A condition monitoring platform using COTS wireless sensor networks - Lessons and experience

Developments in Micro-Electro-Mechanical Systems (MEMS), wireless communication systems and ad-hoc networking have created new dimensions to improve asset management not only during the operational phase but throughout an asset's lifecycle based on using improved quality of information obtained with respect to two key aspects of an asset: its location and condition. In this paper, we present our experience as well as lessons learnt from building a prototype condition monitoring platform to demonstrate and to evaluate the use of COTS wireless sensor networks to develop a prototype condition monitoring platform with the aim of improving asset management by providing accurate and real-time information. © 2010 IEEE.

Warped Mixtures for Nonparametric Cluster Shapes

A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a model which warps a latent mixture of Gaussians to produce nonparametric cluster shapes. The possibly low-dimensional latent mixture model allows us to summarize the properties of the high-dimensional clusters (or density manifolds) describing the data. The number of manifolds, as well as the shape and dimension of each manifold is automatically inferred. We derive a simple inference scheme for this model which analytically integrates out both the mixture parameters and the warping function. We show that our model is effective for density estimation, performs better than infinite Gaussian mixture models at recovering the true number of clusters, and produces interpretable summaries of high-dimensional datasets.

Monitoring offshore pipelines using forced transverse vibration: Data analysis

Vibration methods are used to identify faults, such as spanning and loss of cover, in long off-shore pipelines. A pipeline `pig', propelled by fluid flow, generates transverse vibration in the pipeline and the measured vibration amplitude reflects the nature of the support condition. Large quantities of vibration data are collected and analyzed by Fourier and wavelet methods.

Active-passive 44 SOA-based switch with integrated power monitoring

The first monolithically integrated 44 switch with power monitoring function using on-chip PIN photodiodes is reported. Using 10Gb/s signals, under active power control an IPDR of 12dB for a 1dB power penalty is achieved. © 2012 OSA.

Construction site image retrieval based on material cluster recognition

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of image processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based construction site image retrieval method is presented. This method is based on image retrieval techniques, and specifically those related with material and object identification and matches known material samples with material clusters within the image content. The results demonstrate the suitability of this method for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

Methods of monitoring of metro lining in Prague

There are several reasons for monitoring of underground structures and they have already been discussed many times, e.g. from the view of ageing or state after accidental event like flooding of Prague metro in 2002. Monitoring of Prague metro is realized in the framework of international research project sponsored by ESF-S3T. The monitoring methods used in Prague are either classical one or new or developing one. The reason for different monitoring methods is the different precision of each method and also for cross-checking between them and their evaluation. Namely we use convergence, tiltmetres, crackmetres, geophysical methods, laser scanning, computer vision and finally installation of MEMS monitoring devices. In the paper more details of each method and obtained results will be presented. The monitoring methods are complemented by wireless data collection and transfer for real-time monitoring. © 2012 Taylor & Francis Group.

Micro-measurement and monitoring system for ageing underground infrastructure (Underground M3)

Advances in the development of computer vision, miniature Micro-Electro-Mechanical Systems (MEMS) and Wireless Sensor Network (WSN) offer intriguing possibilities that can radically alter the paradigms underlying existing methods of condition assessment and monitoring of ageing civil engineering infrastructure. This paper describes some of the outcomes of the European Science Foundation project "Micro-Measurement and Monitoring System for Ageing Underground Infrastructures (Underground M3)". The main aim of the project was to develop a system that uses a tiered approach to monitor the degree and rate of tunnel deterioration. The system comprises of (1) Tier 1: Micro-detection using advances in computer vision and (2) Tier 2: Micro-monitoring and communication using advances in MEMS and WSN. These potentially low-cost technologies will be able to reduce costs associated with end-of-life structures, which is essential to the viability of rehabilitation, repair and reuse. The paper describes the actual deployment and testing of these innovative monitoring tools in tunnels of London Underground, Prague Metro and Barcelona Metro. © 2012 Taylor & Francis Group.

Brillouin scattering of cluster-assembled carbon films

The low frequency vibrational spectrum of cluster beam deposited carbon films was studied by Brillouin light scattering. In thin films the values of both bulk modulus and shear modulus has been estimated from the shifts of surface phonon peaks. The values found indicate a mainly sp2 coordinated random network with low density. In thick films a bulk longitudinal phonon peak was detected in a spectral range compatible with the value of the index of refraction and of the elastic constants of thin films. High surface roughness, combined with a rather strong bulk central peak, prevented the observation of surface phonon features. © 1998 Elsevier Science Ltd. All rights reserved.