This report describes the design, building, and testing of the Structure Climbing Monkey Robot (SCMR). It is composed of seven successive joints and linkages with two grippers at the two ends. Each gripper can act as the base or the end of the robot. The SCMR has the ability to climb any structure. The gripper plates can be changed to grab different kinds of structures, but this one is made to grab 2x4‘s. A program was written to assist the user to grab four non-coplanar, non-orthogonal points. The SCMR is actuated by a total of nine motors: two to open and close the two grippers and seven to control the movement of the SCMR. Planetary gear motors are used with a worm gear to control the motion of each joint. The worm gear increases the torque of the motor and reduces the rotational speed to a usable value. The SCMR is just over 45 inches long and weighs about 30 pounds. The motion of the SCMR is controlled by the microcontroller Arduino Mega 2560, Vex Robotic quadrature encoders, and Pololu 18v15 motor driver chips. Code was written in the languages Arduino and Processing to actuate the motors and create the GUI, respectively. The motors can be controlled individually or run simultaneously while incrementing a specified angle.

This thesis discussed the mobile land robots for the robotic competitions. The topics discussed in this thesis are robotic systems, mobile land robots, robot competitions, and example of robot designs. Question-answer sections are added to help understand the requirements to build the robot. Examples include three different teams who participated in different robotic competitions to provide a context for robotic competitions. The thesis was divided into the five chapters. The first and second chapters explained the different kind of robotics systems, and opportunities. The focus of the information was the mobile land robots, which was explained under the third chapter, mobile land robots. The aim of the thesis was to guide those who want to design, build, and compete in the mobile robot competition. As a result, the information from various resources been gathered and has been given a form of thesis to help individuals or group of individuals to guide them through the robotic competitions.

Anomaly detection is a relevant problem in the field of Mechanical Engineering, because the analysis of mechanical systems often relies on identifying deviations from what is considered "normal". The mechanical sciences are represented by a heterogeneous collection of data types: some systems may be highly dimensional, may contain exclusively spatial or temporal data, may be spatiotemporally linked, or may be non-deterministic and best described probabilistically. Given the broad range of data types in this field, it is not possible to propose a single processing method that will be appropriate, or even usable, for all data types. This has led to human observation remaining a common, albeit costly and inefficient, approach to detecting anomalous signals or patterns in mechanical data. The advantages of automated anomaly detection in mechanical systems include reduced monitoring costs, increased reliability of fault detection, and improved safety for users and operators. This dissertation proposes a hierarchical framework for anomaly detection through machine learning, and applies it to three distinct and heterogeneous data types: state-based data, parameter-driven data, and spatiotemporal sensor network data. In time-series data, anomaly detection results were robust in synthetic data generated using multiple simulation algorithms, as well as experimental data from rolling element bearings, with highly accurate detection rates (>99% detection, <1% false alarm). Significant developments were shown in parameter-driven data by reducing the sample sizes necessary for analysis, as well as reducing the time required for computation. The event-space model extends previous work into a geospatial sensor network and demonstrates applications of this type of event modeling at various timescales, and compares the model to results obtained using other approaches. Each data type is processed in a unique way relative to the others, but all are fitted to the same hierarchical structure for system modeling. This hierarchical model is the key development proposed by this dissertation, and makes both novel and significant contributions to the fields of mechanical analysis and data processing. This work demonstrates the effectiveness of the developed approaches, details how they differ from other relevant industry standard methods, and concludes with a proposal for additional research into other data types. / Ph. D.

An existing water filtration system at the Channel Islands Marine & Wildlife Institute (CIMWI) wastes approximately 25 gallons of water per day rinsing out solid waste under light load. To reduce CIMWI’s water and energy consumption, an automated system was designed and built to recover the rinse water and return it to the existing filtration loop. Models for fluid system requirements, basic energy needs, and photo- voltaic energy generation were created to aid in component selection. Basic sensors and electronics were programmed in Python for use with a Raspberry Pi single board computer to collect and process water recovery data over time. Pump automation and data acquisition energy needs were met with a 100W photovoltaic module, pulse width modulation (PWM) charge controller, and an absorbed glass mat (AGM) battery. A prototype system, $732 in total cost, was installed and was found to recover 19 gallons of water over the initial 30-hour testing period under light load. Models and software developed for this project could be adapted to aid in the creation of similar water recovery systems.

To solve the problem of limited tactile sensing in humanoid robotics as well as provide for future planned mechanical prostheses, an innovative tactile sensor system was created and embedded into two realistic-looking artificial skin gloves. These artificial skin tactile sensors used small piezoelectric ceramic disks to measure applied force at multiple points on each glove. The gloves were created using silicone rubber to simulate both the texture and look of human skin, while maintaining both flexibility and durability. The sensor outputs were buffered by high-impedance voltage-following operational amplifiers, and then read sequentially using a multiplexing scheme by a microcontroller. Sensor data were sent via USB to a computer, where a graphical user display was created to show the tactile information in real time. These prototypes successfully demonstrated the viability of small piezoelectric elements embedded in silicone rubber for use in creating flexible and elastic tactile sensors.

