Parameter Study of Statistics of Modal Parameter Estimates Using Automated Operational Modal Analysis
For any modal parameter estimation (MPE) method, there are a few control inputs that can have an impact on the modal parameter estimates. These control inputs are typically involving parameters like the maximum model order and how many time values or freq
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Parameter Study of Statistics of Modal Parameter Estimates Using Automated Operational Modal Analysis Silas S. Christensen and Anders Brandt
Abstract For any modal parameter estimation (MPE) method, there are a few control inputs that can have an impact on the modal parameter estimates. These control inputs are typically involving parameters like the maximum model order and how many time values or frequency lines that should be included in the MPE. In this paper, a comprehensive study on the influence of these parameters is conducted using the multi-reference Ibrahim Time Domain algorithm (similar to the cov-SSI method). Data from a laboratory Plexiglas plate are investigated, and an automated Operational Modal Analysis (OMA) algorithm is used to systematically select physical poles. The effect of each of the various control parameters are discussed in the paper. Keywords Structural health monitoring (SHM) · Operational modal analysis (OMA) · Automated OMA (AOMA) · Modal parameter estimation (MPE) · Damping
34.1 Introduction Conventional maintenance of civil-engineering structures relates to on-site inspections. For older structures or in case of recent failures that have been corrected, inspections are done more frequently. In most cases these structures are in good condition, hence the inspection is unavailing. Depending on accessibility, as well as the extent of the inspection, maintenance can be expensive. Furthermore, some faults are not detected through conventional maintenance due to human error. A novel approach to structural maintenance is Structural Health Monitoring (SHM), which refers to a system that allows for a systematic characterization of the health of a civil-engineering structure. The system is based on sensor technology, while the health of the structure relates to how much of its lifetime has already been used, and therefore how much of it is left. It is common to monitor modal parameters, as changes in these correspond to changes to the structure, i.e. boundary conditions, re-distributions of loads etc. Operational Modal Analysis (OMA), is a popular concept that allows to determine modal parameters for structures in operation. It involves measuring the ambient response of structures, i.e. the forces that cause the response are unknown. The counterpart to OMA is Experimental Modal Analysis (EMA), in which the input of the system is measured. EMA is popular to use on smaller structures, i.e. objects that can fit into a laboratory, such that it is possible to isolate the structure from external forces, thereby controlling the input to the system by means of known excitation. For larger structures, i.e. most civil-engineering structures, the presence of external forces is inevitable, hence OMA is employed. A thorough comparison of EMA and OMA for measurements on a Plexiglass plate show that they perform equally, see [12]. It is crucial that the methods for estimating the modal parameters are consistent. There are many methods for Modal Parameter Estimation (MPE), and they can generally be divid
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