Line-of-sight stabilization of an optical instrument using magnetostnctlve actuators is described in this study. Various stabilization methods, i.e. gyroscopic, hydraulic, piezoelectric, electrodynamic and magnetostrictive methods, are compared and magnetostrictive stabilization is selected for its relatively large stroke length, low input voltage and wide frequency bandwidth. The system makes use of two magnetostrictive actuators, one at each end of the optical instrument, mounted between the moving base and instrument. Each actuator is equipped with cylindrical rods of Terfenol-D, a highly magnetostrictive material. Field coils are wound around the rods to produce a strain in the rods, thereby exciting angular motion of the instrument. Actuator stroke length is enhanced by means of a hingeless gain mechanism, rod prestressing and field biasing. Dynamic characteristics of the system are modelled to facilitate actuator, coil and control system design. A linear, single-degree-of-freedom actuator model, in state-space and transfer function forms, is derived and coupled to a distributed model of the optical instrument, using the Rayleigh-Ritz method. Transfer functions between actuator coil voltages and instrument angular acceleration are derived. Normal mode shapes, natural frequencies and damping factors are predicted. Design concepts for bias field, prestress, actuator gain and optical instrument support structure, are discussed and the most suitable concepts are selected. The required actuator gain, rod length and diameter, prestress spring stiffness, coil resistance and inductance are calculated. System components are designed in detail and safety of the design is checked. The actuators are characterized quasi-statically to determine the saturation strain, linear range of operation and DC bias field. The system is dynamically characterized to obtain transfer functions between the coil voltage and instrument angular acceleration. The test setups are described and limitations of the setups are discussed. Test results are processed and discussed. A comparison with the modelled results shows that the model is highly inaccurate. Reasons for inaccuracies are given and updating of the model is motivated. An updated model is obtained from the experimental results. The model is divided into electrical and mechanical subsystem models. The SDOF actuator models are replaced with 2DOF models (one for each actuator) and coupled to the instrument and base models, using substructure synthesis. The electrical and mechanical subsystem models are subsequently coupled. It is shown that the updated system model is considerably more accurate than the original model. A linear, suboptimal, disturbance feedforward plus output feedback controller, with output integral feedback, is designed, implemented and tested. An H2 optimal controller is designed and modified to improve robustness. The controller model is coupled to that of a suboptimal observer. An output integral feedback loop is added to further improve robustness. The controller is implemented in digital filter form. The test apparatus and procedure are described. Test results are processed and discussed. It is shown that the LOS stabilization system achieves 80% of the required isolation, over a frequency bandwidth of 0 Hz to 100 Hz. A summary of the work done, conclusions that can be drawn from the results, problems encountered and recommendations for future work, are given. / Thesis (PhD (Mechanical Engineering))--University of Pretoria, 2006. / Mechanical and Aeronautical Engineering / unrestricted

Thesis (PhD (Industrial Engineering))--University of Stellenbosch, 2007. / Off-road working vehicles are subjected to high levels of vibration input on the rough terrain and irregular roads they work. The human operators are therefore exposed to high levels of whole body vibration (WBV) and at risk of developing health problems. A number of international standards address the matter of whole body vibration, and the European Union issued a directive which limits the exposure of workers in the EU to WBV. Unfortunately, to date there is no law in South Africa requiring compliance with any of these EU standards nor guidelines. There are vehicles which are not fitted with suspension and/or suspension seats. The three wheeled logger used in forestry is a highly manoeuvrable and effective bulk handler, but without any form of suspension and no space under the operator’s seat to install a suspension seat. However, a suspension cushion can be retrofitted to existing vehicles largely alleviating the problem. To isolate low frequency vibration large suspension travel is required which makes an air suspension cushion attractive, as it can fully collapse. Additionally, a Helmholtz resonator if added to the cushion in the form of a pipe and tank, provides anti-resonance at a specific frequency. The resonator can be tuned by adjusting