Rapid localization of acoustic source using sensor clusters in 3D homogeneous and heterogeneous structures

Yin, Shenxin; Xiao, Huifang; Cui, Zhiwen; Kundu, Tribikram

doi:10.1177/1475921720945195

Cited by 16 publications

(3 citation statements)

References 35 publications

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“…Up to now, a lot of work has been done by using the Lamb wave for damage evaluation and monitoring. Aimed at detecting unknown damage in three-dimensional heterogeneous structures, a localization is proposed by Yin et al [9]. This technique helps to localize the acoustic source with only a few sensors, which is heuristic for the scenario that limited sensors can be used for the monitoring of structures.…”

Section: Introductionmentioning

confidence: 99%

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Qiu

Liao

et al. 2023

Smart Mater. Struct.

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Since numerous sensors are needed to create a sensor array for the structural health monitoring of large-scale structures, the equipment quantity and cost considerably increase. This study proposes a sparse, triangle-shaped sensor array to identify, orient, and assess the degree of structural damage in composite constructions in order to overcome this shortcoming. The damage-scattered Lamb waves are recorded by the sparse sensor array with a variety of features that are then extracted and fed into the Support Vector Machine (SVM) classification method. The location and severity of the damage in composite constructions can be determined by training the SVM model. The principle component analysis (PCA) technique is used to compress the wave feature vectors while maintaining the majority of the damage information because the high dimension of the wave feature vectors required a significant amount of calculation during the training phase. Proof-of-concept tests show that the trained model, by utilizing the many properties of Lamb wave signals, can orient and define the degree of damage with excellent accuracy. Multiple lamb wave properties can be used to make up for the triangle sensor array's loss of damage information. In conjunction with the SVM, the triangle-shaped sensor array that was proposed in this study can efficiently make it easier to identify and characterize damage to large-scale structures while using fewer sensors.

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Section: Introductionmentioning

confidence: 99%

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Qiu

Liao

et al. 2023

Smart Mater. Struct.

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“…Kundu’s technique places three sensors in an L-shape to predict the location of the acoustic source. This technique can be used for complex inhomogeneous structures [ 21 ], highly anisotropic structures [ 22 ], and three-dimensional structures [ 23 ]. Wu et al [ 24 ] and Yin et al [ 25 ] suggested various sensor placement alternatives in cluster geometries to achieve more flexibility and/or more accurate predictions.…”

Section: Introductionmentioning

confidence: 99%

Experimental Research on Rapid Localization of Acoustic Source in a Cylindrical Shell Structure without Knowledge of the Velocity Profile

Yin

Cui

et al. 2021

Sensors

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Acoustic source localization in a large pressure vessel or a storage tank-type cylindrical structure is important in preventing structural failure. However, this can be challenging, especially for cylindrical pressure vessels and tanks that are made of anisotropic materials. The large area of the cylindrical structure often requires a substantial number of sensors to locate the acoustic source. This paper first applies conventional acoustic source localization techniques developed for the isotropic, flat plate-type structures to cylindrical structures. The experimental results show that the conventional acoustic source localization technique is not very accurate for source localization on cylindrical container surfaces. Then, the L-shaped sensor cluster technique is applied to the cylindrical surface of the pressure vessel, and the experimental results prove the applicability of using this technique. Finally, the arbitrary triangle-shaped sensor clusters are attached to the surface of the cylindrical structure to locate the acoustic source. The experimental results show that the two acoustic source localization techniques using sensor clusters can be used to monitor the location of acoustic sources on the surface of anisotropic cylindrical vessels, using a small number of sensors. The arbitrarily triangle-shaped sensors can be arbitrarily placed in a cluster on the surface of the cylindrical vessel. The results presented in this paper provide a theoretical and experimental basis for the surface acoustic source localization method for a cylindrical pressure vessel and lay a theoretical foundation for its application.

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“…Another ASL technique in highly anisotropic plates using ‘‘L’’-shaped sensor clusters was proposed by Park et al 28 and Sen et al 29,30 using wavefront shapes. Yin et al 31,32 extended applications of “L”-shaped sensor clusters to two- and three-dimensional heterogeneous structures.…”

Section: Introductionmentioning

confidence: 99%

A fast approach for acoustic source localization on a thin spherical shell

Zhou

Cui

Kundu

2021

Structural Health Monitoring

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Thin spherical shell structures are wildly used as pressure vessels in the industry because of their property of having equal in-plane normal stresses in all directions. Since very large pressure difference between the inside and outside of the wall exists, any formation of defects in the pressure vessel wall has a huge safety risk. Therefore, it is necessary to quickly locate the area where the defect maybe located in the early stage of defect formation and make repair on time. The conventional acoustic source localization techniques for spherical shells require either direction-dependent velocity profile knowledge or a large number of sensors to form an array. In this study, we propose a fast approach for acoustic source localization on thin isotropic and anisotropic spherical shells. A solution technique based on the time difference of arrival on a thin spherical shell without the prior knowledge of direction-dependent velocity profile is provided. With the help of “L”-shaped sensor clusters, only 6 sensors are required to quickly predict the acoustic source location for anisotropic spherical shells. For isotropic spherical shells, only 4 sensors are required. Simulation and experimental results show that this technique works well for both isotropic and anisotropic spherical shells.

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Rapid localization of acoustic source using sensor clusters in 3D homogeneous and heterogeneous structures

Cited by 16 publications

References 35 publications

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Experimental Research on Rapid Localization of Acoustic Source in a Cylindrical Shell Structure without Knowledge of the Velocity Profile

A fast approach for acoustic source localization on a thin spherical shell

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