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Non-contacting acoustic and ultrasonic measurements are of interest in applications ranging from nondestructive evaluation to rock physics and medical imaging. The fundamental workings of the detector-the interferometer-are easily explained in undergraduate physics courses, but practical implementations are dominated by specialized, and commercial, devices. We present a robust and relatively inexpensive detector, which consists of a heterodyne interferometer and phase locked loop frequency demodulator, as an open-source alternative. We illustrate the broadband capabilities with the detection of ultrasonic waves in a mudstone sample, and low-frequency (100 Hz) vibrations of a piston.

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We consider the use of optical coherence tomography (OCT) imaging to predict the quality of meat.We find that intramuscular fat (IMF) absorbs infrared light about nine times stronger than muscle, which enables us to estimate fat content in intact meat samples. The method is made very efficient by extracting relevant information from the three-dimensional high-resolution images generated by OCT using principal component analysis (PCA). The principal components are then used as regressors into a support vector regression (SVR) prediction model. The SVR model is found to predict IMF content stably and accurately, with an R 2 value of 0.94. Our study paves the way for automated, contact-less, non-destructive, real time classification of the quality of meat samples.

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