Uncertainty in Collocated and Array Sensors
A special issue of Sensors (ISSN 1424-8220).
Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 501
Special Issue Editors
Interests: geodetic/positioning sensors; acceleration sensors; oceanography sensors; measurement uncertainties; signal analysis; error propagation
2. School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
3. China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: use of experimental techniques in fluid mechanics such as PIV, LDA, HWA, pressure, temperature (use of liquid crystals), wall shear and aerodynamic force measurements, and flow visualization; investigating flow phenomena such as dynamic stall and stall flutter of pitching and plunging wings; flow control using pulsating jets; aerodynamics of UAVs; performance of swim fins and sails; flow in microchannels with superhydrophobic/superhydrophylic surfaces; flow in stent models/aneurysms/self-oscillating flexible tubes; valveless pumping
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Special Issue Information
Dear Colleagues,
A basic requirement for successful functioning of sensor arrays and networks (for example, to control robots and flow in wind turbines, or to model seismic waves) is not simply a low average value of noise for each sensor, but, each moment, the output of all sensors in a network differ little from the corresponding “true” values. This requirement is not always satisfied, and sometimes leads to pitfalls; a notable example is a dispute on a famous theory of theoretical physics, proved to reflect measurement errors.
In the past, to overcome the problem of noise in sensor networks, there have been proposed statistical techniques to identify and discard faulty sensors producing inconsistent data. A more promising approach is to analyze the output of collocated sensors (sets of sensors simultaneously recording the same signal, mostly used for backup), and on this basis to develop techniques to control and mitigate the different types of sensors noise.
The first results of such approaches indicate differences in signals by collocated instruments occasionally beyond the limits of random noise, especially in dynamic measurements (rapidly and intensively changing values). These results raise various questions, for example “how to separate the response of a sensor and of an overall measurement system from the source signals, path effects and other signal distortion effects?” and “how to reconstruct a low-noise signal from signals of collocated sensors?”.
In this Special Issue, we plan to publish articles from academia and industry, investigating in detail the problems of identification, modeling and mitigation of uncertainty/noise in networks of sensors, especially based on collocated sensors.
Sources, characteristics, propagation effects and impacts of noise, contribution of various components of the measuring system in the error budget, and techniques to minimize uncertainty in static and dynamic conditions are to be covered.
Topics to be covered include (but are not limited to) various fields of engineering (civil, mechanical, geodetic, electronic/electrical, chemical, environmental and bio-mechanical), sciences (physics and geophysics, atmospheric, space and marine sciences, chemistry, medicine) and metrology.
Case studies, laboratory and field results, data analysis, methodological approaches, review and theoretical articles are welcome for this Special Issue.
Prof. Dr. Stathis C. Stiros
Prof. Dr. Demetri Mathioulakis
Guest Editors
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Keywords
- Uncertainty and noise
- Array and network sensors
- Collocated sensors
- Sensor response
- Dynamic and static noise
- Calibration
- Signal processing
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