Structural health monitoring of multi-spot welded joints using a lead zirconate titanate based active sensing approach

2015 ◽  
Vol 25 (1) ◽  
pp. 015031 ◽  
Author(s):  
Ping Yao ◽  
Qingzhao Kong ◽  
Kai Xu ◽  
Tianyong Jiang ◽  
Lin-sheng Huo ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Welded Joints ◽  
Lead Zirconate ◽  
Active Sensing ◽  
Structural Health ◽  
Zirconate Titanate ◽  
Spot Welded

Reusable piezoelectric transducer for structural health monitoring using both Lamb wave and electromechanical impedance modes

2020 ◽  
Vol 31 (16) ◽  
pp. 1898-1909
Author(s):  
Qijian Liu ◽  
Yuan Chai ◽  
Xinlin Qing
Keyword(s):  
Structural Health Monitoring ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lamb Wave ◽  
Lead Zirconate ◽  
Aluminum Plate ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Zirconate Titanate ◽  
Piezoelectric Lead Zirconate Titanate

A variety of structural health monitoring techniques have been developed to support the efficient online monitoring of structural integrity. Moreover, Lamb wave and electromechanical impedance methods are increasingly used for structural health monitoring applications due to their high sensitivity and effectiveness in detecting damage. However, these techniques require transducers to be permanently attached to structures because of the usage of baselines recorded under the condition without damage. In this study, a reusable piezoelectric lead zirconate titanate transducer for monitoring corrosion damage on the aluminum plate is introduced, which can be removed from the test specimen and reused with the repeatability of signals. The reusable piezoelectric lead zirconate titanate transducer is bonded on the aluminum plate using the ethylene-acrylic acid copolymer with an aluminum enclosure. A series of experiments are conducted on an aluminum plate, including the investigation for repeatability of signals and the capability of corrosion detection of the designed piezoelectric lead zirconate titanate transducer through the Lamb wave and electromechanical impedance methods. The simulated corrosion defect with the area of 15 × 15 mm2 is detected during experiments. The experimental results confirm that the reusable piezoelectric lead zirconate titanate transducer can effectively evaluate the corrosion damage to plate structure and can be reused many times.

scholarly journals A New Structural Health Monitoring Strategy Based on PZT Sensors and Convolutional Neural Network

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2955 ◽  
Author(s):  
Mario de Oliveira ◽  
Andre Monteiro ◽  
Jozue Vieira Filho
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Convolutional Neural Network ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lead Zirconate ◽  
Industrial Applications ◽  
Electromechanical Impedance ◽  
Structural Health

Preliminaries convolutional neural network (CNN) applications have recently emerged in structural health monitoring (SHM) systems focusing mostly on vibration analysis. However, the SHM literature shows clearly that there is a lack of application regarding the combination of PZT-(lead zirconate titanate) based method and CNN. Likewise, applications using CNN along with the electromechanical impedance (EMI) technique applied to SHM systems are rare. To encourage this combination, an innovative SHM solution through the combination of the EMI-PZT and CNN is presented here. To accomplish this, the EMI signature is split into several parts followed by computing the Euclidean distances among them to form a RGB (red, green and blue) frame. As a result, we introduce a dataset formed from the EMI-PZT signals of 720 frames, encompassing a total of four types of structural conditions for each PZT. In a case study, the CNN-based method was experimentally evaluated using three PZTs glued onto an aluminum plate. The results reveal an effective pattern classification; yielding a 100% hit rate which outperforms other SHM approaches. Furthermore, the method needs only a small dataset for training the CNN, providing several advantages for industrial applications.

An experimental study on piezoelectric energy harvesting from wind and ambient structural vibrations for wireless structural health monitoring

2019 ◽  
Vol 23 (5) ◽  
pp. 1010-1023 ◽  
Author(s):  
Naveet Kaur ◽  
Dasari Mahesh ◽  
Sreenitya Singamsetty
Keyword(s):  
Structural Health Monitoring ◽  
Energy Harvesting ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lead Zirconate ◽  
Piezoelectric Energy Harvesting ◽  
Structural Vibrations ◽  
Ambient Wind ◽  
Piezoelectric Energy ◽  
Zirconate Titanate

