Fibre optic distributed sensor system for condition monitoring of synthetic ropes

Reliability of the measuring devices is very important problem. Optical fibre sensors are very efficient. The use of optical fibre sensors for monitoring the physical and chemical parameters has been expanding over resent years. These sensors are applied for monitoring the structural integrity of long, parallel lay synthetic ropes. Such ropes are corrosion free, however, their operational lifetime under cyclic load is not well understood and premature failure can occur due to slippage and breakage of yarns within the rope. The monitoring system has been proposed which is based on acoustic detection of yarn breakage. Monitoring the strain and temperature is performed using the array of fibre gratings distributed along the rope length.

Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Automatic object segmentation from calibrated images

This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape representation of a potentially texture-less object by computing a visual hull. We propose an automatic approach where the object to be segmented is identified by the pose of the cameras instead of user input such as 2D bounding rectangles or brush-strokes. The key behind our method is a pairwise MRF framework that combines (a) foreground/background appearance models, (b) epipolar constraints and (c) weak stereo correspondence into a single segmentation cost function that can be efficiently solved by Graph-cuts. The segmentation thus obtained is further improved using silhouette coherency and then used to update the foreground/background appearance models which are fed into the next Graph-cut computation. These two steps are iterated until segmentation convergences. Our method can automatically provide a 3D surface representation even in texture-less scenes where MVS methods might fail. Furthermore, it confers improved performance in images where the object is not readily separable from the background in colour space, an area that previous segmentation approaches have found challenging. © 2011 IEEE.

Characterisation and fluidisation of synthetic pit latrine sludge

Half of the world’s urban population will live in informal settlements or “slums” by 2030. Affordable urban sanitation presents a unique set of challenges as the lack of space and resources to construct new latrines makes the de-sludging of existing pits necessary and is something that is currently done manually with significant associated health risks. Therefore various mechanised technologies have been developed to facilitate pit emptying, with the majority using a vacuum system to remove material from the top of the pit. However, this results in the gradual accumulation of unpumpable sludge in the pit, which eventually fills the latrine and forces it to be abandoned. This study has developed a method for fluidising unpumpable pit latrine sludge, based on laboratory experiments using a harmless synthetic sludge. Such a sludge consisting of clay and compost was developed to replicate the physical characteristics of pit latrine sludges characterised in Botswana during the 1980s. Undrained shear strength and density are identified as the critical parameters in controlling pumpability and a method of sludge characterisation based on these parameters is reported. In a series of fluidisation tests using a one fifth scale pit emptying device the reduction in sludge shear strength was found to be caused by i) dilution, which increases water content, and ii) remoulding, which involves mechanical agitation to break down the structure of the material. The tests demonstrated that even the strongest of sludges could be rendered “pumpable” by sufficient dilution. Additionally, air injection alone produced a three-fold decrease in strength of consolidated samples as a result of remoulding at constant water content. The implications for sludge treatment and disposal are discussed, and the classification of sludges according to the equipment required to remove them from the latrine is proposed. Possible field tests to estimate sludge density and shear strength are suggested. The feasibility of using low cost vacuum cleaners to replace expensive vane pumps is demonstrated. This offers great potential for the development of affordable pit emptying technologies that can remove significantly stronger sludges than current devices through fluidising the wastes at the bottom of the pit before emptying