Tracking transients in steelpan strikes using surveillance technology.

This paper presents advancements in tracking features in high-speed videos of Caribbean steelpans illuminated by electronic speckle pattern interferometry, made possible by incorporating robust computer vision libraries for object detection and image segmentation, and cleaning of the training dataset. Besides increasing the accuracy of fringe counts by 10% or more compared to previous work, this paper introduces a segmentation-regression map for the entire drum surface yielding interference fringe counts comparable to those obtained via object detection. Once trained, this model can count fringes for musical instruments not part of the training set, including those with non-elliptical antinode shapes.

ConvNets for counting: Object detection of transient phenomena in steelpan drums.

We train an object detector built from convolutional neural networks to count interference fringes in elliptical antinode regions in frames of high-speed video recordings of transient oscillations in Caribbean steelpan drums, illuminated by electronic speckle pattern interferometry (ESPI). The annotations provided by our model aim to contribute to the understanding of time-dependent behavior in such drums by tracking the development of sympathetic vibration modes. The system is trained on a dataset of crowdsourced human-annotated images obtained from the Zooniverse Steelpan Vibrations Project. Due to the small number of human-annotated images and the ambiguity of the annotation task, we also evaluate the model on a large corpus of synthetic images whereby the properties have been matched to the real images by style transfer using a Generative Adversarial Network. Applying the model to thousands of unlabeled video frames, we measure oscillations consistent with audio recordings of these drum strikes. One unanticipated result is that sympathetic oscillations of higher-octave notes significantly precede the rise in sound intensity of the corresponding second harmonic tones; the mechanism responsible for this remains unidentified. This paper primarily concerns the development of the predictive model; further exploration of the steelpan images and deeper physical insights await its further application.

Primarily nonlinear effects observed in a driven asymmetrical vibrating wire.

The purpose of the work reported here is to further experimentally explore the wide variety of behaviors exhibited by driven vibrating wires, primarily in the nonlinear regime. When the wire is driven near a resonant frequency, it is found that most such behaviors are significantly affected by the splitting of the resonant frequency and by the existence of a "characteristic" axis associated with each split frequency. It is shown that frequency splitting decreases with increasing wire tension and can be altered by twisting. Two methods are described for determining the orientation of characteristic axes. Evidence is provided, with a possible explanation, that each axis has the same orientation everywhere along the wire. Frequency response data exhibiting nonlinear generation of transverse motion perpendicular to the driving direction, hysteresis, linear generation of perpendicular motion (sometimes tubular), and generation of motion at harmonics of the driving frequency are exhibited and discussed. Also reported under seemingly unchanging conditions are abrupt large changes in the harmonic content of the motion that sometimes involve large subharmonics and harmonics thereof. Slow transitions from one stable state of vibration to another and quasiperiodic motions are also exhibited. Possible musical significance is discussed.