scholarly journals Vibration-based damage detection of structural joints in presence of uncertainty

2018 ◽  
Vol 148 ◽  
pp. 14006 ◽  
Author(s):  
Hussein Al-Bugharbee ◽  
Ali Abolfathi ◽  
Irina Trendafilova
Keyword(s):  
Damage Detection ◽  
Singular Spectrum Analysis ◽  
Complex Structures ◽  
Frequency Method ◽  
Time Frequency ◽  
Vibrational Response ◽  
Reference Space ◽  
Vehicle Structure ◽  
Manufacturing Tolerances ◽  
Very High

Early damage detection of structure’s joints is essential in order to ensure the integrity of structures. Vibration-based methods are the most popular way of diagnosing damage in machinery joints. Any technique that is used for such a purpose requires dealing with the variability inherent to the system due to manufacturing tolerances, environmental conditions or aging. The level of variability in vibrational response can be very high for mass-produced complex structures that possess a large number of components. In this study, a simple and efficient time frequency method is proposed for detection of damage in connecting joints. The method suggests using singular spectrum analysis for building a reference space from the signals measured on a healthy structure and then compares all other signals to that reference space in order to detect the presence of faults. A model of two plates connected by a series of mounts is used to examine the effectiveness of the method where the uncertainty in the mount properties is taken into account to model the variability in the built-up structure. The motivation behind the simplified model is to identify the faulty mounts in trim-structure joints of an automotive vehicle where a large number of simple plastic clips are used to connect the trims to the vehicle structure.

Fuzzified time-frequency method for identification and localization of power system faults

2021 ◽  
pp. 1-13
Author(s):  
Pullabhatla Srikanth ◽  
Chiranjib Koley
Keyword(s):  
Power System ◽  
High Accuracy ◽  
Fuzzy Decision ◽  
Frequency Method ◽  
Time Frequency ◽  
Novel Approach ◽  
S Transform ◽  
Different Types ◽  
Power System Faults ◽  
Frequency Magnitude

In this work, different types of power system faults at various distances have been identified using a novel approach based on Discrete S-Transform clubbed with a Fuzzy decision box. The area under the maximum values of the dilated Gaussian windows in the time-frequency domain has been used as the critical input values to the fuzzy machine. In this work, IEEE-9 and IEEE-14 bus systems have been considered as the test systems for validating the proposed methodology for identification and localization of Power System Faults. The proposed algorithm can identify different power system faults like Asymmetrical Phase Faults, Asymmetrical Ground Faults, and Symmetrical Phase faults, occurring at 20% to 80% of the transmission line. The study reveals that the variation in distance and type of fault creates a change in time-frequency magnitude in a unique pattern. The method can identify and locate the faulted bus with high accuracy in comparison to SVM.

Structural Damage Assessment Using Output-Only Measurement: Localization and Quantification

2013 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Null Space ◽  
Singular Spectrum Analysis ◽  
Damage Index ◽  
Computation Efficiency ◽  
Output Only

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Damage detection in composite structures using Lamb wave analysis and time-frequency approach

2011 ◽  
Author(s):  
Yingtao Liu ◽  
Masoud Yekani Fard ◽  
Seung B. Kim ◽  
Aditi Chattopadhyay ◽  
Derek Doyle
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Composite Structures ◽  
Wave Analysis ◽  
Time Frequency

IDENTIFICATION OF IMPACT FORCE ON THE GAS PIPE BASED ON ANALYSIS OF THE ACOUSTIC WAVE

2008 ◽  
Vol 22 (09n11) ◽  
pp. 1039-1044 ◽  
Author(s):  
MIN-SOO KIM ◽  
SANG-KWON LEE ◽  
SUNG-JONG KIM
Keyword(s):  
Acoustic Wave ◽  
Cavity Mode ◽  
Impact Force ◽  
Correlation Technique ◽  
Frequency Method ◽  
Time Frequency ◽  
Long Time ◽  
Mode Characteristics ◽  
The Impact ◽  
The Waves

An acoustic wave signal measured on the gas pipe due to impact force is transfer to the far distance through the medium inside of duct. This signal is very complex since it includes the acoustic wave and solid wave. Acoustic wave is affected by the cavity mode inside of duct. The analysis of this acoustic wave gives information about the impact force. For the analysis of this signal, the correlation technique has been used for a long time. This method has a limitation for the application since the waves have dispersive and cavity mode characteristics for the flexible wave. In this paper, we present the time-frequency method for the identification of impact force and the location of impact on the gas pipe. The results give the useful information for the impact force and are applied to the analysis of leakage location of the gas pipe.

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