This thesis reports the development of micromachined accelerometers and gyroscopes that can be used for micromachined inertial measurement units (IMUs). Micromachined IMUs started to appear in the market in the past decade as low cost, moderate performance alternative in many inertial applications including military, industrial, medical, and consumer applications. In the framework of this thesis, a number of accelerometers and gyroscopes have been developed in three different fabrication processes, and the operation of these fabricated devices is verified with extensive tests. In addition, the fabricated accelerometers were combined with external readout electronics to obtain hybrid accelerometer systems, which were tested in industrial test facilities. The accelerometers and gyroscopes are designed and optimized using the MATLAB analytical simulator and COVENTORWARE finite element simulation tool. First set of devices is fabricated using a commercial foundry process called SOIMUMPs, while the second set of devices is fabricated using the electroplating processes developed at METU-MET facilities. The third set of devices is designed for a new advanced process based on DRIE, which is under development. Mechanical and electrical test results of the fabricated accelerometers and gyroscopes are in close agreement with the designed values. The testing of the SOI and nickel accelerometers is also performed in industrial test environments. In order to perform these tests, accelerometers are hybrid connected to commercially available capacitive readout circuits. These accelerometer systems require only two DC supply voltages for operation and provide an analog output voltage related to the input acceleration. The industrial tests show that the SOI accelerometer system yields a 799 &micro / g/&amp / #8730 / Hz average noise floor, a 1.8 mg/&amp / #8730 / Hz peak noise floor, a 22.2 mV/g sensitivity, and a 0.1 % nonlinearity, while the nickel accelerometer system yields a 228 &micro / g/&amp / #8730 / Hz average noise floor, a 375 &micro / g/&amp / #8730 / Hz peak noise floor, a 1.02 V/g sensitivity, and a 0.23 % nonlinearity. Long-term drift components of the accelerometers are determined to be smaller than 20 mg. These systems are the highest performance micromachined accelerometer systems developed in Turkey, and they can be used in implementation of a national inertial measurement unit.

La fatigue est un phénomène bien connu dans le monde du sport provoquant une chute des performances et une augmentation du risque de blessures. La communauté scientifique s’intéresse donc à la quantification de ce phénomène au moyen de différents outils d’analyse du mouvement. Cependant certains sports comme la course à pied soumettent les athlètes à des sollicitations mécaniques violentes impactant fortement sur leur santé et leurs performances. Ces sollicitations se traduisent souvent par des chocs importants, un nombre de cycles élevé et sont accompagnées de postures complexes du corps. Les outils d’analyse du mouvement ne sont alors pas toujours adaptés pour la mesures de ces données ni à l’étude du mouvement de l’athlète dans des conditions réelles de pratique. L’accélération apparait alors comme une caractéristique riche en informations. Elle peut permettre de mesurer et d’analyser la pratique de la course à pied afin de quantifier la dérive de la réponse mécanique du corps humain. Par la validation d’outils issus de l’accélérométrie, ces travaux de thèse permettront d’étudier les phénomènes mécaniques intervenant durant la pratique de la course à pied afin de quantifier et prédire leurs effets sur les phénomènes de fatigue des athlètes. / Fatigue is a well known phenomenon in the sports world causing a decrease of performance and an increase of injury risk. The scientific community is therefore concerned with the quantification of this phenomenon using different motion analysis tools. However some sports like running inflict violent mechanical loads to the athletes strongly impacting their health and performance. These loads frequently result in significant shocks, a high number of cycles and are accompanied by complex postures of the body. The motion analysis tools are then not always suitable for the measurement of this information or to study the athlete’s movement in real conditions of practice. The acceleration then appears as a feature rich in information.It can allow to measure and analyze the practice of running in order to quantify the drift of the mechanical response of the human body. By validating accelerometric tools, these thesis works will allow to study the mechanical phenomena intervening in the practice of running in order to quantify and predict their effects on the athlete’s fatigue.

The main subject of this thesis is use of inertial sensors for better motion and stability control of mobile robots. In background research are described the basic methods of mobile robots localization. Second part of background research is about mobile robot stability, in this part are described the methods of mobile robots stability control. In next part is description of MEMS accelerometers and gyroscopes and description of basic method of filtering and integration which are useful for input processing of these sensors. Thesis continues with inertial sensors analysis for application on control of wheeled and legged mobile robots. In end of thesis are specified the experiment results, which confirm the applicability of sensors for mobile robot control.

