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Publication Number: FHWA-HRT-12-072
Date: May 2013

 

Smart Pavement Monitoring System

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FOREWORD

This report documents the development of a novel self-powered sensor system for continuous structural health monitoring of new/reconstruction or resurfacing of asphalt and concrete pavements. The system consists of a wireless integrated circuit sensor that consumes less than 1 microwatt of power and interfaces directly with and draws its operational power from a piezoelectric transducer. Each sensor node is self-powered and capable of continuously monitoring and storing the dynamic strain levels in pavement structure. The data from all the sensors are periodically uploaded wirelessly through radio frequency (RF) transmission using a RF reader either manually operated or mounted on a moving vehicle. The integrated wireless sensor can provide many benefits to highway agencies by helping facilitate more effective pavement maintenance and rehabilitation/preservation decision making by detecting possible damage, monitoring mechanical load history, and predicting the fatigue life of the monitored pavements.

Jorge E. Pagán-Ortiz
Director, Office of Infrastructure
Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document. This report does not constitute a standard, specification, or regulation.

 

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

 

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

 

Technical Report Documentation Page

1. Report No.

FHWA-HRT-12-072

2. Government Accession No. 3 Recipient's Catalog No.
4. Title and Subtitle

Smart Pavement Monitoring System

5. Report Date

May 2013

6. Performing Organization Code
7. Author(s)

Nizar Lajnef, Karim Chatti, Shantanu Chakrabartty, Mohamed Rhimi, and Pikul Sarkar

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

Michigan State University
426 Auditorium Road
East Lansing, MI 48824

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH61-08-C-00015

12. Sponsoring Agency Name and Address

Federal Highway Administration
Office of Acquisition Management
1200 New Jersey Avenue SE
Washington, DC 20590

13. Type of Report and Period Covered

Final Report, September 2008–July 2012

14. Sponsoring Agency Code

 

15. Supplementary Notes

The Contracting Officer's Representative (COR) was Fred Faridazar, HRDI-20.

16. Abstract

This report describes the efforts undertaken to develop a novel self-powered strain sensor for continuous structural health monitoring of pavement systems under the Federal Highway Administration. Efforts focused on designing and testing a sensing system that consists of a novel self-powered wireless sensor capable of detecting damage and loading history for pavement structures. The developed system is based on the integration of a piezoelectric transducer with an array of ultra-low power floating gate computational circuits. A miniaturized sensor was developed and tested. The sensor is capable of continuous battery-less monitoring of strain events integrated over the occurrence duration time. The work conducted under this project resulted in the following:

  • The development of a sensor that has the following attributes: (1) Self-powered, continuous, and autonomous sensing; (2) autonomous computation and non-volatile storage of sensing variables; (3) small size such that it can be installed using existing installation procedures that are accepted by State highway agencies and will not constitute a major disruption to current practices; (4) wireless communication to eliminate the need for embedding wires in the pavement structure and the use of fixed data acquisition systems on the side of the road; (5) robustness to withstand harsh loading and environmental conditions during initial construction and throughout the life of the pavement; and (6) the ability of integration in large-scale sensor networks.

  • The manufacturing of the sensor electronics and the characterization of their basic functionalities in a laboratory setting.

  • The design and characterization of the self-powering scheme based on piezoelectric transduction.

  • The design and testing of a robust packaging system to withstand loading and environmental conditions for field implementation.

  • The development of a sensor-specific data interpretation algorithm for predicting remaining fatigue life of a pavement structure using cumulative limited compressed strain data stored in the sensor memory.
17. Key Words

Pavement management, Structural health monitoring, Smart self-powered sensors, Remaining fatigue life prediction

18. Distribution Statement

No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161.

