Optimising cam motion using piecewise polynomials

The paper presents a method of synthesising cam profiles based on the use of piecewise polynomials together with an optimisation technique. Special cases and limitations are discussed and illustrated, making the procedure complete and systematic for any design requirements. Using piecewise polynomials, the complete cam profile can be designed as a combined linear system. The optimisation technique described goes even further, manipulating the variables in the linear system to select the ideal combination. In addition, a means to prove the validity of the results is explained

Aspects of the design of a circular warp knitting machine

The warp knitting machine market has long been dominated by large-scale flat models, which have been steadily developed. Tubular fabrics are generally made in a special version of flat warp knitting machines containing two needle bars, one for each side of the tube, joined on the sides by yarns knitting alternatively on each bar. Warp knitting technology has failed to enter the circular knitting industry, dominated by weft knitting, due to its complexity in achieving warp knit structures in circular form. This thesis presents the design, synthesis, manufacture and test of an innovative method of producing tubular warp knitting fabrics, using a circular format rather than flat needle bars. This novel concept opens up many industrial applications from medical textiles to fruit packaging. [Continues.

A general design method of cam profile based on cubic splines and dynamic model : case study of a gravity-driven tricycle

This paper proposes a general design method for cams based on the kinematics and dynamics of a mechanical system. According to the actuator’s trajectory, the cam profile is generated in reverse based on the kinematic model of the system. Firstly, the cam design’s optimising problem is converted into the execution trajectory’s optimisation to obtain the optimum operation trajectory according to the actuator’s requirements. Secondly, the relationship between the cam profile and the actuation trajectory is modelled based on the kinematics and dynamics of the mechanical system. Then, applying the cubic spline interpolation method, the cam profile is generated, and the error compensation methods are illustrated through numerical analysis. Finally, the validity of the presented design method is verified through experiments, which demonstrate the reliability of this method

Five-axis tool path generation using piecewise rational bezier motions of a flat-end cutter

Master'sMASTER OF ENGINEERIN

CAD interface and framework for curve optimisation applications

Computer Aided Design is currently expanding its boundaries to include more design features in its processes. Design is identified as an iterative process converging to solutions satisfying a set of constraints. Its close relation with optimisation indicate that there is strong potential for the integration of optimisation and CAD. The problem addressed in this thesis lies in interfacing the geometric representation of design with other non-geometric aspects. The example of free-form curve modelling is taken to investigate such relationships. Assumptions are made that Optimisation is powered by Evolutionary Computing algorithms like Genetic Algorithms (GA). The geometric definition of curves is commonly supported by NURBS, whose construction constraints are defined locally at the data points. Here the NURBS formulation is used with GA in an attempt to provide complementary handles on the curves shape other than the usual data point coordinates and control points weights. Differential properties are used for optimising NURBS, Hermite interpolation allows for the definition of higher order constraints (tangent, normal, bi-normal) at data points. The assignment of parameter values at the data points, known as parameterisation also provides control of the curve’s shape. Curve optimisation is also performed at the geometric modelling level. Old mathematical theorems established by Frénet and further developed by other mathematicians provide means of defining a curve’s shape with it’s intrinsic equations. Such representation is possible by using Function Representation (F-rep) algebra available in the ACIS software. Frep allows more generic and exact means of interfacing with the curve’s geometry and new functionality for curve inspection and optimisation are proposed in this thesis. The integration of optimisation findings and CAD are documented in the definition of a framework. The framework architecture proposed reconstructs a new CAD environment from separate elements bolted together in a generic Application Programming Interface (API) named “Oli interface”. Functionality created to interface optimisation and CAD makes a requirement list of the work that both sides should undertake to achieve design optimisation in the CAD environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Automation and Control Architecture for Hybrid Pipeline Robots

The aim of this research project, towards the automation of the Hybrid Pipeline Robot (HPR), is the development of a control architecture and strategy, based on reconfiguration of the control strategy for speed-controlled pipeline operations and self-recovering action, while performing energy and time management. The HPR is a turbine powered pipeline device where the flow energy is converted to mechanical energy for traction of the crawler vehicle. Thus, the device is flow dependent, compromising the autonomy, and the range of tasks it can perform. The control strategy proposes pipeline operations supervised by a speed control, while optimizing the energy, solved as a multi-objective optimization problem. The states of robot cruising and self recovering, are controlled by solving a neuro-dynamic programming algorithm for energy and time optimization, The robust operation of the robot includes a self-recovering state either after completion of the mission, or as a result of failures leading to the loss of the robot inside the pipeline, and to guaranteeing the HPR autonomy and operations even under adverse pipeline conditions Two of the proposed models, system identification and tracking system, based on Artificial Neural Networks, have been simulated with trial data. Despite the satisfactory results, it is necessary to measure a full set of robot’s parameters for simulating the complete control strategy. To solve the problem, an instrumentation system, consisting on a set of probes and a signal conditioning board, was designed and developed, customized for the HPR’s mechanical and environmental constraints. As a result, the contribution of this research project to the Hybrid Pipeline Robot is to add the capabilities of energy management, for improving the vehicle autonomy, increasing the distances the device can travel inside the pipelines; the speed control for broadening the range of operations; and the self-recovery capability for improving the reliability of the device in pipeline operations, lowering the risk of potential loss of the robot inside the pipeline, causing the degradation of pipeline performance. All that means the pipeline robot can target new market sectors that before were prohibitive

VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

Biological image analysis

In biological research images are extensively used to monitor growth, dynamics and changes in biological specimen, such as cells or plants. Many of these images are used solely for observation or are manually annotated by an expert. In this dissertation we discuss several methods to automate the annotating and analysis of bio-images. Two large clusters of methods have been investigated and developed. A first set of methods focuses on the automatic delineation of relevant objects in bio-images, such as individual cells in microscopic images. Since these methods should be useful for many different applications, e.g. to detect and delineate different objects (cells, plants, leafs, ...) in different types of images (different types of microscopes, regular colour photographs, ...), the methods should be easy to adjust. Therefore we developed a methodology relying on probability theory, where all required parameters can easily be estimated by a biologist, without requiring any knowledge on the techniques used in the actual software. A second cluster of investigated techniques focuses on the analysis of shapes. By defining new features that describe shapes, we are able to automatically classify shapes, retrieve similar shapes from a database and even analyse how an object deforms through time

Gait optimality for undulatory locomotion with applications to C. elegans phenotyping

This thesis focuses on the optimality and efficiency of organism locomotion strategies, specifically of microscopic undulators, in two distinct parts. Undulators loco- mote by propagating waves of bending deformation along their bodies, and at the microscale (ie low Reynolds number) interactions between undulators and their surroundings are well-described by biomechanical models due to high viscosity and negligible inertia. Frameworks such as resistive force theory enable the determination of optimal gaits for micro-undulators, often defined as the waveform maximising the ratio of swimming speed to energetic cost. Part I explores this avenue of research in a theoretical setting. Primary mathematical focus has been on finding optimal waveforms for straight-path forwards locomotion, but organisms do not move exclusively this way: turning and manoeuvring is key to survival. Here we establish a mathematical model, extend- ing previous approaches to modelling swimming micro-undulators, now introducing path curvature, to obtain optimal turning gaits. We obtain an analytical result demonstrating that high-curvature shapes minimise energetic cost when the penalty for bending is reduced. Imposing limitations on the curvature, and investigating multiple high-dimensional shape-spaces, we show that optimal turning results can be closely approximated as constant-curvature travelling waves. Part II adopts an experimental approach. Quantitative phenotyping tools can be used in behavioural screens of the model organism C. elegans to detect differences between wildtype and mutant strains. Expanding the current set of tools to include more orthogonal features could enable increased detection of deficiencies. Here we develop efficiency as a phenotyping lens for C. elegans, quantifying the gait optimality of rare human genetic disease model strains. Genetic diseases in humans are modelled in C. elegans with disease-associated orthologs. We find worm gait efficiency is found to correlate highly with percentage time paused. High efficiencies are exhibited during reversals and backing motions, due to suppressed head-swinging and increase in speed.Open Acces

Computational Tools and Experimental Methods for the Development of Passive Prosthetic Feet

Modern prosthetic foot designs are incredibly diverse in comparison to what was o↵ered to amputees at the turn of the millennium. Powered ankles can supply natural levels of joint torque, whilst passive feet continue to optimise for kinematic goals. However, most passive feet still do not solve the issue of unhealthy loads, and an argument can be made that optimisation methods have neglected the less active and elderly amputee. This thesis creates a framework for a novel approach to prosthetic foot optimisation by focusing on the transitionary motor tasks of gait initiation and termination.An advanced FEA model has been created in ANSYS® using boundary con-ditions derived from an ISO testing standard that replicates stance phase loading. This model can output standard results found in the literature and goes beyond by parameterising the roll-over shape within the software using custom APDL code. Extensive contact exploration and an experimental study have ensured the robustness of the model. Subject force and kinematic data can be used for specific boundary conditions, which would allow for easy adaptation to the transitionary motor tasks.This FEA model has been used in the development of prosthetic experiment tool, which can exchange helical springs to assess e↵ects of small changes in sti↵-ness on gait metrics. A rigorous design methodology was employed for all compo-nents, including parametric design studies, response surface optimisation, and ISO level calculations. The design has been manufactured into a working prototype and is ready for clinical trials to determine its efficacy.The conclusion of this framework is in the development of an experimental method to collect subject data for use in the models. A pilot study uncovered reliable protocols, which were then verified with ANOVA statistics. Proportional ratios were defined as additions to metric peak analyses already found in the liter-ature. These tools are ready for deployment in full clinical trials with amputees, so that a new prosthetic optimisation pathway can be discovered for the benefit of less active or elderly amputees