Monitoring of fatigue cracking in steel bridges is of high interest to many bridge owners and agencies. Due to the variety of deterioration sources and locations of bridge defects, there is currently no single method that can detect and address the potential sources globally. In this paper, we presented a dual mode sensing methodology integrating acoustic emission and ultrasonic wave inspection based on the use of low-profile piezoelectric wafer active sensors (PWAS). After introducing the research background and piezoelectric sensing principles, PWAS crack detection in passive acoustic emission mode is first presented. Their acoustic emission detection capability has been validated through both static and compact tension fatigue tests. With the use of coaxial cable wiring, PWAS AE signal quality has been improved. The active ultrasonic inspection is conducted by the damage index and wave imaging approach. The results in the paper show that such an integration of passive acoustic emission detection with active ultrasonic sensing is a technological leap forward from the current practice of periodic and subjective visual inspection and bridge management based primarily on history of past performance.
According to the Federal Highway Administration (FHWA) National Bridge Inventory (NBI) of 2007, the number of structurally deficient and functionally obsolete bridges is 72,524 and 79,792, respectively [
To address this urgent need, the authors are conducting research on novel and promising sensing approaches together with energy harvesting devices to reduce the dramatic uncertainty inherent into steel bridge inspection and maintenance plan [
The monitoring of fatigue cracking in bridges has been approached with acoustic emission using either resonant or broadband sensors. Acoustic emission monitoring is capable of detecting crack growth behavior [
Historically, AE signals have been captured with specially designed and fabricated AE sensors. Conventional AE sensors are made of piezoelectric crystals as the sensing elements which are encapsulated for protection and coupled together with a wear plate for good acoustic coupling. The frequency content and sensitivity of the sensor are controlled by the geometry and properties of the piezoelectric crystal as well as the housing for the crystal.
Piezoelectric wafer active sensors (PWAS) can function as an active sensing or passive device or network using piezoelectric principles and provide a correlation between mechanical and electrical variables. They can be permanently attached to the structure to monitor condition at will and can operate in active guided wave interrogation or passive AE sensing modes. The transmission of actuation and sensing between the PWAS and the host structure is achieved through the bonding adhesive layer. The adhesive layer (Figure
PWAS and structure interaction through the interface layer.
An important characteristic of PWAS, which distinguishes them from conventional ultrasonic transducers, is their capability of exciting multiple guided Lamb wave modes at a single frequency. There are at least two Lamb modes, A0 and S0, existing simultaneously when the product of the wave frequency and structure thickness (
Lamb wave mode tuning on a 1-mm thick aluminum alloy 2024-T3 using 7-mm PWAS. (a) Experimental wave amplitude within 0~700 kHz; (b) predicted strain curves [
An example of PWAS tuning is presented in Figure
Dupont et al. [
In the subject project, we adapted PWAS as AE sensors to detect stress waves with frequency components concentrated at 150 kHz where the acoustic signals propagating with minimal attenuation and background noise due to the rubbing of structural components.
Laboratory tests have been conducted to investigate the PWAS application as an AE sensor. A typical commercial R15I (
The test setup is illustrated in Figure
AE testing setup. (a) Test setup schematic; (b) laboratory test setup.
In the first part of the work, a 1.6-mm thick aluminum plate, approximately 300-mm by 300-mm, was used for testing PWAS AE detection. PWAS and R15I were placed adjacently on the plate, about 165 mm away from the plate edge where the PLB was applied. In total, five PLB of various lead sizes were applied. The PWAS transducer detected all of them with comparable amplitudes to those captured by R15I, as summarized in Table
AE detection on the 1.6-mm aluminum plate.
PLB size | PWAS AE amplitude (dB) | R15I AE amplitude (dB) |
---|---|---|
0.7 mm | 83 | 82 |
0.5 mm | 89 | 89 |
0.5 mm | 78 | 78 |
0.3 mm | 88 | 86 |
0.3 mm | 84 | 78 |
Figure
0.5 mm PLB detection on 1.6-mm aluminum plate. (a) PWAS AE waveform and its frequency spectrum; (a) R15I AE waveform and its frequency spectrum.
Looking at the AE waveforms by PWAS and R15I present in Figure
An expanded view of the early PWAS response is shown in Figure
PWAS response compared to theoretical prediction. (a) PWAS waveform; (b) theoretical out-of-plane displacement by PlotRLQ.
The second part of the work was conducted on a 19-mm thick steel plate. 0.5 mm HB PLB was applied on the surface of the plate about 72 mm away from PWAS. The R15I transducer was glued on the plate with a distance of 98 mm from the PLB.
The PLB was detected by PWAS with an AE amplitude of 73 dB in contrast to the 87 dB detected by R15I. The waveforms and their frequency spectra are provided in Figure
0.5 mm PLB detection on 19-mm steel plate. (a) PWAS AE waveform and its frequency spectrum; (a) R15I AE waveform and its frequency spectrum.