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

146

22. Price

N/A

Form DOT F 1700.7 Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION

CHAPTER 2. SMART SENSING SYSTEM DEVELOPMENT

CHAPTER 3. DEVELOPMENT OF WIRELESS COMMUNICATION AND DATA UPLOAD PROTOCOL

CHAPTER 4. LABORATORY MECHANICAL TESTING OF THE PIEZOELECTRIC TRANSDUCER

CHAPTER 5. DESIGN OF ROBUST PACKAGING SYSTEM AND INITIAL FIELD TRIALS

CHAPTER 6. LABORATORY FATIGUE TESTING AND DEVELOPMENT OF SENSOR-SPECIFIC DAMAGE PROGNOSIS ALGORITHMS

CHAPTER 7. CONCLUSION

APPENDIX A. DEVELOPMENT AND LABORATORY TESTING OF A PASSIVE TEMPERATURE GAUGE

APPENDIX B. INTEGRATION AND LABORATORY TESTING OF WIRELESS PROTOCOL WITH OTHER EXISTING INSTRUMENTATION

APPENDIX C. DATASHEET AND CALIBRATION CERTIFICATE FOR USED COD GAUGE

APPENDIX D. DATASHEET FOR USED LVDTS

REFERENCES

 

LIST OF FIGURES

Figure 1. Illustration. Array of self-powered sensors capable of monitoring cumulative strain history of the host pavement structure

Figure 2. Illustration. Complete circuit implementation of self-powered event counter

Figure 3. Illustration. IIHEI process in a PMOS FG transistor

Figure 4. Illustration. IIHEI using an energy band diagram

Figure 5. Illustration. Concept of piezoelectricity-driven IIHEI

Figure 6. Illustration. Electrical model of an analog FG memory cell

Figure 7. Equation. IIHEI current

Figure 8. Equation. Source current

Figure 9. Equation. FG voltage

Figure 10. Equation. Injection current as a function of the FG voltage

Figure 11. Equation. Differential equation for the source voltage

Figure 12. Equation. System variables

Figure 13. Equation. Source voltage as a function of the cumulative duration of the injection process, t

Figure 14. Photo. Sensor prototype manufactured on a DIP40 packaging system

Figure 15. Photo. Prototype mounted on a testing board and connected to a computer using a parallel port for data upload

Figure 16. Graph. Theoretical and measured results for source voltage response

Figure 17. Equation. Source voltage for short-term monitoring

Figure 18. Equation. Source voltage for long-term monitoring

Figure 19. Equation. Change in source voltage

Figure 20. Graph. Injector response measured at various source currents

Figure 21. Graph. Injector response measured by using eight prototypes fabricated in different runs

Figure 22. Graph. Injector response measured under different temperature conditions

Figure 23. Illustration. Sensor connection package

Figure 24. Photo. Sensor interface board

Figure 25. Illustration. System architecture of the entire sensor

Figure 26. Illustration. Conventional OPAMP-based regulator

Figure 27. Illustration. Diodic current conveyer regulator

Figure 28. Graph. Simulated response for the OPAMP-based regulator

Figure 29. Graph. Simulated response for the diodic regulator

Figure 30. Illustration. Measured results from an OPAMP-based LDO showing potential stability problems

Figure 31. Graph. Measured responses for a fabricated diodic regulator

Figure 32. Graph. Measured responses for a fabricated diodic regulator with a longer diodic chain

Figure 33. Illustration. Piezo-sensor module

Figure 34. Illustration. RF interrogation module on separate silicon substrates/ICs

Figure 35. Illustration. Ultra-linear FG injector circuit

Figure 36. Graph. Measured response of the linear injector circuit showing a dynamic range greater than 4 V and resolution greater than 13 bits

Figure 37. Graph. Measured resolution over a dynamic range of 4 V output

Figure 38. Graph. Measured response from over-voltage protection circuit showing the output clamped to 9 V

Figure 39. Illustration. Principle of HF RFID used in the sensing system

Figure 40. Illustration. Equivalent circuit model for the RFID system and the load modulation scheme for wireless communication

Figure 41. Equation. Input voltage

Figure 42. Illustration. System-level architecture of the wireless communication system for the sensor

