Structural Health Monitoring and Non-destructive Evaluation ,
Sensors and Smart Infrastructure Systems ,
Data Mining, Pattern Recognition and Machine Learning ,
Pipeline Monitoring
KEYWORDS: Ultrasonics, Environmental sensing, Waveguides, Temperature metrology, Damage detection, Structural health monitoring, Lithium, Digital filtering, Sensors, Signal processing
Guided wave ultrasonics is an attractive technique for structural health monitoring, especially on pressurized pipes. However, civil infrastructure components, including pipes, are often subject to large environmental and operational variations that prevent traditional baseline subtraction-based approaches from detecting damage. We collect ultrasonic data on a large-scale pipe segment in its normal operating conditions and observe large environmental variations. We developed a damage detection method based on singular value decomposition (SVD) that is robust to those benign variations. We further develop an online novelty detection framework based on our SVD method to detect the presence of a mass scatterer on the pipe at the same time that we collect the data. We examine the framework with both synthetic simulations and field experimental data. The results show that the framework can effectively detect the presence of a scatterer and is robust to large environmental and operational variations.
KEYWORDS: Ultrasonics, Transducers, Signal detection, Environmental sensing, Ferroelectric materials, Received signal strength, Waveguides, Signal processing, Temperature metrology, Receivers
The paper presents experimental results of applying an ultrasonic monitoring system to a real-world operating hot-water
supply system. The purpose of these experiments is to investigate the feasibility of continuous ultrasonic damage
detection on pipes with permanently mounted piezoelectric transducers under environmental and operational variations.
Ultrasonic guided wave is shown to be an efficient damage detector in laboratory experiments. However, environmental
and operational variations produce dramatic changes in those signals, and therefore a useful signal processing approach
must distinguish change caused by a scatterer from change caused by ongoing variations. We study pressurized pipe
segments (10-in diameter) in a working hot-water supply system that experiences ongoing variations in pressure,
temperature, and flow rate; the system is located in an environment that is mechanically and electrically noisy. We
conduct pitch-catch tests, with a duration of 10 ms, between transducers located roughly 12 diameters apart. We applied
different signal processing techniques to the collected data in order to investigate the ongoing environmental and
operational variations and the stationarity of the signal. We present our analysis of these signals and preliminary
detection results.
Piezoelectric sensors that are embedded in large structures and are inter-connected as a sensor network can provide
critical information regarding the integrity of the structures being monitored. A viable data communication
scheme for sensor networks is needed to ensure effective transmission of messages regarding the structural heath
conditions from sensor nodes to the central processing unit. In this paper we develop a time reversal based data
communication scheme that utilizes guided elastic waves for structural health monitoring applications. Unlike
conventional data communication technologies that use electromagnetic radio waves or acoustical waves, the
proposed method utilize elastic waves as message carriers and steel pipes as transmission channels. However,
the multi-modal and dispersive characteristics of guided waves make it difficult to interpret the channel responses
or to transfer correctly the structural information data along pipes. In this paper, we present the basic principles
of the proposed time reversal based pulse position modulation and demonstrate by simulation that this method
can effectively overcome channel dispersion, achieve synchronization, and delivery information bits through
steels pipes or pipe-like structures correctly.
Embedded sensors in large civil structures for structural health monitoring applications require data communication
capabilities between sensor nodes. Conventional communication modalities include electromagnetic
waves or acoustical waves. However, ultrasonic guided elastic waves that can propagate on solid structures such
as pipes for a great distance have rarely been studied for data communication purposes. The multi-modal and
dispersive characteristics of guided waves make it difficult to interpret the channel responses and to transfer useful
information along pipes. Time reversal is an adaptive transmission method that can improve the spatial and
temporal wave focusing. Based on the focusing effect of time reversal, we have developed a data communication
technique using guided waves in a highly dispersive pipe environment.
