Structural health monitoring (SHM) enables wide-area, in situ, and continuous evaluation of the health of mechanical, civil, and aerospace structures to detect the existence, location, and severity of damage. In this paper, we introduce a sparse and scalable sensor network, driven by custom ultra-low power and highly integrated CMOS transceivers, that is suitable for a variety of active SHM applications using ultrasonic guided waves. The transceivers both generate electrical actuation signals for piezoelectric transducers and provide broadband lownoise reception of returned signals. Specifically, the transmitter can generate narrow-band Hanning-windowed sinusoids (5 cycles long) up to 12.7 Vpp with a center frequency in the 100 kHz to ∼2.8 MHz range. The waveform is synthesized using filtered pulse-width modulation (PWM), which is integrated with a programmable phasedlocked loop (PLL) to achieve low distortion and high repeatability. The fully-differential low-noise receiver is capable of performing a Hilbert transform on-chip to extract both amplitude and phase information from the received signal. For long term monitoring, we propose a two-step SHM strategy, in which damage is first detected using environmentally compensated data and is then localized and characterized. Furthermore, we discuss two commonly-used SHM damage localization algorithms, namely RAPID and delay-and-sum, in terms of computation, memory, and power consumption for the proposed sparse SHM networks. The proposed approach has been effectively demonstrated both in simulations and in experiments on an SHM test bed.
Xinyao Tang, Joel B. Harley, Kevin Bi, Tayfun Özdemir, Martin B. Pawloski, and Soumayjit Mandal, "Sparse sensor networks for active structural health monitoring using highly integrated CMOS transceivers," Proc. SPIE 10598, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018, 105983H (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 09, 2018; Published: 27 March 2018); https://doi.org/10.1117/12.2296664.
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