QC 20110412

In the field of mechatronics, different types of robotic arms are used for various applications. Control of robotic arms from a distance is required in certain situations, such as hazardous environments. The purpose of this thesis was to investigate the feasibility, speed, and accuracy of the movement of a robotic arm following the movement of one handheld Inertial Measuring Unit (IMU). The assessment of accuracy was determined through experiments with pre-established movements and examined responses from the arm. The robot arm has four degrees of freedom and is controlled by integrating and filtering the IMU data to obtain the linear position, and inverse kinematics are used to obtain the arm joint angles required to reach the position. The robotic arm was constructed using Solid Edge 3D CAD, 3D printed in PLA plastic. After construction electronic components were connected and assembled. The programs were implemented in MATLAB, and the data was processed and transferred through the Arduino Integrated Development Environment (IDE). The results indicate that the robotic arm demonstrates good capability in executing given coordinates. The accuracy of the IMU-based position tracking is inconsistent and not suitable for all applications. The system's total speed for reading and executing movements is found to be satisfactory, but improvements in precision are necessary for more demanding implementations. The primary causes of errors in the system are attributed to the precision of the measuring device, manufacturing deviations, and limitations in the IMU calculation. This study contributes to the understanding of linear position tracking using inertial sensors, filtering techniques, and communication between microcontrollers, providing insights for future research and development in the field. / Inom området mekatronik används olika typer av robotarmar för olika tillämpningar. Kontroll av robotarmar på avstånd krävs i situationer som farliga miljöer. Syftet med denna avhandling var att undersöka genomförbarhet, hastighet och rörelseprecision hos en robotarm som följer rörelsen av en handhållen tröghetsmätningsenhet (IMU). Bedömningen av noggrannheten fastställdes genom experiment med förutbestämda rörelser och undersökta svar från armen. Robotarmen har fyra frihetsgrader och styrs genom att integrera och filtrera IMU-data för att erhålla den linjära positionen, och inverskinematik används för att erhålla de nödvändiga armledsvinklarna för att nå positionen. Robotarmen konstruerades med hjälp av Solid Edge 3D CAD, 3D-utskrivet i PLA-plast och elektroniska komponenter monterades. Programmen implementerades i MATLAB och data bearbetades och överfördes via Arduino Integrated Development Environment. Resultaten visar att robotarmen har god förmåga att utföra givna koordinater, men noggrannheten i IMU-baserad positionsspårning är inkonsekvent och inte lämplig för alla tillämpningar. Systemets totala hastighet för att läsa av och utföra rörelser anses vara tillfredsställande, men förbättringar av precisionen är nödvändiga för mer krävande implementeringar. De främsta orsakerna till fel i systemet tillskrivs precisionen hos mätinstrumentet, tillverkningsavvikelser och begränsningar i IMU-beräkningen. Denna studie bidrar till förståelsen av linjär positionsspårning med tröghetssensorer, filtreringstekniker och kommunikation mellan mikrokontroller, vilket ger insikter för framtida forskning och utveckling inom området.

One of the causes of work-related Musculoskeletal Disorders (MSDs) is the manual handling of heavy objects. To reduce the risk of such injuries, workers are instructed to follow general guidelines on how to lift and carry objects depending on their mass. Current ergonomic assessments using wearable sensors can differentiate correct from incorrect body postures but are limited. Being able to estimate the mass of an object during ergonomic assessment would be a great improvement. This work investigates a combination of Inertial Measurement Units (IMUs) and Electromyography (EMG) sensors for offline estimation of an object’s mass for different movements. 10 participants performed 26 lifting and carrying trials with loads from 0 to 19 kg, while wearing a 17IMU motion capture system and EMG sensors on both biceps brachii and both erector spinae. Two methods were considered to estimate the carried mass: (1) supervised machine learning and (2) musculoskeletal modeling. First, the data was used to select features, train, and compare regression models. The lowest Mean Squared Error (MSE) for 10-fold cross-validation for lifting and carrying combined was 5.8113 for a Gaussian Process Regression (GPR) model with an exponential kernel function. Then, a MSE of 4.42 and a Mean Absolute Error (MAE) of 1.63 kg were obtained also with a GPR for Leave-One-Subject-Out Cross-Validation (LOSOCV) only for lifting and frontal carrying trials. For the same trials, the upper-extremity musculoskeletal model, scaled to each participant, estimated the mass with a MSE of 1.78 and a MAE of 0.95 kg. The study was restricted to lifting and frontal carrying, but the combination of the two technologies showed great potential for object mass estimation.

