsikterna för att kunna införa ett automatiskt, kostnadseffektivt och väl fungerande kvalitetskontrollsystem är mycket goda. / Volvo Powertrain in Köping, Sweden produces gearboxes for heavy vehicles such as trucks and busses. Each produced gearbox is tested before delivery. The test run includes a variety of automated function tests, i.e. test of oil pressure. Besides the automated tests a manual quality test is performed. The test person is listening, in order to detect jarring sounds. A typical fault that is detected in this test is gear defects. A disadvantage with manual defect detection is that the acceptance level is subjective. It is also hard to determine which gear that is damaged, sometimes resulting in the wrong gear being replaced and rejected. After a disassembly the gearbox needs to be tested and it can not pass until the damaged gear is replaced. The goal of this thesis work has been to develop a system that can detect defects automatic through sound and vibration measurements of the gearbox. It is also desirable to be able to isolate the source of a defect to a specific gear. With the knowledge of which gear is defective, the reparation of the gearbox is facilitated. This would save time and reduce the defective work expense. The work has been divided into three main parts: analysis, software development and development of measurement system. The first part was a mathematical analysis of how to isolate the contribution from each moving part from the sound or vibration signal respectively. In order to achieve this, a number of time averages is calculated from the sensor signals. The second part was to develop the software that handles the signal processing and diagnosis. The third part was to build and test the measurement system and develop programs which control the measurements and communicate with the gearbox control system. The defect detection system needs to be fast and able to diagnose defects on short series of measurement. The results from the experiments are promising and the potential to develop a complete system is good. The current defect detection system detects and isolates gear defects on all shafts in the gearbox. Additional test runs of gearboxes with similar defects are needed in order to validate the method. Defective bearings are also detectable with the method presented, but this has not been evaluated since appropriate data has been unavailable.

Denna rapport behandlar utveckling av en tvåhjulig balanserande robot. En PID-regulator är implementerad i en mikrokontroller, som även AD-omvandlar en sensorsignal, samt styr motorer via H-bryggor med pulsbreddsmodulering. I rapporten förklaras framtagning av diskret PID-regulator, processorkort, motorkort, val av komponenter och sensor för att mäta robotens vinkel mot ett vertikalplan. Roboten kan balansera stillastående, men behöver kompletteras ytterligare med hjulåterkoppling för att kunna balansera medan den kör. Roboten balanserar med mätdata från en mekanisk golvavkännare (potentiometer). Andra sorters sensorer diskuteras också, t ex accelerometer, gyro och optisk sensor. / This report explain the development of a two wheel balancing robot. A PID-regulator is implemented in a microcontroller, which also AD-converts a sensor signal, and generate pulse width modulated signals to drive H-bridges. It is discussed how to develop a discretisized PID regulator, microcontroller and H-bridge circuit boards, as well as how to chose components and suitable sensors for measuring the robots angle against a vertical plane. The robot is able to balance on its own when standing still, but it need to have feedback from its wheel position if it should be able to maintain balancing when moving. The robot use a mechanical floor feeler (potentiometer). Other sensors are also discussed, e g accelerometer, rate gyro and optical sensor.

This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component. The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system. Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.