Performance of Linear Field Reconstruction Techniques with Noise and Uncertain Sensor Locations

We consider a wireless sensor network, sampling a bandlimited field, described by a limited number of harmonics. Sensor nodes are irregularly deployed over the area of interest or subject to random motion; in addition sensors measurements are affected by noise. Our goal is to obtain a high quality reconstruction of the field, with the mean square error (MSE) of the estimate as performance metric. In particular, we analytically derive the performance of several reconstruction/estimation techniques based on linear filtering. For each technique, we obtain the MSE, as well as its asymptotic expression in the case where the field number of harmonics and the number of sensors grow to infinity, while their ratio is kept constant. Through numerical simulations, we show the validity of the asymptotic analysis, even for a small number of sensors. We provide some novel guidelines for the design of sensor networks when many parameters, such as field bandwidth, number of sensors, reconstruction quality, sensor motion characteristics, and noise level of the measures, have to be traded off

In-situ health monitoring for wind turbine blade using acoustic wireless sensor networks at low sampling rates

PhD ThesisThe development of in-situ structural health monitoring (SHM) techniques represents a challenge for offshore wind turbines (OWTs) in order to reduce the cost of the operation and maintenance (O&M) of safety-critical components and systems. This thesis propos- es an in-situ wireless SHM system based on acoustic emission (AE) techniques. The proposed wireless system of AE sensor networks is not without its own challenges amongst which are requirements of high sampling rates, limitations in the communication bandwidth, memory space, and power resources. This work is part of the HEMOW- FP7 Project, ‘The Health Monitoring of Offshore Wind Farms’. The present study investigates solutions relevant to the abovementioned challenges. Two related topics have been considered: to implement a novel in-situ wireless SHM technique for wind turbine blades (WTBs); and to develop an appropriate signal pro- cessing algorithm to detect, localise, and classify different AE events. The major contri- butions of this study can be summarised as follows: 1) investigating the possibility of employing low sampling rates lower than the Nyquist rate in the data acquisition opera- tion and content-based feature (envelope and time-frequency data analysis) for data analysis; 2) proposing techniques to overcome drawbacks associated with lowering sampling rates, such as information loss and low spatial resolution; 3) showing that the time-frequency domain is an effective domain for analysing the aliased signals, and an envelope-based wavelet transform cross-correlation algorithm, developed in the course of this study, can enhance the estimation accuracy of wireless acoustic source localisa- tion; 4) investigating the implementation of a novel in-situ wireless SHM technique with field deployment on the WTB structure, and developing a constraint model and approaches for localisation of AE sources and environmental monitoring respectively. Finally, the system has been experimentally evaluated with the consideration of the lo- calisation and classification of different AE events as well as changes of environmental conditions. The study concludes that the in-situ wireless SHM platform developed in the course of this research represents a promising technique for reliable SHM for OWTBs in which solutions for major challenges, e.g., employing low sampling rates lower than the Nyquist rate in the acquisition operation and resource constraints of WSNs in terms of communication bandwidth and memory space are presente

Level based sampling techniques for energy conservation in large scale wireless sensor networks

As the size and node density of wireless sensor networks (WSN) increase,the energy conservation problem becomes more critical and the conventional methods become inadequate. This dissertation addresses two different problems in large scale WSNs where all sensors are involved in monitoring,but the traditional practice of periodic transmissions of observations from all sensors would drain excessive amount of energy. In the first problem,monitoring of the spatial distribution of a two dimensional correlated signal is considered using a large scale WSN. It is assumed that sensor observations are heavily affected by noise. We present an approach that is based on detecting contour lines of the signal distribution to estimate the spatial distribution of the signal without involving all sensors in the network. Energy efficient algorithms are proposed for detecting and tracking the temporal variation of the contours. Optimal contour levels that minimize the estimation error and a practical approach for selection of contour levels are explored. Performance of the proposed algorithm is explored with different types of contour levels and detection parameters. In the second problem,a WSN is considered that performs health monitoring of equipment from a power substation. The monitoring applications require transmissions of sensor observations from all sensor nodes on a regular basis to the base station,which is very costly in terms of communication cost. To address this problem,an efficient sampling technique using level-crossings (LCS) is proposed. This technique saves communication cost by suppressing transmissions of data samples that do not convey much information. The performance and cost of LCS for several different level-selection schemes are investigated. The number of required levels and the maximum sampling period for practical implementation of LCS are studied. Finally,in an experimental implementation of LCS with MICAzmote,the performance and cost of LCS for temperature sensing with uniform,logarithmic and a combined version of uniform and logarithmically spaced levels are compared with that using periodic sampling

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

Array communications in wireless sensor networks

Imperial Users onl