1,720,987 research outputs found
The Possibilistic Kalman Filter: Definition and Comparison with the Available Methods
Full text linkThe Kalman filter (KF) is a commonly used algorithm for predicting the state variables of a system. It is based on the model of the system and some measurements (observed over time) that are characterized by their own uncertainty. This article defines a possibilistic KF whose main feature is to predict the values of the state variables and the associated uncertainty when uncertainty contributions of nonrandom nature are present. This possibilistic KF is defined in the mathematical framework of the possibility theory and employs random-fuzzy variables and the related mathematics since these variables can properly represent measurement results together with the associated uncertainty. A comparison with the available methods is provided, as well as the final validation
A comparison between different methods for processing the random part of random-fuzzy variables representing measurement results
No full textIn the recent years, fuzzy variables and random-fuzzy
variables have been proposed to represent the measurement results
with their associated uncertainty. However, up to now,
the different authors do not yet agree in the mathematical way
fuzzy variables should be composed together, so that different approaches
have been proposed. This paper compares these approaches,
in order to find their advantages and disadvantages and
shows a new proposal, that is supposed to overcome, hopefully,
the disadvantages of the original ones
How to process the random part of RFVs: comparison of available methods and new proposal
No full textIn the recent years, fuzzy variables and random-fuzzy variables have been proposed to represent the measurement results
with their associated uncertainty. However, up to now, the different authors do not yet agree in the mathematical way fuzzy variables
should be composed together, so that different approaches have been proposed. This paper compares these approaches, in order to
find their advantages and disadvantages and shows a new proposal, that is supposed to overcome, hopefully, the disadvantages of the
original ones
A software trigger based synchronization for multipurpose distributed acquisition systems
No full textSynchronization is one of the key aspects and a requirement for modern day technologies. It's a requirement for almost every sector including power, health, retail, navigation, banking. Synchronization is also important when using distributed acquisition systems. Synchronous acquisition is strictly needed in applications like Phasor Measurement Units (PMU) and wide area sensor networks. Since the data from the sensors are all collectively processed by a central unit, it is important that the data from all sensors is synchronized. Therefore, the concept of synchronized sampling when using distributed acquisition systems forms an interesting research area. There have been numerous research papers discussing different methods to do this. But, in most of them, the available technology is specific to a particular application. This paper shows an initial attempt to present a solution with a PTP driven software trigger that could potentially be used for multiple applications
The impact of Internet transmission on the uncertainty in the electric power quality estimation by means of a distributed measurement system
No full textThere is increasing evidence, in literature, that the estimation of the electric power quality requires the simultaneous measurement of several quantities and indices, in all lines connected to the same point of common coupling. The increase in the performance that the measuring systems based on digital signal processing techniques has undergone during recent years and the capability of the digital systems of interconnecting and exchanging data are making these systems more and more appealing and cost-effective for power quality applications. Moreover, the availability of a world-wide, low-cost, and public-domain interconnection system, the Internet, is pushing the evolution of the remote measurement systems, where the measurement results provided by in-field measurement systems are collected and stored by a central unit, toward the distributed measurement systems, where different systems, located in different places, share the same data in order to perform a measurement. It is known that the major drawback of these systems is the lack of synchronization of the shared data, due to the variable and unpredictable throughput of the net, which may affect the uncertainty of the result of the measurement in a quite significant way. This paper analyzes a distributed measurement system for electric power quality measurements and shows how the possible detrimental effects of data transmission over an Internet connection can be reduced by means of a suitable use of averaging techniques, thus avoiding a strict and expensive synchronization between the different units of the distributed measurement system. At last, an estimate of the effects of the possible transmission delays on the measurement uncertainty is given
Low-cost real-time motion capturing system using inertial measurement units
Full text linkHuman movement modeling - also referred to as motion-capture - is a rapidly expanding field of interest for medical rehabilitation, sports training, and entertainment. Motion capture devices are used to provide a virtual 3-dimensional reconstruction of human physical activities - employing either optical or inertial sensors. Utilizing inertial measurement units and digital signal processing techniques offers a better alternative in terms of portability and immunity to visual perturbations when compared to conventional optical solutions.
In this paper, a cable-free, low-cost motion-capture solution based on inertial measurement units with a novel approach for calibration is proposed. The goal of the proposed solution is to apply motion capture to the fields that, because of cost problems, did not take enough benefit of such technology (e.g., fitness training centers). According to this goal, the necessary requirement for the proposed system is to be low-cost. Therefore, all the considerations and all the solutions provided in this work have been done according to this main requirement
A possibilistic approach for measurement uncertainty propagation in prognostics and health management
Full text linkIn this paper, a similarity-based data-driven prognostic algorithm for the estimation of the Remaining Useful Life of a product is proposed. It is based on the exploitation of run-to-failure data of products, which are supposed to be characterized by similar operational conditions. The core of the contribution is the application of a possibilistic framework, namely a Random-Fuzzy Variable approach, for the representation and propagation of the measurement uncertainty, which is a crucial source of uncertainty in Prognostics and Health Management. The results obtained for a real application case as Medium and High Voltage Circuit Breakers, have shown a high prognostic power of the algorithm, which therefore represents a potential tool for an effective Predictive Maintenance strategy
- …
