SlideShare a Scribd company logo
Sensitivity comparison of PVDF and nanocomposite PVDF-
TrFE/ZnO by Pitch Catch measurement
Development and characterization of PVDF nanocomposite for structural
health monitoring
 PVDF poly(vinyledene difluoride)-TrFE(Trifluoroethylene)/ZnO Zinc Oxide
nanocomposite piezo sensor is developed in solvent cast method.
 PVDF-TrFE-3g
 ZnO in two different concentration 10&60wt%
1. PVDF-TrFE pellets dissolved in DMF(dimethyl Formamide) for 30minutes
2. Zinc oxide dispersion in DMF under sonication for 4hours
3. Same zinc oxide solution is then mix with PVDF-TrFE solution
4. Continuous stirring for 10minutes.
5. Cast the prepared solution on a glass mould keep it in furnce at 120degC for
2hours.
Characterization of PVDF-TrFE/ZnO nanocomposite film
 X-ray diffraction for structural study
 Dielectric study
 Sensitivity : pitch catch measurement
X-ray diffraction
Here, peak positions of reflections corresponding to PVDF(110) and
ZnO(101) are marked in the pattern which is matching with the literature
value
Dielectric study
For PVDF permittivity is 16.2
@10kHz, for PVDF-TrFE/ZnO at
10wt% of ZnO Permittivity is
11.22 & for PVDF-TrFE/ZnO at
60wt% of ZnO Permittivity is
5.665.
Piezoelectric coefficient
Sensor Freq
(Hz)
(Hz)
d33(pC/N
)
Permittivity(ε) g33(Vm/N)(g=d/ε)
(Vm/N)
PVDF 100 22 16.2 1.35
10wt%
of ZnO
100 10
11.2
0.89
60wt%
of ZnO
100 15
5.665
2.64
Further, the poled PVDF-TrFE/ZnO nano-composite samples were evaluated for piezoelectric
properties.
1.35
0.89
2.64
0
0.5
1
1.5
2
2.5
3
5 7 9 11 13 15 17
g,VoltageCoefficient(mVm/N)
Permittivity
Above graph says as the g33, sensitivity depends on the permittivity, it says sensitivity is more for the
60wt% ZnO dopant to the PVDF-TrFE, i.e2.64mVm/N at 5.665 permittivity
Pitch catch measurement
i) For the test, in Fig. 1, one aluminum cantilever beam is
used. On the beam one actuator (PZT) and one sensor
(PVDF) is bonded using structural epoxy.
ii) The actuator is connected to one channel of function
generator and also to one channel of CRO. Thus, input to
actuator can be seen on the CRO screen.
iii) The sensor is connected to one channel of CRO. This
channel is selected as a trigger.
Frequency 100-400Hz
Amplitude 10Vpp
Frequency response
 The specimens were excited using two square 13 mm PZT wafers which
were temporary adhered with araldite to the base of the specimen and
actuated out of phase by an 10 Vpp which was sent to the Piezos
through a function generator to drive them between 100 Hz and 15MHz
in first trial. Finally, how the piezos will responds for higher frequency
range has been observed. i.e., from 15Hz,15Kz and 15Mhz
Keeping amplitude constant and varying the frequency from 100 Hz to 400 Hz,
variation in voltage output is observed.
As the frequency increases voltage of nanocomposite sensor starts deteriorating from 7 to 5V and PVDF from
3to2V.
Frequency response of PVDF and Nanocomposite sensor from Hz to Mega
Hertz(MHz) range:
As the frequency increases
from 15 Hz to 15MHz range
amplitude starts decreasing
and voltage peak to peak
reduces 9V to 1 V for
nanocomposite and 4V to
736mV.
What is Structural Health Monitoring (SHM)
“The process of implementing a damage detection and
characterization strategy for aerospace, mechanical
and civil engineering structures”
Not a new concept
•Has been around for several decades
•Advances in electronics made it easier
to implement.
Several non-destructive evaluation (NDE) tools available for
monitoring.
 Health monitoring
Operational Evaluation
Data Feature Extraction
Statistical Models Development
1. Strain gages
2. Inclinometers
3. Displacement transducers
4. Accelerometers
5. Temperature gages
6. Pressure transducers
7. Acoustic sensors
8. Piezometers
9. Laser optical devices
Instrumentation used:
SHM Involves:
• Most of these sensors can be wirelessly connected.
• Technology using solar energy is very common in instrumentation.
• Latest technology even has self powered systems, i.e. no external power required.
Monitoring Metrics
Measure:
 Acceleration
 Strain
 Climatic Conditions
 Curvature
 Displacements
 Load
Identify:
 Corrosion
 Cracking
 Strength
 Tension
 Location of rebar
/delaminations
Damage Detection and Impact Prediction:
Damage detection is a problem of prime interest in aircraft
structures
Aim of current study is to analyze damage detection caused
due to impact on structure and use those observation for
prediction of impact location and energy
This study will be helpful in real-time impact detection in aircraft structures.
Real-time detection will be better than damage detection after failure. This will save lot of
time and also reduce failures caused because of damages occurred in structures.
Methodology:
 Impact of known energy will be made on composite structure at known
location
 Strain developed in structure will be observed with PVDF sensor
 These will be compared with conventional strain gages
 Pattern and profile for strains developed under various energies of
impact will be taken
 These profiles will be used to conversely predict the impact energy and
location based on damage occurred
1. Static Analysis
Proportionality of Response :
PVDF sensor was fixed on composite
plate
Impact was made at a fixed distance
from the sensor with different energies
Corresponding voltage values were
recorded
Impact Position
PVDF Sensor
Results: Energy(J) +ve peak -ve peak Max. of abs
1 1.04188 -1.14113 1.14113
2 1.549449 -1.36849 1.549449
3 2.06722 -1.90539 2.06722
Voltage increased
proportionally with
increase in impact energy
Proportionality factor from
obtained values is
0.463V/J
Direction Dependence and Repeatability:
Impacts were made around
PVDF sensor in a circular path
With same energy, impacts were
made with step of 10°
2trials for 1J energy and one
trial for 2J were conducted
O
b
s
e
r
v
a
t
i
o
n
Angle
Trial 1_1J Trial 2_1J Trial 1_2J
+ve peak -ve peak +ve peak -ve peak +ve peak -ve peak
-90 1.091693 -1.56037 1.132474 -1.52887 1.507252 -2.33628
-80 1.150267 -1.6023 1.041477 -1.34567 2.033199 -2.38395
-70 1.140076 -1.55194 1.029984 -1.75659 1.343843 -2.02198
-60 1.270749 -1.50136 1.027031 -1.09734 1.433522 -1.30784
-50 1.553907 -2.00647 1.020616 -0.86894 1.353675 -1.25856
