A method for identification of parameters of a non-linear dynamic system, such as an induction motor with saturation effect taken into account, is presented in this paper. Adaptive identifier with structure similar to model of the system performs identification. This identifier can be regarded as a special neural network, therefore its adaptation is based on the gradient descent method and Back-Propagation well known in the neural networks theory. Parameters of electromagnetic subsystems were derived from the values of synaptic weights of the estimator after its adaptation. Testing was performed with simulations taking into account noise in measured quantities. Deviations of identified parameters in case of electrical parameters of the system were up to 1% of real values. Parameters of non-linear magnetizing curve were identified with deviations up to 6% of real values. Identifier was able to follow sudden changes of rotor resistance, load torque and moment of inertia.
This paper evaluates the feasibility of using an Artificial Neural Network (ANN) model for estimating the nominal shear capacity of Reinforced Concrete (RC) beams against diagonal shear failure subjected to shear and flexure. A feedforward back-propagation ANN model was developed utilizing 622 experimental data points of RC beams, which include 111 deep beams data and 20 beams tested for low longitudinal steel ratios. The ANN model was trained on 70% of the data and then it was validated using the remaining 30% data (new data were not used for training). The trained ANN model was compared with three existing approaches, including the American Concrete Institute (ACI) code. The ANN model predictions when compared to the experimental data were very favorable, regarding also the other approaches. The prediction of ANN model was also checked for size effect and deep beams separately. The ANN model was found to be very robust in all situations. The safe form of ANN model was also derived and compared with the design equations of the three methods.
The optimization problem of two or more special-purpose functions of the energy system is subjected to an analysis. Based on experience of our research and general knowledge of partial solutions of energy system optimization at the level of control of production and power energy supply by energy companies in the Czech Republic, a special-purpose (cost) function has been defined. By analysing the special-purpose function, penalty and limitations have been defined. Using the fuzzy logic, a set of suitable solutions for the special-purpose function is accepted. An optimum of the special-purpose function is looked for using the simulated annealing method. The history of electricity consumption is sorted by day and by hour, representing the multidimensional data. When using the cluster analysis, type daytime diagrams of consumption are defined. Type daytime diagrams form prototypes of identified clusters. The so-called self-organizing neural network with Kohonen map attached is used to perform the cluster analysis. The result of our research is presented by an experiment.
A new method to detect damages on crates of beverages is investigated. It is based on a pattern-recognition-system by an artificial neural network (ANN) with a feedforward multilayer-perceptron topology. The sorting criterion is obtained by mechanical vibration analysis which provides characteristic frequency spectra for all possible damage cases and crate models. To support the network training, a large number of numerical data-sets is calculated by the finite-elementmethod (FEM). The combination of artificial neural networks with methods of numerical simulation is a powerful instrument to cover the broad range of possible damages. First results are discussed with respect to the influence of modelling inaccuracies of the finite-element-model and the support of the ANN by training-data obtained from numerical simulation. Also the feasibility of neuro-numerical ANN training will be dwelled on.
Classical Russian pendulum seismometer S-5-S was modified for recording of the rotational components of ground motion around the vertical or horizontal axes; the modified sensor is denoted here as S-5-SR. Experimental field testing of the S-5-SR sensor started in December 2010 in the Karvina coal region that is known as an area of intensive mining induced seismicity. First seismic station was installed in Doubrava village characterized by thick sedimentary layers. Next seismic station was installed in Orlova village, in different local geological conditions, i.e. in region without sedimentary layers. More than 200 mining induced seismic events were recorded on each seismic station during the period of six months of seismic monitoring. The recorded wave patterns confirm the existence of rotational ground motion components in this region; the strongest recorded value of this component exceeded 1 mrad.s-1. Analysis of the obtained records is presented in this paper., Zdeněk Kaláb, Jaromír Knejzlík and Markéta Lednická., and Obsahuje bibliografii
In this paper a new black box approach for rainfall-runoff modelling at a daily scale is presented. The considered black box model is non-linear regression based on Parzen probability density function. When using only measured rainfall as an input to any black box model there is a serious problem with building in the necessary memory. A standard approach to tackle this issue is to force a black box with a large number of rainfall and runoff variables of the past. In practice however, any regression technique, will have difficulties handling so large (possibly dependent) input set. For that reason, a more hydrological approach is proposed. Two linear reservoirs are used to model the memory. The reservoir constants are found by simple piecewise linear regression. An application to the Beerze catchment in the Netherlands is shown. A good correspondence between measured and estimated runoff is achieved. and Príspevok prezentuje nový prístup k zrážkovo-odtokovému modelovaniu, ktorý vychádza z metódy čiernej skrinky. V prípade, ak sa pri predpovedi prietokov použijú v modeli tohto typu ako vstupy len zrážkomerné pozorovania, môžu nastať ťažkosti s dostatočným zohľadnením pamäte procesu. Štandardný prístup ako riešiť tento problém, je zahrnúť dostatočné množstvo zrážkových a odtokových premenných zohľadňujúcich minulosť procesu odtoku. V praxi však môžu vzniknúť problémy pri aplikácii regresných metód na takýto súbor vstupných údajov (pravdepodobne vzájomne závislých). Preto je v príspevku navrhnutý hydrologicky vhodnejší prístup, pričom boli navrhnuté dve lineárne nádrže na modelovanie pamäte procesu odtoku. Konštanty nádrží boli určené metódou lineárnej regresie. Bol navrhnutý nelineárny regresný model založený na aplikácii Parzenovej funkcie hustoty rozdelenia pravdepodobnosti. V príspevku je uvedená aplikácia tohto prístupu na povodí Beerze v Holandsku. Dosiahla sa dobrá zhoda medzi meranými a modelovanými hodnotami odtoku.
