Crack identification with parametric optimization of entropy &amp; wavelet transformation

Wimarshana, Buddhi; Wu, Nan; Wu, Chenyu

doi:10.12989/smm.2017.4.1.033

Cited by 9 publications

(5 citation statements)

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“…However, due to the strong dispersive characteristics of Lamb waves, the waves usually display strong nonlinearity and disorder themselves as they travel in a structure [16]. Moreover, the existence of structural damages, including cracks, delamination and imperfect contacts, usually has an influence on the local stiffness of the structure, and eventually it may bring about disorder or nonlinearity to the waves and change the complexity of the received signals [17][18][19][20]. Therefore, to detect the structural damages effectively and accurately, two crucial problems which need to be overcome are how to separate and enhance the nonlinear and disorder information of the damage from the received signals, and how to develop an indicator or feature with high sensitivity and resolution to quantify the nonlinearity and disorder related to the structural damage.…”

Section: Introductionmentioning

confidence: 99%

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

Song

Ming

et al. 2022

Smart Mater. Struct.

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In this research, a new method based on singular spectrum analysis (SSA) and fuzzy entropy is developed for damage detection on thin wall-like structures, and the normalized fuzzy entropy is employed as an indicator to identify the severity of the damage. The Lead Zirconate Titanate (PZT) transducers are used in this research to generate and detect the Lamb waves. During the detection, the collected signals from the PZT sensors are firstly decomposed and reconstructed by SSA to extract the feature of the damage, and then the reconstructed signals with the feature of the damage are processed to obtain the normalized fuzzy entropy. An experimental setup of an aluminium plate with added magnets is fabricated to validate the proposed method. The experimental results show that when magnets are attached on the aluminium plate, the normalized fuzzy entropy is smaller than that when there are no magnets. That is because when magnets are placed on the plate, the movement and some vibration modes of Lamb waves are disturbed by the added magnets and this disturbing effect can be enhanced by increasing the number and locations of the added magnets, and eventually the complexity and nonlinearity of the waves are weakened. The experimental results of a single damage with different number of magnets indicate that the normalized fuzzy entropy decreases linearly as the number of the added magnets increases, which demonstrates that the proposed method can be used to detect the severity of the damage. Moreover, the experimental results of multi-damage on different locations indicate that the normalized fuzzy entropy is relevant with both the total number and locations of the added magnets. The normalized fuzzy entropy decreases linearly as the total number of the magnets increases, and the entropy of a single damage is smaller than that of the multi-damage with the same total number of magnets, which demonstrates that the proposed method also can be used for multi-damage detection on a thin plate. This study provides us a new approach to identifying a single or multiple damages on thin wall-like structures.

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Section: Introductionmentioning

confidence: 99%

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

Song

Ming

et al. 2022

Smart Mater. Struct.

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“…In recent years, entropy has gradually received attention in the field of damage identification. Rojas used ultrasound to detect tiny perforations in plate-shaped structural members and discussed the optimal configuration of the sensor [ 19 ]. In 2017, Wimarshana et al used wavelet transformation and sampling entropy to detect breathing cracks on a cantilever beam and optimized the sampling entropy parameters [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Damage Detection of Regular Civil Buildings Using Modified Multi-Scale Symbolic Dynamic Entropy

Lin

Lee

Hsu

et al. 2022

Entropy

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Based on the examination of the fundamental characteristics of structures, structural health monitoring (SHM) has received increased attention in recent years. Studies have shown that the SHM method using entropy analysis can precisely identify the damaged location of the structure, which is very helpful for the daily inspection or maintenance of civil structures. Although entropy analysis has shown excellent accuracy, it still consumes too much time and too many resources in terms of data processing. To improve the dilemma, in this study, modified multi-scale symbolic dynamic entropy (MMSDE) is adopted to identify the damaged location of the civil structure. A damage index (DI) based on the entropy diagram is also proposed to clearly indicate the damage location. A seven-story numerical model was created to verify the efficiency of the proposed SHM system. The results of the analysis of each case of damage show that the MMSDE curve for the damaged floor is lower than that for the healthy floor, and the structural damage can be correctly diagnosed by the damage index. Subsequently, a scaled-down steel benchmark experiment, including 15 damage cases, was conducted to verify the practical performance of the SHM system. The confusion matrix was used to further evaluate the SHM system. The results demonstrated that the MMSD-based system can quickly diagnose structural safety with reliability and accuracy. It can be used in the field of long-term structural health monitoring in the near future.

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“…Nowadays, more and more researchers in various fields use entropy for different forms of signal analysis or malfunction monitoring. In 2017, Wimarshana et al applied wavelet transformation and sampling entropy to detect breathing cracks on a cantilever beam and optimized the parameters of sampling entropy to increase detection efficiency [ 18 ]. Guan et al applied cross-sample entropy to the failure detection of shear structures and input white noise to simulate random loads by using finite element models [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Composite Multiscale Cross-Sample Entropy Analysis for Long-Term Structural Health Monitoring of Residential Buildings

Lin

Lee

2020

Entropy

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This study proposesd a novel, entropy-based structural health monitoring (SHM) system for measuring microvibration signals generated by actual buildings. A structural health diagnosis interface was established for demonstration purposes. To enhance the reliability and accuracy of entropy evaluation at various scales, composite multiscale cross-sample entropy (CMSCE) was adopted to increase the number of coarse-grained time series. The degree of similarity and asynchrony between ambient vibration signals measured on adjacent floors was used as an in-dicator for structural health assessment. A residential building that has been monitored since 1994 was selected for long-term monitoring. The accumulated database, including both the earthquake and ambient vibrations in each seismic event, provided the possibility to evaluate the practicability of the CMSCE-based method. Entropy curves obtained for each of the years, as well as the stable trend of the corresponding damage index (DI) graphs, demonstrated the relia-bility of the proposed SHM system. Moreover, two large earthquake events that occurred near the monitoring site were analyzed. The results revealed that the entropy values may have been slightly increased after the earthquakes. Positive DI values were obtained for higher floors, which could provide an early warning of structural instability. The proposed SHM system is highly stable and practical.

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Crack identification with parametric optimization of entropy & wavelet transformation

Cited by 9 publications

References 0 publications

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

Singular spectrum analysis and fuzzy entropy-based damage detection on a thin aluminium plate by using PZTs

Damage Detection of Regular Civil Buildings Using Modified Multi-Scale Symbolic Dynamic Entropy

Composite Multiscale Cross-Sample Entropy Analysis for Long-Term Structural Health Monitoring of Residential Buildings

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