In this thesis, the performance of piezoelectric patches on investigation of vibration characteristics and active vibration control of a smart beam is presented. The smart beam is composed of eight surface-bonded piezoelectric patches symmetrically located on each side of a cantilever aluminium beam. At first, vibration characteristics of the smart beam is investigated by employment of piezoelectric patches as sensors and actuators. Smart beam is excited by either impact hammer or piezoelectric patch and the response of the smart beam particular to these excitations is measured by piezoelectric patches used as sensors. In order to investigate the performance of piezoelectric patches in sensing, the measurements are also conducted by commercially available sensing devices. Secondly, active vibration suppression of the smart beam via piezoelectric sensor/actuator pair is considered. For this purpose, system identification of the smart beam is conducted by using four piezoelectric patches as actuators and another piezoelectric patch as a sensor. The designed robust controller is experimentally implemented and active vibration suppression of the free and first resonance forced vibration is presented. Thirdly, active vibration control of the smart beam is studied by employment of piezoelectric patches as self-sensing actuators. Following the same approach used in the piezoelectric sensor/actuator pair case, system identification is conducted via self-sensing piezoelectric actuators and robust controller is designed for active vibration suppression of the smart beam. Finally, active vibration suppression via self-sensing piezoelectric actuators is experimentally presented.

This thesis investigates particular topics in advanced motion control of two distinct mechanical systems: human-like motion control of redundant robot manipulators and advanced sensing and control for energy-efficient operation of electromagnetic devices. Control of robot manipulators for human-like motions has been one of challenging topics in robot control for over half a century. The first part of this thesis considers methods that exploits robot manipulators??? degrees of freedom for such purposes. Jacobian transpose control law is investigated as one of the well-known controllers and sufficient conditions for its universal convergence are derived by using concepts of ???stability on a manifold??? and ???transferability to a sub-manifold???. Firstly, a modification on this method is proposed to enhance the rectilinear trajectory of the robot end-effector. Secondly, an abridged Jacobian controller is proposed that exploits passive control of joints to reduce the attended degrees of freedom of the system. Finally, the application of minimally-attended controller for human-like motion is introduced. Electromagnetic (EM) access control systems are one of growing electronic systems which are used in applications where conventional mechanical locks may not guarantee the expected safety of the peripheral doors of buildings. In the second part of this thesis, an intelligent EM unit is introduced which recruits the selfsensing capability of the original EM block for detection purposes. The proposed EM device optimizes its energy consumption through a control strategy which regulates the supply to the system upon detection of any eminent disturbance. Therefore, it draws a very small current when the full power is not needed. The performance of the proposed control strategy was evaluated based on a standard safety requirement for EM locking mechanisms. For a particular EM model, the proposed method is verified to realize a 75% reduction in the power consumption.

The study of self-sensing cementitious materials is a constantly expanding topic of study in the materials and civil engineering fields and refers to the creation and utilization of cement-based materials (including cement paste, cement mortar, and concrete) that are capable of sensing (i.e. measuring) stress and strain states without the use of embedded or attached sensors. With the inclusion of electrically conductive fillers, cementitious materials can become truly self-sensing. Previous researchers have provided only qualitative studies of self-sensing material stress-electrical response. The overall goal of this research was to modify and apply previously developed predictive models on cylinder compression test data in order to provide a means to quantify stress-strain behavior from electrical response. The Vipulanandan and Mohammed (2015) stress-resistivity model was selected and modified to predict the stress state, up to yield, of cement cylinders enhanced with nanoscale iron(III) oxide (nanoFe2O3) particles based on three mix design parameters: nanoFe2O3 content, water-cement ratio, and curing time. With the addition of a nonlinear model, parameter values were obtained and compiled for each combination of nanoFe2O3 content and water-cement ratio for the 28-day cured cylinders. This research provides a procedure and lays the framework for future expansion of the predictive model.

