Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: information map

Sortuj według:

Ogranicz wyniki do:

Early detection and localization of stator inter-turn short circuit faults based on variational mode decomposition and deep learning in induction motor

Guedidi Asma, Laala Widad, Guettaf Abderrazak, Arif Ali

Diagnostyka

2023

Vol. 24, No. 4

art. no. 2023401

The existing diagnostic techniques for detecting inter-turn short circuits (ITSCs) in induction motors face two primary challenges. Firstly, they suffer from reduced sensitivity, often failing to detect ITSCs when only a few turns are short-circuited. Secondly, their reliability are compromised by load fluctuations, leading to false alarms even in the absence of actual faults. To address these issues, a novel intelligent approach to diagnose ITSC fault is proposed. Indeed, this method encompasses three core components: a novel multi-sensor fusion technique, a knowledge map, and enhanced Convolutional Neural Networks (CNNs). First, the raw data collected from multiple sensors undergoes a transformation into 2D data using a novel image transformation based on Hilbert transform (HT) and variational mode decomposition (VMD), which is concatenate to a novel information map including frequency fault information and rotational speed. Then, this 3D multi information image is used as input to an improvement CNN model that apply a transfer learning for an enhanced version of SqueezNet with incorporating a novel attention mechanism module to precisely identify fault features. Experimental results and performance comparisons demonstrate that the proposed model attains high performance surpassing other Deep Learning (DL) methods in terms of accuracy. In addition, the model has consistently demonstrated its ability to make precise predictions and accurately classify fault severity, even under different working conditions.

Polowy system informacyjny wykorzystujący GIS

Rataj V.

Inżynieria Rolnicza

2003

R. 7, nr 11

179--186

Praca przedstawia algorytm kroków, niezbędnych do zbudowania polowego systemu informacyjnego na bazie standardowego GIS. Wykorzystanie tego systemu pokazano na przykładzie przestrzennie zróżnicowanych informacji dotyczących uprawy pszenicy ozimej. Algorytm oparto na mapach gleby oraz zasobności w składniki pokarmowe, na podstawie których opracowano mapy aplikacyjne nawożenia pszenicy ozimej, a następnie przeprowadzono poszczególne za biegi polowe. W okresie uprawy rejestrowano również przestrzenne zróżnicowanie nakładów produkcyjnych. Na podstawie uzyskanych wydajności (plon, jakość, cena sprzedaży) oraz nakładów produkcyjnych sporządzono mapę przestrzennie zróżnicowanej opłacalności produkcji pszenicy ozimej.

The paper presents algorythm of steps which are needed for creating the field information system on the basis of standard GIS. Application of the presented information system is shown on an example of spatially differentiated information used at winter wheat cultivation. Algorythm is based on information maps of soil properties and content of nutrients in the soil. Subsequently, application maps of nutrients application for winter wheat were elaborated. Based on those maps, individual respective field operations were performed. During the whole season spatial variability of production costs was recorded. On the basis of returns (yield, quality, realisation price) and production costs, the map of spatially differentiated rentability of winter wheat production was worked out.