the pipe’s length and diameter as well as the volume of the tank. Larger diameter pipes have less friction and give better reduction of the transmissibility curve at the anti-resonance frequency. The SEAT value is a single number used to compare suspension seats for a specific input vibration. It is calculated from the weighted input acceleration power spectral density curve and the suspension seat transmissibility curve. The former is obtained from the vehicle and is vehicle, path and speed dependent. The latter is the only variable that can be improved by using a better suspension seat/cushion. The input power spectral density often contains significant energy at frequencies where the human operator is most sensitive. The cushion resonator could be tuned to position the anti-resonance in the transmissibility curve at these frequencies. The resultant output vibration would thus be lower than the input vibration at that frequency. In this dissertation an analytical model describes the state variables in the cushion, pipe and tank. A Simulink model predicts the transmissibility curve with a solid mass as well as with a two degree of freedom seated human model. Initially the prototype was tested with a solid mass to compare the transmissibility curve produced by the simulation with the experimental results. It was required to evaluate the contribution of the resonator without the complexity of the human impedance. Subsequent tests were carried out with human subjects. Test results showed high inter subject similarity at the anti-resonance frequencies. Design guidelines are formulated that can be used by the suspension cushion designer to specify the pipe diameter and length and the volume of the tank to determine the optimal transmissibility. Input psd from ISO7096 class EM3 vehicles is used as an example during the design process. A prototype air suspension cushion was designed to reduce output vibration on the three wheeled logger. Laboratory tests with human subjects showed a significant improvement at the problematic frequencies through the tuning of the resonator. Using a Helmholtz resonator with the air suspension cushion the overall SEAT value improved by 25% compared with a 100mm foam cushion. However, the current tank and pipe need to be reduced in size for practical implementation to the vehicle. Future work would include finding an alternative mass to replace the air in the pipe. This should reduce the size of the tank and the pipe required. Additionally the simultaneous effect of multiple resonators at different frequencies should be investigated. This is required for vehicles having an input psd with significant energy at more than one frequency band.

Thesis (doctoral)--Helsinki University of Technology, 2007. / Includes bibliographical references (p. 142-151). Also available on the World Wide Web.

This thesis presents the practical and novel work in the area of optimal placement of actuators and sensors for sound-structure interaction systems. The work has been done by the author during his PhD candidature. The research is concentrated in systems with non-ideal boundary conditions as in the case in practical engineering applications. An experimental acoustic cavity with five walls of timber and a thin aluminium sheet fixed tightly on the cavity mouth is chosen in this thesis as a good representation of general sound-structure interaction systems. The sheet is intentionally so fixed that it does not satisfy ideal boundary conditions. The existing methods for obtaining optimal sensor-actuator location using analytic models with ideal boundary conditions are of limited use for such problem with non-ideal boundary conditions. The method presented in this thesis for optimal placement of actuators and sensors is motivated by energy based approach and model uncertainty inclusion. The optimal placement of actuator and sensor for the experimental acoustic cavity is used to construct a robust feedback controller based on minimax LQG control design method. The controller is aimed to reduce acoustic potential energy in the cavity. This energy is due to the structure-borne sound inside the sound-structure interaction system. Practical aspects of the method for optimal placement of actuator and sensors are highlighted by experimental vibration and acoustic noise attenuation for arbitrary disturbance using feedback controllers with optimal placement of actuator and sensor. The disturbance is experimentally set to enter the system via a spatial location different from the controller input as would be in any practical applications of standard feedback disturbance rejections. Experimental demonstration of the novel methods presented in this thesis attenuate structural vibration up to 13 dB and acoustic noise up to 5 dB for broadband frequency range of interest. This attenuation is achieved without the explicit knowledge of the model of the disturbance.

