Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel.

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE).

Massive Ultrasonic Data Compression Using Wavelet Packet Transformation Optimized by Convolutional Autoencoders.

Ultrasonic signal acquisition platforms generate considerable amounts of data to be stored and processed, especially when multichannel scanning or beamforming is employed. Reducing the mass storage and allowing high-speed data transmissions necessitate the compression of ultrasonic data into a representation with fewer bits. High compression accuracy is crucial in many applications, such as ultrasonic medical imaging and nondestructive testing (NDT).

Transmission of Images With Ultrasonic Elastic Shear Waves on a Metallic Pipe Using Amplitude Shift Keying Protocol.

Transmission of information using ultrasonic elastic waves on existing metallic pipes provides an alternative communication option across physical barriers in a highly partitioned industrial complex, such as a nuclear facility. This work investigates the feasibility of the transmission of digital images over metallic pipes. Ultrasonic communication systems for transmission of images on a nuclear-grade stainless steel pipe were assembled for bench-scale demonstration.

Introduction to the special issue on ultrasonics and ferroelectrics.

The sixteen articles in this special section were presented at the 2013 IEEE Ultrasonics, Ferroelectrics, and Frequency Control (UFFC) Symposium that was held in Prague, the Czech Republic, from July 21-25, 2013.

System-on-chip design for ultrasonic target detection using split-spectrum processing and neural networks.

Ultrasonic detection and characterization of targets concealed by scattering noise is remarkably challenging. In this study, a neural network (NN) coupled to split-spectrum processing (SSP) is examined for target echo visibility enhancement using experimental measurements with input signal-to-noise ratio around 0 dB. The SSP-NN target detection system is trainable and consequently is capable of improving the target-to-clutter ratio by an average of 40 dB.

Hardware-efficient realization of a real-time ultrasonic target detection system using IIR filters.

In this study, we address the increased computational demands of a frequency-diverse ultrasonic target detection system by developing a zero-phase IIR (ZP-IIR) filter. Several ZP-IIR filter types including Chebyshev-I, Chebyshev- II, and Butterworth were analyzed for their detection performance. The 4th-order filters with 8-bit quantized coefficients are shown to improve the flaw-to-clutter ratio by approximately 10 dB.

A successive parameter estimation algorithm for chirplet signal decomposition.

In ultrasonic imaging systems, the patterns of detected echoes correspond to the shape, size, and orientation of the reflectors and the physical properties of the propagation path. However, these echoes often are overlapped due to closely spaced reflectors and/or microstructure scattering. The decomposition of these echoes is a major and challenging problem.

Ultrasonic data compression via parameter estimation.

Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path.