Статьи на перевод PVDF_P(VDF-TrFE) / 2012-Dodds,J-Thesis (Development of Piezoelectric Zinc Oxide Nanoparticle-Poly(Vinylidene Fluoride))

List of Equations

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Nomenclature

AC: Alternating current

Al: Aluminum

DC: Direct current

DI: Deionized

EMI: Electromagnetic interference

FBG: Fiber Bragg grating

FRP: Fiber-reinforced polymer

IDT: Inter-digital transducer

MEK: Methyl ethyl ketone

MFC: Macro fiber composite

PVC: Polyvinyl chloride

PVDF: Poly(vinylidene fluoride)

PVDF-TrFE: Poly(vinylidene Fluoride)-Trifluoroethylene PZT: Lead zirconate titanate

RMSD: Root-mean-square deviation

SEM: Scanning electron microscope/microscopy SHM: Structural health monitoring

SNR: Signal to noise ratio

ZnO: Zinc Oxide

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Chapter 1: Introduction

1.1 Structural Health Monitoring Motivation

Damage to civil infrastructure systems, such as fatigue, corrosion, impact, scour, and extreme loading, pose a severe economic burden for society, lead to catastrophic structural failures, and jeopardize public safety. The knowledge of the health of a structure prior to escalating to catastrophic failure is invaluable for saving lives and money. With the American Society of Civil Engineers giving America’s infrastructure an overall D grade in 2009 and the average bridge age in the United States standing at above 50 years [1, 2], there is an urgent need for assessing structural safety so that priorities can be set for retrofit and replacement of existing structures, as well as for ensuring proper techniques to efficiently and effectively monitor new structures.

Implementation of robust and effective SHM systems could have prevented a number of significant structural disasters. A stark example of damage-induced structural failure is the collapse and falling of the Seongsu Bridge in Seoul, Korea, where deficient welds and structural connections led to the deaths of 32 people and injuries to 17 [3]. Another example is the failure and collapse of the Lakeview Drive Bridge onto Interstate70 in South Strabane, Pennsylvania (2005). Post-failure analysis has found that cracks in the bridge superstructure allowed deicing salt and water to penetrate and corrode the reinforced-concrete structure’s steel reinforcement bars, ultimately causing its collapse

[4]. In 2009, a ~1.5 in (4 cm) long structural crack was identified in an eyebar in the Interstate-80 San Francisco-Oakland Bay Bridge. The severity of damage and the need for immediate repairs caused the Bay Bridge to be closed for five days, which

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subsequently impacted traffic, local businesses, and the surrounding communities [5]. More recently in 2010, a pipeline in San Bruno, California, ruptured due to outdated and poor welding, combined with a spike in pipeline pressure [6]. In fact, numerous other catastrophic events have occurred in the past, but most civil infrastructures today still rely on time-, labor-, and cost-intensive visual inspection practices for assessing structural performance and damage. Similarly, airplane disasters, such as in 1988 when an Aloha Airlines airplane ripped apart in mid-flight due to stress corrosion cracks, have demonstrated that even a piece of equipment as valuable as an airplane does not always receive adequate structural monitoring [7]. These structural failures and their associated adverse societal impacts could have been prevented or mitigated if a more robust SHM system had been in place.

Currently, there are many ways to monitor the health of a structure, each with its own advantages and disadvantages. The trade-offs between cost and performance of monitoring systems are evaluated in Chapter 2. This thesis finds that piezoelectric composite materials offer an SHM solution that can be affordable while still remaining effective.

1.2 Thesis Goal and Outline

The goal of this study is to characterize the piezoelectric sensing and actuation performance of spin-coated poly(vinylidene fluoride)-trifluoroethylene/Zinc Oxide (PVDFTrFE/ZnO) thin films for eventual use in SHM. This piezoelectric thin film acts as a transducer (in this case as an actuator and a sensor) similar to PVDF, but with enhanced piezoelectricity. Those enhanced properties come from the integration of piezoelectric

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ZnO nanoparticles within the nanocomposite’s PVDF-TrFE matrix (which is also piezoelectric). Sensing and actuation properties are validated, and guided wave-based SHM is also demonstrated.

