Guided waves can propagate long distances and are sensitive to subtle structural damage. Guided-wave based damage
localization often requires extracting the scatter signal(s) produced by damage, which is typically obtained by
subtracting an intact baseline record from a record to be tested. However, in practical applications, environmental and
operational conditions (EOC) dramatically affect guided wave signals. In this case, the baseline subtraction process can
no longer perfectly remove the baseline, thereby defeating localization algorithms.
In previous work, we showed that singular value decomposition (SVD) can be used to detect the presence of damage
under large EOC variations, because it can differentiate the trends of damage from other EOC variations. This capability
of differentiation implies that SVD can also robustly extract a scatter signal, originating from damage in the structure,
that is not affected by temperature variation. This process allows us to extract a scatterer signal without the challenges
associated with traditional temperature compensation and baseline subtraction routines. . In this work, we use to
approach to localize structural damage in large, spatially and temporally varying EOCs.
We collect pitch-catch records from randomly placed PZT transducers on an aluminum plate while undergoing
temperature variations. Damage is introduced to the plate during the monitoring period. We then use our SVD method
to extract the scatter signal from the records, and use the scatter signal to localize damage using the delay-and-sum
method. To compare results, we also apply several temperature compensation methods to the records and then perform
baseline subtraction. We show that our SVD-based approach successfully localize damage while current temperature-compensated
baseline subtraction methods fail.
Alkali-silica reaction (ASR) is a chemical reaction that can occur between alkaline components in cement paste and reactive forms of silica in susceptible aggregates when sufficient moisture is present. The ASR product, known as ASR gel, can cause expansion and cracking that damages the structure. We pass ultrasonic signals through concrete laboratory specimens and use three different ultrasonic methods to detect the onset of ASR damage, or the presence of ASR damage while still at the microscale. Our test specimens are fabricated with aggregate known to be reactive and are then exposed to an aggressive environment to accelerate ASR development. We use swept-sine excitations and obtain pitch-catch records from specimens that have been exposed to the accelerated environment. From this data, we demonstrate an ultrasonic passband method shows high frequency components diminish faster than low frequency components, and therefore the ultrasonic passband shifts to the low frequency side due to ASR damage. The test results also show that the ultrasonic passband is logically related to specimen size. We also demonstrate a stretching factor method is able to track the progress of ASR damage in concrete very well. These methods are shown to be more reliable than attenuation spectrum or attenuation methods that do not detect the ASR damage in concrete at early stages.
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.
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