In this paper we describe the use of modified passive capillary samplers (PCSs) to investigate the water isotope variability of snowmelt at selected sites in Slovenia during winter 2011/2012 and during winter 2012/2013. First, PCS with 3 fibreglass wicks covering approximately 1 m2 were tested to determine sample variability. We observed high variability in the amount of snowmelt water collected by individual wick (185 to 345 g) and in the isotope composition of oxygen (δ18O −10.43‰ to −9.02‰) and hydrogen (δ2H −70.5‰ to −63.6‰) of the collected water. Following the initial tests, a more detailed investigation was performed in winter 2012/2013 and the variability of snowmelt on the local scale among the different levels (i.e. within group, between the close and more distant groups of wicks) was investigated by applying 30 fibreglass wicks making use of Analysis Of Variance (ANOVA) and a balanced hierarchical sampling design. The amount of snowmelt water collected by an individual wick during the whole experiment was between 116 and 1705 g, while the isotope composition varied from −16.32‰ to −12.86‰ for δ18O and from −120.2‰ to −82.5‰ for δ2H. The main source of variance (80%) stems from the variability within the group of wicks (e.g. within group) while other sources contribute less than 20% of the variability. Amount weighted samples for the 2012–2013 season show no significant differences among groups, but significant differences for particular sampling events were observed. These investigations show that due to the variability within the group of wicks, a large number of wicks (> 5) are needed to sample snowmelt.
The paper presents the preliminary results of the analysis of two archival SAR datasets acquired by ERS-1/2 satellites of the same area of Roznow Lake in Southern Poland. Both datasets cover the same period of 8 years (1992 - 2000) and refers to the same area by the 50% of overlap between the neighbouring satellite tracks. The main purpose of this analysis was to derive the overlapping data about deformation velocity calculated using PSI (Persistent Scatterers Interferometry). The presented PSI results refer to PS (Persistent Scatterers) located on active landslides and therefore representing landslide movement. In Polish Carpathians, due to sparse urbanization, vegetation and rough relief the obtained PS density is usually not very high and generally difficult to interpret. The application of two overlapping datasets, where both of them observe the same phenomena, allow to cross-validate the data by identification of common PS points. For two datasets acquired from different tracks, usually many PS are not common and occur at different locations. Such situation could be explained by the difference between the incidence angles for both acquisitions. In a case of two tracks and therefore different terrain objects might act as PS. By joining the PS point sets from such neighbouring tracks the density of PS could be significantly increased. In order to perform a PSI analysis of Roznow Lake the data acquired from 179 and 408 tracks have been used and a few hundred of PS were obtained from PSI processing. For both tracks similar deformations velocity were obtained within a range of +/- 6 mm/yr. The PS points on active landslides are usually related to the buildings (walls, roofs) and roads affected usually by high risk., Zbigniew Perski, Andrzej Borkowski, Tomasz Wojciechowski and Antoni Wójcik., and Obsahuje bibliografii
Whereas most plant suspension cultures are grown heterotrophically in the presence of sugars, a limited number of photoautotrophic cultures have been established which are able to grow with CO2 as the sole carbon source. Photoautotrophic cultures are useful to address various aspects of photosynthesis, source-sink regulation, nitrogen metabolism, production of secondary metabolites, and defence responses. The homogenous populations of these cultures provide an ideal and sensitive system to obtain reproducible results. The availability of an increasing number of photoautotrophic cultures from different economically important species provides the basis also for practical applications. and T. Roitsch, A. K. Sinha.
This paper presents the results of geophysical survey performed in the Pilawa River valley in the area of Middle Pomerania (Poland). The resistivity imaging method was applied. Resistivity profile measuring eight hundred metres allowed to investigate the geologic structure to the depth of 150 metres. The resistivity cross section shows the structure of Pleistocene sediments and the depth of Miocene - Pleistocene boundary. The significant lowering of the boundary is related to assumable ice-sheet margin range of Pomeranian phase of North Polish Glaciation. The lowering of the boundary may be a result of sediments compaction and the subglacial tunnel slope as well., Bogdan Żogała, Ryszard Dubiel, Józef Lewandowski, Waclaw M. Zuberek and Grzegorz Gąska., and Obsahuje bibliografické odkazy