Structural Health Monitoring using ARMarkov Observers

نویسندگان

  • Prasad Dharap
  • Bong-Hwan Koh
  • Satish Nagarajaiah
  • PRASAD DHARAP
  • BONG-HWAN KOH
  • SATISH NAGARAJAIAH
چکیده

A new method based on a bank of ARMarkov observers is proposed in this study for determination of the extent of damage. The objective of this article is to present a new formulation using a predesigned set of ARMarkov observers to determine the extent of damage and track further changes in the stiffness of the damaged member. The primary advantages of the proposed formulation over the existing methods are: (1) ARMarkov observers are designed based on interaction matrix formulation so that knowledge about exact initial conditions is not necessary, and (2) noise statistics are not required a priori to design a bank of ARMarkov observers when compared to a bank of Kalman filters. The simulation results of several examples including a planar truss structure with progressive damage in a member are presented to highlight the capability of the proposed method. The proposed method works well in the case of either a full set or a limited number of available measurements. It is shown that sensitivity enhancing control (SEC) can be easily incorporated into the proposed method to enhance the sensitivity of structural damage. In case of noisy output measurements, it is shown that it is possible to distinguish between the errors due to structural damage and due to noise in output measurements.

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

A Pitch-Catch Based Online Structural Health Monitoring of Pressure Vessels, Considering Corrosion Formation

Structural health monitoring is a developing research field which is multifunctional and can estimate the health condition of the structure by data analyzing and also can prognosticate the structural damages. Illuminating the damages by using piezoelectric sensors is one of the most effective techniques in structural health monitoring. Pressurized equipments are very important components in pro...

متن کامل

Damage detection and structural health monitoring of ST-37 plate using smart materials and signal processing by artificial neural networks

Structural health monitoring (SHM) systems operate online and test different materials using ultrasonic guided waves and piezoelectric smart materials. These systems are permanently installed on the structures and display information on the monitor screen. The user informs the engineers of the existing damage after observing signal loss which appears after damage is caused. In this paper health...

متن کامل

Time-Domain Identification Using ARMARKOV/Toeplitz Models With Quasi-Newton Update

Recursive identification methods using time-domain data have been developed in [l, 21 utilizing a gradient-based identification technique for estimating the Markov parameters of a system. This identification technique utilizes the ARMARKOV representation of a time-invariant finite-dimensional system which relates the current output of a system to past outputs as well as current and past inputs....

متن کامل

ARMARKOV Least-Squares Identi cation

In recent work, ARMARKOV representations have been proposed as an extension of ARMA representations of nite-dimensional linear time-invariant systems. ARMARKOV representations have the same form as ARMA representations, but explicitly involve Markov parameters. This paper generalizes ARMA least-squares time-domain identi cation to ARMARKOV representations. The ARMARKOV/least-squares identi cati...

متن کامل

Feature Selection in Structural Health Monitoring Big Data Using a Meta-Heuristic Optimization Algorithm

This paper focuses on the processing of structural health monitoring (SHM) big data. Extracted features of a  structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. The PSO-Harmony algorithm is introduced for feature selection to enhance the capability of the proposed method for processing the  measure...

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 2006