Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Active control of the accordion modes of a submerged hull

Active vibration control of a submerged hull is presented. A submarine hull can be idealised as a ring stiffened finite cylinder with applied fluid loading. At low frequencies, rotation of the propeller results in discrete tones at the blade passing frequency and its harmonics. The low frequency axial and radial vibration modes of the submerged body can result in a high level of radiated noise. Global hull modes are difficult to attenuate since passive control techniques such as damping materials are not practical due to size and weight constraints. This work investigates active vibration control of a submarine hull for attenuation of the structural and acoustic responses. Based on a feedforward algorithm at tonal frequencies, active vibration suppression of the axial and radial hull displacements are investigated. The effect of the various control arrangements on the structure-borne radiated noise is examined. Numerical simulations of the control performance are presented.

From subspace learning to distance learning: A geometrical optimization approach

In this paper, we adopt a differential-geometry viewpoint to tackle the problem of learning a distance online. As this problem can be cast into the estimation of a fixed-rank positive semidefinite (PSD) matrix, we develop algorithms that exploits the rich geometry structure of the set of fixed-rank PSD matrices. We propose a method which separately updates the subspace of the matrix and its projection onto that subspace. A proper weighting of the two iterations enables to continuously interpolate between the problem of learning a subspace and learning a distance when the subspace is fixed. © 2009 IEEE.