Flowmeter based on a piezoelectric PVDF tube

Medeiros, Khrissy Aracélly Reis; Barbosa, Carlos Roberto Hall; d’Almeida, J.R.M.; Ribeiro, Alexandre S.; Paula, Igor Braga de

doi:10.1016/j.measurement.2019.02.059

Cited by 12 publications

(3 citation statements)

References 36 publications

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“…An initial comparison of the graphs ( Figure 12 a) suggests that the nonpolar α and the polar β and γ phases (responsible for the piezo and pyro electric properties) coexist in both treated and untreated samples. However, this was expected; as many previous studies [ 72–74 ] have shown that typically melt‐spun PVDF fibers contain a noticeable amount of β ‐phase content solely because of the mechanical stretching process that is applied during the extrusion process.…”

Section: Resultsmentioning

confidence: 91%

A Piezo Smart‐Braid Harvester and Damper for Multifunctional Fiber Reinforced Polymer Composites

2020

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The past decade has seen the rapid development of wearable electronics, wireless sensor networks (WSNs), and self‐powered implantable sensors. However, these devices usually require a continuous source of power supply to operate safely and accurately while having the least reliance on conventional battery systems—due to the recharging/maintenance burdens of batteries. Vibration‐based piezoelectric energy harvesting (PEH) from environment, man‐made machinery, and human body movements seems to be a promising solution. Herein, the first integration of a piezoelectric poly(vinylidene fluoride) (PVDF) yarn‐braid microgenerator into a fiber reinforced polymer composite (FRPC) structure is reported. It is demonstrated that the developed smart composite exhibits multifunctional performances, including simultaneous structural (with ≈10% increased Young's modulus), energy harvesting, and vibration damping (with a damping factor of 125%). The results show that an average output voltage of 3.6 V and a power density of 2.2 mW cm−3 can be achieved at strains below 0.15%, under cyclic loading tests between 1 and 10 Hz. Moreover, noticeable improvements are made in the crystallinity percentage and β‐phase content of as‐received PVDF yarns by, respectively, ≈34% and ≈37%, as a result of the applied coreless radial and axial corona poling techniques.

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Section: Resultsmentioning

confidence: 91%

A Piezo Smart‐Braid Harvester and Damper for Multifunctional Fiber Reinforced Polymer Composites

2020

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“…However, the use of PZT piezoelectric transducers presents a major disadvantage due to its harmfulness and negative effects on the environment. Medeiros et al demonstrated the applicability of using poly(vinylidene fluoride) (PVDF) polymers thanks to their particular piezoelectric properties for flow measurement [28]. Nogin et al used a PVDFbased piezoelectric sensor to diagnose broken bar defects in the internal combustion engine rotor [29].…”

Section: Introductionmentioning

confidence: 99%

Non-invasive intelligent monitoring system for fault detection in induction motor based on lead-free-piezoelectric sensor using ANN

GANA

Achour

Belaid

et al. 2022

Meas. Sci. Technol.

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This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements have been collected then monitored in real time and transmitted via an ESP32 board. A new bio-flexible piezoelectric sensor developed previously in our laboratory, was used for vibration analysis. Moreover an infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network algorithm implemented on the microcontroller. Besides, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of vibration analysis, thermal signature analysis and artificial neural network provides a better diagnosis. It ensures efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

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“…Recently, piezoelectric materials have been widely employed in agriculture sector, 1–3 automotive industry, 4 control, 5,6 health monitoring, 7–9 energy harvesting, 10,11 biomedical and medical, 12–16 measuring instruments, 17,18 nanomedicine, 19 robotics, 20,21 textile industry, 22 and so on. A remarkable property of these materials is converting mechanical deformations into electrical energy and vice versa.…”

Section: Introductionmentioning

confidence: 99%

Material properties identification of a piezoelectric beam using inverse method

Nematollahi

Hasanshahi

Eftekhari

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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This paper presents an inverse method for material properties identification of a piezoelectric beam (piezoelectric charge and relative dielectric coefficients) using a wavelet-based neural network as an inverse tool. The identification analysis is carried out by using two approaches. In the first approach, i.e. sensor mode analysis, the input data for wavelet-based neural network training are measured voltages at several specific points on the beam's top surface resulting from the applied beam tip deflection. In the second approach, i.e. actuation mode analysis, the input data are values of the beam tip deflection caused by applying voltage on the beam's top surface. In this study, the input parameters employed to train the wavelet-based neural network are obtained using the finite element method. The identification results are compared with those of some conventional neural networks including radial basis function and multilayer perceptron. The results show that the proposed neural network is an efficient tool in the material properties identification problem.

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Flowmeter based on a piezoelectric PVDF tube

Cited by 12 publications

References 36 publications

A Piezo Smart‐Braid Harvester and Damper for Multifunctional Fiber Reinforced Polymer Composites

A Piezo Smart‐Braid Harvester and Damper for Multifunctional Fiber Reinforced Polymer Composites

Non-invasive intelligent monitoring system for fault detection in induction motor based on lead-free-piezoelectric sensor using ANN

Material properties identification of a piezoelectric beam using inverse method

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