Temat: monitoring konstrukcji - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Analysis of positioning error and its impact on high frequency properties of differential signal coupler
Autorzy:: Zmuda, M.
Szczepański, S.
Kozieł, S.
Powiązania:: https://bibliotekanauki.pl/articles/200709.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: high speed data transmission monitoring
coupler positioning accuracy
manufacturing of coupling structures
monitoring wysokiej prędkości transmisji danych
dokładność pozycjonowania
produkcja konstrukcji sprzęgła
Opis:: This paper presents the analysis of the effect of differential signal coupler positioning accuracy on its high frequency performance parameters for contact-less high speed chip-to-chip data transmission on PCB application. Our considerations are continuation of the previous works on differential signal coupler concept, design methodology and analysis for high speed data transmission monitoring. The theoretical analysis of possible coupler positioning innaccuracies is extended for representative design cases by simulations carried out using EM simulator. The results reported here confirm that the concept of contactless monitoring of high speed chip-to-chip data transmission in a pair of coupled microstrip lines is of practically usefulness without applying the expensive and precise positioning system.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 2; 549-553
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Ensemble of feature extraction methods to improve the structural damage classification in a wind turbine foundation
Autorzy:: Leon-Medina, Jersson X.
Parés, Núria
Anaya, Maribel
Tibaduiza, Diego A.
Pozo, Francesc
Powiązania:: https://bibliotekanauki.pl/articles/27311417.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: structural health monitoring
wind turbine foundation
damage classification
machine learning
feature extraction
XGBoost
monitorowanie stanu konstrukcji
fundament turbiny wiatrowej
klasyfikacja uszkodzeń
uczenie maszynowe
ekstrakcja cech
Opis:: The condition monitoring of offshore wind power plants is an important topic that remains open. This monitoring aims to lower the maintenance cost of these plants. One of the main components of the wind power plant is the wind turbine foundation. This study describes a data-driven structural damage classification methodology applied in a wind turbine foundation. A vibration response was captured in the structure using an accelerometer network. After arranging the obtained data, a feature vector of 58 008 features was obtained. An ensemble approach of feature extraction methods was applied to obtain a new set of features. Principal Component Analysis (PCA) and Laplacian eigenmaps were used as dimensionality reduction methods, each one separately. The union of these new features is used to create a reduced feature matrix. The reduced feature matrix is used as input to train an Extreme Gradient Boosting (XGBoost) machine learning-based classification model. Four different damage scenarios were applied in the structure. Therefore, considering the healthy structure, there were 5 classes in total that were correctly classified. Five-fold cross validation is used to obtain a final classification accuracy. As a result, 100% of classification accuracy was obtained after applying the developed damage classification methodology in a wind-turbine offshore jacket-type foundation benchmark structure.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 3; art. no. e144606
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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