We are seeing a revolution in computing and artificial intelligence; intelligent machines have become ingrained in and improved every aspect of our lives. Despite the increasing number of intelligent devices and breakthroughs in artificial intelligence, we have yet to achieve truly intelligent environments. Audio is one of the most common sensing and actuation modalities used in intelligent devices. In this thesis, we focus on how we can more robustly integrate audio intelligence into a wide array of resource-constrained platforms that enable more intelligent environments. We present systems and methods for adaptive audio filtering that enables us to more robustly embed acoustic intelligence into a wide range of real time and resource-constrained mobile, embedded, and cyber-physical systems that are adaptable to a wide range of different applications, environments, and scenarios. First, we introduce methods for embedding audio intelligence into wearables, like headsets and helmets, to improve pedestrian safety in urban environments by using sound to detect vehicles, localize vehicles, and alert pedestrians well in advance to give them enough time to avoid a collision. We create a segmented architecture and data processing pipeline that partitions computation between embedded front-end platform and the smartphone platform. The embedded front-end hardware platform consists of a microcontroller and commercial-off-the shelf (COTS) components embedded into a headset and samples audio from an array of four MEMS microphones. Our embedded front-end platform computes a series of spatiotemporal features used to localize vehicles: relative delay, relative power, and zero crossing rate. These features are computed in the embedded front-end headset platform and transmitted wirelessly to the smartphone platform because there is not enough bandwidth to transmit more than two channels of raw audio with low latency using standard wireless communication protocols, like Bluetooth Low-Energy. The smartphone platform runs machine learning algorithms to detect vehicles, localize vehicles, and alert pedestrians. To help reduce power consumption, we integrate an application specific integrated circuit into our embedded front-end platform and create a new localization algorithm called angle via polygonal regression (AvPR) that combines the physics of audio waves, the geometry of a microphone array, and a data driven training and calibration process that enables us to estimate the high resolution direction of the vehicle while being robust to noise resulting from movements in the microphone array as we walk the streets. Second, we explore the challenges in adapting our platforms for pedestrian safety to more general and noisier scenarios, namely construction worker safety sounds of nearby power tools and machinery that are orders of magnitude greater than that of a distant vehicle. We introduce an adaptive noise filtering architecture that allows workers to filter out construction tool sounds and reveal low-energy vehicle sounds to better detect them. Our architecture combines the strengths of both the physics of audio waves and data-driven methods to more robustly filter out construction sounds while being able to run on a resource-limited mobile and embedded platform. In our adaptive filtering architecture, we introduce and incorporate a data-driven filtering algorithm, called probabilistic template matching (PTM), that leverages pre-trained statistical models of construction tools to perform content-based filtering. We demonstrate improvements that our adaptive filtering architecture brings to our audio-based urban safety wearable in real construction site scenarios and against state-of-art audio filtering algorithms, while having a minimal impact on the power consumption and latency of the overall system. We also explore how these methods can be used to improve audio privacy and remove privacy-sensitive speech from applications that have no need to detect and analyze speech. Finally, we introduce a common selective audio filtering platform that builds upon our adaptive filtering architecture for a wide range of real-time mobile, embedded, and cyber-physical applications. Our architecture can account for a wide range of different sounds, model types, and signal representations by integrating an algorithm we present called content-informed beamforming (CIBF). CIBF combines traditional beamforming (spatial filtering using the physics of audio waves) with data driven machine learning sound detectors and models that developers may already create for their own applications to enhance and filter out specified sounds and noises. Alternatively, developers can also select sounds and models from a library we provide. We demonstrate how our selective filtering architecture can improve the detection of specific target sounds and filter out noises in a wide range of application scenarios. Additionally, through two case studies, we demonstrate how our selective filtering architecture can easily integrate into and improve the performance of real mobile and embedded applications over existing state-of-art solutions, while having minimal impact on latency and power consumption. Ultimately, this selective filtering architecture enables developers and engineers to more easily embed robust audio intelligence into common objects found around us and resource-constrained systems to create more intelligent environments.

