Recently, neural networks have emerged as potential tools in the area of fault detection and diagnosis. This paper deals with multi neural network based fault detection and diagnosis approach. The architecture adopted is a Radial Basis function neural network (RBF). The approach is applied for detection and diagnosis of suitable parameters failures on a DC-motor based on the patterns of parameters changes. The simulation results illustrated that after training the neural networks, the system is able to detect the different motor failures.
In this paper, we consider linear complementarity problems with positive definite matrices through a multi-agent network. We propose a distributed continuous-time algorithm and show its correctness and convergence. Moreover, with the help of Kalman-Yakubovich-Popov lemma and Lyapunov function, we prove its asymptotic convergence. We also present an alternative distributed algorithm in terms of an ordinary differential equation. Finally, we illustrate the effectiveness of our method by simulations.
The GRACE satellites have provided gravity field solutions with approximately monthly resolution since April 2002. The monthly solutions enable investigations of the annual, semi-annual and secular mass variations, which mainly occur in a thin layer of the Earth’s surface. By the end of the GRACE science mission in 2017, the time span has increased to 15 years, making the possibility of determining longer-period variations feasible. First attempts to determine multi-annual variations, i.e. periods of some years but less than 10, are presented in this study. A combination of 3 different PSD estimation methods has been used for identifying the regions of multi-annual mass variations. As a result, 8 different areas have been found with significant multi-annual mass variations. The source of multi-annual mass variations in most detected regions can be identified as related to the ENSO cycle. and Kiss Annamária, Földváry Lóránt.
a1_Imaging the four fluorescence bands of leaves, the red (F690) and far-red (F740) chlorophyll (Chl) fluorescence as well as the blue (F440) and green (F520) fluorescence of leaves and the corresponding fluorescence ratios is a fast and excellent nondestructive technique to detect the photosynthetic activity and capacity of leaves, of gradients over the leaf area as well as the effect of various strain and stress parameters on plants. This review primarily deals with the first and pioneering multi-colour fluorescence imaging results obtained since the mid-1990s in a cooperation with French colleagues in Strasbourg and in my laboratory in Karlsruhe. Together we introduced not only the joint imaging of the red and far-red Chl fluorescence but also of the blue and green fluorescence of leaves. The two instrumental setups composed for this purpose were (1) the Karlsruhe-Strasbourg UV-Laser Fluorescence Imaging System (Laser-FIS) and (2) the Karlsruhe Flash-Light Fluorescence Imaging System (FL-FIS). Essential results obtained with these instruments are summarized as well as the basic principles and characteristics of multi-colour fluorescence imaging. The great advantage of fluorescence imaging is that the fluorescence yield in the four fluorescence bands is sensed of several thousand up to 200,000 pixels per leaf area in one image. The multi-colour FIS technique allows to sense many physiological parameters and stress effects in plants at an early stage before a damage of leaves is visually detectable. Various examples of plant stress detection by the multi-colour FIS technique are given. Via imaging the Chl fluorescence ratio F690/F740 it is even possible to determine the Chl content of leaves. The FIS technique also allows to follow the successive uptake of diuron and loss of photosynthetic function and to screen the ripening of apples during storage., a2_Particularly meaningful and of high statistical relevance are the fluorescence ratio images red/far-red (F690/F740), blue/red (F440/F690), and blue/green (F440/F520) as well as images of the fluorescence decrease ratio RFd, which is an indicator of the net CO2 assimilation rates of leaves., H. K. Lichtenthaler., and Obsahuje bibliografické odkazy
UK-Slovenian collaborative research connected to EU COST-Action 625 began in 2003 and has involved interdisciplinary research into the current activity, structural architecture and landscape expression of the Ravne and Idrija strike-slip fault systems in NW Slovenia. The Ravne fault may be the best exposed actively propagating strike-slip fault system in Europe and through combined structural fieldwork, earthquake seismology and airborne LiDAR (Light Detection And Ranging) surveys, a new understanding of the fault’s along-strike segmentation, three dimensional geometry and stepover zone kinematics has been gained. The Idrija Fault in contrast, is poorly exposed, but defines a regional lineament with an intensely brecciated fault core; it may have been responsible for the largest historical earthquake to have ever affected the region. High-resolution LiDAR images recently obtained for both fault systems allow for efficient focussed fieldwork and future work will be devoted to documenting the timing of previous earthquakes and the connectivity and displacement transfer between active faults at the NE corner of the Adria microplate., Dickson Cunningham, Andrej Gosar, Vanja Kastelic, Stephen Grebby and Kevin Tansey., and Obsahuje bibliografii