Experimental and Theoretical Investigations of the Impact Localization of a Passive Smart Composite Plate Fabricated Using Piezoelectric Materials

Dezfouli, M.M.S.; Hassan, Mohd Roshdi; Ruslan, Mohd Hafidz; Mat, Sohif; Bakhtyar, B.

doi:10.1155/2013/326713

Cited by 3 publications

(6 citation statements)

References 19 publications

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“…Two major mechanical parts of a smart composite structure are widely investigated: the beams [5, 13-15, 18, 20-23, 32, 35, 37-39, 41, 46, 47, 49, 50] and the plates [7,12,16,17,19,22,26,27,29,31,33,34,36,42,43,45,48]. This approach is mainly due to the ease of modeling these two parts.…”

Section: Structure Typementioning

confidence: 99%

“…If resin is used, the tows can be combined to form tapes [24,28,30]. The tows can also be woven together to make woven fabrics [12, 14, 18, 25,27,29,34,36,43,50], or the tows can be braided or knitted together to make fibre preforms (level c). Mat is a sheet-like material consisting of randomly oriented chopped fibres which are held together by a binder [26,44,48,49].…”

Section: Reinforcement Formsmentioning

confidence: 99%

“…[31,33], 1.7 bars as in [5], 2.1 bars as in [5, 27], 3 bars as in [25], 5 bars as in [43], 6 bars as in [12, 16, 22, 29] and 7 bars as in [15, 20,23,42,45]). When a hand lay-up method is selected [36], the ambient pressure is used. For filament winding [24,30], Teflon tapes are used to compact the fibres.…”

Section: Applied Pressurementioning

confidence: 99%

“…Therefore, it is necessary to glue the transducer on a ply with a glue compatible with the resin. Another method is to use a ply with cut-out [5, 7, 12, 14, 15, 18, 20,23,36,42,45,50]. The cut-out has to have the exact geometry of the transducer.…”

Section: Inclusion Of the Piezoelectric Transducersmentioning

confidence: 99%

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A review of manufacturing techniques of smart composite structures with embedded bulk piezoelectric transducers

Meyer¹,

Lachat²,

Akhras³

2019

Smart Mater. Struct.

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Since the mid-1980's, sensors and actuators have been combined with composite materials in order to enhance and increase the functionalities of the resulting products. These innovative devices are called intelligent, adaptive or smart structures. Their main applications are related but not limited to vibration control, structural health monitoring, shape control and energy harvesting. One possible way of developing these devices is to embed the smart materials inside the structure. In this case, the main challenge is the way of embedding the smart material during the manufacturing process. This review presents the key elements of the manufacturing process, provides an overview of the techniques developed to embed the bulk piezoelectric transducers in the composite and details the achievements made with them. In conclusion, some guidelines for futures researches and developments are proposed

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Section: Structure Typementioning

confidence: 99%

Section: Reinforcement Formsmentioning

confidence: 99%

Section: Applied Pressurementioning

confidence: 99%

Section: Inclusion Of the Piezoelectric Transducersmentioning

confidence: 99%

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A review of manufacturing techniques of smart composite structures with embedded bulk piezoelectric transducers

Meyer¹,

Lachat²,

Akhras³

2019

Smart Mater. Struct.

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“…Due to their excellent electromechanical coupling ability, lead zirconate-titanate ceramics have been widely used as actuators and sensors [1][2][3][4] for health monitoring of large and complex structures, as well as functional materials for environmental power generation [5][6][7]. However, degradation of their electromechanical properties generally limits the application of piezoelectric ceramic materials.…”

Section: Introductionmentioning

confidence: 99%

Evolution of the Electrical Displacement and Energy Dissipation of Lead Zirconate‐Titanate Ceramics under Cyclical Load

Cang

Chen

2020

Advances in Materials Science and Engineering

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In this paper, the electromechanical behavior of lead zirconate-titanate ceramics (P51) has been characterized and modeled. The variation of the energy dissipation and peak electrical displacement of the P51 ceramic has been investigated in details. The total strain of P51 under cyclical loading consists of elastic deformation (εije), immediate ferroelectric domain switching deformation (εijd), and time-dependent deformation (εijc). Thus, an expression for the energy dissipation of P51 can be theoretically derived. In addition, a practical method for calculating the dissipated energy has been proposed by integrating the curve of a hysteresis loop. The experimental results show that the peak electrical displacement and dissipated energy both decrease monotonously with the increase of the number of cycles. Furthermore, ferroelectric 90° domain switching was observed by X-ray diffraction (XRD) and the percentage of domain switching has been calculated by the variation of the peak intensity ratio of (002) to (200) at about 45 degrees. Then, grain debonding, crack, and crush were found around voids inside the specimen by using scanning electron microscope (SEM). It is indicated that switching of more capable-switch domains stimulates larger dissipated energy and a bigger peak electrical displacement at the initial cyclic loading. Finally, an exponential functional model has been proposed to simulate the peak evolution of electrical displacement based on the energy dissipation of P51 ceramics under cyclical load.

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Low Velocity Impact Monitoring of Composite Tubes Based on FBG Sensors

Huan,

Lu,

Shen

et al. 2024

Sensors

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Carbon fiber reinforced composites (CFRP) are susceptible to hidden damage from low velocity external impacts during their service life. To ensure the proper monitoring of the state of the composites, it is crucial to predict the location of an impact event. In this paper, fiber Bragg grating (FBG) sensors are affixed to the surface of a carbon fiber composite tube, and an optical sensing interrogator is used to capture the central wavelength shift of the FBG sensors due to low-velocity impacts. A discrete wavelet transform is used for noise reduction in the response signals. Then, the differences in the captured response signals of the FBG sensors at different locations of the impact were analyzed. Moreover, two methods were implemented to predict the location of low-velocity impacts, according to the differences in the captured response signals. The BP neural network-based method utilized three data sets to train the neural network, resulting in an average localization error of 20.68 mm. In contrast, the method based on error outliers selected a specific data set as the reference dataset, achieving an average localization error of 13.98 mm. The comparison of the predicted results shows that the latter approach has a higher predictive accuracy and does not require a significant amount of data.

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Experimental and Theoretical Investigations of the Impact Localization of a Passive Smart Composite Plate Fabricated Using Piezoelectric Materials

Cited by 3 publications

References 19 publications

A review of manufacturing techniques of smart composite structures with embedded bulk piezoelectric transducers

A review of manufacturing techniques of smart composite structures with embedded bulk piezoelectric transducers

Evolution of the Electrical Displacement and Energy Dissipation of Lead Zirconate‐Titanate Ceramics under Cyclical Load

Low Velocity Impact Monitoring of Composite Tubes Based on FBG Sensors

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