scholarly journals Identification of damage-expected members of truss structures using frequency response function

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668791 ◽  
Author(s):  
Moon-Jeong Kim ◽  
Hee-Chang Eun
Keyword(s):  
Damage Detection ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Truss Structure ◽  
Truss Structures ◽  
Modal Data ◽  
Damage Indices ◽  
Proper Orthogonal Modes ◽  
Proper Orthogonal

A damaged member in a truss structure leads to a variation in the initial responses of its adjacent members. A flexibility-based approach extracting from the modal data should be implemented as one of the structural damage detection methods. The frequency response function data as dynamic measurements provide more information on the system characteristics compared with modal data. Proper orthogonal modes from the frequency response functions extracted in the given frequency ranges and their modified forms can be utilized as damage indices to detect damages. This study considers damage detection of a truss structure using a frequency response function–based approach transformed to the proper orthogonal modes and a flexibility-based approach using the first few modal data for undamaged and damaged states. The utilization of these two methods is compared through numerical experiments on truss structures. The methods can rarely detect the damaged member accurately, but a group of damage-expected members is detected despite the existence of external noise. It is shown that the frequency response function–based approach can be utilized more explicitly than the flexibility-based approach.

scholarly journals The Researches on Damage Detection Method for Truss Structures

2018 ◽  
Vol 38 ◽  
pp. 03030
Author(s):  
Meng Hong Wang ◽  
Xiao Nan Cao
Keyword(s):  
Numerical Simulation ◽  
Frequency Response ◽  
Response Function ◽  
Time Domain ◽  
Experimental Analysis ◽  
Frequency Response Function ◽  
Principal Component ◽  
Truss Structures ◽  
Time Domain Signal ◽  
The Time Domain

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Structural damage detection in plates using a deep neural network–couple sparse coding classification ensemble method

2020 ◽  
pp. 107754632092915
Author(s):  
Vahid Bokaeian ◽  
Faramarz Khoshnoudian ◽  
Milad Fallahian
Keyword(s):  
Damage Detection ◽  
Frequency Response ◽  
Response Function ◽  
Sparse Coding ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Principal Component ◽  
Plate Structures ◽  
Feature Extraction Method ◽  
Damage Scenarios

The present study aims at identifying damages in plate structures by applying a pattern recognition–based damage detection technique using the frequency response function. The large number of degrees of freedom is one of the crucial obstacles in the way of accurately identifying damages in plate structures. On the other hand, frequency response functions include many details that dramatically lower the computing speed and enlarge the memory needed for storing data, hampering the application of this method. Furthermore, this study performs principal component analysis as an authoritative feature extraction method with the purpose of reducing the dimensions of the measured frequency response function data and generating distinct feature patterns. Also, because there has been no individual optimal classifier applicable to all problems, an ensemble comprising two powerful classifiers containing couple sparse coding classification and deep neural networks is used to predict the structure damage. This study evaluates the accuracy of damage detection by the proposed method in square-shaped structural plates with the lengths of 1 m and 2 m under different damage scenarios, namely, single and multiple element.

DAMAGE DETECTION USING THE FREQUENCY-RESPONSE-FUNCTION CURVATURE METHOD

1999 ◽  
Vol 226 (5) ◽  
pp. 1029-1042 ◽  
Author(s):  
R.P.C. SAMPAIO ◽  
N.M.M. MAIA ◽  
J.M.M. SILVA
Keyword(s):  
Damage Detection ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function

scholarly journals Damage detection based on output-only measurements using cepstrum analysis and a baseline-free frequency response function curvature method

2022 ◽  
Vol 105 (1) ◽  
pp. 003685042110644
Author(s):  
Ayisha Nayyar ◽  
Ummul Baneen ◽  
Muhammad Ahsan ◽  
Syed A Zilqurnain Naqvi ◽  
Asif Israr
Keyword(s):  
Damage Detection ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Damage Index ◽  
Real Life ◽  
System Response ◽  
Response Functions ◽  
Frequency Response Functions ◽  
Output Only

Low-severity multiple damage detection relies on sensing minute deviations in the vibrational or dynamical characteristics of the structure. The problem becomes complicated when the reference vibrational profile of the healthy structure and corresponding input excitation, is unavailable as frequently experienced in real-life scenarios. Detection methods that require neither undamaged vibrational profile (baseline-free) nor excitation information (output-only) constitute state-of-art in structural health monitoring. Unfortunately, their efficacy is ultimately limited by non-ideal input excitation masking crucial attributes of system response such as resonant frequency peaks beyond first (few) natural frequency(ies) which can better resolve the issue of multiple damage detection. This study presents an improved frequency response function curvature method which is both baseline-free and output-only. It employs the cepstrum technique to eliminate [Formula: see text] decay of higher resonance peaks caused by the temporal spread of real impulse excitation. Long-pass liftering screens out the bulk of low-frequency sensor noise along with the excitation. With more visible resonant peaks, the cepstrum purified frequency response functions (regenerated frequency response functions) register finer deviation from an estimated baseline frequency response function and yield an accurate damage index profile. The simulation and experimental results on the beam show that the proposed method can successfully locate multiple damages of severity as low as 5%.

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