|Title:||Surveying-computing integrated approach to tracking a tunnel boring machine during microtunneling|
|Subject:||Hong Kong Polytechnic University -- Dissertations|
Tunneling -- Equipment and supplies
|Department:||Department of Civil and Structural Engineering|
|Pages:||xxi, 164 leaves : ill. (some col.) ; 30 cm.|
|Abstract:||Effective resource management on dynamic jobsites is crucial to successful construction project delivery. Automation systems for positioning and tracking construction resources, such as equipment, materials, tools and laborers involved on the site, provide engineers with reliable operations data, enhanced situational awareness and more effective project control. Technological advances have opened up the prospect of applying state-of-the-art radio frequency (RF) technologies, such as the global positioning system (GPS) and the radio frequency identification (RFID), for resource tracking in construction engineering. The performances of RF systems, however, could be severely degraded and thus become unreliable, due to signal blockage, distortion or deterioration when applied in an enclosed or partially covered environment. This thesis research aims to tackle challenging resource tracking problems in the enclosed, complicated underground space of microtunneling construction. In such projects a steerable, remotely controlled tunnel boring machine (TBM) drills a subsurface utility tunnel with diameters generally ranging from 0.6 to 2.5 m. Accurate TBM tracking provides vital guidance to steering its advancement along an as-designed tunnel alignment in the underground space. However, on the majority of microtunneling sites, the TBM is only roughly guided by conventional laser alignment systems. The operators, therefore, still rely heavily on experiences for TBM steering and alignment control. Although advanced TBM guidance systems have been developed by integrating sophisticated mechanical, optical and electromagnetic subsystems, the high complexity of the system design can compromise system reliability, while considerably increasing the system's price and consumption cost.|
This research proposes an automated and cost-effective solution for precise TBM tracking through surveying-computing integration. A robotic total station is remotely controlled by preprogrammed procedures to automatically track and survey the observation points fixed on the TBM. Thus, the TBM's position in the underground space is mapped on the fly within millimeter level accuracy. Any deviations from the as-designed alignment can also be derived instantaneously. Furthermore, given the coordinates of a minimum of three observation points on the TBM, the TBM's orientation (as defined with its three body rotation angles of yaw, pitch and roll) is determined by applying sophisticated point-to-angle computing algorithms in real time, rather than by using any orientation gauges or instruments (such as inclinometers, gyroscopes and compasses). A Monte Carlo simulation approach is then formulated and applied in order to ensure the performances of the proposed solution satisfy practical application requirements in terms of the accuracy. Two well-established point-to-angle computing algorithms originating from space science and navigation engineering, the deterministic tri-axis attitude determination (TRIAD) algorithm and the optimal Quaternion method, are elaborated, evaluated and compared. Besides, four possible layout options for fixing a limited quantity of observation points on the TBM are considered in the simulations. A hardware-software integrated prototype of the proposed TBM tracking solution was developed in house for concept proving and verifying the application value. The prototype system has undergone extensive validation testing. Its functionality was first tested in the laboratory. With the assistance of industry partners, the practical applicability of the system was further verified over a three-month period in late 2009, on an ongoing microtunneling site in Hong Kong. Coupled with a 1.2 m diameter TBM, the system had been successfully implemented in tracking the installation of a 55 m long section of concrete tunnel. The TBM's position and orientation data were gathered automatically and completely. The data updating frequency was once per minute. The research has made essential contributions to the state of the art in resource tracking, computing and automation in construction engineering research. In terms of industrial contributions, the research has delivered a surveying-computing integrated, automated and cost-effective solution to tracking a working TBM in the underground space, holding high potential to advance the state of the practice in microtunneling operations.
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