Real-Time Fatigue Monitoring of Bridges
Using Electrochemical Fatigue Sensor (EFS) System
Masoud Malekzadeh, Ph.D. and Sadegh Panahi, Managing Director& COO
Metal Fatigue Solutions, Las Vegas, NV, USA
INTRODUCTION
One of the major and most common challenges to steel bridges’ integrity is fatigue. Long-term repetitive
loading eventually causes the initiation of small cracks in the steel which are commonly referred to as
fatigue cracks. These cracks typically occur in areas where the stresses are higher. Most of these higher
stress areas are known and are referred to as fatigue susceptible locations or fatigue critical locations
(FCLs). As time passes, these cracks gradually grow in size and number until one moment when they
reach a critical size and cause structural failure. Given the aging US highway bridge system, the need for
reliable sensors and monitoring technologies to alert bridge owners when cracks are reaching these critical
lengths has never been greater.The main objective of this study is to introduce and discuss a unique fatigue
sensor developed by Metal Fatigue Solutions, one that has been in commercial use throughout North
America for over 5 years.
The Electrochemical Fatigue Sensor (EFS) System
First introduced in 1992 the Electrochemical Fatigue Sensor (EFS) system has proven itself valuable for
timely detection of growing fatigue cracks – typically well before the unaided eye will spot them. It serves
to:
Define Crack Growth (whether the crack is growing or not?)
How Rapid or Slow is the Growth?
Define the Presence of Micro-Plasticity (in similar details elsewhere on the same bridge)
Assist in Evaluation of Effective Retrofits (did the retrofit stop the crack growth?)
Retrofit Selection (which retrofit is most effective in stopping the crack growth?)
FUNDAMENTAL PRINCIPAL OF EFS The EFS system consists of three main components including an electrolyte-filled sensor, a potentiostat
data link (PDL) that provides a constant voltage between the sensor and the structure and acquires the
data, and a data collection and analysis software. The science behind EFS is grounded in fundamental
electro-chemical principles. The EFS system anodically polarizes the inspection area, through a small
applied voltage, creating a passive film. There are basically two sensors installed near the area of interest
including one for reference (R) and one as the crack measurement (CM) sensor. The CM sensor is
positioned at a location of interest while the R sensor is located next to the CM sensor, where the crack is
not expected. The EFS response signal (current in micro-amps) from the two sensors are collected and
compared in order to identify the possible growing fatigue crack.
Installation of Reference Sensor (R) and Crack Measurement (CM) Sensor
The EFS response signal or current flowing within the cell fluctuates as a function of the mechanical
stress. Therefore, the transient current is monitored and interpreted to determine the fatigue level in the
structure. Once growing cracks are formed within the inspected area, the passive layer is broken down
which in turn produces a change in the EFS signal. This abnormal behavior is detected through real-time
signal processing of transient signal. Basically, the more steel is exposed, the more passive film changes
which indicates fatigue status in the structure. The frequency content and magnitude of the transient signal
(EFS signal) are affected by changes in the passive layer. Currently, live data sets are being transferred
from different sites (infrastructures) to the central office (data center) using virtual private network (VPN)
as it is shown in the following Figure.
Data Transmission Plan for MFS
6
. . . . . . .
Internet
Data Processing Center (Office)
Cloud Storage and Website for data Presentation
Network 1 (Bridge in State A)
Grid Power4G LTE Modem
VPN Router
Network 2 (Bridge in State B)
Grid Power4G LTE Modem
VPN Router
Subsequently, the live stream of data is analyzed using the Fast Fourier Transform (FFT) utilizing
windowing technique to detect any possible phase difference between crack and reference sensor. Once
the crack is detected the next important stage is to identify whether the crack is growing or not. The ratio
between crack sensor and reference sensor in frequency domain (Energy ratio) is used as decision metric
to determine the rate of crack growth. For instance, three measurements form individual locations of a
real-life bridge are presented below which are indicating three different stage of crack growth.
EFS Signal in Time Domain and Signal Domain (Not growing, insignificant growing and crack growths)
The accuracy of the crack detection and rate of crack growth using EFS sensor is compared to the visual
inspection conducted by a third party inspection team and reported in the following table. This beside
several other reports of other agencies indicating the efficacy and accuracy of EFS sensor in identifying
the current condition of the crack.
Next in development, Metal Fatigue Solutions is evaluating the efficiency of the EFS for long-term
monitoring applications. It is organizing three major research projects through three universities to study
different aspects of the long-term application including battery life, continuous data collection, handling
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Energy Ratio =1 Crack Not Growing Energy Ratio =2 Crack Growth is insignificant Energy Ratio =11.4 Crack Growths
large amounts of data sets and algorithm development. For addition information or to discuss this research
report further, please contact Dr. Masoud Malekzadeh at [email protected], or Mr.
Sadegh Panahi at [email protected].