-40 1.495541 -1.91412 1.385657 -1.58436 1.377144 -1.63372
-30 1.743303 -2.33434 0.771667 -0.83048 1.532751 -2.08906
-20 1.362303 -1.45809 1.344471 -1.47443 1.687561 -1.86865
-10 1.475035 -1.86387 1.460196 -1.95776 1.721271 -2.13295
0 1.004034 -1.41232 1.119668 -1.48516 1.70534 -2.60267
10 1.179591 -1.90361 1.221367 -1.77897 1.20738 -1.7414
20 1.100083 -1.9348 1.256186 -1.66937 1.495461 -2.21248
30 1.182704 -1.80934 0.940167 -1.25182 1.087983 -1.60236
40 1.061459 -1.55429 1.000197 -1.32096 1.112323 -1.43387
50 1.097387 -1.33743 1.032448 -1.23148 1.679943 -2.08662
60 0.942713 -1.33263 0.859171 -1.37734 1.579155 -2.07065
70 1.113512 -1.62083 1.085304 -1.7484 1.681362 -2.69384
80 1.007912 -1.62993 1.141654 -1.74292 1.079625 -1.88151
90 1.92805 -1.6861 1.391464 -1.54187 1.299706 -1.64393
Impact energy : 1J
Impact energy 2J
Results: fit
Trial1
1J
Trial 2
1J
Trial
2J
+ve 1.257 1.119 1.469
-ve 1.685 1.68 1.947
max 1.697 1.46 1.959
Further Approach:
Dynamic (time-domain) analysis of PVDF sensor
Previously-:
PVDF sensor was tested for SHM application
•Static analysis was performed for impacts of known energies
•Repeatability and proportionality was verified for PVDF sensor
•Directional dependence of sensor to impacts was analysed
Further Approach:
 Dynamic (time-domain) analysis of PVDF sensor
2. Dynamic Analysis
Test Set-Up
 The composite plate was fixed with 4 sensors as shown in
schematic figure
 4 strain gauge were also placed at same position for direct
comparison with sensor
 Impacts were made at various location with same energy
is dielectric
constant of material
Working Formulae:
The voltage generated by a piezo-sensor is given by:
where, C is capacitance of material given by:
Sensitivity of material to strain is defined as,
Conversely, strain to the sensor can be calculated as,
‘Y’ is Young’s Modulus of
elasticity
l , b , t represent the length,
breadth & thickness of sensor
resp.
Pre-Calculations:
 4 PVDF sensors of thickness 120µm, 25µm, 50µm and100µm were
taken and applied at respective positions on the test composite plate.
 Using the working formulae the strain developed per unit voltage
generated for the sensors was found to be:
Sensor thickness(µm) ε/V (µstrains)
120 26.7
25 128.4
50 64.24
100
32.12
Observations:
Shown below are responses of PVDF sensors and corresponding strain gauges for impact at centre
of composite plate (245,170).
Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to
sensor1on composite plate (370,230).
Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to
sensor2 on composite plate (125,230).
Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to
sensor3 on composite plate (370,105).
Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to
sensor4 on composite plate (125,105)
Dynamic Analysis:
 Two important features in dynamic response of sensor are response time and relaxation time.
 Since, throughout the experiment responses of sensors were recorded for a single impact
which causes strain to develop in the composite and reduces gradually afterwards.
 The rise time and settling time for strain caused due to impact as measured by strain gauge
and PVDF sensor will be compared here forth.
 Rise time: time taken for sensor output to increase from zero/offset
to maximum, corresponding to strain developed in structure.
 Relaxation time: time taken for settling of sensor output from max.
back to zero/offset (or 0.7of maximum).
 Shown here, is the response of RSG1 and PVDF sensror1 for impact at location 1 (75,175)
 Response time
TrRSG –TrPVDF =0.023sec
 Rise time
 PVDF=17msec
 RSG=61msec
 Settling time
 PVDF=12.36msec
 RSG=33.08msec
*Above values are for PVDF sensor1 and RSG1 at centre impact. Similar results
were obtained in other trials as well for all sensors.
Results:
Frequency Response Analysis
 Cantilever 1 (for RSG and PVDF)
 50cm x 1.8cm x 0.4cm
 Tip distance 4.5cm
Free Vibrations
Schematic of the setup made for comparison of frequency response of
strain gauge and FBG sensor with PVDF sensor
t
b
l
Composite Cantilever
 Cantilever 2 (for FBG and PVDF)
◦ 25cm x 4cm x 0.1cm
◦ Tip distance 4cm
The experiment:
 PVDF sensor and RSG were fixed on a cantilever beam of composite
material.
 The cantilever was forced to free vibrations and responses from RSG
and sensor was recorded.
 The frequency spectra of the two sensors was obtained and
compared.
 On another composite cantilever, PVDF sensor and FBG sensor were
fixed.
 Same procedure was followed for this cantilever as well, for
comparison of FBG and PVDF sensor.
Results:
 Shown here are the
responses for PVDF
sensor and strain gauge
along with and their
respective frequency
spectra for first trial.
Results:
 Shown here are the
responses PVDF sensor
and FBG along with their
respective frequency
spectra for first trial.
Observations:
PVDF & FBG
FBG PVDF
Trial1 18.43 18.33 37.22 50 117.8 135.6
Trial2 18.45 18.24 37.06 50 117.6 135.9
PVDF & RSG
RSG PVDF
Trial1 13.25 82.65 13 83 240
Trial2 13.64 81.82 13 82 239
Trial3 26.76 170.4 26 170 478
Trial4 26.79 26 170 478
Trial5 25 25 170 480
Trial6 25.44 26.67 51.67 168.3 478.3
Conclusions:
 A good agreement was found in frequency spectra of PVDF sensor
and RSGs as well as FBGs for free vibration of composite cantilever.
Conclusion
fit
Trial1
1J
Trial 2
1J
Trial
2J
+ve 1.257 1.119 1.469
-ve 1.685 1.68 1.947
max 1.697 1.46 1.959
Part 1: X-ray diffraction shows at(110) reflection highest peak is 20.-
-- and (101) reflection highest peak is 36.----for ZnO
Dielectric as the dielectric constant increases sensitivity decreases
as shown in the graph no----
Piezo coefficient though piezo coefficient is less for nanocomposites
its sensitivity is high
Frequency response as the frequency increases PVDF is comes in
mV and nano will be in V.
Response time
TrRSG –TrPVDF =23msec
Rise time
PVDF=17msec
RSG=61msec
Settling time
PVDF=12.36msec
RSG=33.08msec
PVDF & FBG
FBG PVDF
Trial1 18.43 18.33 37.22 50 117.8 135.6
Trial2 18.45 18.24 37.06 50 117.6 135.9
PVDF & RSG
RSG PVDF
Trial1 13.25 82.65 13 83 240
Trial2 13.64 81.82 13 82 239
Trial3 26.76 170.4 26 170 478
Trial4 26.79 26 170 478
Trial5 25 25 170 480
Trial6 25.44 26.67 51.67 168.3 478.3
Part 2:
Part 3:
Thank You