This case study examined emitted sound and actuated piezoelectric current in a solderpaste jet printing machine to conclude whether quality degradation could be detected with an autoencoder machine learning model. An autoencoder was used to detect anomalies in non-realtime that were defined asa diameter drift with an averaging window from a target diameter. A sensor and datacollection system existed for the piezoelectric current, and a microphone was proposedas a new sensor to monitor the system. The sound was preprocessed with a Fast Fourier Transform to extract information of the existing frequencies. The results of the model, visualized through reconstruction error plots and an Area Under the Curve score, show that the autoencoder successfully detected conspicuous anomalies. The study indicated that anomalies can be detected prior to solder paste supply failure using the sound. When the temperature was varied or when the jetting head nozzle was clogged by residual solder paste, the sound model identified most anomalies although the current network showed better performance. / Denna fallstudie undersökte emitterat ljud och drivande piezoelektrisk ström i en jetprinter med lödpasta för att dra slutsatsen om kvalitetsbrister kunde detekteras med en autoencoder maskininlärningsmodell. En autoencoder användes för att detektera avvikelser definierade som diametertrend med ett glidande medelvärde från en bördiameter. Tidigare studier har visat att den piezoelektriska strömmen i liknande maskiner kan användas för att förutspå kvalitetsbrister. En mikrofon föreslogs som en ny sensor för att övervaka systemet. Ljudet förbehandlades genom en snabb fouriertransform och frekvensinnehållet användes som indata i modellen. Resultaten visualiserades genom rekonstruktionsfel och metoden Area Under the Curve. Modellen upptäckte framgångsrikt tydliga avvikelser. För vissa felfall visade ljudet som indata bättre prestanda än strömmen, och för andra visade strömmen bättre prestanda. Till exempel indikerade studien att avvikelser kan detekteras före lodpasta-försörjningsfel med ljudet. Under varierande temperatur och då munstycket var igentäppt av kvarvarande lödpasta identifierade nätverket med ljud som indata de flesta avvikelser även om nätverket med strömmen visade bättre prestanda.

In this experimental study the in-lined poled piezoelectric poly(vinylidene fluoride)(PVDF) bicomponent fiber was investigated the suitability in applications within the area of textile sensors when used in a bowel stent. Today there are only piezoelectric films made of PVDF available. Compared to a film, a fiber increases the amounts of application abilities. In this study a plain weave, resembling a coordinate system was made of the piezoelectric PVDF fiber and tested on top of two different beds; one hard and one elastic made of foam. The structure was then developed into two structures; one integrated in the stents structure with a plain weave pattern and one secondary structure as a plain weave placed onto the stent. Two test methods were developed in order to resemble the bowel movements to test the two piezoelectric PVDF fiber based structures. A reliability test in a reometer was made of the fiber, giving high differences in mean values. An in vivo test was conducted in a pig where the stent was placed in the orifice of the stomach. Both structures shown response when both developed methods was used. Due to large irregularities within the piezoelectric PVDF fiber the evaluation between the two structures was not possible. The most favorable structure was the secondary structure due to the larger continuous process ability and application areas. It was also seen that the reliability of the piezoelectric PVDF fiber is low, giving a non-reliable sensor. / Program: Textilteknik

The McTronX research group at the North-West University is currently researching self-sensing techniques for Active Magnetic Bearings (AMB). The research is part of an ongoing effort to expand the knowledge base on AMBs in the School of Electrical, Electronic and Computer Engineering to support industries that make use of the technology. The aim of this project is to develop an integrated co-processor based power electronic drive with the emphasis placed on the ability of the co-processor to execute AMB self-sensing algorithms. The two primary techniques for implementing self-sensing in AMBs are state estimation and modulation. This research focuses on hardware development to facilitate the implementation of the modulation method. Self-sensing algorithms require concurrent processing power and speed that are well suited to an architecture that combines a digital signal processor (DSP) and a field programmable gate array (FPGA). A comprehensive review of various power amplifier topologies shows that the pulse width modulation (PWM) switching amplifier is best suited for controlling the voltage and current required to drive the AMB coils. Combining DSPs and power electronics to form an integrated co-processor based power electronic drive requires detail attention to aspects of PCB design, including signal integrity and grounding. A conceptual design is conducted and forms part of the process of compiling a subsystem development specification for the integrated drive, in conjunction with the McTronX Research Group. Component selection criteria, trade-off studies and various circuit simulations serve as the basis for this essential phase of the project. The conceptual design and development specification determines the architecture, functionality and interfaces of the integrated drive. Conceptual designs for the power amplifier, digital controller, electronic supply and mechanical layout of the integrated drive is provided. A detail design is performed for the power amplifier, digital controller and electronic supply. Issues such as component selection, power supply requirements, thermal design, interfacing of the various circuit elements and PCB design are covered in detail. The output of the detail design is a complete set of circuit diagrams for the integrated controller. The integrated drive is interfaced with existing AMB hardware and facilitates the successful implementation of two self-sensing techniques. The hardware performance of the integrated coprocessor based power electronic drive is evaluated by means of measurements taken from this experimental self-sensing setup. The co-processor performance is evaluated in terms of resource usage and execution time and performs satisfactorily in this regard. The integrated co-processor based power electronic drive provided sufficient resources, processing speed and flexibility to accommodate a variety of self-sensing algorithms thus contributing to the research currently underway in the field of AMBs by the McTronX research group at the North-West University. / Thesis (M.Ing. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2009.

