Displacement plays a crucial role in structural health monitoring, but the accurate measurement of structural displacement remains a challenging task. Nowadays, some researchers attempt to estimate structural displacement by fusing vision camera and accelerometer measurements. Considering hardware limitations and computational costs, vision measurements are commonly performed at a low sampling rate. Nevertheless, the use of a low sampling rate may cause temporal aliasing in vision measurements, which can cause large displacement errors. In this study, we propose a finite impulse response (FIR) filter-based technique to estimate structural displacement using high-sampling acceleration measurement and low-sampling vision measurement with temporal aliasing. By explicitly eliminating the error induced by temporal aliasing, the displacement estimation accuracy can be significantly improved compared to existing FIR filter-based techniques. The proposed technique was experimentally validated on a single-story building model, and the results show that the displacement estimation performance of the technique was insensitive to the sampling rate of vision measurements. Structural displacement was accurately estimated even when temporal aliasing was present in vision measurements.
Nonlinear ultrasonic modulation is favored for early-stage fatigue crack detection by inspecting the modulation components at the sum and difference of two distinct input frequencies. However, it is difficult to extract the modulation components using a conventional spectral density function considering the modulation components can be easily buried under noisy environments. In this study, we proposed a new nonlinear ultrasonic analysis method inspired by phase-based motion magnification. First, a one-dimensional time-domain ultrasonic signal is filtered to remove the large motions of the primary linear response components. Then, the filtered signal is used to construct a two-dimensional video and the phase-based motion magnification algorithm is applied to enhance the movements at the predetermined modulation frequencies inside the video. This step is achieved by phase denoising and phase magnification, which supports large magnification factors and is significantly insensitive to noise. Finally, an amplified one-dimensional signal is extracted from the two-dimensional video and can be used for further nonlinear ultrasonic analysis. The proposed method was successfully validated with a group of synthetic data at different noise levels. Additionally, we have also successfully applied the proposed method for fatigue crack detection in a steel padeye.
Considering the diminishing dimensions of modern silicon wafers (50-100 μm thick and their coating layers are in an nm scale) and potential defect sizes, spatial resolutions for the corresponding non-destructive evaluation (NDE) solutions should be in the order of sub-μm or nm. However, the spatial resolutions of current NDE techniques are often in the range of μm or mm. In this study, an ultrafast ultrasonic measurement system is developed using a femtosecond pulse laser. The proposed ultrafast ultrasonic measurement system can generate ultrasonic waves up to several THz (1012 Hz), and measure the corresponding responses with a sampling rate up to PHz (1015 Hz). In this system, the femtosecond pulse laser beam is split into pump and probe pulses for a pulse-echo ultrasonic measurement. The pump pulse produces ultrafast ultrasound onto the target silicon wafer, and the ultrasound travels through the thickness direction. Then, the waves reflected from the coating layer are measured using an optically delayed probe pulse. Using the proposed system, the coating thicknesses of silicon wafers in the range of 50 nm to 200 nm were successfully estimated.
KEYWORDS: Ultrasonics, Modulation, Aluminum, Transducers, Signal to noise ratio, Ferroelectric materials, Signal detection, Fourier transforms, Linear filtering
Due to crack-induced nonlinearity, ultrasonic wave can distort, create accompanying harmonics, multiply waves of different frequencies, and, under resonance conditions, change resonance frequencies as a function of driving amplitude. All these nonlinear ultrasonic features have been widely studied and proved capable of detecting fatigue crack at its very early stage. However, in noisy environment, the nonlinear features might be drown in the noise, therefore it is difficult to extract those features using a conventional spectral density function. In this study, nonlinear spectral correlation is defined as a new nonlinear feature, which considers not only nonlinear modulations in ultrasonic waves but also spectral correlation between the nonlinear modulations. The proposed nonlinear feature is associated with the following two advantages: (1) stationary noise in the ultrasonic waves has little effect on nonlinear spectral correlation; and (2) the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced simply by using a wideband input. To validate the proposed nonlinear feature, micro fatigue cracks are introduced to aluminum plates by repeated tensile loading, and the experiment is conducted using surface-mounted piezoelectric transducers for ultrasonic wave generation and measurement. The experimental results confirm that the nonlinear spectral correlation can successfully detect fatigue crack with a higher sensitivity than the classical nonlinear coefficient.