More Related Content

What's hot

MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
The Research Council of Norway, IKTPLUSS
 
Ultrasonic Testing (UT)- NDT
Ultrasonic Testing (UT)- NDTUltrasonic Testing (UT)- NDT
Ultrasonic Testing (UT)- NDT
Sukesh O P
 
Semester2FinalPresentation
Semester2FinalPresentationSemester2FinalPresentation
Semester2FinalPresentation
Michael Wilson
 
Intro To Ultrasonics
Intro To UltrasonicsIntro To Ultrasonics
Intro To Ultrasonics
Worley parsons
 
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
Shail Mishra
 
Nd at s best practices for single mode tier i ii testing 01-2011
Nd at s   best practices for single mode tier i  ii testing 01-2011Nd at s   best practices for single mode tier i  ii testing 01-2011
Nd at s best practices for single mode tier i ii testing 01-2011
Dean Murray
 
Handheld Laser Barcode Scanners
Handheld Laser Barcode ScannersHandheld Laser Barcode Scanners
Handheld Laser Barcode Scanners
Premier Farnell
 
Ultrasonic guided waves application on oil and gas pipeline
Ultrasonic guided waves application on oil and gas pipelineUltrasonic guided waves application on oil and gas pipeline
Ultrasonic guided waves application on oil and gas pipeline
Mohammad Javad Ranjbar
 
Nd At S Best Practices For Single Mode Tier I Ii Testing 01 2011
Nd At S   Best Practices For Single Mode Tier I  Ii Testing 01 2011Nd At S   Best Practices For Single Mode Tier I  Ii Testing 01 2011
Nd At S Best Practices For Single Mode Tier I Ii Testing 01 2011
Dean Murray
 
Ch17
Ch17Ch17
App152 en measurement-railroad-rails-laser-profile-sensors
App152 en measurement-railroad-rails-laser-profile-sensorsApp152 en measurement-railroad-rails-laser-profile-sensors
App152 en measurement-railroad-rails-laser-profile-sensors
ISATECK
 
Fiber otdr testing
Fiber otdr testingFiber otdr testing
Fiber otdr testing
bsateeshbsnl
 
Radio frequency mems
Radio frequency memsRadio frequency mems
Radio frequency mems
POLAYYA CHINTADA
 
Electronic Ballast Tester
Electronic Ballast TesterElectronic Ballast Tester
Electronic Ballast Tester
Lisun Group
 
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
IRJET Journal
 
Introduction of Transmission Line Pulse (TLP) Testing for ESD Analysis - De...
Introduction of  Transmission Line Pulse (TLP) Testing for ESD Analysis  - De...Introduction of  Transmission Line Pulse (TLP) Testing for ESD Analysis  - De...
Introduction of Transmission Line Pulse (TLP) Testing for ESD Analysis - De...
Wei Huang
 
Electromagnetic Interference in Automotive and Aerospace
Electromagnetic Interference in Automotive and AerospaceElectromagnetic Interference in Automotive and Aerospace
Electromagnetic Interference in Automotive and Aerospace
Altair
 
Optical Time Domain Reflector
Optical Time Domain ReflectorOptical Time Domain Reflector
Optical Time Domain Reflector
Sameer Kumar Poduru
 
Acoustic emission signatures of electrical discharge machining
Acoustic emission signatures of electrical discharge machiningAcoustic emission signatures of electrical discharge machining
Acoustic emission signatures of electrical discharge machining
koshyp
 
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
LTDH2013
 

What's hot (20)

MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
MEMS Based Reconfigurable RF Systems for SoftwareRadio, Wireless Sensors, and...
 