By examining the frequency spectra, it can be noted that PWAS has major frequency components beyond 200 kHz, showing a wider frequency response compared to resonant type R15I AE sensor.
Compact tension (CT) specimens made of the same material as the steel plate used in Section
AE detection on a 1/2′′ CT specimen. (a) Geometry of the specimen and arrangement of transducers; (b) a snapshot of the actual specimen. AE PWAS are circled (rest are for active sensing). The R15I were installed on the other side of the specimen.
The results of crack localization from PWAS sensors and R15I during CT testing are shown in Figure
Comparison of crack localization in CT test on 1/2′′ steel specimen. (a) Cumulative acoustic energy by PWAS and R15I; (b) cracking detection and localization by R15I; (c) cracking detection and localization by PWAS.
In the validation tests, it has been noticed that PWAS on steel specimens exhibited higher floor noise compared to the standard R15I AE sensors, therefore, providing a poor SNR ratio. To enhance the signal quality toward field application and decrease the background floor noise, we improved PWAS installation by using a coaxial cable similar to that used for R15I sensors. The shield of the coax was connected to the steel plate very close to the PWAS while the center conductor was connected to the positive electrode of the PWAS, as shown in Figure
PWAS installation using a coaxial cable.
Detection of a 0.3 mm PLB about 20 mm away from a coaxial cable wired PWAS was evaluated (Figure
PLB detection on steel plate using coaxial cable wired PWAS.
In the dual mode sensing schematic, after significant cracking has been identified by passive mode AE detection, active mode sensing using pitch-catch interrogation is evoked to quantify crack growth through damage index and array imaging. A PWAS network consisting of several sensors spatially distributed on the plate can be used to interrogate the plate with one sensor generating the guided wave and the others receiving the structural response. When an elastic Lamb wave is transmitted and travels through the structure, wave scattering occurs in all directions where there is a change in the material properties due to damage. The scatter signal is defined as the difference between the measurement during the development of damage and the baseline signal at the initial stage. One advantage of using scatter signals is to minimize the influence caused by boundaries or other structural features which would otherwise complicate the Lamb wave analysis.
We assume that cracking is the sole source of changes in the detected Lamb waves. Also being assumed is that the waves travel in straight paths in the plate structures. Hence, the objective of our Lamb wave signal analysis is to extract damage-related characteristics from the measured sensory data. In this research damage index (DI) is defined as [
For the active sensing implemented during the CT test presented in Section
AE detection on a 1/2′′ CT specimen. (a) Geometry of the specimen and arrangement of transducers; (b) a snapshot of the actual specimen. AE PWAS are circled (rest are for active sensing). The R15I was installed on the other side of the specimen.
The array imaging methods have the incredible capability to map the structure and existing damage in it, providing a means to qualitatively assess the structural integrity. The sparse array uses scatter signals from a network of sensors to construct a diagnosis image. The image construction is based on triangulation principle and conducted by shifting back the scatter signals at time quantities defined by the transmitter-receiver locations used in the pitch-catch mode. Assuming a single damage scatter is located at point
The crack detection demonstration was conducted on a 1-mm thick aluminum plate. The imaging was performed by a four-PWAS network to assess a simulated hairline crack centered inside, shown in Figure
Array imaging for crack growth detection. (a) Test specimen and sensor network; (b) array imaging of a hairline crack of 18 mm length. Sensor locations are marked as green face circles.
The image result of the crack at 18 mm is shown in Figure
Piezoelectric wafer active sensors (PWAS) have made tremendous progress in structural health monitoring during the past decade, but their exposure to civil infrastructure has been little discussed so far. The work presented here intends to explore PWAS applications for in-field monitoring of infrastructure (e.g., civil steel bridges) using both acoustic emission and active wave propagation sensing. Laboratory demonstration on both thin aluminum and thick steel plates, the PWAS have been proved as AE sensors. The use of coaxial wiring cables has greatly improved the PWAS waveform signal-to-noise ratio, making it more suitable for field application. The PWAS AE sensing of fatigue cracking on a CT specimen showed that it can provide concentrated detection around the crack tip with a relatively fewer numbers of acoustic emission events than the R15I AE transducers. The PWAS active mode sensing using propagating guided waves can interrogate the structures at will and provide a clear indication and quantitative estimation of the crack growth through damage index or array imaging. The dual mode sensing of the presented PWAS methodology has shown its promising application to insitu health monitoring and diagnosis of steel bridges.
This paper was performed under the support of the US Department of Commerce, National Institute of Standards and Technology, Technology Innovation Program, Cooperative Agreement number 70NANB9H9007. The authors would also like to thank Dr. Adrian Pollock from Mistras Group for his insightful comments on the presented passive sensing.