Momentum BP Neural Networks in Structural Damage Detection Based on Static Displacements and Natural Frequencies

2007 ◽  
pp. 35-40
Author(s):  
Xudong Yuan ◽  
Chao Gao ◽  
Shaoxia Gao
Keyword(s):  
Neural Networks ◽  
Damage Detection ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Structural Damage Detection ◽  
Bp Neural Networks

Structural Damage Detection Using Parameters Combined with Changes in Flexibility Based on BP Neural Networks

2011 ◽  
Vol 243-249 ◽  
pp. 5475-5480
Author(s):  
Zhang Jun
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Damage Detection ◽  
Bp Neural Network ◽  
Structural Damage ◽  
The State ◽  
Structural Damage Detection ◽  
Bp Neural Networks ◽  
Simply Supported ◽  
Modal Flexibility

Modals of BP neural networks with different inputs and outputs are presented for different damage detecting schemes. To identify locations of structural damages, the regular vectors of changes in modal flexibility are looked on as inputs of the networks, and the state of localized damage are as outputs. To identify extents of structural damage, parameters combined with changes in flexibility and the square changes in frequency are as inputs of the networks, and the state of damage extents are as outputs. Examples of a simply supported beam and a plate show that the BP neural network modal can detect damage of structures in quantitative terms.

VIBRATION-BASED STRUCTURAL DAMAGE DETECTION UNDER VARYING TEMPERATURE CONDITIONS

2013 ◽  
Vol 13 (05) ◽  
pp. 1250082 ◽  
Author(s):  
XIAO-QING ZHOU ◽  
WEN HUANG
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Environmental Changes ◽  
Model Updating ◽  
Modal Testing ◽  
Structural Damage Detection ◽  
Vibration Data ◽  
Temperature Conditions ◽  
Vibration Properties

In vibration-based structural damage detection, it is necessary to discriminate the variation of structural properties due to environmental changes from those caused by structural damages. The present paper aims to investigate the temperature effect on vibration-based structural damage detection in which the vibration data are measured under varying temperature conditions. A simply-supported slab was tested in laboratory to extract the vibration properties with modal testing. The slab was then damaged and the modal testing was conducted again, in which the temperature varied. The modal data measured under different temperature conditions were used to detect the damage with a two-stage model updating technique. Some damage was falsely detected if the temperature variation was not considered. Natural frequencies were then corrected to those under the same temperature conditions according to the relation between the temperature and material modulus. It is shown that all of the damaged elements can be accurately identified.

Structural damage detection using convolutional neural networks combining strain energy and dynamic response

Meccanica ◽  
2019 ◽  
Vol 55 (4) ◽  
pp. 945-959 ◽  
Author(s):  
Shuai Teng ◽  
Gongfa Chen ◽  
Panpan Gong ◽  
Gen Liu ◽  
Fangsen Cui
Keyword(s):  
Neural Networks ◽  
Dynamic Response ◽  
Damage Detection ◽  
Convolutional Neural Networks ◽  
Structural Damage ◽  
Strain Energy ◽  
Structural Damage Detection

Response-Only Frequency-Domain Method for Structural Damage Detection

2009 ◽  
Author(s):  
Shuncong Zhong ◽  
S. Olutunde Oyadiji
Keyword(s):  
Damage Detection ◽  
Frequency Domain ◽  
Natural Frequency ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Frequency Domain Method ◽  
Structural Damage Detection ◽  
Frequency Curve ◽  
Domain Method ◽  
Auxiliary Mass

This paper proposes a response-only method in frequency domain for structural damage detection by using the derivative of natural frequency curve of beam-like structures with a traversing auxiliary mass. The approach just uses the response time history of beam-like structures and does not need the external source of force excitation. The natural frequencies of a damaged beam with a traversing auxiliary mass change due to change in flexibility and inertia of the beam as the auxiliary mass is traversed along the beam. Therefore the auxiliary mass can enhance the effects of the crack on the dynamics of the beam and, therefore, facilitating locating the damage in the beam. That is, the auxiliary mass can be used to probe the dynamic characteristic of the beam by traversing the mass from one end of the beam to the other. However, it is impossible to obtain accurate modal frequencies by the direct operation of the Fast Fourier Transform of the response data of the structure because the frequency spectrum can be only calculated from limited sampled time data which results in the well-known leakage effect. A spectrum correction method is employed to estimate high accurate frequencies of structures with a traversing auxiliary mass. In the present work, the modal responses of damaged simply supported beams with auxiliary mass are computed using the Finite Element Analysis. The graphical plots of the natural frequencies versus axial location of auxiliary mass are obtained. The derivatives of natural frequency curve can provide crack information for damage detection of beam-like structures. However, it is suggested that the derivative do not go beyond the third derivative of natural frequency curves to avoid the difference approximation error which will be magnified at higher derivative. The sensitivity of crack index for different noise, crack depth, auxiliary mass and damping ratio are also investigated. The simulated result demonstrated the efficiency and precision of the response-only frequency-domain method which can be recommended for the real application in structural damage detection.

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