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Piezoelectric actuators frequently exhibit a time-dependent behavioral phenomenon known as hysteresis, resulting in a lag in the deformation of the actuator compared to linear models. The presence of hysteresis complicates control systems involving piezoelectric actuators. However, traditional modeling methods for piezoelectric actuated smart structures often treat the piezoelectric patches as linear actuators without considering hysteresis, leading to suboptimal controller performance. This thesis aims to establish a comprehensive model by integrating the Euler-Bernoulli beam bending model with the hysteresis dynamics induced by two opposing piezoelectric patches attached to a beam. A model expansion method is employed to transform the partial differential equations describing beam vibration into a set of ordinary differential equations in the modal coordinate frame. These equations are then coupled with the Bouc-Wen model describing the hysteresis of piezoelectric materials. Model parameters are identified using a genetic algorithm tested against experimental data across varied excitation frequencies. The experimental dataset is divided into two sets: a training set for the genetic algorithm and a validation set to verify the identified model. Results demonstrate that the inclusion of hysteresis in a nonlinear model provides better agreement with experimental results than the linear model, thereby enhancing the predictive capability of piezoelectric actuator behavior. This thesis has laid the foundation for future work on advanced control methods to mitigate beam vibration under external excitation, thus optimizing smart structure performance.

Nature and its variety of motion forms have inspired new robot designs with inherentunderactuated dynamics. The fundamental characteristic of these controlled mechanicalsystems, called underactuated, is to have the number of actuators less than the number ofdegrees of freedom. The absence of full actuation brings challenges to planning feasibletrajectories and designing controllers. This is in contrast to classical fully-actuated robots.A particular problem that arises upon study of such systems is that of generating periodicmotions, which can be seen in various natural actions such as walking, running,hopping, dribbling a ball, etc. It is assumed that dynamics can be modeled by a classicalset of second-order nonlinear differential equations with impulse effects describing possibleinstantaneous impacts, such as the collision of the foot with the ground at heel strikein a walking gait. Hence, we arrive at creating periodic solutions in underactuated Euler-Lagrange systems with or without impulse effects. However, in the qualitative theory ofnonlinear dynamical systems, the problem of verifying existence of periodic trajectoriesis a rather nontrivial subject.The aim of this work is to propose systematic procedures to plan such motions and ananalytical technique to design orbitally stabilizing feedback controllers. We analyze andexemplify both cases, when the robotmodel is described just by continuous dynamics, andwhen continuous dynamics is interrupted from time to time by state-dependent updates.For trajectory planning, systems with one or two passive links are considered, forwhich conditions are derived to achieve periodicmotions by encoding synchronizedmovementsof all the degrees of freedom. For controller design we use an explicit form tolinearize dynamics transverse to the motion. This computation is valid for an arbitrarydegree of under-actuation. The linear system obtained, called transverse linearization, isused to analyze local properties in a vicinity of the motion, and also to design feedbackcontrollers. The theoretical background of these methods is presented, and developedin detail for some particular examples. They include the generation of oscillations forinverted pendulums, the analysis of human movements by captured motion data, and asystematic gait synthesis approach for a three-link biped walker with one actuator.

<p>A short, 30cm, test section was used to study the effect of electrohydrodynamic (EHD) forces on flow redistribution in a horizontal, shell and tube heat exchanger subject to both boiling and condensation. The use of a short test section allows for a consistent flow pattern across the test section length which provides further insight into the true effect of EHD.</p> <p>It was found that the voltage polarity of the applied voltages influences the flow distribution. For the current geometry studied, it was found that positive polarity voltages tend to pull liquid away from heat transfer surface and that negative voltages tended to repel more liquid toward the heat transfer surface. Using this knowledge we were able to show that positive voltages were more effective for convective condensation heat transfer enhancement, whereas negative voltages were more effective for convective boiling heat transfer enhancement. A twofold enhancement of convective boiling heat transfer was achieved for positive voltages and a 4fold enhancement was achieved for negative voltages. Similar pressure drop penalties were seen for both cases, approximately twice that of the no EHD case.</p> <p>Furthermore, the effect of DC level, peak to peak voltage, frequency and duty cycle waveform parameters on convective boiling enhancement were studied to explore the range of controllability for the current set of flow parameters. It was found that these various waveform parameters can induce different flow patterns and consequently different heat transfer and pressure drop configurations. In general the heat transfer is enhanced by EHD, but different pressure drop penalties can be achieved for a given enhancement ratio using different waveforms. High heat transfer for relatively low pressure drop was achieved using either negative DC signals or 50%duty cycle pulse waveforms. In some cases the enhancement is quite little compared to the pressure drop, for example the zero DC level, varying peak to peak voltage data. It is suggested that in a system where the heat exchanger pressure drop due to EHD is more dominant than the system pressure drop, it may be possible to use EHD as a method of retarding the system rather than enhancing it thereby broadening the scope of controllability.</p> <p>Finally we showed the proof of concept of using DC EHD as a rapid control mechanism for the load conditions. Using -8kVDC the water side heat flux could be varied by approximately ±3.2 kW/m² within 5 seconds. As a comparison, the same experiment was repeated using the refrigerant flow rate to control the load. Response times were similar for both experiments and although the power required for the flow rate control was less, the minimal variability in flow parameters for the EHD control make it a more attractive method of load control.</p> / Master of Applied Science (MASc)