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Książka

W koszyku

Application of rotation rate sensors for structural health monitoring of reinforced concrete beams = Zastosowanie czujników prędkości rotacji w monitorowaniu stanu belek żelbetowych / Piotr Adam Bońkowski. - Opole : Politechnika Opolska. Oficyna Wydawnicza, 2023. - 244 strony : fotografie, ilustracje, wykresy ; 24 cm.

(Studia i Monografie, ISSN 1429-6063 ; z. 581)

Autor

Bońkowski Piotr Adam.

Forma i typ

Książki Publikacje naukowe

Temat

Analiza modalna Belka Czujniki MEMS Konstrukcje żelbetowe Monitoring strukturalny (SHM)

Gatunek

Monografia

Dziedzina i ujęcie

Architektura i budownictwo Inżynieria i technika

Bibliografia, netografia na stronach 199-225.

INTRODUCTION AND SCOPEOF WORK DERIVATIVES OF THE NATURAL MODES, DYNAMIC AXIS ROTATIONS AND CURVATURE CHANGE IN STRUCTURAL HEALTH MONITORING REVIEW OF THE APPLICATION OF INCLINOMETERS, ROTATION RATE AND ROTATION ACCELERATION SENSORS IN MODAL ANALYSIS AND STRUCTURAL MONITORING Rotation Rate and rotation acceleration sensors Shearography InclinometersLITERATURĘ REVIEW OF MONITORING OF REINFORCED CONCRETE STRUCTURES USING VIBRATION-BASED METHODS Studies on generał methods of damage detection and problems in the monitoring of r/c structures Stiffness distribution reconstruction methods LITERATURĘ REVIEW ON THE MASS LOCALISATION AND IDENTIFICATION TECHNIQUES MODEL UPDATING AND MODAL ANALYSIS METHODOLOGY Model updating Optimisation problem Genetic algorithms Computer system Experimental modal analysis APPLICATION OF ROTATION RATE SENSORS IN MASS IDENTIFICATION Numerical analysis of mass identification using rotational modes simply supported beam cantilever beam Experimental Results General description Modal analysis Modal analysis of a Steel beam in free-free configuration Modal analysis of a Steel beam in the simply supported configuration Mass identification Steel beam in the free-free configuration Simply supported Steel beam STIFFNESS DISTRIBUTIONRECONSTRUCTIONOFDAMAGED REINFORCED CONCRETE BEAMSWITH ROTATIONRATESENSORS Modal analysis Ultrahigh performance concrete beam results Reinforced concrete beam results Stiffness distribution reconstruction Ultrahigh performance concrete beams Reinforced concrete beam results Free-Free configuration Simply supported configuration CONCLUDING REMARKS Stiffness and mass matrices of finite elements Steel prings technical data Numerical model of a Steel beam Ultrahigh performance concrete samples technical data Rotation rate and translational acceleration sensors properties Numerical models of reinforced concrete beams

Sygnatura czytelni BWB: V E 114

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Książka

W koszyku

Cointegration-based approach for structural health monitoring : theory and applications / Phong Ba Dao. - Kraków : Wydawnictwa AGH, 2018. - 123, [1] strona : ilustracje, fotografie, wykresy ; 24 cm.

(Rozprawy, Monografie = Dissertations, Monographs / [Akademia Górniczo-Hutnicza im. Stanisława Staszica], ISSN 0867-6631 ; 339)

Autor

Dao Phong Ba.

Forma i typ

Książki Publikacje naukowe

Temat

Kointegracja. Monitoring strukturalny (SHM)

Gatunek

Opracowanie

Dziedzina i ujęcie

Inżynieria i technika Matematyka

Bibliografia, netografia na stronach 114-[124].

1.1.SHM and similar research fields 1.2.Effects of varying environmental and operational conditions on SHM 1.3.Why cointegration has been applied to SHM 1.4.A review of cointegration-based approaches for SHM 1.5.Motivation and scope of this monograph 2.Stationarity and nonstationarity 2.1.Definitions and basic concepts 2.2.Time series and stationarity 2.3.Unit root tests 2.4.The Dickey-Fuller (DF) and augmented Dickey-Fuller (ADF) tests 3.Cointegration method 3.1.Introduction to cointegration 3.2.Cointegration and common trends 3.3.Testing for cointegration 3.4.Johansen's cointegration procedure 3.5.Testing for stationarity 3.6.Example using the Weierstrass-Mandelbrot cosine fractal function 3.7.Summary and discussion 4.Lag length selection in cointegration analysis used for SHM 4.1.Background 4.2.Conventional selection methods from econometrics 4.2.1.Methods based on the information criteria 4.2.2.Methods based on the likelihood ratio test 4.2.3.Methods based on the sequential modified likelihood ratio test 4.2.4.Sample size and lag length selection 4.3.Optimal lag length selection based on stationarity analysis used for structural damage detection 4.4.Summary and conclusions 5.Cointegration-based approach to SHM applications 5.1.Damage detection scenarios 5.1.1.Using geometrical features of cointegration residuals 5.1.2.Using wavelet variance characteristics of cointegration residuals 5.1.2.1.Fractal-based signal processing using wavelets 5.1.2.2.Wavelet-based fractal analysis of cointegration residuals 5.1.3.Using stationary statistical characteristics of cointegration residuals 5.2.Case study 1: Structural damage detection in aluminium plates using lamb waves under temperature variations 5.2.1.Lamb wave data contaminated by temperature 5.2.2.Lag length selection results 5.2.3.Damage detection results using cointegration residuals 5.2.4.Damage detection results using wavelet variance characteristics of cointegration residuals 5.2.5.Damage detection results using stationary statistical characteristics of cointegration residuals 5.3.Case study 2: Impact damage detection in composite plates using nonlinear acoustics under load changes 5.3.1.Principle of nonlinear vibro-acoustic wave modulation technique 5.3.2.Vibro-acoustic data for different frequencies of modal excitations 5.3.3.Lag length selection results 5.3.4.Damage detection results using stationary statistical characteristics of cointegration residuals 5.4.Summary and conclusions 6.Cointegration-based approach to condition monitoring of wind turbines 6.1.Condition monitoring and fault diagnosis of wind turbines using SCADA data 6.2.1.Review of previous work 6.2.2.Discussion 6.3.Cointegration-based approach to condition monitoring of wind turbines 6.4.Experimental wind turbine data 6.5.Case study 1: Using various process parameters of the wind turbine 6.5.1.Optimal cointegrating vectors 6.5.2.Condition monitoring and fault detection using cointegration residuals 6.5.3.Discussion 6.6.Case study 2: Using only the temperature data of gearbox and generator

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