Ultrasonic Testing (UT)- NDT
Ultrasonic Testing (UT)- NDTUltrasonic Testing (UT)- NDT
Ultrasonic Testing (UT)- NDT
 
Semester2FinalPresentation
Semester2FinalPresentationSemester2FinalPresentation
Semester2FinalPresentation
 
Intro To Ultrasonics
Intro To UltrasonicsIntro To Ultrasonics
Intro To Ultrasonics
 
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
OTDR(OPTICAL TIME DOMAIN REFLECTOMETER)
 
Nd at s best practices for single mode tier i ii testing 01-2011
Nd at s   best practices for single mode tier i  ii testing 01-2011Nd at s   best practices for single mode tier i  ii testing 01-2011
Nd at s best practices for single mode tier i ii testing 01-2011
 
Handheld Laser Barcode Scanners
Handheld Laser Barcode ScannersHandheld Laser Barcode Scanners
Handheld Laser Barcode Scanners
 
Ultrasonic guided waves application on oil and gas pipeline
Ultrasonic guided waves application on oil and gas pipelineUltrasonic guided waves application on oil and gas pipeline
Ultrasonic guided waves application on oil and gas pipeline
 
Nd At S Best Practices For Single Mode Tier I Ii Testing 01 2011
Nd At S   Best Practices For Single Mode Tier I  Ii Testing 01 2011Nd At S   Best Practices For Single Mode Tier I  Ii Testing 01 2011
Nd At S Best Practices For Single Mode Tier I Ii Testing 01 2011
 
Ch17
Ch17Ch17
Ch17
 
App152 en measurement-railroad-rails-laser-profile-sensors
App152 en measurement-railroad-rails-laser-profile-sensorsApp152 en measurement-railroad-rails-laser-profile-sensors
App152 en measurement-railroad-rails-laser-profile-sensors
 
Fiber otdr testing
Fiber otdr testingFiber otdr testing
Fiber otdr testing
 
Radio frequency mems
Radio frequency memsRadio frequency mems
Radio frequency mems
 
Electronic Ballast Tester
Electronic Ballast TesterElectronic Ballast Tester
Electronic Ballast Tester
 
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...
 
Introduction of Transmission Line Pulse (TLP) Testing for ESD Analysis - De...
Introduction of  Transmission Line Pulse (TLP) Testing for ESD Analysis  - De...Introduction of  Transmission Line Pulse (TLP) Testing for ESD Analysis  - De...
Introduction of Transmission Line Pulse (TLP) Testing for ESD Analysis - De...
 
Electromagnetic Interference in Automotive and Aerospace
Electromagnetic Interference in Automotive and AerospaceElectromagnetic Interference in Automotive and Aerospace
Electromagnetic Interference in Automotive and Aerospace
 
Optical Time Domain Reflector
Optical Time Domain ReflectorOptical Time Domain Reflector
Optical Time Domain Reflector
 
Acoustic emission signatures of electrical discharge machining
Acoustic emission signatures of electrical discharge machiningAcoustic emission signatures of electrical discharge machining
Acoustic emission signatures of electrical discharge machining
 
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
Sesión técnica, sala KM 19, Advances in detection and characterisation of met...
 

Viewers also liked

Structural Health Monitoring
Structural Health MonitoringStructural Health Monitoring
Structural Health Monitoring
JNTU
 
Structural Health Monitoring Presentation
Structural Health Monitoring PresentationStructural Health Monitoring Presentation
Structural Health Monitoring Presentation
aileencv
 
Sensor based structural health monitoring of concrete structures
Sensor based structural health monitoring of concrete structuresSensor based structural health monitoring of concrete structures
Sensor based structural health monitoring of concrete structures
Sayed Abulhasan Quadri
 
Smart Sensors for Infrastructure and Structural Health Monitoring
Smart Sensors for Infrastructure and Structural Health MonitoringSmart Sensors for Infrastructure and Structural Health Monitoring
Smart Sensors for Infrastructure and Structural Health Monitoring
Jeffrey Funk
 
SHM (Structural Health Monitoring)
SHM (Structural Health Monitoring)SHM (Structural Health Monitoring)
SHM (Structural Health Monitoring)
Sreekanth G
 
Prsentation on structural health monitoring
Prsentation on structural health monitoringPrsentation on structural health monitoring
Prsentation on structural health monitoring
Lakshmi K N
 
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
Peter Brusilovsky
 
Structural Health Monitoring: The paradigm and the benefits shown in some mon...
Structural Health Monitoring: The paradigm and the benefits shown in some mon...Structural Health Monitoring: The paradigm and the benefits shown in some mon...
Structural Health Monitoring: The paradigm and the benefits shown in some mon...
Full Scale Dynamics
 
wireless sensor network
wireless sensor networkwireless sensor network
wireless sensor network
A. Shamel
 
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping SampleConsumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
Knowmade
 
fan speed control by using temperature sensor
fan speed control by using temperature sensorfan speed control by using temperature sensor
fan speed control by using temperature sensor
Nandeesh Boya
 
Instructions aeon labs door window sensor gen5
Instructions   aeon labs door window sensor gen5Instructions   aeon labs door window sensor gen5
Instructions aeon labs door window sensor gen5
Domotica daVinci
 
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
Yole Developpement
 
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewertenMit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
ifm electronic gmbh
 
DCMS AKCP Product Presentation
DCMS AKCP Product PresentationDCMS AKCP Product Presentation
DCMS AKCP Product Presentation
Fanky Christian
 
8279 in microprocessor
8279 in microprocessor8279 in microprocessor
8279 in microprocessor
Aisu
 
paper presentation _ survey of wireless sensor netwrok
paper presentation _ survey of wireless sensor netwrokpaper presentation _ survey of wireless sensor netwrok
paper presentation _ survey of wireless sensor netwrok
ejbyun77
 
Security in wireless sensor networks
Security in wireless sensor networksSecurity in wireless sensor networks
Security in wireless sensor networks
Piyush Mittal
 
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
Fernando Passold
 
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor SystemsSurface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
Fuentek, LLC
 

Viewers also liked (20)

Structural Health Monitoring
Structural Health MonitoringStructural Health Monitoring
Structural Health Monitoring
 
Structural Health Monitoring Presentation
Structural Health Monitoring PresentationStructural Health Monitoring Presentation
Structural Health Monitoring Presentation
 
Sensor based structural health monitoring of concrete structures
Sensor based structural health monitoring of concrete structuresSensor based structural health monitoring of concrete structures
Sensor based structural health monitoring of concrete structures
 
