A substructure approach to local damage detection of shear structure

2011 ◽  
Vol 19 (2) ◽  
pp. 309-318 ◽  
Author(s):  
Zhenhua Xing ◽  
Akira Mita
Keyword(s):  
Damage Detection ◽  
Local Damage ◽  
Substructure Approach ◽  
Shear Structure

Substructure Damage Detection Method for Shear Structure Using Sub-Time Series and ARMAX

2013 ◽  
Vol 558 ◽  
pp. 149-159 ◽  
Author(s):  
Liu Mei ◽  
Akira Mita ◽  
Zhen Hua Xing
Keyword(s):  
Time Series ◽  
Damage Detection ◽  
Degrees Of Freedom ◽  
Detection Method ◽  
Processing System ◽  
Computing Power ◽  
Detection Systems ◽  
Iterative Computation ◽  
Substructure Approach ◽  
Shear Structure

A local damage detection method for shear structure based on substructure approach and sub-time series superposition is proposed, which is promising for application in parallel and distributed damage detection systems. This method requires only three sensors to identify localized damage in any story of a building and it doesnt require constructing the structure models. A substructure method was used in this method to divide a complete structure into several substructures. Each substructure has a considerably smaller number of degrees of freedom (DOFs) which makes fewer requirements on the computing power of the data processing system. The algorithm is simple, which involves only algebra calculation and does not need any iterative computation. Moreover the damage detection process can be independently conducted on each substructure. Thus, this method is easy, efficient and suitable for being embedded into parallel and distributed damage detection systems. To better assess the performance of the method proposed above, experimental verification of the proposed approach has been conducted, which shows the proposed method works quite well and stably.

Application of the EKE and LSE-UI Based Substructure Approach for Damage Detection with Limited Output Measurements

2011 ◽  
Vol 255-260 ◽  
pp. 4171-4175
Author(s):  
Ying Lei ◽  
Chao Liu
Keyword(s):  
Damage Detection ◽  
Least Squares ◽  
Structural Damage ◽  
Structural Parameters ◽  
Least Squares Estimation ◽  
Complex Case ◽  
Benchmark Problem ◽  
Unknown Inputs ◽  
Limited Output ◽  
Substructure Approach

This paper presents an effort to apply the EKE (extended Kalman estimator) and LSE-UI (least squares estimation for unknown input) technique to detect structures damage with limited output measurements. This technique can be extended to detect structural local damage in complex structures based on substructure approach. Structural parameters and the unknown inputs are identified by a recursive algorithm based on sequential application of the extended Kalman estimator for the extended state vector and the least squares estimation for the unknown inputs. Only a limited number of measured acceleration responses of the benchmark structure subject to unmeasured excitation inputs are utilized. This structural damage detection method is applied to the ASCE SHM benchmark building to test its efficacy and provide a solution to the complex case of the Phase I benchmark problem. Damage detection results indicate that the proposed technique can detect and localize structural damage of the complex benchmark problem with good accuracy.

Non-dominated solution set based on time–frequency infograms for local damage detection of rotating machines

2019 ◽  
Vol 92 ◽  
pp. 213-227 ◽  
Author(s):  
Xingxing Jiang ◽  
Juanjuan Shi ◽  
Weiguo Huang ◽  
Zhongkui Zhu
Keyword(s):  
Damage Detection ◽  
Solution Set ◽  
Local Damage ◽  
Rotating Machines ◽  
Time Frequency

scholarly journals Nonnegative Matrix Factorization of time frequency representation of vibration signal for local damage detection – comparison of algorithms

2018 ◽  
Vol 29 ◽  
pp. 00010
Author(s):  
Jacek Wodecki
Keyword(s):  
Damage Detection ◽  
Matrix Factorization ◽  
Nonnegative Matrix Factorization ◽  
Single Channel ◽  
Classical Method ◽  
Nonnegative Matrix ◽  
Vibration Signal ◽  
Local Damage ◽  
Time Frequency ◽  
Frequency Representation

Local damage detection in rotating machine elements is very important problem widely researched in the literature. One of the most common approaches is the vibration signal analysis. Since time domain processing is often insufficient, other representations are frequently favored. One of the most common one is time-frequency representation hence authors propose to separate internal processes occurring in the vibration signal by spectrogram matrix factorization. In order to achieve this, it is proposed to use the approach of Nonnegative Matrix Factorization (NMF). In this paper three NMF algorithms are tested using real and simulated data describing single-channel vibration signal acquired on damaged rolling bearing operating in drive pulley in belt conveyor driving station. Results are compared with filtration using Spectral Kurtosis, which is currently recognized as classical method for impulsive information extraction, to verify the validity of presented methodology.

Damage detection of multi-storeyed shear structure using sparse and noisy modal data

2015 ◽  
Vol 15 (5) ◽  
pp. 1215-1232
Author(s):  
S.K. Panigrahi ◽  
S. Chakraverty ◽  
S.K. Bhattacharyya
Keyword(s):  
Damage Detection ◽  
Modal Data ◽  
Shear Structure

Selection of informative frequency band in local damage detection in rotating machinery

2014 ◽  
Vol 48 (1-2) ◽  
pp. 138-152 ◽  
Author(s):  
Jakub Obuchowski ◽  
Agnieszka Wyłomańska ◽  
Radosław Zimroz
Keyword(s):  
Damage Detection ◽  
Frequency Band ◽  
Rotating Machinery ◽  
Local Damage ◽  
Selection Of
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