Energy harvesting is an emerging technology holding promise of sustainability amid the alarming rate at which the human community is depleting the natural resources to cater its needs. There are several ways of harvesting energy in a renewable fashion such as through solar, wind, hydro-electric, geothermal, and artificial photosynthesis. This study focuses on energy harvesting from wind vibrations and ambient structural vibrations (such as from rail and road bridges) through piezo transducers using the direct piezoelectric effect. First, the potential of the piezoelectric energy harvesting from ambient wind vibrations has been investigated and presented here. Lead zirconate titanate patches have been attached at the fixed end of aluminum rectangular and trapezoidal cantilevers, which have been exposed to varying wind velocity in a lab-size wind tunnel. The effect of perforations and twisting (distortion) on the power generated by the patches under varying wind velocity has also been studied. It has been observed that the power is comparatively higher in rectangular-shaped cantilever than the trapezoidal one. Perforations and shape distortion showed promising result in terms of higher yield. The laboratory experiments have also been extended to the real-life field condition to measure the actual power generated by the lead zirconate titanate patches under the ambient wind vibrations. Next, energy harvesting from the ambient structural vibrations has been done both experimentally and numerically. Four different prototypes have been considered. The power has been measured across the lead zirconate titanate patches individually and in parallel combination. A maximum power output for Prototype 1 to Prototype 4 has been found to be 4.3428, 11.844, 25.97, and 43.12 µW, respectively. Numerical study has also been carried out in ANSYS 14.5 to perform the parametric study to examine the effect of addition of mass at the free end of cantilever. In a nutshell, this article provides a comprehensive study on the effect of various factors on the amount of energy generated by piezoelectric patches under wind and structural vibrations. The energy generated is sufficient for driving low-power-consuming electronics that can further be used for other applications like wireless structural health monitoring, and so on.

scholarly journals A New Structural Health Monitoring Strategy Based on PZT Sensors and Convolutional Neural Network

2018 ◽  
Author(s):  
Mario A. de Oliveira ◽  
Andre V. Monteiro ◽  
Jozue Vieira Filho
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Convolutional Neural Network ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lead Zirconate ◽  
Industrial Applications ◽  
Electromechanical Impedance ◽  
Structural Health

Preliminaries Convolutional Neural Network (CNN) applications have recently emerged in Structural Health Monitoring (SHM) systems focusing mostly on vibration analysis. However, the SHM literature shows clearly that there is a lack of application regarding the combination of PZT (Lead Zirconate Titanate) based method and CNN. Likewise, applications using CNN along with the Electromechanical Impedance (EMI) technique applied to SHM systems are rare. To encourage this combination, an innovative SHM solution through the combination of the EMI-PZT and CNN is presented here. To accomplish this, the EMI signature is split into several parts followed by computing the Euclidean distances among them to form a RGB (red, green and blue) frame. As a result, we introduce a dataset formed from the EMI-PZT signals of 720 frames, encompassing a total of 4 types of structural conditions for each PZT. In a case study, the CNN-based method was experimentally evaluated using three PZTs glued onto an aluminum plate. The results reveal an effective pattern classification; yielding a 100% hit rate which outperforms other SHM approaches. Furthermore, the method needs only a small dataset for training the CNN, providing several advantages for industrial applications.

Acousto-ultrasonics-based health monitoring for nano-engineered composites using a dispersive graphene-networked sensing system

2020 ◽  
pp. 147592172092974
Author(s):  
Yehai Li ◽  
Kai Wang ◽  
Qiang Wang ◽  
Jianwei Yang ◽  
Pengyu Zhou ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lead Zirconate ◽  
Ultrasonic Waves ◽  
Sensing Element ◽  
Engineering Structures ◽  
Practical Applications ◽  
Structural Health ◽  
Sensing System

Sensing is a fundamental yet crucial part of a functional structural health monitoring system. Substantial research has been invested in developing new sensing techniques to enhance sensing efficiency and accuracy. Practical applications of structural health monitoring approaches to real engineering structures require strict criteria for the sensing system (e.g. weight, position, intrusion and endurance), which challenge existing sensing techniques. The boom in nanotechnology has offered promising solutions for the development of new sensing approaches. However, a bottleneck still exists when considering the density of sensors and surface-mounted modality of installation. In this study, graphene nanoparticles are dispersed into a glass fibre/epoxy composite to form a dispersive network sensing system. The piezoresistivity of the graphene-formed network changes locally as a result of the change of inter-nanoparticle distances which triggers the ‘tunnelling effect’ and drives the sensor to respond to propagating elastic waves. Due to the dense graphene network formed within the composite, only a small area is required, functioning as a single sensing element to capture ultrasonic waves. To validate such capability, passive acoustic emission tests and active guided ultrasonic wave tests are performed individually. The graphene-networked sensing system can precisely capture wave signals which contain effective features to identify impact spot or damage location. Integrating passive graphene-formed network and active lead zirconate titanate wafers can form a dense network, capable of fulfilling general structural health monitoring tasks.

