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Non-intrusive Measurement Techniques

2020
Non-intrusive measurement techniques are based on optical techniques and have tremendous advantages, but as all measurement techniques they have their limitations and drawbacks. Aside the arduous technical issues associated with data processing and analysis, their main physical limitation is simply based on visual access of the experimental domain of ...
Bruno Chanetz   +5 more
openaire   +1 more source

Toward smart energy user: Real time non-intrusive load monitoring with simultaneous switching operations

, 2021
Non-intrusive load monitoring is a promising technology in intelligent energy consumption management, which can provide insights for electricity use patterns and customer living habits, leading to the technical support of multiple smart energy use ...
Yu Liu   +4 more
semanticscholar   +1 more source

Non-intrusive Load Monitoring

2019
The issues relating to the energy conservation and efficiency have gained a role of great importance, from the point of view of both the consumer and the energy provider. Furthermore, over the years, the infrastructures for energy distribution have undergone an ageing process, which have led to the study of the possibility in smart grids implementation,
Roberto Bonfigli, Stefano Squartini
openaire   +1 more source

Non-intrusive refractometer sensor

Pramana, 2010
An experimental realization of a simple non-intrusive refractometer sensor is demonstrated in this communication. The working principle of the sensor is based on intensity modulation of the back-reflected light when output light from an optical fibre end focusses onto air-medium interface.
openaire   +1 more source

Compressive Non-Intrusive Load Monitoring

Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 2020
In non-intrusive load monitoring (NILM), an increase in sampling frequency translates to capturing unique signal features during transient states, which, in turn, can improve disaggregation accuracy. Smart meters are capable of sampling at a high frequency (typically 20kHz).
Shikha Singh   +2 more
openaire   +1 more source

Non-intrusive electric field sensing

SPIE Proceedings, 2014
This paper presents an overview of non-intrusive electric field sensing. The non-intrusive nature is attained by creating a sensor that is entirely dielectric, has a small cross-sectional area, and has the interrogation electronics a long distance away from the system under test. One non-intrusive electric field sensing technology is the slab coupled
S. M. Schultz   +4 more
openaire   +2 more sources

Non Intrusive Load Monitoring

Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, 2015
Buildings across the world contribute significantly to the overall energy consumption. Targeted feedback can help occupants optimise energy consumption. In our first work we present techniques for actionable feedback across fridges and air conditioning (HVAC) units, which can save upto 25% of fridge energy and identify homes needing feedback on HVAC ...
openaire   +1 more source

Distributed non-intrusive load monitoring

ISGT 2011, 2011
Smart grid support for demand response provides strategies for an electricity service provider to shed loads during peak usage periods with minimal consumer inconvenience. Direct load control is a strategy for doing this in which consumers enroll appliances such as electric water heaters, air conditioners, and battery vehicles in a program to respond ...
David C. Bergman   +5 more
openaire   +1 more source

Non-Intrusive Methods

2015
Chapter 12 considers a spectral approach to UQ, namely Galerkin expansion, that is mathematically very attractive in that it is a natural extension of the Galerkin methods that are commonly used for deterministic PDEs and (up to a constant) minimizes the stochastic residual, but has the severe disadvantage that the stochastic modes of the solution are ...
openaire   +1 more source

A non-intrusive PESQ measure

2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014
We present NISQ, a data-driven non-intrusive speech quality measure that has been trained to predict the PESQ score for a given speech signal. NISQ is based on feature extraction and a binary tree regression based model. A training method using the intrusive PESQ algorithm to automatically label large quantities of speech data is presented and utilized.
Dushyant Sharma   +4 more
openaire   +1 more source

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