Work-related musculoskeletal disorders constitutes a substantial burden for society, generating individual suffering and financial costs. Quantifying the musculoskeletal stress and establishing exposure-response relationships is an important step in facing this problem. Observational methods for assessing exposure in the field of ergonomics have shown poor results, and the technical measurement methods that exists are often complicated to use which limits their scope to scientific purposes. This work describes the development of a prototype measurement system aimed to simplify ambulatory measurements of musculoskeletal load, specifically aimed at the wrist and hand. Wearable sensors including Inertial Measurement Units (IMU:s) and Electromyography (EMG) were connected to a smartphone and used for measuring wrist movement and forearm muscle activity. Data sampled in the smartphone was stored online in a cloud database, and a webapplication was developed to visualize work-load exposure. Testing under controlled conditions indicated that muscular rest can be measured and classified according to suggested risk thresholds. Accurate angular measurements were difficult to implement because of lacking inter-sensor alignment in the horizontal plane, as well as uncertainties in the Bluetooth protocol. Future work should focus on the IMU:s and look to further develop a method of correcting the relative angle error, as well as investigating accurate time synchronization of the two sensors.Alternatively, deriving angular velocities directly from the IMU gyroscopes could be investigated.

Ergonomic assessments to determine risks of work-related musculoskeletal disorders as well as to compare designs of work-tasks and workstations, are imperative for high sustainability and productivity in any given industry. Hence, assessment tools that can objectively and reliably capture postures, joint angles and muscle activities play very important role in properly determining risks relating to work and various tasks. The introduction of direct measurement instruments/tools has been helping and continue to help improve upon observational assessment methods to attain objectivity and reliability. This project aimed at contributing to future improvements of industrial risk assessment measures in ergonomics by identifying and testing direct measurement instruments/tools that can enhance observational risk assessment methods and introduce a new way of signal processing, hence, reducing assessment time while increasing objectivity and reliability. Several candidate instruments were identified and out of the identified, ten were selected as potential candidates. Two out of the ten, Wergonic and ErgoHandMeter were then selected and tested on common observation risk assessment factors that could be measured and answers provided directly or by analyses. The Wergonic instrument was modified to enhance its measuring capability from one fully and partially two factors to six factors. New algorithms were also employed to analyse measurements of the ErgoHandMeter in order to answer questions regarding repetitive movements. The two instruments tested, are able to measure and provide results for six commonly and one rarely assessed biomechanical risk factors. By combining selected potential candidates, many of the commonly targeted biomechanical risk factors in observational instruments can be measured by the selected direct measurement instruments. However, some factors especially force measurement remain a challenge for measuring by direct wearable sensor instruments.

