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A statistical data-driven approach for vibration-based condition monitoring of bolted connections in structural systems

Abstract:

A variety of civil infrastructure assets such as bridges, pipes and railways form an integral part of modern societies. However, these structures are vulnerable to changes in environmental conditions and physical or direct damages. These vulnerabilities have brought rise to Structural Health Monitoring (SHM) systems, which are installed in civil infrastructure assets to monitor the health of structures through installed sensors. SHM is achieved by implementing techniques that identify, localise and assess the damage on infrastructure assets. Structural elements in metallic infrastructures assets have been connected using rivet joints and bolts since 1900s. The integrity of these connections is a crucial factor in the overall stiffness and strength of a structure; hence, it is beneficial to install a damage identification system which monitors the dynamic response within connections and detects any differences that may arise due to changes in connection characteristics. Previous studies investigated the dynamic response through modal-based properties where modal damping is one of the least researched topics due to mathematical complexities in obtaining damping matrix and limitations in the traditional methods to obtain damping ratio in both time and frequency domains. Probability Distribution Decay Rate (PDDR) algorithm has been proposed which seems to be able to overcome the limitations in time domain to detect changes in the overall damping by observing changes in the statistical parameters. However, PDDR method limitations are following: (1) was tested on only sensors that is placed close to structural connection with loosened bolts; (2) only achieves levels 1 and 3 of Rytter’s damage classification (detection and quantification). Several techniques such as, Data fusion, damage localisation, supervised and unsupervised learning, and dimensionality reduction technique were implemented to PDDR algorithm to fuse the distribution data together and observe any deviation in the physical condition of the structure and localise the damage in the structure with bolted connections. Comparison was done between Kalman and Bayesian fusion methodologies using single story frame and 4-Storey steel frame datasets and it showed an improvement in detection, localisation and classification from individual sensors.

M.Sc. Unmanned Ground Vehicle (UGV)

The dissertation portrays the development of the Unmanned Ground Vehicle (UGV) that is capable of navigating through complex environments. The objectives of the project were accomplished where Robot Operating Systems (ROS) packages have been employed into the Nexus robot and programming microcontroller which is connected to external devices such as sensors and motor controller to be integrated with ROS.  An investigation was conducted to explore existing approaches and hardware devices to attain suitable methods that can be applied in the robot design. The project involves using Simultaneous Localisation And  Mapping (SLAM) to map and localise the landscape and the  Navigation_Stack was used to provide a target to reach, plans a path while avoiding obstacles. In addition, the Nexus robot applied a PD controller with the aim of controlling and regulating the amount of voltage going to the motors and reducing the positional error caused by the difference in speed of the motors. Nexus robot was able to partially control and regulate the voltage going to motors and maintained the positional error. However, during the testing phase, the laser finder was damaged which led to using Gazebo to simulate the robot. The robot in the  simulation was able to navigate and map terrain while avoiding  obstacles. Some challenges were faced regarding control system and movement of Nexus robot; several improvements are suggested.

B.Eng. Maze Solving Robot

This thesis presents the development of two autonomous robots that are able to navigate through a maze. The aim of the project was achieved by programming the microcontrollers combined with a sensor,  wireless communication, data logger and motor drive circuit. A  Literature review was done to investigate the existing hardware and software devices to determine the optimum components to be implemented in the design. The project consisted of programming the main robot to solve a maze, map it, store the map and transmit it to a follower robot.  This allowed the follower robot to use the instructions received to  navigate through the maze. Both robots were designed and tested and were  able to navigate through the maze. However, some challenges were  encountered regarding the displayed map and the motors used;  improvements are suggested.