Figure 43. Illustration. Architecture of the sensor

Figure 44. Photo. Micrograph of the sensor prototyped in a 0.02-mil (0.5- ) CMOS process

Figure 45. Illustration. Envelope recovery module

Figure 46. Illustration. Output of the envelope recovery module using hysteretic and non-hysteretic comparators when a noisy RF signal is applied

Figure 47. Illustration. Hysteretic comparator used in the improved envelope recovery circuit

Figure 48. Graph. Output of the envelope recovery module using hysteretic and non-hysteretic comparators when a valid ASK modulated RF signal is applied

Figure 49. Illustration. Measured output of the envelope recovery module using hysteretic and non-hysteretic comparators when a valid ASK modulated RF signal is applied

Figure 50. Illustration. Functional architecture of the single-slope ADC

Figure 51. Equation. Residential value in the counter

Figure 52. Graph. Digital output stream produced by the ADC when the input voltage is varied

Figure 53. Illustration. Structure of the Dickson voltage multiplier

Figure 54. Equation. Output voltage

Figure 55. Illustration. Function blocks of the modulator and demodulator

Figure 56. Illustration. Charge pump used for implementing the high-voltage generator

Figure 57. Illustration. Timing diagram of the non-overlapping clock generator

Figure 58. Graph. Sample results from fabricated prototype

Figure 59. Illustration. State machine implemented by DBM

Figure 60. Photo. Manufactured external reader and internal interface board

Figure 61. Photo. Second prototype antenna adapted to the H-shaped gauge

Figure 62. Illustration. Measured results for ASK modulation

Figure 63. Illustration. Close-up view of measured results for ASK modulation

Figure 64. Illustration. Measured results showing the sensor entering an injection state

Figure 65. Illustration. Measured results showing the sensor entering a tunneling state

Figure 66. Illustration. Measured results showing the sensor data received by the reader when it sends an acquire command

Figure 67. Illustration. Measured results showing multi-channel sensor data received by the reader when the sensor is in a continuous sampling state

Figure 68. Photo. Sensor placed under a concrete specimen

Figure 69. Photo. Receiver placed on top of the concrete specimen

Figure 70. Photo. Concrete specimen placed between a reader and receiver

Figure 71. Photo. Test setup with an asphalt concrete (AC) specimen introduced between the reader and the receiver

Figure 72. Photo. Oscilloscope showing the voltage measured at the receiver

Figure 73. Illustration. Communication signals transmitted through concrete

Figure 74. Illustration. Communication signals transmitted through asphalt

Figure 75. Flowchart. Design flow to optimize the matching network that can maximize the powering and reading distance between the sensor and the reader

Figure 76. Graph. Simulation results showing the power received at the sensor when the sensor-reader distance is varied

Figure 77. Graph. Simulation results showing the voltage induced at the sensor when the sensor-reader distance is varied

Figure 78. Photo. Experimental setup used to validate the proposed reactive voltage-boosting method

Figure 79. Illustration. Equivalent circuit model for the setup

Figure 80. Graph. Non-linear resistive model for the voltage multiplier on the sensor IC

Figure 81. Graph. Comparison of the voltage generated by an 18-stage voltage multiplier for the new and the previously used matching network

Figure 82. Graph. Comparison of the voltage generated by a 12-stage voltage multiplier for the new and previously used matching network

Figure 83. Photo. Experimental setup for the indirect tensile test

Figure 84. Photo. Command unit for the indirect tensile test setup

Figure 85. Photo. Piezoelectric disk transducer attached to the tested asphalt specimen

Figure 86. Graph. Correlation between measured strains and voltage output of the transducer at varying temperatures

Figure 87. Illustration. Piezoelectric strain scavenger

Figure 88. Equation. Varitional indicator

Figure 89. Equation. Kinetic energy

Figure 90. Equation. External work

Figure 91. Equation. Potential energy

Figure 92. Equation. Variational indicator

Figure 93. Equation. Longitudinal displacement

Figure 94. Equation. Electric field

Figure 95. Equation. Piezoelectric constitutive equation

Figure 96. Equation. Stiffness

Figure 97. Equation. Applied load induced by strain

Figure 98. Equation. Electromechanical coupling and capacitance matrices

Figure 99. Graph. Voltage transfer function of PVDF film and PZT piezo under 400 microstrain loading across 10 megaohm load resistance

Figure 100. Graph. Output voltage amplitude of PVDF film and PZT piezo under 400 microstrain versus load resistance

Figure 101. Photo. PVDF piezo film bounded to Plexiglas® beam

Figure 102. Photo. PVDF embedded in epoxy and bounded to Plexiglas® beam

Figure 103. Photo. PVDF piezo film embedded in epoxy and bounded to concrete

Figure 104. Photo. Bending test setup to check the activation strain loss from a configuration to another

Figure 105. Photo. Setup of sensor calibration and fatigue tests

Figure 106. Photo. Slab compactor

Figure 107. Photo. Compacted slab with embedded transducers

Figure 108. Photo. Cut asphalt specimen with embedded piezoelectric generator

Figure 109. Graph. Sample of voltage response of PZT with time under applied sinusoidal strain

Figure 110. Photo. Piezoelectric transducer embedded in concrete

Figure 111. Photo. Piezoelectric transducer covered with a layer of rubber

Figure 112. Photo. Concrete specimen with embedded piezoelectric generator

Figure 113. Photo. Concrete specimen loaded in a temperature-controlled environment

Figure 114. Graph. Sample voltage response of embedded PZT at 14 °F (-10 °C) under applied 177 and 441 microstrain load

Figure 115. Graph. Sample voltage response of embedded PZT under 278 microstrain at 32 and 86 °F (0 and 30 °C)

Figure 116. Graph. Correlation between measured strains and voltage output of the transducer at varying temperatures

Figure 117. Graph. Effect of temperature on the output voltage at different levels of fluctuating strains

Figure 118. Photo. Example of commercially available asphalt strain gauge

Figure 119. Photo. Second example of commercially available asphalt strain gauge

Figure 120. Photo. Marking the proposed locations of the gauges

Figure 121. Photo. Placing sand/binder pad and fitting gauges

Figure 122. Photo. Placing screened asphalt on top of gauges and carefully compacting

Figure 123. Photo. Compacting the unscreened asphalt over the gauge arrays

Figure 124. Photo. Laying instrument wiring and piping in aggregate base

Figure 125. Photo. Cutting grooves in cement-treated base for instrument leads

Figure 126. Photo. Collecting a concrete strain gauge using steel frames

Figure 127. Illustration. Cross section of commercialized strain gauges

Figure 128. Photo. Thermocouple covered with a layer of polyurethane foam

Figure 129. Graph. Measured output from protected and unprotected thermocouples

Figure 130. Photo. Testing of the selected protective materials under compaction condition

Figure 131. Photo. Material prototype placed in a compactor

Figure 132. Photo. Compacted asphalt material

Figure 133. Photo. Material specimen recovered from the asphalt beam after compaction

Figure 134. Illustration. Finite element model of the H-shaped package

Figure 135. Illustration. Simulated stress distributions

Figure 136. Illustration. Simulated nodal deflections

Figure 137. Photo. Manufacturing process of the used molds

Figure 138. Photo. Molds forming

Figure 139. Photo. Finished molds

Figure 140. Photo. Piezoelectric transducer embedded in Araldite® GY-6010 epoxy 80

Figure 141. Photo. Polyurethane thermal insulator coat deposited on top of the epoxy core

Figure 142. Photo. Tested prototypes of piezoelectric transducer embedded in epoxy and coated with a polyurethane thermal insulator