The McTronX research group at the North-West University is currently researching self-sensing techniques for Active Magnetic Bearings (AMB). The research is part of an ongoing effort to expand the knowledge base on AMBs in the School of Electrical, Electronic and Computer Engineering to support industries that make use of the technology. The aim of this project is to develop an integrated co-processor based power electronic drive with the emphasis placed on the ability of the co-processor to execute AMB self-sensing algorithms. The two primary techniques for implementing self-sensing in AMBs are state estimation and modulation. This research focuses on hardware development to facilitate the implementation of the modulation method. Self-sensing algorithms require concurrent processing power and speed that are well suited to an architecture that combines a digital signal processor (DSP) and a field programmable gate array (FPGA). A comprehensive review of various power amplifier topologies shows that the pulse width modulation (PWM) switching amplifier is best suited for controlling the voltage and current required to drive the AMB coils. Combining DSPs and power electronics to form an integrated co-processor based power electronic drive requires detail attention to aspects of PCB design, including signal integrity and grounding. A conceptual design is conducted and forms part of the process of compiling a subsystem development specification for the integrated drive, in conjunction with the McTronX Research Group. Component selection criteria, trade-off studies and various circuit simulations serve as the basis for this essential phase of the project. The conceptual design and development specification determines the architecture, functionality and interfaces of the integrated drive. Conceptual designs for the power amplifier, digital controller, electronic supply and mechanical layout of the integrated drive is provided. A detail design is performed for the power amplifier, digital controller and electronic supply. Issues such as component selection, power supply requirements, thermal design, interfacing of the various circuit elements and PCB design are covered in detail. The output of the detail design is a complete set of circuit diagrams for the integrated controller. The integrated drive is interfaced with existing AMB hardware and facilitates the successful implementation of two self-sensing techniques. The hardware performance of the integrated coprocessor based power electronic drive is evaluated by means of measurements taken from this experimental self-sensing setup. The co-processor performance is evaluated in terms of resource usage and execution time and performs satisfactorily in this regard. The integrated co-processor based power electronic drive provided sufficient resources, processing speed and flexibility to accommodate a variety of self-sensing algorithms thus contributing to the research currently underway in the field of AMBs by the McTronX research group at the North-West University. / Thesis (M.Ing. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2009.

This work describes a self-sensing technique for a piezoelectrically driven MRI-compatible tweezer style end effector, suitable for robot assisted, MRI guided surgery. Nested strain amplification mechanisms are used to amplify the displacement of the piezo actuators to practical levels for robotics. By using a hysteretic piezoelectric model and a two port network model for the compliant nested strain amplifiers, it is shown that force and displacement at the tweezer tip can be estimated if the input voltage and charge are measured. One piezo unit is used simultaneously as a sensor and an actuator, preserving the full actuation capability of the device. Experimental validation shows an average of 12% error between the self-sensed and true values.

Many cases have evinced the importance of having structural health monitoring (SHM) strategies that can allow the detection of the structural health of infrastructures or buildings, in order to prevent the potential economic or human losses. Nanocomposite material like the Carbon nanofiller-modified composites have great potential for SHM because these materials are piezoresistive. So, it is possible to determine the damage status of the material by studying the conductivity change distribution, and this is essential for detecting the damage on the position that can-not be observed by eye, for example, the inner layer in the aerofoil. By now, many researchers have studied how damage influences the conductivity of nanocomposite material and the electrical impedance tomography (EIT) method has been applied widely to detect the damage-induced conductivity changes. However, only knowing how to calculate the conductivity change from damage is not enough to SHM, it is more valuable to SHM to know how to determine the mechanical damage that results in the observed conductivity changes. In this article, we apply the machine learning methods to determine the damage status, more specifically, the number, radius and the center position of broken holes on the material specimens by studying the conductivity change data generated by the EIT method. Our results demonstrate that the machine learning methods can accurately and efficiently detect the damage on material specimens by analysing the conductivity change data, this conclusion is important to the field of the SHM and will speed up the damage detection process for industries like the aviation industry and mechanical engineering.

Proportional valves are widely used in fluid systems for controlling the volume flow rate or fluid pressure. The actuation of this valves is done by PWM-driven proportional solenoids, which enable self-sensing position determination abilities due to air gap-dependent electrical behaviour, e. g. for condition monitoring or position controlling tasks. However, the sensor properties of conventional proportional solenoids are poor due to ambiguities caused by hysteresis effects (magnetic hysteresis, eddy currents) and saturation effects. Thus, a sensor-designed actuator was developed with very low hysteresis effects and unique position determination by using electrical sheet and a particular air gap design. This paper deals with investigations of a novel self-sensing position determination approach on a demonstrator of the sensor-designed solenoid. The advantage of this method is an online consideration of transient effects such as mean current change and armature motion as well as temperature-dependent resistance. For this, a combined evaluation of the differential inductance and flux linkage during PWM periods is proposed.