The outline of this thesis is as follows. Chapter 2 presents a general overview of SHM to introduce this field of study. Next, the fabrication procedure and characterization of the piezoelectric nanocomposites is presented in Chapter 3. A total of five unique sample sets of varying ZnO concentrations (i.e., ranging from 0 to 20 wt.% in 5 wt.% increments) have been fabricated. Second, thin film remnant polarization has been quantified by subjecting films to high-voltage alternating current (AC) excitations for obtaining their electric polarization-to-electric field hysteresis responses. The aforementioned ferroelectric characterization study and subsequent high-voltage poling process for enhancing piezoelectricity is also discussed in Chapter 3. Next in Chapter 4, the sensing performance of nanocomposites fabricated using different ZnO concentrations has been investigated. Chapter 4 compares thin film sensing response using voltage time history results obtained from hammer impact tests. The PVDF-

TrFE/ZnO thin films’ performances have also been compared to results from commercially poled PVDF-TrFE specimens. Free vibration tests, where specimens have been mounted onto a flexible cantilever beam and excited, have also been used as validation for dynamic strain sensing. Finally, Chapter 5 showcases how these piezoelectric thin films can be used as actuators for damage detection and SHM. Here, a new method of film fabrication is explained. Actuation testing using a pitch-catch methodology is explored, and time domain results have been acquired to demonstrate the films’ potential for damage detection.

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Chapter 2: A Review of Structural Health Monitoring

2.1 Introduction

Structural health monitoring can be defined as a methodology capable of monitoring the performance of structures throughout their operational service lifetime, while being able to identify various types and severities of damage incurred in a structure [8]. SHM should go through the four basic steps of operational evaluation, data acquisition, feature selection and information condensation, and statistical model development for feature discrimination [9]. Structures are evaluated from the most basic level of damage presence, up to damage location, damage nature, damage extent, and finally to entire structural prognosis.

2.2 Structural Health Monitoring Solutions

Currently the field of SHM is dominated (in actual implementation) by simplistic solutions that do not obtain enough structural health information. For example, visual inspection is often performed because it requires no special equipment [10]. However, this type of inspection requires an expert or trained engineer present at the possible damage location, which is difficult and expensive for both geographically remote structures and for difficult-to-reach locations within structures. Visual inspection cannot detect hairline cracks or the internal state of a structure. Setting standards for visual inspections is difficult, given the wide variety of inspector experience (e.g., structural knowledge, eyesight, and time pressure) and the wide variety of structures in service. In a particular study looking at visual bridge evaluation, bridges were more likely to be

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rated as adequate, rather than with “low” or “high” condition ratings. It was hypothesized that these ratings did not reflect the actual state of the bridges, but rather that inspectors did not want to give extreme ratings and cause alarm [10]. In addition to visual inspection, some bridge inspections also use techniques such as chain-dragging, where the changing sound of a chain dragged over a bridge deck provides key structural health information. These techniques are all somewhat inherently subjective and provide a limited assessment of the inspected structure [11].

Due to the limitations of visual inspection and other current SHM methods, significant research related to sensor development, damage detection algorithms, and SHM methodologies has been conducted over the last several decades. One example of SHM in action today involves fiber optics and fiber Bragg grating (FBG) sensors. FBGs use measurements of changes in optical signals traveling in fibers to measure thermal or mechanical strain in a structure [11]. They have been used for distributed structural sensing in laboratory and field applications [12]. They are effective at distributed strain detection in the line of the optical fiber and have the advantages of being lightweight, requiring no power at the point of sensing, and not being affected by electromagnetic interference (EMI). Moyo et al. [13] have been able to provide a rugged sensing system using FBGs for civil infrastructure systems, specifically highway bridges. They have been able to measure temperature and static and dynamic strains on bridges, as well as measuring curing strength and progress, and measuring temperatures. However, these sensors require many costly channels, which can cost up to $4,000 each [14], to obtain the previously discussed information about the structure under investigation. The sensor also has difficulties differentiating between thermal and mechanical strains.

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Vibration-based methods or modal analysis are another popular SHM technique. The dynamic responses of structures are measured by accelerometers, and system identification techniques are employed for quantifying global vibration modal changes to structural damage or changing environmental conditions [15]. A general damage detection strategy involves measuring the change in resonant frequency of the structure over time. Resonant frequency depends on structural stiffness, and cracks or other damage can decrease stiffness to cause changes in the structure’s natural frequency.