Harvesting Vibration Energy for Structural Health Monitoring in Aircraft

2009 ◽  
Vol 413-414 ◽  
pp. 439-446 ◽  
Author(s):  
C.A. Featherston ◽  
Karen M. Holford ◽  
Bea Greaves
Keyword(s):  
Structural Health Monitoring ◽  
Energy Harvesting ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Electrical Energy ◽  
Lead Zirconate ◽  
Body Motion ◽  
Structural Health ◽  
Piezoelectric Energy ◽  
Harvesting Systems

The concept of harvesting energy is not a new one: there has been an interest in this area for around 10 years. Devices typically use either vibration (rigid body motion) or thermal gradients and can harvest sufficient energy to power telemetry, small devices or to charge a battery or capacitance device. However, for the new generation of aircraft, (both fixed wing and rotating) there is now an urgent need to develop energy harvesting systems in order to provide localised power for sensors in structural health monitoring systems (SHM). By implementing SHM, aircraft manufacturers can benefit from improved safety, reduced maintenance and extended aircraft life. The work presented examines the feasibility of designing an energy harvesting system powered by the vibrations of aircraft panels generated in flight. PZT (lead zirconate titanate) harvesters are bonded to an aluminium alloy panel, representative of an aircraft wing panel which is vibrated across a range of amplitudes (up to + 0.2mm) and frequencies (up to 300Hz). By recording voltage and current outputs from each harvester, generated power is calculated which when normalised for area and mass indicates values of up to 7.0 Wm-2 and 2.5Wkg-1 respectively, representing mechanical to electrical energy conversion efficiencies of up to 35% dependant on frequency of vibration. From these values it is estimated that a harvester area of down to 71cm2 or mass of as little as 20g is necessary to meet the current minimum power requirements of SHM systems of 50mW. With predicted reductions in sensor power consumption indicating system power requirements in the order of 0.1-1mW, this work shows that piezoelectric energy harvesting has future potential for powering aerospace SHM systems.

Piezoelectric sensor–based damage progression in concrete through serial/parallel multi-sensing technique

2019 ◽  
Vol 19 (2) ◽  
pp. 339-356 ◽  
Author(s):  
Balamonica K ◽  
Jothi Saravanan T ◽  
Bharathi Priya C ◽  
Gopalakrishnan N
Keyword(s):  
Damage Detection ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Structural Damage ◽  
Data Retrieval ◽  
Lead Zirconate ◽  
Structural Damage Detection ◽  
Retrieval Process ◽  
Zirconate Titanate ◽  
In Series

Structural damage detection using unmanned Structural Health Monitoring techniques is becoming the need of the day with the technologies available presently. Sensors made of Lead Zirconate Titanate materials, due to their simplicity and robustness, are increasingly used as an effective monitoring sensor in Structural Health Monitoring. Continuous monitoring of the structures using Lead Zirconate Titanate sensors often results in a laborious data retrieval process due to the large amount of signal generated. To speed up the data retrieval process, a multi-sensing technique in which the Lead Zirconate Titanate patches are connected in series and parallel is proposed for structural damage detection. The proposed method is validated using an experimental investigation carried out on a reinforced concrete beam embedded with smart Lead Zirconate Titanate sensor units. The beam is subjected to damage, and the location of damage is identified using conductance signatures obtained from patches sensed individually and through multiplexing. This article proposes an effective methodology for selection of patches to be connected in series/parallel to maximise the efficiency of damage detection. Damage quantification using conventional statistical metrics such as root mean square deviation, mean absolute percentage deviation and cross correlations are found to be ineffective in identifying the location of damage from the multiplexed signatures. In turn, dynamic metrics such as moving root mean square deviation, moving mean absolute percentage deviation and moving cross correlation with overlapped moving blocks of data are proposed in the present work and their ability to detect the damage location from multiplexed signatures is discussed.

Durability of Embedded PZTs in Structural Health Monitoring Systems under Cyclic Loading

2014 ◽  
Vol 891-892 ◽  
pp. 1255-1260 ◽  
Author(s):  
Sanghyun Yoo ◽  
Akbar Afaghi Khatibi ◽  
Everson Kandare
Keyword(s):  
Cyclic Loading ◽  
Structural Health Monitoring ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Low Cycle Fatigue ◽  
Maintenance Cost ◽  
Clear Understanding ◽  
Structural Health ◽  
Service Conditions

Structural Health Monitoring (SHM) systems are developed to decrease the maintenance cost and increase the life of engineering structures by fundamentally changing the way structural inspections are performed. However, this important objective can only be achieved through the consistent and predictable performance of a SHM system under different service conditions. The capability of a Piezoelectric lead Zirconate Titanate (PZT)-based SHM system in detecting structural flaws strongly depends on the sensor signals as well as actuator performance. But service conditions can change the behaviour of transducers, raising questions about long term SHM system capability. Although having a clear understanding of the reliable sensor life is important for surface mounted systems, however, this is particularly critical for embedded sensors. This is due to the fact that opportunity for replacement of sensors exists for surface bonded transducers while for the embedded systems, sensor replacement is not straightforward. Therefore, knowledge of the long term behaviour of embedded-SHM systems is critical for their implementation. This paper reports a study on the degradation of embedded PZT transducers under cyclic loadings. Carbon/epoxy laminates with an embedded PZT were subjected to fatigue loading and their performance was monitored using Scanning Laser Vibrometery (SLV). The functionality of PZT transducers under sensing and actuating modes were studied. High and low cycle fatigue tests were performed to establish strain-voltage relationships which can be used to identify critical cyclic loading parameters (number of cycles and R value) under sensing and actuating modes.

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