Figure 143. Photo. Specimens placed in the compactor

Figure 144. Graph. Measured compaction curves

Figure 145. Photo. Recovered sample 1 after compaction

Figure 146. Photo. Recovered sample 2 after compaction

Figure 147. Photo. Final version of the prototype with an external resin layer

Figure 148. Photo. Recovered specimen

Figure 149. Illustration. Layout of ASGs

Figure 150. Graph. Simulated longitudinal strain using Viscoroute

Figure 151. Graph. Measured longitudinal strain using thin H-shape and bone shape made of conathane

Figure 152. Graph. Measured longitudinal strain using thin H-shape and bone shape made of araldite

Figure 153. Graph. Measured longitudinal strain using thick H-shape and bone shape made of conathane

Figure 154. Graph. Measured longitudinal strain using thick H-shape and bone shape made of araldite

Figure 155. Graph. Measured longitudinal strain with bone-shaped conathane strain gauges using two different thicknesses

Figure 156. Photo. Prototype installation at TFHRC's ALF

Figure 157. Photo. Grinding the existing pavement before bonding gauges to the surface

Figure 158. Photo. Placed sensor prototype

Figure 159. Photo. Testing the wireless reading functions for the installed prototype

Figure 160. Photo. Different tested types of package prototypes

Figure 161. Photo. Prepared grooves for prototype installation

Figure 162. Photo. Special epoxy used to bond gauges to surface

Figure 163. Photo. Installed prototypes

Figure 164. Photo. Installation of the prototype packaging system installed during a construction project near Lansing, MI

Figure 165. Photo. Specimen preparation and placement

Figure 166. Photo. Manual compaction of HMA patches

Figure 167. Photo. Installed prototypes ahead of the compactor

Figure 168. Graph. Strain amplitude variation of a concrete beam under cyclic load with constant amplitude

Figure 169. Equation. Strain cumulative density

Figure 170. Graph. Cumulative distribution of strain expressed in voltage

Figure 171. Graph. Normalized density distribution expressed as normalized voltage

Figure 172. Graph. Relative error of fitting per gate for specimens at different life stages versus number of gates per sensor

Figure 173. Equation. Cumulative distribution

Figure 174. Equation. Cumulative loading time

Figure 175. Equation. Mean of the cumulative strain

Figure 176. Equation. Standard deviation

Figure 177. Equation. Mean of the applied strain amplitude at time t

Figure 178. Equation. Standard deviation of the applied strain amplitude at time t

Figure 179. Equation. Mean of the damage coefficient

Figure 180. Equation. Variance of the damage coefficient

Figure 181. Equation. Reliability index

Figure 182. Equation. Probability of failure

Figure 183. Graph. Strain distribution histogram at different life stages of the beam at 100 cycles

Figure 184. Graph. Strain distribution histogram at different life stages of the beam at 25,000 cycles

Figure 185. Graph. Strain distribution histogram at different life stages of the beam at 40,500 cycles

Figure 186. Graph. Fitting the sensor's output at different life stages of the specimen at 100 cycles

Figure 187. Graph. Fitting the sensor's output at different life stages of the specimen at 25,000 cycles

Figure 188. Graph. Fitting the sensor's output at different life stages of the specimen at 40,500 cycles

Figure 189. Graph. Probability distribution of the damage coefficient versus the number of cycles of loading

Figure 190. Graph. Variance damage coefficient distribution

Figure 191. Graph. Variation of the mean

Figure 192. Graph. Probability of failure of one of the samples versus the number of load cycles

Figure 193. Graph. Reliability index of one of the samples versus the number of load cycles

Figure 194. Equation. Linear damage accumulation rule

Figure 195. Equation. Remaining life

Figure 196. Equation. Cumulative distribution function

Figure 197. Graph. Probability density function of the damage index at failure

Figure 198. Equation. Remaining life CDF

Figure 199. Equation. Survival probability function of the beam

Figure 200. Equation. Expectation of the survival probability function

Figure 201. Equation. Function of the damage index

Figure 202. Graph. Normalized estimated remaining life versus the normalized specimen's lifetime using three fitting shape functions

