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To reduce inspection cost, random-sampling is currently the most popular method to check the quality of steel bridge painting construction. The "randomness" of sampling is the key assumption of the statistical random sampling theory. Only when inspection spots are "randomly" selected, is the decision-making based on the collected data meaningful. Therefore, no mater using human-inspectors, robotinspectors or remote-sensing, the question -"where to take measurement" need to be answered. The research proposed a CAD modeling to assist in generating a stratified sampling scheme and random inspection spots. A surface element with four vertexes is introduced as a basic unit to represent steel structures. The geometry operation to trim stratified sampling scheme is defined. Then, the algorithms to produce random inspection spots are derived. This paper starts with interesting finding of "un-equal" quality happened in the recent painted steel bridges to point out the need of a CAD system for generating stratified sampling scheme and random inspection spots. For years, robotics have been helping the inspection work in certain construction areas. A potential extension of this research is the combination of CAD-sampling plan and inspection robots or remote-sensing. In the future, the CAD-produced random sampling plan could guide robot-inspectors to handle a camera and a probe to test quality of steel bridge painting where it is dangerous for human inspectors to access.

Automated Inspection Planning Through CAD Modeling for Steel Bridge Painting Construction