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Combining Simulation and Experiment for Acoustic-Load Identification.
Abstract not provided.
Predicting Flight Environments with a Small-Scale, Direct-Field Acoustic Test Facility.
Abstract not provided.
Predicting chatter using machine learning and acoustic signals from low-cost microphones
Machining chatter is a phenomenon resulting from self-oscillation between a machining tool and workpiece. This self-oscillation results in variation on the machined product that reduces the ability to meet desired specifications. Chatter is a widely studied topic as it directly relates to the quality of machined products. Here, this study details the application of a Random Forest (RF) classifier with Recursive Feature Elimination (RFE) to machining audio collected by a single microphone during down-milling operations. This approach allows straightforward feature elimination that results in an easily understood set of analyzed dimensions. Stability is predicted solely based on the classification output of the RF classifier. Our approach proves highly predictive with consistent machining setup and a small sample set. We also review transferability between machining setups and present key findings. Our RF approach demonstrates the ability to analyze and classify chatter through a low-cost approach with limited training data required. The motivation for using a single microphone is to enable detection on machines without other sensors, such as accelerometers, present in the machining setup. The value of the in-process sensor and chatter classifier is highlighted because the machining setup included asymmetric dynamics that reduced the accuracy of the traditional analytical stability solution. We see a natural progression to deploying this audio-only methodology with real-time processing and classification using either a laptop or smartphone. This progression will allow visual indicators during the machining process that can alert machinists of progression into unstable machining processes.
Application of the double-difference relocation method to acoustic emission events in high-pressure
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Optical and acoustic ground effects simulations from terminal defense asteroid disruption via the PI method
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Investigation of effective factors of woven structure fabrics for acoustic absorption
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An adaptive multigrid solver for DPG methods with applications in linear acoustics and electromagnetics
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Acoustic scattering characteristics and inversions for suspended concentration and particle size above mixed sand and mud beds
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Optical and acoustic phonons in turbostratic and cubic boron nitride thin films on diamond substrates
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Acoustic fingerprints in nature: A self-supervised learning approach for ecosystem activity monitoring
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Can acoustic recordings of cave-exiting bats in winter estimate bat abundance in hibernacula?
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Discard survival of coastal elasmobranchs in a small-scale fishery using acoustic telemetry and recapture data
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