Damage Identification Using Sensitivity-Enhancing Control and Identified Models

2005 ◽  
Vol 128 (2) ◽  
pp. 210-220 ◽  
Author(s):  
Jason A. Solbeck ◽  
Laura R. Ray
Keyword(s):  
Transfer Function ◽  
Closed Loop ◽  
Damage Identification ◽  
Structural Models ◽  
Damage Parameter ◽  
Measured Parameter ◽  
Parameter Vector ◽  
Input Output ◽  
Output Data ◽  
Torsional System

This paper investigates a coherence approach for locating structural damage using modal frequencies and transfer function parameters identified from input-output data using Observer/Kalman filter identification (OKID). Autonomous damage identification using such forward methods generally require (i) a structural model by which to relate measured and predicted modal properties induced by damage, and (ii) good sensitivity of modal parameter changes to damage states. Using the coherence approach, a damage parameter vector comprised of a finite set of modal frequencies and transfer function parameters is hypothesized for each damage case using either identified or analytic structural models. Measured parameter vectors are extracted from experimental input-output data for a damaged structure using OKID and are compared to hypotheses to determine the most likely damage state. The richness of the parameter vector set, which is comprised of high-quality frequency measurements and lower-quality transfer function parameters, is evaluated in order to determine the ability to uniquely localize damage. The method is evaluated experimentally using a three-degree-of-freedom torsional system and a space-frame truss. Damage parameter hypotheses are generated from a model of the healthy structure developed by system identification in the torsional system, and an analytic model is used to generate damage hypotheses for the truss structure. Feedback control laws enhance the parameter vectors by including closed-loop modal frequencies in order to reduce noise sensitivity and improve uniqueness of parameter vector hypotheses to each damage case. Results show improvements in damage identification using damage parameter vectors comprised of open- and closed-loop modal frequencies, even when model error exists in structural models used to form damage parameter vector hypotheses.

scholarly journals Harmonic Transfer Function Based Damage Identification of Breathing Cracked Jeffcott Rotor

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Jie Zhao ◽  
Hans DeSmidt ◽  
Meng Peng
Keyword(s):  
Transfer Function ◽  
Damage Identification ◽  
Strain Energy Release ◽  
Damage Parameter ◽  
Rotor System ◽  
Crack Model ◽  
Identification Algorithm ◽  
Lagrange Principle ◽  
Jeffcott Rotor ◽  
Vibration Responses

This paper proposes a vibration-based damage identification method based on 6-dof Jeffcott rotor system, which is based on harmonic balance and Newton-Raphson methods. First, the equations of motion are derived by using energy method and Lagrange principle. The crack model is based on strain energy release rate (SERR) in fracture mechanics and modified to accommodate 6-dof Jeffcott rotor model. Then, Gear’s method is used to solve the vibration responses of nominal and damaged rotor systems. By processing vibration responses, the transfer function shifts between nominal and damaged systems are taken as the input of damage identification algorithm. Finally, damage severity can be correlated with the damage parameter estimated via developed damage identification model. Numerical examples are shown to demonstrate the effectiveness in identifying the breathing crack in the rotor system.

scholarly journals On the Design of Hyperstable Feedback Controllers for a Class of Parameterized Nonlinearities. Two Application Examples for Controlling Epidemic Models

2019 ◽  
Vol 16 (15) ◽  
pp. 2689 ◽  
Author(s):  
Manuel De la Sen
Keyword(s):  
Transfer Function ◽  
Closed Loop ◽  
Equilibrium Points ◽  
Linear Part ◽  
Type Inequality ◽  
Epidemic Models ◽  
Time Varying ◽  
Input Output ◽  
Controlled System ◽  
Feed Forward

This paper studies the hyperstability and the asymptotic hyperstability of a single-input single-output controlled dynamic system whose feed-forward input-output dynamics is nonlinear and eventually time-varying consisting of a linear nominal part, a linear incremental perturbed part and a nonlinear and eventually time-varying one. The nominal linear part is described by a positive real transfer function while the linear perturbation is defined by a stable transfer function. The nonlinear and time-varying disturbance is, in general, unstructured but it is upper-bounded by the combination of three additive absolute terms depending on the input, output and input-output product, respectively. The non-linear time-varying feedback controller is any member belonging to a general class which satisfies an integral Popov’s-type inequality. This problem statement allows the study of the conditions guaranteeing the robust stability properties under a variety of the controllers designed for the controlled system and controller disturbances. In this way, set of robust hyperstability and asymptotic hyperstability of the closed-loop system are given based on the fact that the input-output energy of the feed-forward controlled system is positive and bounded for all time and any given initial conditions and controls satisfying Popov’s inequality. The importance of those hyperstability and asymptotic hyperstability properties rely on the fact that they are related to global closed-loop stability, or respectively, global closed-loop asymptotic stability of the same uncontrolled feed-forward dynamics subject to a great number of controllers under the only condition that that they satisfy such a Popov’s-type inequality. It is well-known the relevance of vaccination and treatment controls for Public Health Management at the levels of prevention and healing. Therefore, two application examples concerning the linearization of known epidemic models and their appropriate vaccination and/or treatment controls on the susceptible and infectious, respectively, are discussed in detail with the main objective in mind of being able of achieving a fast convergence of the state- trajectory solutions to the disease- free equilibrium points under a wide class of control laws under deviations of the equilibrium amounts of such populations.