System identification is used in engineering sciences to build mathematical models from data. A common issue in system identification problems is that the true inputs to the system are not fully known. In this thesis, existing approaches to unknown input problems are classified and some of their properties are analyzed.  A new indirect framework is proposed to treat system identification problems with unknown inputs. The effects of the unknown inputs are assumed to be measured through possibly unknown dynamics. Furthermore, the measurements may also be dependent on other known or measured inputs and can in these cases be called indirect input measurements. Typically, these indirect input measurements can arise when a subsystem of a larger system is of interest and only a limited set of sensors is available. Two examples are when it is desired to estimate parts of a mechanical system or parts of a dynamic network without full knowledge of the signals in the system. The input measurements can be used to eliminate the unknown inputs from a mathematical model of the system through algebraic manipulations. The resulting indirect model structure only depends on known and measured signals and can be used to estimate the desired dynamics or properties. The effects of using the input measurements are analyzed in terms of identifiability, consistency and variance properties. It is shown that cancelation of shared dynamics can occur and that the resulting estimation problem is similar to errors-in-variables and closed-loop estimation problems because of the noisy inputs used in the model. In fact, the indirect framework unifies a number of already existing system identification problems that are contained as special cases. For completeness, an instrumental variable method is proposed as one possibility for estimating the indirect model. It is shown that multiple datasets can be used to overcome certain identifiability issues and two approaches, the multi-stage and the joint identification approach, are suggested to utilize multiple datasets for estimation of models. Furthermore, the benefits of using the indirect model in filtering and for control synthesis are briefly discussed.  To show the applicability, the framework is applied to the roll dynamics of a ship for tracking of the loading conditions. The roll dynamics is very sensitive to changes in these conditions and a worst-case scenario is that the ship will capsize.  It is assumed that only motion measurements from an inertial measurement unit (IMU) together with measurements of the rudder angle are available. The true inputs are thus not available, but the measurements from the IMU can be used to form an indirect model from a well-established ship model. It is shown that only a subset of the unknown parameters can be estimated simultaneously. Data was collected in experiments with a scale ship model in a basin and the joint identification approach was selected for this application due to the properties of the model. The approach was applied to the collected data and gave promising results. / Till skillnad från många andra industrier där avancerade styrsystem har haft en omfattande utveckling under de senaste decennierna så har styrsystem för skepps- och marinindustrin inte alls utvecklats i samma utsträckning. Det är framförallt under de senaste 10 åren som lagkrav och stigande driftskostnader har ökat intresset för effektivitet och säkerhet genom användning av styrsystem. Rederier och den marina industrin är nu intresserade av hur de avancerade styrsystem som används inom andra områden kan tillämpas för marina ändamål. Huvudmålet är typiskt att minska den totala energianvändningen, och därmed också bränsleförbrukningen, genom att hela tiden planera om hur skeppet skall användas med hjälp av ny information samt styra skeppet och dess ingående system på ett sätt som maximerar effektiviteten. För många av dessa avancerade styrsystem är det grundläggande att ha en god förståelse för beteendet hos det systemet som skall styras. Ofta används matematiska modeller av systemet för detta ändamål. Sådana modeller kan skapas genom att observera hur systemet reagerar på yttre påverkan och använda dessa observationer för att finna eller skatta den modell som bäst beskriver observationerna. Observationerna är mätningar som görs med så kallade sensorer och tekniken att skapa modeller från mätningarna kallas för systemidentifiering. Detta är i grunden ett utmanande problem och det kan försvåras ytterligare om de sensorer som behövs inte finns tillgängliga eller är för dyra att installera. I denna avhandling föreslås en ny teknik där de mätningar som finns tillgängliga används på ett nytt och annorlunda sätt. Detta kan minska mängden nödvändiga sensorer eller möjliggöra användandet av alternativa sensorer i modell-framtagningen. Med hjälp av denna nya teknik kan enkla sensorer användas för att skatta en matematisk modell för en del av skeppet på ett sätt som inte är möjligt med traditionella metoder. Genom att skatta denna modell kan fysikaliska egenskaper hos skeppet, så som dess massa och hur massan är fördelad över skeppet, övervakas för att upptäcka förändringar. Just dessa två egenskaper har stor inverkan på hur skeppet beter sig och om skeppet är fellastat kan det i värsta fall kapsejsa. Vetskapen om dessa fysikaliska egenskaper kan alltså utöver effektivisering användas för att varna besättningen eller påverka styrsystemen så att farliga manövrar undviks. För att visa att tekniken fungerar i verkligheten har den använts på mätningar som har samlats in från ett skalenligt modellskepp. Experimenten utfördes i bassäng och resultaten visar att tekniken fungerar. Denna nya teknik är inte specifik för marint bruk utan kan också vara användbar i andra typer av tillämpningar. Även i dessa tillämpningar möjliggörs användandet av färre eller alternativa sensorer för att skatta modeller. Tekniken kan vara speciellt användbar när en modell av ett system eller process som verkar i ett nätverk av många system är av intresse, något som också diskuteras i avhandlingen.

Sensitive devices are affected by extreme vibration excitations during operation so require isolation from high levels of vibration excitations. When these excitation characteristics of the devices are well known, the vibration isolation can be achieved accurately. However, it is possible to have expected profile information of the excitations with respect to frequency. Therefore, it is practical and useful to implement this information in the design process for vibration isolation. In this thesis, passive vibration isolation technique is examined and a computer code is developed which would assist the isolator selection process. Several sample cases in six degree of freedom are designed for a sample excitation and for sample assumptions defined for an inertial measurement unit. Different optimization methods for design optimizations are initially compared and then different designs are arranged according to the optimization results using isolators from catalogues for these sample cases. In the next step, the probable designs are compared according to their isolator characteristics. Finally, one of these designs are selected for each case, taking into account both the probable location deviations and property deviations of isolators.