Smart Sensors for Infrastructure and Structural Health Monitoring
Smart Sensors for Infrastructure and Structural Health MonitoringSmart Sensors for Infrastructure and Structural Health Monitoring
Smart Sensors for Infrastructure and Structural Health Monitoring
 
SHM (Structural Health Monitoring)
SHM (Structural Health Monitoring)SHM (Structural Health Monitoring)
SHM (Structural Health Monitoring)
 
Prsentation on structural health monitoring
Prsentation on structural health monitoringPrsentation on structural health monitoring
Prsentation on structural health monitoring
 
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
 
Structural Health Monitoring: The paradigm and the benefits shown in some mon...
Structural Health Monitoring: The paradigm and the benefits shown in some mon...Structural Health Monitoring: The paradigm and the benefits shown in some mon...
Structural Health Monitoring: The paradigm and the benefits shown in some mon...
 
wireless sensor network
wireless sensor networkwireless sensor network
wireless sensor network
 
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping SampleConsumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping Sample
 
fan speed control by using temperature sensor
fan speed control by using temperature sensorfan speed control by using temperature sensor
fan speed control by using temperature sensor
 
Instructions aeon labs door window sensor gen5
Instructions   aeon labs door window sensor gen5Instructions   aeon labs door window sensor gen5
Instructions aeon labs door window sensor gen5
 
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
SCiO Molecular Sensor from Consumer Physics: Mobile Spectrometer Dongle - tea...
 
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewertenMit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
Mit Vision-Sensoren Objekte und Szenarien erkennen und bewerten
 
DCMS AKCP Product Presentation
DCMS AKCP Product PresentationDCMS AKCP Product Presentation
DCMS AKCP Product Presentation
 
8279 in microprocessor
8279 in microprocessor8279 in microprocessor
8279 in microprocessor
 
paper presentation _ survey of wireless sensor netwrok
paper presentation _ survey of wireless sensor netwrokpaper presentation _ survey of wireless sensor netwrok
paper presentation _ survey of wireless sensor netwrok
 
Security in wireless sensor networks
Security in wireless sensor networksSecurity in wireless sensor networks
Security in wireless sensor networks
 
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
Programação de Kits Lego NXT usando Linguagem Gráfica Nativa (ou NXT-G)
 
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor SystemsSurface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
Surface Acoustic Wave (SAW) Wireless Passive RF Sensor Systems
 

Similar to Structural health monitoring

Measurement of VoD of explosives.pptx
Measurement of VoD of explosives.pptxMeasurement of VoD of explosives.pptx
Measurement of VoD of explosives.pptx
Dr Romil Mishra
 
Validation of IR instrument
Validation of IR instrumentValidation of IR instrument
Validation of IR instrument
Santhosh Kalakar dj
 
Valve_Spring_Fault_Detection_Final_1.pdf
Valve_Spring_Fault_Detection_Final_1.pdfValve_Spring_Fault_Detection_Final_1.pdf
Valve_Spring_Fault_Detection_Final_1.pdf
andreikeino1
 
TENSILE TEST REPORT
TENSILE TEST REPORTTENSILE TEST REPORT
TENSILE TEST REPORT
musadoto
 
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
IRJET Journal
 
Modeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
Modeling, Simulation and Design of a Circular Diaphragm Pressure SensorModeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
Modeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
khalil fathi
 
strain measurement
strain measurement strain measurement
strain measurement
SagnikChakraborty22
 
5862792.ppt
5862792.ppt5862792.ppt
5862792.ppt
ssuser2cd740
 
Behavior of Ultrasound Energy in the Presence of Obstacle
Behavior of Ultrasound Energy in the Presence of ObstacleBehavior of Ultrasound Energy in the Presence of Obstacle
Behavior of Ultrasound Energy in the Presence of Obstacle
IRJET Journal
 
Ir spectroscopy
Ir spectroscopyIr spectroscopy
UV-VIS SPECTRO final.ppt
UV-VIS SPECTRO final.pptUV-VIS SPECTRO final.ppt
UV-VIS SPECTRO final.ppt
Jgdishrathi
 
Session 10 radiation survey of a clinical installation
Session 10 radiation survey of a clinical installationSession 10 radiation survey of a clinical installation
Session 10 radiation survey of a clinical installation
Centro Nacional de Radioterapia Nora Astorga
 
PRESENTATION ESA.pptx
PRESENTATION ESA.pptxPRESENTATION ESA.pptx
PRESENTATION ESA.pptx
Chandu794921
 
Commissioning of Truebeam LINAC
Commissioning of Truebeam LINACCommissioning of Truebeam LINAC
Commissioning of Truebeam LINAC
VIneeth C
 
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
IRJET Journal
 
Acoustic Emission testing
Acoustic Emission testingAcoustic Emission testing
Nvh(vibration measurement technic and control)
Nvh(vibration measurement technic and control)Nvh(vibration measurement technic and control)
Nvh(vibration measurement technic and control)
MilanKundalia
 
IEEE paper Peizo_published
IEEE paper Peizo_publishedIEEE paper Peizo_published
IEEE paper Peizo_published
Prashant Singh Sengar
 
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdf
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdfCase Studies from 25 Years of Troubleshooting Vibration Problems.pdf
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdf
ssuser75ec351
 
Experimental Physics Final Oral Presentation Microwave
Experimental Physics Final Oral Presentation MicrowaveExperimental Physics Final Oral Presentation Microwave
Experimental Physics Final Oral Presentation Microwave
sylue200493
 

Similar to Structural health monitoring (20)

Measurement of VoD of explosives.pptx
Measurement of VoD of explosives.pptxMeasurement of VoD of explosives.pptx
Measurement of VoD of explosives.pptx
 
Validation of IR instrument
Validation of IR instrumentValidation of IR instrument
Validation of IR instrument
 
Valve_Spring_Fault_Detection_Final_1.pdf
Valve_Spring_Fault_Detection_Final_1.pdfValve_Spring_Fault_Detection_Final_1.pdf
Valve_Spring_Fault_Detection_Final_1.pdf
 
TENSILE TEST REPORT
TENSILE TEST REPORTTENSILE TEST REPORT
TENSILE TEST REPORT
 
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
IRJET- A Review on Boiler Tube Assessment in Power Plant using Ultrasonic Tes...
 
Modeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
Modeling, Simulation and Design of a Circular Diaphragm Pressure SensorModeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
Modeling, Simulation and Design of a Circular Diaphragm Pressure Sensor
 
strain measurement
strain measurement strain measurement
strain measurement
 
5862792.ppt
5862792.ppt5862792.ppt
5862792.ppt
 
Behavior of Ultrasound Energy in the Presence of Obstacle
Behavior of Ultrasound Energy in the Presence of ObstacleBehavior of Ultrasound Energy in the Presence of Obstacle
Behavior of Ultrasound Energy in the Presence of Obstacle
 
Ir spectroscopy
Ir spectroscopyIr spectroscopy
Ir spectroscopy
 
UV-VIS SPECTRO final.ppt
UV-VIS SPECTRO final.pptUV-VIS SPECTRO final.ppt
UV-VIS SPECTRO final.ppt
 
Session 10 radiation survey of a clinical installation
Session 10 radiation survey of a clinical installationSession 10 radiation survey of a clinical installation
Session 10 radiation survey of a clinical installation
 
PRESENTATION ESA.pptx
PRESENTATION ESA.pptxPRESENTATION ESA.pptx
PRESENTATION ESA.pptx
 
Commissioning of Truebeam LINAC
Commissioning of Truebeam LINACCommissioning of Truebeam LINAC
Commissioning of Truebeam LINAC
 
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
Finite Element Analysis of MEMS based Piezoresistive Diamond Thin Film Cantil...
 
Acoustic Emission testing
Acoustic Emission testingAcoustic Emission testing
Acoustic Emission testing
 
Nvh(vibration measurement technic and control)
Nvh(vibration measurement technic and control)Nvh(vibration measurement technic and control)
Nvh(vibration measurement technic and control)
 
IEEE paper Peizo_published
IEEE paper Peizo_publishedIEEE paper Peizo_published
IEEE paper Peizo_published
 
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdf
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdfCase Studies from 25 Years of Troubleshooting Vibration Problems.pdf
Case Studies from 25 Years of Troubleshooting Vibration Problems.pdf
 
Experimental Physics Final Oral Presentation Microwave
Experimental Physics Final Oral Presentation MicrowaveExperimental Physics Final Oral Presentation Microwave
Experimental Physics Final Oral Presentation Microwave
 

Recently uploaded

Wearable antenna for antenna applications
Wearable antenna for antenna applicationsWearable antenna for antenna applications
Wearable antenna for antenna applications
Madhumitha Jayaram
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Victor Morales
 
digital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdfdigital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdf
drwaing
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
MIGUELANGEL966976
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
gerogepatton
 
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSA SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
IJNSA Journal
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
jpsjournal1
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
IJECEIAES
 
Heat Resistant Concrete Presentation ppt
Heat Resistant Concrete Presentation pptHeat Resistant Concrete Presentation ppt
Heat Resistant Concrete Presentation ppt
mamunhossenbd75
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
nooriasukmaningtyas
 
sieving analysis and results interpretation
sieving analysis and results interpretationsieving analysis and results interpretation
sieving analysis and results interpretation
ssuser36d3051
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
KrishnaveniKrishnara1
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
gerogepatton
 
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
Mukeshwaran Balu
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
kandramariana6
 
Literature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptxLiterature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptx
Dr Ramhari Poudyal
 
Recycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part IIIRecycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part III
Aditya Rajan Patra
 

Recently uploaded (20)

Wearable antenna for antenna applications
Wearable antenna for antenna applicationsWearable antenna for antenna applications
Wearable antenna for antenna applications
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
 
digital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdfdigital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdf
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
 
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSA SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
 
Heat Resistant Concrete Presentation ppt
Heat Resistant Concrete Presentation pptHeat Resistant Concrete Presentation ppt
Heat Resistant Concrete Presentation ppt
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
 
sieving analysis and results interpretation
sieving analysis and results interpretationsieving analysis and results interpretation
sieving analysis and results interpretation
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
 
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
 
Literature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptxLiterature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptx
 
Recycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part IIIRecycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part III
 

