Abstract: An example method comprises identifying a plurality of zones of a spectrogram of an audio sample associated with an operation cycle of an imaging device, generating a set of audio models by transforming the audio sample to a power spectrum and identifying a plurality of audio features within the power spectrum and for the plurality of zones, generating a plurality of simulated audio samples using the set of audio models by adjusting an audio feature of the plurality of audio features, and outputting a set of training data including the audio sample and the plurality of simulated audio samples to train a predictive model indicative of a predicted failure of the imaging device.

Abstract: Provided acoustic devices include an external housing defining an expansion chamber and a wall extending through and partitioning the expansion chamber into a central chamber and a peripheral chamber adjacent the central chamber, wherein an inlet and outlet communicate with the central chamber, and wherein the wall includes a plurality of apertures formed therethrough to allow air movement to and from the central and expansion chambers, the plurality of apertures sized to provide an average flow resistance ranging from 100 MKS Rayls to 5000 MKS Rayls. The acoustic devices advantageously show significant sound attenuation while streamlining air flow to reduce pressure drop across the expansion chamber.

Abstract: Provided acoustic devices include an external housing defining an expansion chamber and a wall extending through and partitioning the expansion chamber into a central chamber and a peripheral chamber adjacent the central chamber, wherein an inlet and outlet communicate with the central chamber, and wherein the wall includes a plurality of apertures formed therethrough to allow air movement to and from the central and expansion chambers, the plurality of apertures sized to provide an average flow resistance ranging from 100 MKS Rayls to 5000 MKS Rayls. The acoustic devices advantageously show significant sound attenuation while streamlining air flow to reduce pressure drop across the expansion chamber.

Abstract: A cellular material barrier system for reducing sound transmission. The cellular material system includes a planar cellular metamaterial arrangement which includes at least one unit cell, the unit cell includes a sound normalizing arrangement, and a planar metamaterial arrangement coupled to the sound normalizing arrangement on a first side, the planar metamaterial arrangement includes a plate, and a frame affixed to the plate, the sound normalizing arrangement configured to normalize incident sound received at non-normal angle to thereby convey sound at normal angles to the planar metamaterial arrangement, the unit cell further comprising a back layer that is coupled to the sound normalizing arrangement on a second side, opposite the first side, the back layer is made from a porous material, including at least one of a fibrous layer, polymeric foams, ceramic foams, and metallic foams.

Abstract: A cellular material barrier system for reducing sound transmission. The cellular material system includes a planar cellular metamaterial arrangement which includes at least one unit cell, the unit cell includes a sound normalizing arrangement, and a planar metamaterial arrangement coupled to the sound normalizing arrangement on a first side, the planar metamaterial arrangement includes a plate, and a frame affixed to the plate, the sound normalizing arrangement configured to normalize incident sound received at non-normal angle to thereby convey sound at normal angles to the planar metamaterial arrangement, the unit cell further comprising a back layer that is coupled to the sound normalizing arrangement on a second side, opposite the first side, the back layer is made from a porous material, including at least one of a fibrous layer, polymeric foams, ceramic foams, and metallic foams.

Abstract: A computer controlled method for predicting acoustical properties for a generally homogeneous porous material includes providing at least one prediction model for determining one or more acoustical properties of homogeneous porous materials, providing a selected prediction model for use in predicting acoustical properties for the generally homogeneous porous material, and providing an input set of at least microstructural parameters corresponding to the selection model. One or more macroscopic properties for the homogeneous porous material are determined based on the input set of the microstructural parameters and acoustical properties for the homogeneous porous material are generated as a function of the one or more macroscopic properties and the selected prediction model.