Combined model-free data-interpretation methodologies for damage detection during continuous monitoring of structures

نویسندگان

  • Irwanda Laory
  • Thanh N. Trinh
  • Daniele Posenato
  • Ian F. C. Smith
چکیده

2 3 Despite the recent advances in sensor technologies and data acquisition systems, interpreting 4 measurement data for structural monitoring remains as challenge. Furthermore, due to the 5 complexity of the structures, materials used and uncertain environments, behavioral models are 6 difficult to build accurately. This paper presents novel model-free data-interpretation methodologies 7 that combine MPCA with each of four regression-analysis methods – Robust Regression Analysis 8 (RRA), Multiple Linear Analysis (MLR), Support Vector Regression (SVR) and Random Forest (RF) – for 9 damage detection during continuous monitoring of structures. The principal goal is to exploit the 10 advantages of both MPCA and regression-analysis methods. The applicability of these combined 11 methods is evaluated and compared with individual applications of MPCA, RRA, MLR, SVR and RF 12 through four case studies. Result showed that the combined methods outperformed non-combined 13 methods in terms of damage detectability and time to detection. 14 Combined model-free data-interpretation methodologies for damage detection during continuous monitoring of structures Irwanda Laory, Thanh N. Trinh, Daniele Posenato, Ian F. C. Smith 1 Graduate Student, Applied Computing and Mechanics Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Station 18,CH-1015 Lausanne, Switzerland (corresponding author). E-mail: [email protected] 2 Postdoctoral Researcher, Applied Computing and Mechanics Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Station 18,CH-1015 Lausanne, Switzerland. E-mail: [email protected] 3 Project Engineer, SMARTEC SA, CH-6928 Manno, Switzerland. E-mail: [email protected] 4 Professor, Applied Computing and Mechanics Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Station 18,CH-1015 Lausanne, Switzerland. E-mail: [email protected] Laory, I., Trinh, T.N., Posenato, D. and Smith, I.F.C. "Combined Model-Free Data-Interpretation Methodologies for Damage Detection during Continuous Monitoring of Structures" J of Computing in Civil Engineering, Vol. 27, No. 6, 2013, pp 657-666. http://cedb.asce.org Copyright ASCE

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Model-free data interpretation for continuous monitoring of complex structures

Civil engineering structures are difficult to model accurately and this challenge is compounded when structures are built in uncertain environments. As consequence, their real behavior is hard to predict; such difficulties have important effects on the reliability of damage detection. Such situations encourage the enhancement of traditional approximate structural assessments through in-service ...

متن کامل

Model Free Interpretation of Monitoring Data

No current methodology for detection of anomalous behavior from continuous measurement data can be reliably applied to complex structures in practical situations. This paper summarizes two methodologies for model-free data interpretation to identify and localize anomalous behavior in civil engineering structures. Two statistical methods i) moving principal component analysis and ii) moving corr...

متن کامل

Methodologies for model-free data interpretation of civil engineering structures

Structural Health Monitoring (SHM) has the potential to provide quantitative and reliable data on the real condition of structures, observe the evolution of their behaviour and detect degradation. This paper presents two methodologies for model-free data interpretation to identify and localize anomalous behaviour in civil engineering structures. Two statistical methods based on i) moving princi...

متن کامل

STRUCTURAL DAMAGE PROGNOSIS BY EVALUATING MODAL DATA ORTHOGONALITY USING CHAOTIC IMPERIALIST COMPETITIVE ALGORITHM

Presenting structural damage detection problem as an inverse model-updating approach is one of the well-known methods which can reach to informative features of damages. This paper proposes a model-based method for fault prognosis in engineering structures. A new damage-sensitive cost function is suggested by employing the main concepts of the Modal Assurance Criterion (MAC) on the first severa...

متن کامل

Evaluating two model-free data interpretation methods for measurements that are influenced by temperature

Interpreting measurement data to extract meaningful information for damage detection is a challenge for continuous monitoring of structures. This paper presents an evaluation of two model-free data interpretation methods that have previously been identified to be attractive for applications in structural engineering: moving principal component analysis (MPCA) and robust regression analysis (RRA...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012