Structural health monitoring

  • 1.
  • 2. Sensitivity comparison of PVDF and nanocomposite PVDF- TrFE/ZnO by Pitch Catch measurement
  • 3. Development and characterization of PVDF nanocomposite for structural health monitoring  PVDF poly(vinyledene difluoride)-TrFE(Trifluoroethylene)/ZnO Zinc Oxide nanocomposite piezo sensor is developed in solvent cast method.  PVDF-TrFE-3g  ZnO in two different concentration 10&60wt% 1. PVDF-TrFE pellets dissolved in DMF(dimethyl Formamide) for 30minutes 2. Zinc oxide dispersion in DMF under sonication for 4hours 3. Same zinc oxide solution is then mix with PVDF-TrFE solution 4. Continuous stirring for 10minutes. 5. Cast the prepared solution on a glass mould keep it in furnce at 120degC for 2hours.
  • 4. Characterization of PVDF-TrFE/ZnO nanocomposite film  X-ray diffraction for structural study  Dielectric study  Sensitivity : pitch catch measurement
  • 5. X-ray diffraction Here, peak positions of reflections corresponding to PVDF(110) and ZnO(101) are marked in the pattern which is matching with the literature value
  • 6. Dielectric study For PVDF permittivity is 16.2 @10kHz, for PVDF-TrFE/ZnO at 10wt% of ZnO Permittivity is 11.22 & for PVDF-TrFE/ZnO at 60wt% of ZnO Permittivity is 5.665.
  • 7. Piezoelectric coefficient Sensor Freq (Hz) (Hz) d33(pC/N ) Permittivity(ε) g33(Vm/N)(g=d/ε) (Vm/N) PVDF 100 22 16.2 1.35 10wt% of ZnO 100 10 11.2 0.89 60wt% of ZnO 100 15 5.665 2.64 Further, the poled PVDF-TrFE/ZnO nano-composite samples were evaluated for piezoelectric properties. 1.35 0.89 2.64 0 0.5 1 1.5 2 2.5 3 5 7 9 11 13 15 17 g,VoltageCoefficient(mVm/N) Permittivity Above graph says as the g33, sensitivity depends on the permittivity, it says sensitivity is more for the 60wt% ZnO dopant to the PVDF-TrFE, i.e2.64mVm/N at 5.665 permittivity
  • 8. Pitch catch measurement i) For the test, in Fig. 1, one aluminum cantilever beam is used. On the beam one actuator (PZT) and one sensor (PVDF) is bonded using structural epoxy. ii) The actuator is connected to one channel of function generator and also to one channel of CRO. Thus, input to actuator can be seen on the CRO screen. iii) The sensor is connected to one channel of CRO. This channel is selected as a trigger. Frequency 100-400Hz Amplitude 10Vpp
  • 9. Frequency response  The specimens were excited using two square 13 mm PZT wafers which were temporary adhered with araldite to the base of the specimen and actuated out of phase by an 10 Vpp which was sent to the Piezos through a function generator to drive them between 100 Hz and 15MHz in first trial. Finally, how the piezos will responds for higher frequency range has been observed. i.e., from 15Hz,15Kz and 15Mhz
  • 10. Keeping amplitude constant and varying the frequency from 100 Hz to 400 Hz, variation in voltage output is observed. As the frequency increases voltage of nanocomposite sensor starts deteriorating from 7 to 5V and PVDF from 3to2V.
  • 11. Frequency response of PVDF and Nanocomposite sensor from Hz to Mega Hertz(MHz) range: As the frequency increases from 15 Hz to 15MHz range amplitude starts decreasing and voltage peak to peak reduces 9V to 1 V for nanocomposite and 4V to 736mV.
  • 12.
  • 13. What is Structural Health Monitoring (SHM) “The process of implementing a damage detection and characterization strategy for aerospace, mechanical and civil engineering structures” Not a new concept •Has been around for several decades •Advances in electronics made it easier to implement. Several non-destructive evaluation (NDE) tools available for monitoring.
  • 14.  Health monitoring Operational Evaluation Data Feature Extraction Statistical Models Development 1. Strain gages 2. Inclinometers 3. Displacement transducers 4. Accelerometers 5. Temperature gages 6. Pressure transducers 7. Acoustic sensors 8. Piezometers 9. Laser optical devices Instrumentation used: SHM Involves: • Most of these sensors can be wirelessly connected. • Technology using solar energy is very common in instrumentation. • Latest technology even has self powered systems, i.e. no external power required.
  • 15. Monitoring Metrics Measure:  Acceleration  Strain  Climatic Conditions  Curvature  Displacements  Load Identify:  Corrosion  Cracking  Strength  Tension  Location of rebar /delaminations
  • 16. Damage Detection and Impact Prediction: Damage detection is a problem of prime interest in aircraft structures Aim of current study is to analyze damage detection caused due to impact on structure and use those observation for prediction of impact location and energy This study will be helpful in real-time impact detection in aircraft structures. Real-time detection will be better than damage detection after failure. This will save lot of time and also reduce failures caused because of damages occurred in structures.
  • 17. Methodology:  Impact of known energy will be made on composite structure at known location  Strain developed in structure will be observed with PVDF sensor  These will be compared with conventional strain gages  Pattern and profile for strains developed under various energies of impact will be taken  These profiles will be used to conversely predict the impact energy and location based on damage occurred
  • 19. Proportionality of Response : PVDF sensor was fixed on composite plate Impact was made at a fixed distance from the sensor with different energies Corresponding voltage values were recorded Impact Position PVDF Sensor
  • 20. Results: Energy(J) +ve peak -ve peak Max. of abs 1 1.04188 -1.14113 1.14113 2 1.549449 -1.36849 1.549449 3 2.06722 -1.90539 2.06722 Voltage increased proportionally with increase in impact energy Proportionality factor from obtained values is 0.463V/J
  • 21. Direction Dependence and Repeatability: Impacts were made around PVDF sensor in a circular path With same energy, impacts were made with step of 10° 2trials for 1J energy and one trial for 2J were conducted
