A Novel Piezoceramic-Based Sensing Technology Combined With Visual Domain Networks for Timber Damage Quantification

Xiong, Haibei; Chen, Lin; Yuan, Cheng; Kong, Qingzhao

doi:10.3389/fmats.2021.688594

Cited by 7 publications

(4 citation statements)

References 42 publications

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“…Meng et al [52] investigated the repair of cracks on timber surfaces using piezoelectric ceramic active sensing. Xiong et al [53] combined the sensing technique based on piezoelectric ceramics with a visual domain network to quantitatively assess the damage condition of timber, and used deep neural network classification, which can effectively identify the crack condition of timber structures.…”

Section: Introductionmentioning

confidence: 99%

Bonding performance monitoring between CFRP and timber column interfaces based on piezoelectric ceramics

Yang¹,

Lv²,

Meng³

et al. 2023

Smart Mater. Struct.

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To address the problem that carbon fibre reinforced polymer (CFRP) composite material is not easy to directly measure the bond strength of the CFRP-timber column interface during the process of strengthening timber column, a real-time monitoring method of CFRP-timber interface bond strength based on piezoelectric ceramic active sensing is proposed to determine the interface bond strength directly from the structural response signal.. A total of 15 specimens were designed for the active monitoring test and tensile test, and the monitoring signals at different enhancement times were compared and analyzed using wavelet packets, power spectral density, and short-time Fourier transform, and it was found that the amplitude and power spectral density of the signals increased as the reinforcement time increased. The mapping relationship between wavelet packet energy and bond strength is obtained, providing a more efficient and robust way of monitoring the bond strength between CFRP and timber columns during reinforcement.

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Section: Introductionmentioning

confidence: 99%

Bonding performance monitoring between CFRP and timber column interfaces based on piezoelectric ceramics

Yang¹,

Lv²,

Meng³

et al. 2023

Smart Mater. Struct.

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“…Liu et al [12] used a wave propagation monitoring technology system to explore the damage characteristics and evolution of wood specimens under axial compression and found that the amplitude of the signal can effectively reflect the damage law for wood. Xiong et al [13] proposed a new sensing technology based on piezoelectric ceramics combined with a visual domain network to quantitatively evaluate the damage to the wood. The experimental results showed that the method can be used to effectively and accurately identify the crack state for wooden structures.…”

Section: Introductionmentioning

confidence: 99%

Study on loose damage monitoring of mortise-tenon joints in traditional wooden structures based on piezoelectric active sensing

Yang¹,

Wang

Meng³

et al. 2023

Smart Mater. Struct.

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In traditional Chinese wooden structural buildings, mortise-tenon joints are used as connection nodes. Under the erosion effects from wind and rain, such nodes are prone to aging and loosening. If theyare not tracked and repaired in time, they are likely to cause structural damage when they encounter sudden loads such as earthquakes. In accordance with engineering practice, one mortise-tenon joint specimen with a penetrating straight tenon and one mortise-tenon joint specimen without a penetrating tenon were constructed. Active sensing technology based on piezoelectric ceramics was used to identify the loosening state of tenon and mortise joints. The amplitude of the piezoelectric signal, wavelet packet energy, information entropy, and damage index based on the root mean square deviation were analyzed. It was found that with the increase in loosening damage, the amplitude of the signal gradually decreases, and the information entropy gradually increases. When the damage reaches a certain extent, the changes in the monitoring signal characteristics is limited. The proposed monitoring method can be used to identify the damage state for mortise-tenon joints effectively, and the research results can provide a valuable guideline for the repair of mortise-tenon joints used in traditional wooden structures.

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“…During the past decades, structural health monitoring (SHM) has received rapidly increasing attention because it can help to protect structures from severe damage (Hou and Xia, 2021). An integral SHM system contains a lot of different kinds of sensors that should be installed on structures to record various types of responses (Yi et al, 2015(Yi et al, , 2017Xiong et al, 2021). Nowadays civil structures such as Guangzhou New TV Tower, Tsing Ma Bridge, and Hong Kong-Zhuhai-Macao Bridge are equipped with advanced SHM systems to ensure the serving structures are in healthy condition (Miguel et al, 2009;He et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Structural damage detection based on modal feature extraction and multi-objective optimization method for steel structures

2022

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Model updating based on intelligent algorithms has achieved great success in structural damage detection (SDD). But the appropriate selection of objective functions remains unclear and becomes an obstacle to applying the methods to real-world steel structures. In this paper, a multi-objective identification method based on modal feature extraction and linear weight sum was proposed, and the best weight values to gain the best solution were also determined. A hybrid particle swarm optimization (HPSO) was selected as a solver to update structural parameters for accurate SDD results. First of all, six single objective functions based on modal feature extraction were considered, and numerical simulations show that the one based on MTMAC indicator exhibits certain superiority over the other. In order to provide a fair comparison among different objective functions, a quantified indicator named damage vector consistency (DVC) is also defined, which describes the consistency between identified result and the assumed one. After that, a multi-objective identification method is formulated by linearly combining an MTMAC-based objective function and another selected single objective function. Different weight values were also investigated to find out the best solution for accurate SDD. Three numerical simulations were conducted, including a simply-supported beam, a two-story steel frame, and a 31-bar plane truss. Their SDD results verify the applicability of the proposed multi-objective optimization method. Some relative discussions are also described in detail.

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A Novel Piezoceramic-Based Sensing Technology Combined With Visual Domain Networks for Timber Damage Quantification

Cited by 7 publications

References 42 publications

Bonding performance monitoring between CFRP and timber column interfaces based on piezoelectric ceramics

Bonding performance monitoring between CFRP and timber column interfaces based on piezoelectric ceramics

Study on loose damage monitoring of mortise-tenon joints in traditional wooden structures based on piezoelectric active sensing

Structural damage detection based on modal feature extraction and multi-objective optimization method for steel structures

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