AUTOMATED APPLICATION FOR STRUCTURAL HEALTH MONITORING

  • Alma Rebeca Velasco Olmos

Student thesis: Master of Philosophy

Abstract

Solving issues in industrial processes, such as the monitoring of deterioration and ageing on materials requires a multidisciplinary point of view to tackle important concerns generated by damage of pieces or structures subjected to stress that may cause economic repercussion and safety hazards. This project proposes an automated structural health monitoring system comprised of a network of sensors attached to a material and, robotic system. The motivation of this work is to develop a tool for research in the active monitoring of materials field and to help to deliver a reliable system for monitoring large structures in the future. The implementation is intended to automate the process, improve time, reduce human operation, and to add a robot as mobile node using a multidisciplinary combination of control, robotics, and Structural health monitoring techniques. This thesis describes, in Chapter 1, the motivation for this project, along with more details on the aim, the steps to achieve the objective and the boundaries defined for this stage of the work. Later, Chapter 2 gives a general background of each field, its requirements to be automated and some literature review in each area. The specifications about the implementation using a range of National Instruments devices are described in Chapter 3. In Chapter 4 and Chapter 5, the results of the application are presented and discussed. Finally, the last chapters displayed the conclusion and future work ideas found in the implementation process, as well as additional reference information of the robot and the implemented system, that are available in the appendixes. In conclusion, the outcome of this thesis is encouraging, even when the work is not entirely completed, and they may offer a good background to create a useful and reliable tool for health monitoring of materials.
Date of Award3 Jan 2018
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorAlexandru Stancu (Supervisor) & Matthieu Gresil (Supervisor)

Keywords

  • Control
  • Automation
  • SHM
  • NDT

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