  • 22. O b s e r v a t i o n Angle Trial 1_1J Trial 2_1J Trial 1_2J +ve peak -ve peak +ve peak -ve peak +ve peak -ve peak -90 1.091693 -1.56037 1.132474 -1.52887 1.507252 -2.33628 -80 1.150267 -1.6023 1.041477 -1.34567 2.033199 -2.38395 -70 1.140076 -1.55194 1.029984 -1.75659 1.343843 -2.02198 -60 1.270749 -1.50136 1.027031 -1.09734 1.433522 -1.30784 -50 1.553907 -2.00647 1.020616 -0.86894 1.353675 -1.25856 -40 1.495541 -1.91412 1.385657 -1.58436 1.377144 -1.63372 -30 1.743303 -2.33434 0.771667 -0.83048 1.532751 -2.08906 -20 1.362303 -1.45809 1.344471 -1.47443 1.687561 -1.86865 -10 1.475035 -1.86387 1.460196 -1.95776 1.721271 -2.13295 0 1.004034 -1.41232 1.119668 -1.48516 1.70534 -2.60267 10 1.179591 -1.90361 1.221367 -1.77897 1.20738 -1.7414 20 1.100083 -1.9348 1.256186 -1.66937 1.495461 -2.21248 30 1.182704 -1.80934 0.940167 -1.25182 1.087983 -1.60236 40 1.061459 -1.55429 1.000197 -1.32096 1.112323 -1.43387 50 1.097387 -1.33743 1.032448 -1.23148 1.679943 -2.08662 60 0.942713 -1.33263 0.859171 -1.37734 1.579155 -2.07065 70 1.113512 -1.62083 1.085304 -1.7484 1.681362 -2.69384 80 1.007912 -1.62993 1.141654 -1.74292 1.079625 -1.88151 90 1.92805 -1.6861 1.391464 -1.54187 1.299706 -1.64393
  • 25. Results: fit Trial1 1J Trial 2 1J Trial 2J +ve 1.257 1.119 1.469 -ve 1.685 1.68 1.947 max 1.697 1.46 1.959 Further Approach: Dynamic (time-domain) analysis of PVDF sensor
  • 26.
  • 27. Previously-: PVDF sensor was tested for SHM application •Static analysis was performed for impacts of known energies •Repeatability and proportionality was verified for PVDF sensor •Directional dependence of sensor to impacts was analysed Further Approach:  Dynamic (time-domain) analysis of PVDF sensor
  • 29. Test Set-Up  The composite plate was fixed with 4 sensors as shown in schematic figure  4 strain gauge were also placed at same position for direct comparison with sensor  Impacts were made at various location with same energy
  • 30. is dielectric constant of material Working Formulae: The voltage generated by a piezo-sensor is given by: where, C is capacitance of material given by: Sensitivity of material to strain is defined as, Conversely, strain to the sensor can be calculated as, ‘Y’ is Young’s Modulus of elasticity l , b , t represent the length, breadth & thickness of sensor resp.
  • 31. Pre-Calculations:  4 PVDF sensors of thickness 120µm, 25µm, 50µm and100µm were taken and applied at respective positions on the test composite plate.  Using the working formulae the strain developed per unit voltage generated for the sensors was found to be: Sensor thickness(µm) ε/V (µstrains) 120 26.7 25 128.4 50 64.24 100 32.12
  • 33. Shown below are responses of PVDF sensors and corresponding strain gauges for impact at centre of composite plate (245,170).
  • 34. Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to sensor1on composite plate (370,230).
  • 35. Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to sensor2 on composite plate (125,230).
  • 36. Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to sensor3 on composite plate (370,105).
  • 37. Shown below are responses of PVDF sensors and corresponding strain gauges for impact near to sensor4 on composite plate (125,105)
  • 38. Dynamic Analysis:  Two important features in dynamic response of sensor are response time and relaxation time.  Since, throughout the experiment responses of sensors were recorded for a single impact which causes strain to develop in the composite and reduces gradually afterwards.  The rise time and settling time for strain caused due to impact as measured by strain gauge and PVDF sensor will be compared here forth.  Rise time: time taken for sensor output to increase from zero/offset to maximum, corresponding to strain developed in structure.  Relaxation time: time taken for settling of sensor output from max. back to zero/offset (or 0.7of maximum).
  • 39.  Shown here, is the response of RSG1 and PVDF sensror1 for impact at location 1 (75,175)
  • 40.  Response time TrRSG –TrPVDF =0.023sec  Rise time  PVDF=17msec  RSG=61msec  Settling time  PVDF=12.36msec  RSG=33.08msec *Above values are for PVDF sensor1 and RSG1 at centre impact. Similar results were obtained in other trials as well for all sensors. Results:
  • 42.  Cantilever 1 (for RSG and PVDF)  50cm x 1.8cm x 0.4cm  Tip distance 4.5cm Free Vibrations Schematic of the setup made for comparison of frequency response of strain gauge and FBG sensor with PVDF sensor t b l Composite Cantilever  Cantilever 2 (for FBG and PVDF) ◦ 25cm x 4cm x 0.1cm ◦ Tip distance 4cm
  • 43. The experiment:  PVDF sensor and RSG were fixed on a cantilever beam of composite material.  The cantilever was forced to free vibrations and responses from RSG and sensor was recorded.  The frequency spectra of the two sensors was obtained and compared.  On another composite cantilever, PVDF sensor and FBG sensor were fixed.  Same procedure was followed for this cantilever as well, for comparison of FBG and PVDF sensor.
  • 44. Results:  Shown here are the responses for PVDF sensor and strain gauge along with and their respective frequency spectra for first trial.
  • 45. Results:  Shown here are the responses PVDF sensor and FBG along with their respective frequency spectra for first trial.
  • 46. Observations: PVDF & FBG FBG PVDF Trial1 18.43 18.33 37.22 50 117.8 135.6 Trial2 18.45 18.24 37.06 50 117.6 135.9 PVDF & RSG RSG PVDF Trial1 13.25 82.65 13 83 240 Trial2 13.64 81.82 13 82 239 Trial3 26.76 170.4 26 170 478 Trial4 26.79 26 170 478 Trial5 25 25 170 480 Trial6 25.44 26.67 51.67 168.3 478.3
  • 47. Conclusions:  A good agreement was found in frequency spectra of PVDF sensor and RSGs as well as FBGs for free vibration of composite cantilever.
  • 48. Conclusion fit Trial1 1J Trial 2 1J Trial 2J +ve 1.257 1.119 1.469 -ve 1.685 1.68 1.947 max 1.697 1.46 1.959 Part 1: X-ray diffraction shows at(110) reflection highest peak is 20.- -- and (101) reflection highest peak is 36.----for ZnO Dielectric as the dielectric constant increases sensitivity decreases as shown in the graph no---- Piezo coefficient though piezo coefficient is less for nanocomposites its sensitivity is high Frequency response as the frequency increases PVDF is comes in mV and nano will be in V. Response time TrRSG –TrPVDF =23msec Rise time PVDF=17msec RSG=61msec Settling time PVDF=12.36msec RSG=33.08msec PVDF & FBG FBG PVDF Trial1 18.43 18.33 37.22 50 117.8 135.6 Trial2 18.45 18.24 37.06 50 117.6 135.9 PVDF & RSG RSG PVDF Trial1 13.25 82.65 13 83 240 Trial2 13.64 81.82 13 82 239 Trial3 26.76 170.4 26 170 478 Trial4 26.79 26 170 478 Trial5 25 25 170 480 Trial6 25.44 26.67 51.67 168.3 478.3 Part 2: Part 3:

Editor's Notes

  1. XRD measurements were carried out in order to study the crystal structure of Zno thin films.
  2. The permittivity is a measure of how much the molecules oppose the external E-field
  3. Resistive strain guage