This paper presents a damage visualization technique using a fully noncontact laser ultrasonic measurement system and a synchronized scanning strategy. The noncontact laser ultrasonic measurement system is composed of a Q-switched Nd:YAG laser for ultrasonic wave generation and a laser Doppler vibrometer (LDV) for ultrasonic wave detection. The laser beams for ultrasonic wave generation and detection are shot on the target structure with a constant and tiny distance, and these two laser beams are synchronously moved over the scanning area. Compared with conventional laser scanning strategies, the ultrasonic responses detected through the synchronized scanning strategy owns a much higher and more stable signal to noise ratio and the scanning time can be significantly reduced with less time averaging. By spatial comparison in the scanning area, damage can be detected and visualized without relying on baseline data obtained from the pristine condition of the target structure. In this paper, the developed technique is validated by visualization hidden corrosion in a steel straight pipe and a steel elbow pipe.
Fatigue crack and its precursor often serves as a nonlinear source, and the nonlinear ultrasonic features created by a fatigue crack have a much higher sensitivity compared with linear features. This paper presents a fatigue crack visualization technique based on noncontact laser ultrasonics and state space techniques. Under a broadband laser pulse excitation, defect nonlinearity exhibits modulation at multiple frequency peaks in a spectral plot due to interactions among various input frequency components of the broadband input. These modulations are weak and hardly discernable in both the frequency and time domains. In order to detect the nonlinear changes caused by fatigue cracks in the time domain, a state space attractor is reconstructed using a single laser pulse response and its geometrical deviations from the baseline data obtained from the pristine condition of a target structure are computed. Through scanning tests using a Q-switched Nd:YAG laser and laser Doppler vibrometer (LDV), the proposed method can be used for visualizing fatigue cracks in metallic plates.
KEYWORDS: Sensors, Modulation, Acoustics, Ferroelectric materials, Active sensors, Spectroscopy, Field programmable gate arrays, Transducers, Signal processing, Algorithm development
Fatigue crack is one of the main culprits for the failure of metallic structures. Recently, it has been shown that nonlinear
wave modulation spectroscopy (NWMS) is effective in detecting nonlinear mechanisms produced by fatigue crack. In
this study, an active wireless sensor node for fatigue crack detection is developed based on NWMS. Using PZT
transducers attached to a target structure, ultrasonic waves at two distinctive frequencies are generated, and their
modulation due to fatigue crack formation is detected using another PZT transducer. Furthermore, a reference-free
NWMS algorithm is developed so that fatigue crack can be detected without relying on history data of the structure with
minimal parameter adjustment by the end users. The algorithm is embedded into FPGA, and the diagnosis is transmitted
to a base station using a commercial wireless communication system. The whole design of the sensor node is fulfilled in
a low power working strategy. Finally, an experimental verification has been performed using aluminum plate specimens
to show the feasibility of the developed active wireless NWMS sensor node.
This paper presents a fatigue crack detection technique based on visualization of nonlinear ultrasonic wave modulation produced by a fatigue crack. When distinctive low frequency (LF) and high frequency (HF) inputs are generated and applied to a structure, the presence of a fatigue crack can provide a mechanism for nonlinear ultrasonic modulation and create spectral sidebands around the frequency of the HF signal. In this study, the two input signals are created by two air-coupled transducers (ACT), and the corresponding ultrasonic responses are scanned over a target specimen using a 3D laser Doppler vibrometer (LDV). The crack-induced spectral sidebands are isolated using a combination of linear response subtraction (LRS), and continuous wavelet transform (CWT) filtering. Then, the extracted spectral sideband components are visualized near the fatigue crack. The effectiveness of the proposed non-contact scanning technique is tested using an aluminum plate with a real fatigue crack.
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