TY - CONF A1 - Hu, Wei-Hua A1 - Caetano, E. A1 - Cunha, A. A1 - Rücker, Werner ED - Carrera, E. ED - Miglioretti, F. ED - Petrolo, M. T1 - Comparison of different statistical approaches for removal of environmental/operational effects on modal properties and damage detection N2 - 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. T2 - SMART2013 - 6th ECCOMAS conference on smart structures and materials CY - Turin, Italy DA - 24.06.2013 KW - Structural health monitoring KW - Environmental/operational effects KW - Principal component regression KW - Multiple linear regression KW - Damage detection PY - 2013 SP - 1 EP - 13 AN - OPUS4-32972 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hu, Wei-Hua A1 - Rohrmann, Rolf A1 - Said, Samir A1 - Rücker, Werner ED - Xu, Y. L. ED - Zhu, S. ED - Xia, Y. ED - Ni, Y.Q. ED - Law, S.S. ED - Yin, J. H. ED - Su, Z.Q. T1 - Development of a vibration-based structural health monitoring system for wind turbines N2 - 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. T2 - SHMII-6 - 6th International conference on structural health monitoring of intelligent infrastructure CY - Hong Kong, China DA - 09.12.2013 KW - Wind turbine KW - Vibration-based structural health monitoring system KW - Automated operational modal analysis KW - Environmental and operational effects KW - Feature extraction KW - Damage detection PY - 2013 SN - 978-962-367-768-4 SP - 1 EP - 10 AN - OPUS4-32973 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -