Filtern
Dokumenttyp
Sprache
- Englisch (9)
Schlagworte
Organisationseinheit der BAM
- 7 Bauwerkssicherheit (2)
- 7.2 Ingenieurbau (2)
The implementation of a continuous dynamic monitoring System in Pedro e Ines footbridge at Coimbra, Portugal, operating since June 2007, enabled to detect different environmental/operational effects on the modal properties, based on appropriate processing of monitoring data collected by a set of accelerometers and thermal sensors.
In order to remove or mitigate such environmental/operational effects with the purpose of damage detection, two different Statistical methods have been adopted, One of them consists in the multiple linear regression (MLR) by performing correlation analysis between measured modal properties and environmental/operational variables. Another is based on the identification of the linear subspace within the modal properties by applying principal component regression (PCR) without using measured values of environmental and operational variables.
This paper presents a comparison ofthe performance of these two alternative approaches on the basis of continuous monitoring data acquired front the instrumented Pedro e Ines footbridge.
In the context of national innovative project IMO-WIND, an integrated long term monitoring System was installed on a prototype of an offshore wind turbine System of 5 megawatt dass. The Federal Institute for Materials Research and Testing (BAM) was responsible for development of the SHM System. It consists of a signal acquisition System and a Signal processing and management System.
The signal acquisition System is composed of 14 acceleration sensors, 110 strain gauges and 4 inclination sensors, installed at the tripod foundation and the tower. It began to work in August 2007. In order to investigate the structural dynamic properties, extract efficient damage index and manage huge amounts of Vibration Signals and analysis results, an automated signal processing and management Software System is developed in LabVIEW® environment. It includes functions such as automated Operational Modal Analysis (OMA) on the basis of Stochastic Subspace Identification (SSI) method and poly-reference Least-Squares Complex Frequency Domain (p-LSCF) approach, investigation of environmental/operational effects on structural dynamic properties under operational conditions, features extraction using Principal Component Regression (PCR) and Multiple Linear Regression (MLR) as well as data/result management and visualization.
Besides, this paper also presents variations of structural modal parameters of a wind turbine system under complex environmental/operational conditions. Comparison of modal parameters automatically extracted by SSI method and poly-reference p-LSCF approach indicates that the latter method provides more stable modal identification results ffom the viewpoint of long term OMA. Subsequently, the influences of temperature, wind velocity, rotation speed and nacelle direction on modal parameters are generally discussed. Finally, variations of indentified modal parameters during two years are presented.
This paper presents the development of a continuous dynamic monitoring System and its applications to different structures, with the purpose of understanding structural real behaviours under operational conditions and detecting early structural modifications. The first part of paper introduces a complete continuous dynamic System, consists of signal acquisition and communication, automated signal processing and management, investigation of the interaction between structures and its environmental/operational conditions, feature extraction and detection of structural modification.
The rest of paper describes the applications of continuous dynamic monitoring System to different structures such as a wind turbine System and a highway bridge.
This paper presents the continuous dynamic measurements of an aging prestressed box-beam bridge during the period from 2000 to 2013, which consists of dynamic properties and environmental/operational factors, as well as the Variation of the extracted health features after removing the environmental/operational effects. Firstly, the variations of frequency estimates, temperatures and traffic loads from 2000 to 2013 are described. Subsequently, correlation analysis between them indicates the nonlinear influences of the temperature on the frequency estimates. The Multiple Linear Regression (MLR) method is used to remove the environmental/operational effects and the health index is proposed by performing the Novelty Detection analysis of the residual errors. Finally, the variations of the health index may indicate clear structural modifications that can be also characterized by the long term monitoring of the dynamic strain in the prestressed cable.
This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.
Vibration-based structural health monitoring of a wind turbine system. Part I: Resonance phenomenon
(2015)
This paper is focused on a resonance phenomenon of a wind turbine system in 5 MW class, on the basis of dynamic signals acquired continuously from the tubular tower under normal operational conditions during two years.
Firstly, technique specifications of the wind turbine system are introduced and a finite element model is developed to characterize the structural dynamic properties. The following part describes the continuous dynamic monitoring system integrated with an automated operational modal analysis procedure using the poly-reference Least Squares Complex Frequency domain (p-LSCF) method. Subsequently, variations and mutual relationships of environmental/operational factors such as vibration amplitude, temperature, wind speed, rotation speed of blades, pitch angle and nacelle direction are also presented. Finally, significant resonance is observed due to the fundamental frequency of the tower matching with the harmonic frequency induced by the rotation of three blades. As the rotation speed of rotor approaches to 8 rpm, the vibration amplitude of the tower increases significantly and the corresponding damping value decreases. With the further rising wind velocity, the rotation speed of blades stops increasing and the input energy just contribute to accumulate the vibration amplitude of tower. Such observation indicates the Sommerfeld effect that aggravates the resonance phenomenon. A vibration control device is necessary to minimize the excessive structural responses.
A companion paper will further discuss the environmental/operational effects on dynamic properties of the wind turbine system under the operational conditions.
The second part of these companion papers mainly researches environmental/operational influences on structural dynamic properties under normal operational conditions during two years, in order to extract a statistical based damage-sensitive indicator for health monitoring of a wind turbine system.
The correlation analyses between experimental identified frequencies, damping values as well as mode shapes and environmental/operational factors such as rotation speed of blades, wind speed, pitch angle, temperature and nacelle direction are presented. It is observed that the frequency estimates are influenced by the nacelle position, the activation of rotor, the rotation speed of blades and the wind speed as well as the temperature. Regarding to the damping estimates, they are mainly associated with variation of the aerodynamic damping due to the increasing wind speed. Besides, the resonance phenomenon is also observed in higher modes. The harmonic frequencies due to blades passing by tower are found and the corresponding damping value decreases. Moreover, the mode shapes in some modes are strongly affected by the position of the nacelle.
Subsequently, two types of simulated damage including the reduction of stiffness in both the rotor blade and the tubular tower are successfully detected by applying the Principal Component Analysis (PCA) based methods to these temperature-sensitive frequency estimates. Comparison of change of the extracted health features indicates that they are more sensitive with the tower damage.
A prototype of wind turbines in 5 megawatt dass was built and tested at the first German offshore wind energy test fteld in the North Sea. In order to investigate dynamic behaviors under a complex state of loads, a continuous dynamic monitoring System was implemented by Federal Institute for Material Research and Testing (BAM). It recorded structural responses and environmental/operational variables from November 2007 to October 2009.
This paper presents significant resonance phenomenon due to the interaction in the tower-nacelle System under operational conditions. Modal parameters are automatically estimated by the poly reference Least Square Complex Frequency domain (p-LSCF) method. Campbell plot demonstrates that a three-blade passage frequency and its multiples f3n match with the natural frequencies of the wind turbine System in several modal Orders. The damping estimates decrease and the Vibration amplitude increase significantly. A control System is necessary to minimize the excessive vibrations.
Automated modal analysis for tracking structural change during construction and operation phases
(2019)
The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical Simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.