|Title:||Knowledge-based understanding and interpretation of construction engineering drawings|
|Subject:||Hong Kong Polytechnic University -- Dissertations|
Structural design -- Data processing
Engineering drawings -- Data processing
|Department:||Department of Building and Real Estate|
|Pages:||xii, 155 leaves : ill. ; 30 cm|
|Abstract:||In the construction industry, many aspects from structural analysis to drawing production have already been computerized, except quantity surveying which includes the measurement of steel reinforcement used in reinforced concrete, still involves large amount of manual processes. Taking off is a very time consuming process. For example, at the tender preparation stage, it normally takes 4 to 5 man-months of an experienced Quantity Surveyor to complete the measurement work of a reasonable size, high-rise construction project. In order to solve this problem, this thesis presents a computer-aided quantity survey system, named as VHSTATION, to automatically recognize and interpret CAD structural engineering drawings, and to take off the amount of steel reinforcement indicated in the drawings. The methodologies integrated in the VHSTATION system include methods for automatic version control to guarantee the most update version to be analyzed; weighting symbols by the statistics of similar instances in candidate drawings under different recognition thresholds in order to adjust symbol recognition order; detecting walls in an architectural plan based on door symbol recognition; automatically extracting geometric features of architectural objects and converting the features into recognition rules, and utilizing Virtual Reality (VR) enabled 3D reconstruction and collision detection techniques to automatically identify and minimize design errors. The integration of these methods not only makes a useful contribution to the task of developing intelligent computer systems to automate the task of quantity surveying, but also provides interesting insight into the research domain of engineering drawings recognition.|
|Rights:||All rights reserved|
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item: