Wyniki wyszukiwania - BazTech

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Vibration monitoring of bridges

Neitzel F., Resnik B., Weisbrich S., Friedrich A.

Reports on Geodesy

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2011

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z. 1/90

331--340

EN

Traditional visual inspection tools, which are typically carried out annually, can only detect obvious damages like disruption, cracks or rust on the surface of bridges. Advanced non-destructive and destructive inspection tools are usually applied when visual inspection can’t provide sufficient information. Besides these techniques engineering surveyors can conduct geometric deformation analysis that provides additional information for damage detection of structures. The implementation of appropriate methods for data acquisition and analysis to detect changes to the material, geometric and dynamic characteristics of structures is summarised under the term Structural Health Monitoring (SHM). The essential idea of SHM is to determine a normal behaviour of undamaged structures and to obtain qualitative conclusions from changes of this behaviour related to the current health status. Information about changes within the dynamic characteristics of structures can be detected by applying accelerometers, which are a component of Ambient Vibration Methods (AVM) as an integral part of SHM. Analysis of acceleration measurements can derive natural frequencies that depend on weight, material, stress and strain as well as the geometry of the object. Hence this data can be used to derive additional information about the capacity and condition of a structure. In this paper we present a measurement system based on low-cost accelerometers that nevertheless performs measurements with high accuracy. This autonomously operatable device features a memory card slot, an internal battery, a waterproof housing and temperature resistant components. Additionally real time data transfer can be obtained via wireless LAN or USB connection to a computer. All necessary steps of data acquisition, processing and interpretation of vibration monitoring will be presented on a practical example.

2

Feed forward neural network and interpolation function models to predict the soil and subsurface sediments distribution in Bam, Iran

Rezaei K., Guest B., Friedrich A., Fayazi F., Nakhaei M., Beitollahi A., Fatemi Aghda S.

Acta Geophysica

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2009

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Vol. 57, no. 2

271-293

EN

An application of the artificial neural network (ANN) approach for predicting mean grain size using electric resistivity data from Bam city is presented. A feed forward back propagation network was developed employing 45 sets of input data. The input variables in the ANN model are the electrical resistivity, water table as a Boolean value and depth; the output is the mean grain size. To demonstrate the authenticity of this approach, the network predictions are compared with those from interpolation methods and the same data. This comparison shows that the ANN approach performs better results. The predicted and observed mean grain size values were compared and show high correlation coefficients. The ANN approach maps show a high degree of correlation with well data based grain size maps and can therefore be used conservatively to better understand the influence of input parameters on sedimentological predictions.

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Wpływ zaworów odcinających na zużycie energii przez duże instalacje chłodnicze

Friedrich A.

Chłodnictwo : organ Naczelnej Organizacji Technicznej

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2004

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R. 39, nr 10

22-23

PL

Wielkość zużycia energii niezbędnej do pracy dużej instalacji chłodniczej wynika przede wszystkim z zastosowanych sprężarek oraz w mniejszym stopniu wentylatorów i pomp. W fazie projektowania instalacji chłodniczej często nie jest natomiast w ogóle brany pod uwagę wpływ zaworów odcinających.

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Tramwaje na EXPO 2000 w Hanowerze

Friedrich A., Wendt J.

TTS Technika Transportu Szynowego

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1999

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R. 6, nr 1-2

57-62

PL

W dniach od 1 czerwca do 31 października 2000 roku odbędzie się w Hanowerze najbliższa światowa wystawa EXPO 2000 pod hasłem "Człowiek, Natura, Technika". Oczekiwanych jest 170 wystawców (krajów) i 40 milionów gości, czyli 300 tysięcy zwiedzających dziennie.