Visuohaptic Simulation of a Borescope for Aircraft Engine Inspection

Consisting of a long, fiber optic probe containing a small CCD camera controlled by hand-held articulation interface, a video borescope is used for remote visual inspection of hard to reach components in an aircraft. The knowledge and psychomotor skills, specifically the hand-eye coordination, required for effective inspection are hard to acquire through limited exposure to the borescope in aviation maintenance schools. Inexperienced aircraft maintenance technicians gain proficiency through repeated hands-on learning in the workplace along a steep learning curve while transitioning from the classroom to the workforce. Using an iterative process combined with focused user evaluations, this dissertation details the design, implementation and evaluation of a novel visuohaptic simulator for training novice aircraft maintenance technicians in the task of engine inspection using a borescope. First, we describe the development of the visual components of the simulator, along with the acquisition and modeling of a representative model of a {PT-6} aircraft engine. Subjective assessments with both expert and novice aircraft maintenance engineers evaluated the visual realism and the control interfaces of the simulator. In addition to visual feedback, probe contact feedback is provided through a specially designed custom haptic interface that simulates tip contact forces as the virtual probe intersects with the {3D} model surfaces of the engine. Compared to other haptic interfaces, the custom design is unique in that it is inexpensive and uses a real borescope probe to simulate camera insertion and withdrawal. User evaluation of this simulator with probe tip feedback suggested a trend of improved performance with haptic feedback. Next, we describe the development of a physically-based camera model for improved behavioral realism of the simulator. Unlike a point-based camera, the enhanced camera model simulates the interaction of the borescope probe, including multiple points of contact along the length of the probe. We present visual comparisons of a real probe\u27s motion with the simulated probe model and develop a simple algorithm for computing the resultant contact forces. User evaluation comparing our custom haptic device with two commonly available haptic devices, the Phantom Omni and the Novint Falcon, suggests that the improved camera model as well as probe contact feedback with the 3D engine model plays a significant role in the overall engine inspection process. Finally, we present results from a skill transfer study comparing classroom-only instruction with both simulator and hands-on training. Students trained using the simulator and the video borescope completed engine inspection using the real video borescope significantly faster than students who received classroom-only training. The speed improvements can be attributed to reduced borescope probe maneuvering time within the engine and improved psychomotor skills due to training. Given the usual constraints of limited time and resources, simulator training may provide beneficial skills needed by novice aircraft maintenance technicians to augment classroom instruction, resulting in a faster transition into the aviation maintenance workforce

AQM Performance in Multiple Congested Link Networks

TCP Reno, the most widely used implementation on the Internet, uses retransmission timeouts and the receipt of three duplicate ACKs to detect packet loss in the network. In case of multiple congested links, it is important to detect packet losses as early as possible in order to prevent unnecessary timeouts and retransmits. Active Queue Management (AQM) schemes seek to improve the overall user response time by using queue build-ups at the routers to detect congestion. Previous research has focused on determining the effects of AQM schemes on HTTP/1.0 traffic in single congested link networks [2]. In this experiment, we evaluated the performance of TCP Reno with drop-tail routers and ECN-enabled TCP with Selective Acknowledgements (SACK) [5] over Adaptive Random Early Detection (ARED) [4] routers in a multiple congested link network. 2. BACKGROUND & RELATED WOR