A Cost-Effective System for Aerial 3D Thermography of Buildings

Three-dimensional (3D) imaging and infrared (IR) thermography are powerful tools in many areas in engineering and sciences. Their joint use is of great interest in the buildings sector, allowing inspection and non-destructive testing of elements as well as an evaluation of the energy efficiency. When dealing with large and complex structures, as buildings (particularly historical) generally are, 3D thermography inspection is enhanced by Unmanned Aerial Vehicles (UAV-also known as drones). The aim of this paper is to propose a simple and cost-effective system for aerial 3D thermography of buildings. Special attention is thus payed to instrument and reconstruction software choice. After a very brief introduction to IR thermography for buildings and 3D thermography, the system is described. Some experimental results are given to validate the proposal

DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES

In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As a result, the mining industry, in its efforts to modernize and advance its methods and techniques, is one of the many industries that has turned to autonomous systems. Vehicle automation in such complex working environments can play a critical role in improving worker safety and mine productivity. One of the most time-consuming tasks of the mining cycle is the transportation of the extracted ore from the face to the main haulage facility or to surface processing facilities. Although conveyor belts have long been the autonomous transportation means of choice, there are still many cases where a discrete transportation system is needed to transport materials from the face to the main haulage system. The current dissertation presents the development of a navigation system for an autonomous shuttle car (ASC) in underground room and pillar coal mines. By introducing autonomous shuttle cars, the operator can be relocated from the dusty, noisy, and potentially dangerous environment of the underground mine to the safer location of a control room. This dissertation focuses on the development and testing of an autonomous navigation system for an underground room and pillar coal mine. A simplified relative localization system which determines the location of the vehicle relatively to salient features derived from on-board 2D LiDAR scans was developed for a semi-autonomous laboratory-scale shuttle car prototype. This simplified relative localization system is heavily dependent on and at the same time leverages the room and pillar geometry. Instead of keeping track of a global position of the vehicle relatively to a fixed coordinates frame, the proposed custom localization technique requires information regarding only the immediate surroundings. The followed approach enables the prototype to navigate around the pillars in real-time using a deterministic Finite-State Machine which models the behavior of the vehicle in the room and pillar mine with only a few states. Also, a user centered GUI has been developed that allows for a human user to control and monitor the autonomous vehicle by implementing the proposed navigation system. Experimental tests have been conducted in a mock mine in order to evaluate the performance of the developed system. A number of different scenarios simulating common missions that a shuttle car needs to undertake in a room and pillar mine. The results show a minimum success ratio of 70%

Calculating and Assessing Mobile Mapping System Point Density for Roadside Infrastructure Surveys

The current generation of Mobile Mapping Systems (MMSs) capture increasingly larger amounts of data in a short time frame. Due to the relative novelty of this technology there is no concrete understanding of the point density that different scanner confgurations and scanner hardware settings will exhibit on objects at specific distances. Depending on the project requirements, obtaining the required point density impacts on survey time, processing time, data storage and is the underlying limit of automated algorithms. Insufficient knowledge of the factors in uencing MMS point density means that defning point density in project specifications is a complicated process. The objectives of this thesis are to calculate point density, to assess MMS laser scanner configuration and hardware settings and to benchmark a selection of MMSs in terms of their point density. The calculation methods involve a combination of algorithms applying 3D surface normals and 2D geometric formulae and outputs profile angle, profile spacing, point spacing and point density. Each of these elements are a major factor in calculating point density on arbitrary objects, such as road signs, poles or buildings - all important features in asset management surveys. These algorithms are combined in a system called the Mobile Mapping Point Density Calculator (MIMIC). MIMIC is then applied in a series of tests identifying the recommended MMS laser scanner configuration and scanner hardware settings for near side infrastructure. The in uence that the scanner orientation and location on the MMS has on point density is quantified, resulting in a recommended MMS laser scanner configuration. A series of benchmarking tests assess the performance of one commercial and two theoretical MMSs in terms of their point density. The recommended configuration identified in the previous tests allows a low specification MMS to increase its performance in relation to a higher specification MMS. The benchmarking tests also highlight that a high pulse repetition rate is preferable to a high mirror frequency for maximising point density. The findings in this thesis enable a MMS to be configured to maximise point density for specific targets. Researchers can utilise MIMIC to tailor their automated algorithm's point density requirements for specific targets