229 research outputs found
Features of cross-correlation analysis in a data-driven approach for structural damage assessment
This work discusses the advantage of using cross-correlation analysis in a data-driven
approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful
diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy
data and outliers, as well as the management of data cleansing stages can be facilitated through the
implementation of a preprocessing stage based on cross-correlation functions. Additionally, this
work evidences an improvement in damage detection when the cross-correlation is included as part
of the whole damage assessment approach. The proposed methodology is validated by processing
data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach
based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the
preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing
maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of
the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft
wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as
mass-added. As the main concluding remark, the suitability of cross-correlation features combined
with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment
algorithm is verified for SHM tasks.Peer ReviewedPostprint (published version
Sensor fusion for tangible acoustic interfaces for human computer intreraction
This thesis presents the development of tangible acoustic interfaces for human computer interaction. The method adopted was to position sensors on the surface of a solid object to detect acoustic waves generated during an interaction, process the sensor signals and estimate either the location of a discrete impact or the trajectory of a moving point of contact on the surface. Higher accuracy and reliability were achieved by employing sensor fusion to combine the information collected from redundant sensors electively positioned on the solid object. Two different localisation approaches are proposed in the thesis. The learning-based approach is employed to detect discrete impact positions. With this approach, a signature vector representation of time-series patterns from a single sensor is matched with database signatures for known impact locations. For improved reliability, a criterion is proposed to extract the location signature from two vectors. The other approach is based on the Time Difference of Arrival (TDOA) of a source signal captured by a spatially distributed array of sensors. Enhanced positioning algorithms that consider near-field scenario, dispersion, optimisation and filtration are proposed to tackle the problems of passive acoustic localisation in solid objects. A computationally efficient algorithm for tracking a continuously moving source is presented. Spatial filtering of the estimated trajectory has been performed using Kalman filtering with automated initialisation
The Public Service Media and Public Service Internet Manifesto
This book presents the collectively authored Public Service Media and Public Service Internet Manifesto and accompanying materials.The Internet and the media landscape are broken. The dominant commercial Internet platforms endanger democracy. They have created a communications landscape overwhelmed by surveillance, advertising, fake news, hate speech, conspiracy theories, and algorithmic politics. Commercial Internet platforms have harmed citizens, users, everyday life, and society. Democracy and digital democracy require Public Service Media. A democracy-enhancing Internet requires Public Service Media becoming Public Service Internet platforms – an Internet of the public, by the public, and for the public; an Internet that advances instead of threatens democracy and the public sphere. The Public Service Internet is based on Internet platforms operated by a variety of Public Service Media, taking the public service remit into the digital age. The Public Service Internet provides opportunities for public debate, participation, and the advancement of social cohesion. Accompanying the Manifesto are materials that informed its creation: Christian Fuchs’ report of the results of the Public Service Media/Internet Survey, the written version of Graham Murdock’s online talk on public service media today, and a summary of an ecomitee.com discussion of the Manifesto’s foundations
Simultaneous localization and mapping for inspection robots in water and sewer pipe networks: a review
At the present time, water and sewer pipe networks are predominantly inspected manually. In the near future, smart cities will perform intelligent autonomous monitoring of buried pipe networks, using teams of small robots. These robots, equipped with all necessary computational facilities and sensors (optical, acoustic, inertial, thermal, pressure and others) will be able to inspect pipes whilst navigating, selflocalising and communicating information about the pipe condition and faults such as leaks or blockages to human operators for monitoring and decision support. The predominantly manual inspection of pipe networks will be replaced with teams of autonomous inspection robots that can operate for long periods of time over a large spatial scale. Reliable autonomous navigation and reporting of faults at this scale requires effective localization and mapping, which is the estimation of the robot’s position and its surrounding environment. This survey presents an overview of state-of-the-art works on robot simultaneous localization and mapping (SLAM) with a focus on water and sewer pipe networks. It considers various aspects of the SLAM problem in pipes, from the motivation, to the water industry requirements, modern SLAM methods, map-types and sensors suited to pipes. Future challenges such as robustness for long term robot operation in pipes are discussed, including how making use of prior knowledge, e.g. geographic information systems (GIS) can be used to build map estimates, and improve the multi-robot SLAM in the pipe environmen
Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands
Book of abstract
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
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