In this paper, we experimentally demonstrate the data communication using time reversal pulse position
modulation (TR-PPM). Three-step laboratory tests have been performed using piezoelectric transducers in a
pitch-catch mode. We first measure the channel responses between the transmitter and the receiver on a pipe.
We then carry out the time reversal transmission by reversing the sounding signal and feeding it back to the
same channel. Finally, we perform the time reversal communication experiment by sending the modulated time
reversal signals as a stream of binary bits at a given data rate. A series of experiments are conducted on steel
pipes. Experimental results demonstrate that time reversal pulse position modulation for data communications
can be achieved successfully using guided elastic waves.
This paper develops a framework of a cognitive sensor networks system for structure defect monitoring and classification
using guided wave signals. Guided ultrasonic waves that can propagate long distances along civil structures have been
widely studied for inspection and detection of structure damage. Smart ultrasonic sensors arranged as a spatially distributed
cognitive sensor networks system can transmit and receive ultrasonic guided waves to interrogate structure defects such
as cracks and corrosion. A distinguishing characteristic of the cognitive sensor networks system is that it adaptively
probes and learns about the environment, which enables constant optimization in response to its changing understanding
of the defect response. In this paper, we develop a sequential multiple hypothesis testing scheme combined with adaptive
waveform transmission for defect monitoring and classification. The performance is verified using numerical simulations
of guided elastic wave propagation on a pipe model and by Monte Carlo simulations for computing the probability of
correct classification.
Monitoring the structural integrity of vast natural gas pipeline networks requires continuous and economical inspection
technology. Current approaches for inspecting buried pipelines require periodic excavation of sections of pipe to assess
only a couple of hundred meters at a time. These inspection systems for pipelines are temporary and expensive. We
propose to use guided-wave ultrasonics with Time Reversal techniques to develop an active sensing and continuous
monitoring system.
Pipe environments are complex due to the presence of multiple modes and high dispersion. These are treated as adverse
effects by most conventional ultrasonic techniques. However, Time Reversal takes advantage of the multi-modal and
dispersive behaviors to improve the spatial and temporal wave focusing. In this paper, Time Reversal process is
mathematically described and experimentally demonstrated through six laboratory experiments, providing
comprehensive and promising results on guided wave focusing in a pipe with/without welded joint, with/without internal
pressure, and detection of three defects: lateral, longitudinal and corrosion-like. The experimental results show that Time
Reversal can effectively compensate for multiple modes and dispersion in pipes, resulting in an enhanced signal-to-noise
ratio and effective damage detection ability. As a consequence, Time Reversal shows benefits in long-distance and lowpower
pipeline monitoring, as well as potential for applications in other infrastructures.
Our earlier research has studied the generation of nearly-longitudinal waves in thick plates by edge excitation at
relatively high frequency-thickness products. These nearly-longitudinal waves, also known as trailing pulses, are
promising for flaw detection due to their shorter wavelength and the capability of retaining the pulse characteristics after
scattering from defects. However, in reality, the edges of the structures may not be accessible. This paper explores
exciting ultrasonic waves using a wedge transducer at oblique incidence. We first describe a simple model for the
formation of trailing pulses by oblique excitation. We then use simulations to examine the creation of nearly-longitudinal
waves in a thick plate, study the effect of incidence angles and discuss the energy distribution through the thickness.
Next we provide experimental results from both pitch-catch and pulse-echo tests to validate the characteristics of the
nearly-longitudinal waves excited by oblique incidence. The good agreement between the simulation and experiments
shows oblique excitation can also produce nearly-longitudinal waves with uniformly-spaced trailing pulses over a range
of incidence angles. The amplitude level of such pulses reaches its maximum when the incidence angle approaches to the
critical angle at the plexiglass-steel interface. The responses by oblique excitation are weaker than those by edge
excitation, but can still illuminate the plate through the thickness when the incidence angle is close to the critical angle.
The results show that the nearly-longitudinal waves by oblique excitation are a good alternative for infrastructure
inspection, especially for plates limiting edge access or permitting only surface access.
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