The Parameters Identification of Airplane Flutter Model Based Global Nonlinear Separable Least Square Method

2012 ◽  
Vol 490-495 ◽  
pp. 2774-2779
Author(s):  
Jie Yao ◽  
Jian Hong Wang
Keyword(s):  
Transfer Function ◽  
Least Square Method ◽  
Least Square ◽  
Model Parameters ◽  
Transfer Function Model ◽  
Input Output ◽  
Function Model ◽  
Output Data ◽  
Noisy Input ◽  
Least Square Problem

considering the noisy input-output data, this paper come up with an idea extending the deviation compensation least square (CLS)to the nonlinear separable least square (NSLS).The least square method employed nonlinear separable least square adaptive to the noisy situation is able to identify accurately the airplane flutter model parameters. Combining the transfer function model, this algorithm successfully converts the identification of noisy system into nonlinear separable least square problem. The square deviation of two noises and the model parameter of the transfer function can be estimated separately by using of above algorithm.

Development of System Identification for Piezoelectric Patch Actuator

2015 ◽  
Vol 761 ◽  
pp. 245-249
Author(s):  
Mohd Nazmin Maslan ◽  
Z. Jamaludin ◽  
Muhamad Arfauz A. Rahman ◽  
Lokman Abdullah ◽  
Mohd Lutfan Abd Latib ◽  
...  
Keyword(s):  
System Identification ◽  
Transfer Function ◽  
Least Square ◽  
Input Output ◽  
Output Data ◽  
Piezoelectric Patch ◽  
Direct Measurements ◽  
Highly Nonlinear

This paper presents the development of the system identification (SI) for the highly nonlinear piezoelectric patch actuator. The transfer function is determined by using the nonlinear least square (NLS) method after the direct measurements of input-output data are taken from the actuator that is installed on a well-equipped platform. The results were validated to ensure that the transfer function derived fits well with the experimental output.

scholarly journals Statistical Inference for Piecewise Affine System Identification

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hong Jianwang ◽  
Ricardo A. Ramirez-Mendoza ◽  
Xiang Yan
Keyword(s):  
System Identification ◽  
Unknown Parameter ◽  
Recursive Least Squares ◽  
Parameter Vector ◽  
Input Output ◽  
Output Data ◽  
Piecewise Affine ◽  
Affine System ◽  
Piecewise Affine System ◽  
Unknown Parameter Vector

This short note studies the problem of piecewise affine system identification, being a special nonlinear system based on our previous contribution on it. Two different identification strategies are proposed to achieve our mission, such as centralized identification and distributed identification. More specifically, for centralized identification, the total observed input-output data are used to estimate all unknown parameter vectors simultaneously without any consideration on the classification process. But for distributed identification, after the whole observed input-output data are classified into their own right subregions, then part input-output data, belonging to the same subregion, are applied to estimate the unknown parameter vector. Whatever the centralized identification and distributed identification, the final decision is to determine the unknown parameter vector in one linear form, so the recursive least squares algorithm and its modified form with the dead zone are studied to deal with the statistical noise and bounded noise, respectively. Finally, one simulation example is used to compare the identification accuracy for our considered two identification strategies.

scholarly journals Method of value chain mapping with international input–output data: application to the agricultural value chain in three Greater Mekong Subregion countries

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ikuo Kuroiwa
Keyword(s):  
Value Chain ◽  
Value Added ◽  
Input Output ◽  
Output Data ◽  
Primary Input ◽  
Goods And Services ◽  
Unit Structure ◽  
Data Application ◽  
Final Output ◽  
Greater Mekong Subregion

AbstractExtending the technique of unit structure analysis, which was originally developed by Ozaki (J Econ 73(5):720–748, 1980), this study introduces a method of value chain mapping that uses international input–output data and reveals both the upstream and downstream transactions of goods and services, as well as primary input (value added) and final output (final demand) transactions, which emerge along the entire value chain. This method is then applied to the agricultural value chain of three Greater Mekong Subregion countries: Thailand, Vietnam, and Cambodia. The results show that the agricultural value chain has been increasingly internationalized, although there is still room to benefit from participating in global value chains, especially in a country such as Cambodia. Although there are some constraints regarding the methodology and data, the method proves useful in tracing the entire value chain.

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