Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "data driven method" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Overview on topology identification technologies for a low-voltage distribution network
Autorzy:
Haotian, Ge
Jiuming, Zhong
Powiązania:
https://bibliotekanauki.pl/articles/27309955.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
data driven method
low-voltage distribution network
signal injection method
topology identification
Opis:
The topology identification of low-voltage distribution networks is an important foundation for the intelligence of low-voltage distribution networks. Its accuracy fundamentally determines the effectiveness of functions such as power system state estimation, operational control, optimization planning, and intelligent electricity consumption. The low-voltage distribution network is composed of transformers, lines, and end users. The key task of topology identification is to distinguish the connection relationship between distribution transformers, low-voltage lines, and phase sequence with end users, which can be divided into transformer user relationship, line user relationship, and phase user relationship. At present, the main methods of low-voltage network topology identification can be divided into signal injection method and data analysis method. The signal injection method requires a large number of additional terminal devices and is difficult to promote. The data analysis method combines the characteristics of switch state, voltage, current, electrical energy, and other data to perform topology analysis. The commonly used methods include correlation analysis and feature learning. Finally, typical problems that urgently need to be solved in topology recognition and representation were proposed, providing a reference for the research and development of low-voltage distribution network topology automatic recognition technology.
Źródło:
Archives of Electrical Engineering; 2023, 72, 4; 1017--1034
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Switching time estimation and active mode recognition using a data projection method
Autorzy:
Hakem, A.
Cocquempot, V.
Pekpe, K. M.
Powiązania:
https://bibliotekanauki.pl/articles/330702.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
switching system
mode recognition
fault detection
fault isolation
data driven method
mode discernability
switching detectability
fault identifiability
system przełączania
tryb rozpoznawania
detekcja uszkodzeń
lokalizacja uszkodzeń
tryb rozróżnialności
identyfikowalność uszkodzeń
Opis:
This paper proposes a data projection method (DPM) to detect a mode switching and recognize the current mode in a switching system. The main feature of this method is that the precise knowledge of the system model, i.e., the parameter values, is not needed. One direct application of this technique is fault detection and identification (FDI) when a fault produces a change in the system dynamics. Mode detection and recognition correspond to fault detection and identification, and switching time estimation to fault occurrence time estimation. The general principle of the DPM is to generate mode indicators, namely, residuals, using matrix projection techniques, where matrices are composed of input and output measured data. The DPM is presented in detail, and properties of switching detectability (fault detectability) and discernability between modes (fault identifiability) are characterized and discussed. The great advantage of this method, compared with other techniques in the literature, is that it does not need the model parameter values and thus can be applied to systems of the same type without identifying their parameters. This is particularly interesting in the design of generic embedded fault diagnosis algorithms.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2016, 26, 4; 827-840
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies