Abstract: A processor of a sensor device receives a plurality of images capturing a scene that depicts at least a portion of a conveyer entering a treatment area of a food processing system. The processor processes one or more images, among the plurality of images, to detect one or more characteristics in the scene. Processing the one or more images includes detecting presence or absence of a product on the at least the portion of the conveyor depicted in the scene, and classifying the scene as having one or more characteristics among a predetermined set of characteristics. The sensor device provides characteristics information indicating the one or more characteristics detected in the scene to a controller. The characteristics information is to be used by the controller to control operation of one or both of the conveyor and the treatment area of the food processing system.

Abstract: A processor of a sensor device receives a plurality of images capturing a scene that depicts at least a portion of a conveyer entering a treatment area of a food processing system. The processor processes one or more images, among the plurality of images, to detect one or more characteristics in the scene. Processing the one or more images includes detecting presence or absence of a product on the at least the portion of the conveyor depicted in the scene, and classifying the scene as having one or more characteristics among a predetermined set of characteristics. The sensor device provides characteristics information indicating the one or more characteristics detected in the scene to a controller. The characteristics information is to be used by the controller to control operation of one or both of the conveyor and the treatment area of the food processing system.

Abstract: A first camera captures a first image of a scene, and a second camera captures a second image capturing thermal distribution across the scene. The first image is processed to detect one or more objects of interest in the scene and to identify respective surface characteristics of the objects. The first image is overlaid with the second image to identify regions of interest in the second image corresponding to the objects of interest in the first image. Values of pixels that belong to respective regions of interest in the second image are converted to temperature values using respective conversion functions that reflect respective emissivity values determined by the identified respective surface characteristics of the corresponding objects of interest in the first image. The temperature values are analyzed to monitor thermal conditions of the one or more objects of interest in the scene.

Abstract: A first camera captures a first image of a scene, and a second camera captures a second image capturing thermal distribution across the scene. The first image is processed to detect one or more objects of interest in the scene and to identify respective surface characteristics of the objects. The first image is overlaid with the second image to identify regions of interest in the second image corresponding to the objects of interest in the first image. Values of pixels that belong to respective regions of interest in the second image are converted to temperature values using respective conversion functions that reflect respective emissivity values determined by the identified respective surface characteristics of the corresponding objects of interest in the first image. The temperature values are analyzed to monitor thermal conditions of the one or more objects of interest in the scene.

Abstract: Disclosed herein are rapid cycle pressure swing adsorption (PSA) process for separating O2 from N2 and/or Ar. The processes use a carbon molecular sieve (CMS) adsorbent having an O2/N2 and/or O2/Ar kinetic selectivity of at least 5 and an O2 adsorption rate (1/s) of at least 0.2000 as determined by linear driving force model at 1 atma and 86° F.

Abstract: Disclosed herein are rapid cycle pressure swing adsorption (PSA) process for separating O2 from N2 and/or Ar. The processes use a carbon molecular sieve (CMS) adsorbent having an O2/N2 and/or O2/Ar kinetic selectivity of at least 5 and an O2 adsorption rate (1/s) of at least 0.2000 as determined by linear driving force model at 1 atma and 86° F.

Abstract: Apparatus and methods are disclosed that allow for the monitoring and analysis of production process data for a multi-step asynchronous cyclic production process (e.g. pressure swing adsorption) in a steady state plant (such as a steam methane reforming plant). Data collected from cooperating sensors is processed applying a moving window discrete Fourier transform (DFT). The transformed data can be further analyzed in the broader steady-state plant environment to accurately detect any process anomalies and avoid false alarms.

Abstract: Apparatus and methods are disclosed that allow for the monitoring and analysis of production process data for a multi-step asynchronous cyclic production process (e.g. pressure swing adsorption) in a steady state plant (such as a steam methane reforming plant). Data collected from cooperating sensors is processed applying a moving window discrete Fourier transform (DFT). The transformed data can be further analyzed in the broader steady-state plant environment to accurately detect any process anomalies and avoid false alarms.