Είναι ευρύτατα γνωστό ότι ο θόρυβος δημιουργείται από δονούμενες επιφάνειες. Για την αντιμετώπιση του θορύβου στην πηγή του, δηλαδή τη δονούμενη επιφάνεια, δύο κυρίως τρόποι έχουν αναπτυχθεί. Ο πρώτος τρόπος αφορά τη χρησιμοποίηση παθητικών μέσων, δηλαδή ηχομονωτικών υλικών που αποσβένουν συγκεκριμένες συχνότητες. Ο δεύτερος τρόπος αφορά τη χρήση ενεργητικών μέσων. Τα ενεργητικά μέσα είναι διατάξεις που αποτελούνται από ένα σύστημα ελέγχου και ένα σύνολο αισθητήρων και ενεργοποιητών. Η λειτουργία ενός τέτοιου Συστήματος Ενεργού Ελέγχου Δονήσεων (ΣΕΕΔ) βασίζεται στην καταγραφή μέσω των αισθητήρων του τρόπου δόνησης της επιφάνειας (πρωτεύον πεδίο δόνησης), την δημιουργία σημάτων ελέγχου από τον ελεγκτή (ίδιου πλάτους αλλά με διαφορά φάσης 180o) και την αποστολή τους στους ενεργοποιητές που θα δημιουργήσουν ένα δευτερεύον πεδίο δόνησης. Η υπέρθεση των δύο πεδίων έχει σαν αποτέλεσμα την δημιουργία ενός εναπομείναντος πεδίου με πλάτη δόνησης αισθητά χαμηλότερα από αυτά του πρωτεύοντος. Το αντικείμενο της παρούσας διατριβής είναι η ανάπτυξη ενός γενικευμένου ΣΕΕΔ, ο έλεγχος του οποίου βασίζεται σε εργαλεία Τεχνητής Νοημοσύνης όπως τα Τεχνητά Νευρωνικά Δίκτυα και οι Γενετικοί Αλγόριθμοι για την αναγνώριση του τρόπου δόνησης οποιασδήποτε επιφάνειας και το βέλτιστο έλεγχο της δόνησής της, χωρίς να απαιτείται καμία πρότερη γνώση της δυναμικής συμπεριφοράς της επιφάνειας. Επιπλέον, το υπό μελέτη ΣΕΕΔ είναι ικανό να ελέγχει τέσσερις συχνότητες αντί μιας που απαντάται συνήθως στην πλειονότητα των εφαρμογών. Ο σκοπός της διατριβής αυτής είναι η απόδειξη της αρχής λειτουργίας ενός τέτοιου συστήματος. Η προσέγγιση για την επίτευξη αυτού του στόχου περιλαμβάνει πειραματικές μετρήσεις ενός πρωτότυπου ΣΕΕΔ σε μία απλοποιημένη πειραματική διάταξη. Τα αποτελέσματα από την εφαρμογή του εν λόγω ΣΕΕΔ δείχνουν ότι παρά τους περιορισμούς που υπεισέρχονται λόγω των δυνατοτήτων του υλικού (hardware) του χρησιμοποιούμενου εξοπλισμού, το υπό μελέτη ΣΕΕΔ λειτουργεί επιτυχώς στη βασική αρχή του, ενώ έχει τις προϋποθέσεις και τη δυναμική για περαιτέρω βελτιστοποίηση και εξέλιξη σε ένα ευρύ φάσμα εφαρμογών. / It is generally approved that noise is created by vibrating surfaces. In order to tackle this phenomenon at its source, mainly two approaches have been followed. The first approach involves passive means, that is sound insulation materials that dampen certain frequencies. The second approach involves the use of active means. The active means are arrangements that consist of a control system and a set of sensors and actuators. The application of such an arrangement for vibration control is called Active Vibration Control (AVC) and is based on the sampling (by means of sensors) of the primary field of vibration of the surface, the creation of control signals by the controller (secondary field - of the same amplitude but with phase difference of 180o) and finally applying these control signals on the vibrating surface, by means of the actuators. The superimposing of the two vibration signals (primary and secondary) results to a residual field where the amplitudes of vibration are significantly lower than in the primary. The objective of the thesis at hand is to develop a Generic AVC with the controller developed using Artificial Intelligence tools such as the Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs), in order to identify the vibration patterns of any surface and the optimal control of its vibration, without any prior knowledge of the dynamic behavior of the surface. Moreover, the developed AVC system will be able to identify and control four dominating frequencies instead of one that is usually the choice in the majority of similar applications. The scope of this work is the ‘Proof of Concept’ of the successful operation of such a generic AVC system. The approach to this end includes experimental testing of a prototype AVC system on a simplified experimental set-up. The results of the application of the developed AVC system, performed also by independent parties in the framework of a EC-funded Basic Research project, prove the successful operation of the developed AVCS, even within the limitation of the contemporary data acquisition platform (hardware and software) used, imposes limitations in the efficiency of the AVCS, and provide the basis for its further development and application in a multitude of problems.