Search results for "feature"
showing 10 items of 4091 documents
Ground-Based measurements of the 2014-2015 holuhraun volcanic cloud (Iceland)
2018
he 2014–2015 Bárðarbunga fissure eruption at Holuhraun in central Iceland was distinguished by the high emission of gases, in total 9.6 Mt SO2, with almost no tephra. This work collates all ground-based measurements of this extraordinary eruption cloud made under particularly challenging conditions: remote location, optically dense cloud with high SO2 column amounts, low UV intensity, frequent clouds and precipitation, an extensive and hot lava field, developing ramparts, and high-latitude winter conditions. Semi-continuous measurements of SO2 flux with three scanning DOAS instruments were augmented by car traverses along the ring-road and along the lava. The ratios of other gases/SO2 were …
Gradual caldera collapse at Bardarbunga volcano, Iceland, regulated by lateral magma outflow
2016
Large volcanic eruptions on Earth commonly occur with a collapse of the roof of a crustal magma reservoir, forming a caldera. Only a few such collapses occur per century, and the lack of detailed observations has obscured insight into the mechanical interplay between collapse and eruption.We usemultiparameter geophysical and geochemical data to show that the 110-square kilometer and 65-meter-deep collapse of Bárdarbunga caldera in 2014–2015 was initiated through withdrawal of magma, and lateral migration through a 48-kilometers-long dike, from a 12-kilometers deep reservoir. Interaction between the pressure exerted by the subsiding reservoir roof and the physical properties of the subsurfac…
Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life
2018
Bearings are one of the most critical components in electric motors, gearboxes and wind turbines. Therefore, bearing fault detection and prognosis of remaining useful life are important to prevent productivity losses. In this study, a novel method is proposed for prognosis of bearing life using an autoencoder and recurrent neural networks-based prediction algorithm. Promising results have been obtained from the experimental data. A monotonic upward trend of the produced health indicator is obtained for all test cases, being one of critical indicators of a proper prognosis. The remaining useful life estimation is moderately accurate under a limited data.
Autoencoders and Data Fusion Based Hybrid Health Indicator for Detecting Bearing and Stator Winding Faults in Electric Motors
2018
The main objective of a condition monitoring programs is to track the health status of critical components of a machine. In this paper, a hybrid health indicator is proposed to monitor the health status of bearings and stator winding of a motor. The proposed method is based on a feature learning from deep autoencoders and data fusion. The features can be learned by autoencoders using individual current and vibration signals, and then learning features are fused to make final health indicators. The experimental data from a permanent magnet synchronous motor is used to validate the proposed method. Promising results in detecting faults and severities of the stator and bearing faults at differ…
CNN based Gearbox Fault Diagnosis and Interpretation of Learning Features
2021
Machine learning based fault diagnosis schemes have been intensively proposed to deal with faults diagnosis of rotating machineries such as gearboxes, bearings, and electric motors. However, most of the machine learning algorithms used in fault diagnosis are pattern recognition tools, which can classify given data into two or more classes. The underlined physical phenomena in fault diagnosis are not directly interpretable in machine learning schemes, thus it is usually called black/gray box models. In this study, convolutional neural networks (CNN) machine learning algorithm is proposed to classify gearbox faults, and the learning features of the CNN filters are visualized to understand the…
Detection of Ventricular Fibrillation Using the Image from Time-Frequency Representation and Combined Classifiers without Feature Extraction
2018
Due the fact that the required therapy to treat Ventricular Fibrillation (V F) is aggressive (electric shock), the lack of a proper detection and recovering therapy could cause serious injuries to the patient or trigger a ventricular fibrillation, or even death. This work describes the development of an automatic diagnostic system for the detection of the occurrence of V F in real time by means of the time-frequency representation (T F R) image of the ECG. The main novelties are the use of the T F R image as input for a classification process, as well as the use of combined classifiers. The feature extraction stage is eliminated and, together with the use of specialized binary classifiers, …
An advanced numerical treatment of EM absorption in human tissue
2020
The numerical computation of local electromagnetic absorption at points within the human tissue is proposed by avoiding the mesh generation in the problem domain. Recently, meshless numerical methods have been introduced as an alter- native computational approach to mesh based methods. This is an important feature to generate competitive procedure able to provide final evaluations for large data amounts in real time. In this paper the smoothed particle hydrodynamics method is considered to compute the electromagnetic absorption. First experiments are performed in two dimension at single frequencies by considering incident TM plane wave on 2D cylinder simulating a simplified model of human t…
Dialektmerkmale des Deutschen in den sprachbiographischen Interviews der bilingualen Oberschlesier
2022
The article is based on language biographies which come from the interviews conducted as part of the German-Polish project LangGener with native inhabitants of the former German territories of today’s Poland. Out of 124 recordings, 20 linguistic biographical interviews with respondents from Upper Silesia were subjected to analysis where special attention was paid to the features of Silesian German dialects occurring in them. Even though the Silesian linguistic landscape is now considered by researchers to be a historical object of studies due to the shifting of borders after World War II and the accompanying population exchange, the article shows that the linguistic material currently obtai…
Characterization of the Etna volcanic emissions through an active biomonitoring technique (moss-bags): Part 2 – Morphological and mineralogical featu…
2013
Volcanic emissions were studied at Mount Etna (Italy) by using moss-bags technique. Mosses were exposed around the volcano at different distances from the active vents to evaluate the impact of volcanic emissions in the atmosphere. Morphology and mineralogy of volcanic particulate intercepted by mosses were investigated using scanning electron microscopy (SEM) equipped with energy dispersive spectrometer (EDS). Particles emitted during passive degassing activity from the two active vents, Bocca Nuova and North East Crater (BNC and NEC), were identified as silicates, sulfates and halide compounds. In addition to volcanic particles, we found evidences also of geogenic, anthropogenic and marin…
CNC Milling Machine Simulation in Engineering Education
2012
In this work an effective simulator for a CNC milling machine is presented. It has been developed in EMC2, a free Opens Source NC software running in Linux environment, developed by an international community. It can be installed on a common PC and is able to: control a CNC machine; read part programs; display the tool path; send instructions to the CNC machine for the cutting process. In this work a new feature has been implemented, which can both display a 3D model of the machine and simulate all the motions of the movable parts of a real 3 axis end milling machine. This simulator lets the users not only verify the toolpath but also detect any possible collision by using the very computer…