However, significant damage needs to be present in order to cause dramatic changes in resonant frequency. It is also often the case where environmental changes can induce greater resonant frequency shifts as compared to minor damage present in the structure [16]. In addition, a severe limitation of this technique is that accelerometers need to be connected to a centralized data repository using coaxial cables (i.e., for data communications and power supply). Also, wired sensing on the Tsing Ma Bridge cost $8 million for 350 sensing channels [17]. Their high costs have limited the installation to only a few sensors per structure, and these sensors distributed over large spatial domains are poorly collocated with localized structural damage. The end result is that the use of distributed and tethered accelerometers suffers from limited effectiveness and damage detection resolution [17].

Another requirement for performing system identification is that the structure must vibrate in response to some external excitation. Vibration can be induced by various means, either due to the structure’s interaction with the environment (e.g., traffic or wind loads acting on a bridge) [18] or due to a deliberate manmade excitations (e.g., impact hammer or structural shaker) [19]. Both strategies have been used for vibrationbased structural monitoring. In fact, the two different strategies can also be thought of as

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two different time scales in which vibration testing can be conducted, namely, forceinduced short-term monitoring and long-term ambient vibrations. Overall, vibration methods are a useful tool for SHM but have difficulty detecting specific damage within structures, as mentioned earlier. For example, accelerometers have tracked the floor displacements of a test structure or a real building under seismic excitations. Analysis can be performed on these structures based on the known shaking that has occurred. For example, Ulusoy et al. [18] have used data generated by 31 sensors installed in a reinforced-concrete building in Irvine, California, subjected to four California earthquakes to perform damage identification.

To overcome the limitations and high costs of tethered sensors, wireless sensors and sensor networks have been developed for densely distributed SHM [17]. Wireless sensors do not depend on expensive coaxial cables for data communications and power delivery. They are low cost, possess distributed computational capabilities, and are thus more suitable for dense instrumentation [17]. In fact, wireless sensor networks have been employed to measure structural vibrations on a bridge in Osage Beach, MO [20], on a footbridge in Berkeley, CA [21], and on the Ashidagawa Bridge in Japan [22], among others. Specifically, Mascerenas et al. [23] have employed a low-power wireless sensor network for bridge acceleration measurements and have successfully detected bridge excitations due to traffic events. In general, wireless systems are able to be triggered on an as-needed basis, thus saving power [24]. Wireless sensors, however, have problems with synching their information with a centralized clock, have limited storage space for sensor information, and run the risk of losing data when sending information wirelessly [24]. In general, the monitoring methods discussed up to this point have been passive systems that only sense/measure structural responses to ambient

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excitations (e.g., traffic and wind). A structural monitoring system should be autonomous and should ideally be able to interrogate structures on demand. A monitoring solution that provides its own power would also be superior to the methods discussed previously.

Piezoelectric materials offer solutions for many of these problems, including providing some of their own power, being affordable, and being easy to implement. Piezoelectric transducers are active and by nature multifunctional such that they can be used for sensing as well as for actuation and energy harvesting. They can be commanded to actively interrogate structures and measure structural response on demand [25]. Sections 2.3 and 2.4 present a detailed discussion of piezoelectric materials, their theory, and their applications for SHM.

2.3 Piezoelectric Material Theory

Before piezoelectric materials are described for their SHM applications, it is necessary to provide their theoretical background. There are many excellent references for guidance on basic piezoelectric theory, including a comprehensive book by Defaÿ [26], used as one of the primary theoretical references for this thesis. Pierre and Jacques Curie first discovered piezoelectric materials in 1880. Piezoelectric materials work on the principle of charge separation, where asymmetry in the basic crystal structure of a material is required for piezoelectricity. An asymmetric atomic structure responds asymmetrically to stress applied to it. Out of the 32 possible crystal structures, 20 are asymmetric and piezoelectric [26].

One way of looking at a dielectric material is to see it in terms of electric dipoles. Stress applied to asymmetric electric dipoles causes a further separation of charges, as