In this manuscript, we report a novel highly sensitive wearable strain sensor based on a highly stretchable multi-walled carbon nanotube (MWCNT)/Thermoplastic Polyurethane (TPU) fiber obtained via a wet spinning process.

This paper presents an automated crack visualization technique using ultrasonic wavefield images obtained by a complete noncontact laser scanning system. First, the complete noncontact laser scanning system is built by integrating and synchronizing a Q-switched Nd:YAG laser for ultrasonic generation, a laser Doppler vibrometer for ultrasonic measurement and galvanometers for scanning. Then, four different laser scanning schemes are compared to find the most effective and practical ultrasonic scanning strategy for the presented application. Second, a novel image processing technique is developed to isolate and visualize crack-induced standing wave energy from the constructed ultrasonic propagation images. Finally, the effectiveness of the proposed laser ultrasonic scanning system and imaging processing technique is experimentally verified using ultrasonic scanning images obtained from an aluminum plate. The test results confirmed that a hidden notch invisible from the scanned surface was successfully detected and visualized, while no false positive alarm was triggered for an intact specimen.

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This study presents a new impact localization technique that can pinpoint the location of an impact event within a complex structure using a time-reversal concept, surface-mounted piezoelectric transducers, and a scanning laser Doppler vibrometer. First, an impulse response function between an impact location and a piezoelectric transducer is approximated by exciting the piezoelectric transducer instead and measuring the response at the impact location using scanning laser Doppler vibrometer. Then, training impulse response functions are assembled by repeating this process for various potential impact locations and piezoelectric transducers. Once an actual impact event occurs, the impact response is recorded by the piezoelectric transducers and compared with the training impulse response functions. The correlations between the impact response and the impulse response functions in the training data are computed using a unique concept of time reversal. Finally, the training impulse response function, which gives the maximum correlation, is chosen from the training data set and the impact location is identified. The proposed impact localization technique has the following advantages over the existing techniques: (a) it can be applied to isotropic/anisotropic plate structures with additional complex features such as stringers, stiffeners, spars, and rivet connections; (b) only simple correlation calculation based on time reversal is required, making it attractive for real-time automated monitoring; and (c) training is conducted using noncontact scanning laser Doppler vibrometer and the existing piezoelectric transducers that may already be installed for other structural health-monitoring applications. Impact events on an actual composite aircraft wing and an actual aluminum fuselage are successfully identified using the proposed technique.