Figure 203. Graph. Remaining life probability versus normalized specimen's lifetime using three fitting shape functions

Figure 204. Graph. Example of data from distributed sensors on a simply supported beam under random loading

Figure 205. Equation. Estimate of X as a function of mu

Figure 206. Equation. System of equations to solve for the case of an OK formulation

Figure 207. Graph. Theoretical and estimated strain probability distributions at 3.74 inches (94.99 mm) using data from groups of three sensors at different locations

Figure 208. Illustration. Example of a class 9 truck used for strain response data generation

Figure 209. Graph. Example of longitudinal strain profile evaluated at the bottom of the HMA layer for a moving load induced by a class 9 truck

Figure 210. Graph. Theoretical and estimated strain probability distributions at a selected transverse location using data from two sensors at different spacing distances

Figure 211. Graph. Maximum observed relative error and average relative error from generated data at all field points using known nodes at different spacing distances

Figure 212. Illustration. Circuit implementation of a temperature-dependent measuring system

Figure 213. Graph. Variations of measured output current (Figure 212) with respect to temperature

Figure 214. Graph. Variations of measured output voltage with respect to temperature

Figure 215. Photo. Overhead view of Dynamax SM200 moisture gauge

Figure 216. Photo. Dynamax SM200 moisture gauge

Figure 217. Graph. Measured output voltage of the moisture cell powered by a 9-V battery

Figure 218. Photo. Testing setup for the moisture cell

 

LIST OF TABLES

Table 1. Hardware changes that were incorporated in different versions of the sensor IC

Table 2. Summary of performance metrics of fabricated prototypes

Table 3. Piezoelectric sensor properties

Table 4. Activation strain at different piezo configurations

Table 5. Reliability index, probability of failure, and damage coefficient at failure for different specimens

Table 6. Predicted remaining life cycles using M-E calibrated coefficients and using the updated sensor output

Table 7. Estimated remaining life using the different fitting shape function

ABBREVIATIONS

AC Asphalt concrete
ADC Analog-to-digital converter
ALF Accelerated loading facility
ASG Asphalt strain gauge
Caltrans California Department of Transportation
CDF Cumulative density function
CMOS Complementary metal oxide semiconductor
COD Crack-opening displacement
CRC Cyclic redundancy check
DBM Digital base-band module
DIP Dual in-line package
FG Floating gate
FHWA Federal Highway Administration
FPGA Field-programmable gate array
FWD Falling weight deflectometer
HF High frequency
HMA Hot mix asphalt
IC Integrated circuit
IIHEI Impact-ionized hot electron injection
LDO Low dropout voltage
LVDT Linear variable differential transformer
M-E Mechanistic-empirical
MOSFET Metal oxide semiconductor field effect transistor
NMOS N-type metal oxide semiconductor
OK Ordinary Kriging
OPAMP Operational amplifier
PCB Printed circuit board
PCC Portland cement concrete
PMOS P-type metal oxide semiconductor
PMS Pavement Management System
PSRR Power supply rejection ratio
PVC Polyvinyl chloride
PVDF Polyvinylidene fluoride
PWM Pulse width modulation
PZT Lead zirconate titanate
RF Radio frequency
RFID Radio frequency identification
SHA State highway agency
SiO2 Silicon dioxide
SM Sensor model
SPI Serial peripheral interface
SPS Specific Pavement Studies
TFHRC Turner-Fairbank Highway Research Center
TI Texas Instruments
TSD Traffic speed deflectometer

The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT).
The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT). Provide leadership and technology for the delivery of long life pavements that meet our customers needs and are safe, cost effective, and can be effectively maintained. Federal Highway Administration's (FHWA) R&T Web site portal, which provides access to or information about the Agency’s R&T program, projects, partnerships, publications, and results.
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United States Department of Transportation - Federal Highway Administration