Detection of Stiffness and Mass Changes Separately Using Output-only Vibration Data

• Author / Creator

  Do, Ngoan Tien

• Structural Health Monitoring (SHM) is a rapidly developing field, which is expected to play an important role in management of infrastructure systems by providing critical information about the structural changes or damage in the structure under monitoring. Among the different components of SHM, data analysis methods and damage detection algorithms are widely considered among the most critical components. For real life applications, the effects of operational and environmental factors on the damage detection process should be appropriately considered since these effects can mask structural damage. In this study, a new vibration based damage detection method for detection of changes in stiffness (e.g. due to damage) and mass (e.g. due to operational effects) is introduced. For this purpose, an improved method using the Autoregressive Moving Average model with eXogenous inputs (ARMAX) in conjunction with a sensor clustering technique is developed. In order to separate the changes in stiffness and mass, two different damage features (DFs) are developed based on the relative difference of ARMAX coefficients: Mass DFs (MDFs), which aim to eliminate operational effects, and Stiffness DFs (SDFs), which detect structural damage. Numerical and experimental case studies are employed for verification of the methodology. First, a numerical study of a 4-DOF spring mass system and the IASC-ASCE (International Association of Structural Control; American Society of Civil Engineers) numerical benchmark problem are presented. Then, a small-scale four-storey steel structure is developed and tested in the laboratory to study the proposed approach with experimental data. Similar to the results of the numerical studies, the methodology is successful in not just determining the location and severity of the damage, but also distinguishing exactly changes in mass and stiffness in the experimental structure. The limitations of the methodology in its current form and recommendations for future work are also discussed at the end of the thesis.

• Subjects / Keywords

  • Damage Detection
  • Structural Health Monitoring

• Graduation date

  Fall 2015

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3G73787M

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.