Systems and processes for optimizing operation of industrial equipment
AssigneeGeorgia-Pacific Corporation
InventorRobert Hartwell Herring, III
Life of this patent
Estimating the term…
Abstract
A system, method, and medium for virtually real time monitoring of machine performance are described. An optimal set-point for a data source is determined. The data source corresponds to operation of a machine. Virtually real time data is received from the data source corresponding to current operation of the machine. A deviation between the virtually real time data and the optimal set-point for the data source is computed. An intensity map is rendered representing the computed deviation according to a predefined visual gradient.
Claims20
A method for virtually real time monitoring of machine performance, comprising:
- determining an optimal set-point for a data source, the data source corresponding to operation of a machine;
- receiving virtually real time data from the data source corresponding to current operation of the machine;
- computing a deviation between the virtually real time data and the optimal set-point for the data source;
- and
- rendering an intensity map representing the computed deviation according to a predefined visual gradient, wherein the predefined visual gradient comprises a color gradient, a set of colors in the color gradient corresponds to an intensity scale derived according to a scaled normal distribution about the optimal set-point, the intensity scale comprises scaled deviation thresholds, and rendering the intensity map further comprises:
- generating a sampling frame for the data source;
- scaling the deviation of the data source to the intensity scale;
- and
- rendering the sampling frame for the data source on the intensity map, wherein a color of the sampling frame is derived from a comparison between the scaled deviation value and the scaled deviation thresholds.
A system for virtually real time monitoring of machine performance, comprising:
- at least one computing device configured to at least:
- determine an optimal set-point for a data source, the data source corresponding to operation of a machine;
- receive virtually real time data from the data source corresponding to current operation of the machine;
- compute a deviation between the virtually real time data and the optimal set-point for the data source;
- render an intensity map representing the computed deviation according to a predefined visual gradient, wherein the predefined visual gradient comprises a color gradient, a set of colors in the color gradient corresponds to an intensity scale derived according to a scaled normal distribution about the optimal set-point, and the intensity scale comprises scaled deviation thresholds;
- generate a sampling frame for the data source;
- scale the deviation of the data source to the intensity scale;
- and
- render the sampling frame for the data source on the intensity map, wherein a color of the sampling frame is derived from a comparison between the scaled deviation value and the scaled deviation thresholds.
A non-transitory computer-readable medium embodying instructions executable in at least one computing device, wherein when executed the instructions cause the at least one computing device to at least:
- determine an optimal set-point for a data source, the data source corresponding to operation of a machine;
- receive virtually real time data from the data source corresponding to current operation of the machine;
- compute a deviation between the virtually real time data and the optimal set-point for the data source;
- render an intensity map representing the computed deviation according to a predefined visual gradient, wherein the predefined visual gradient comprises a color gradient, a set of colors in the color gradient corresponds to an intensity scale derived according to a scaled normal distribution about the optimal set-point, and the intensity scale comprises scaled deviation thresholds;
- generate a sampling frame for the data source;
- scale the deviation of the data source to the intensity scale;
- and
- render the sampling frame for the data source on the intensity map, wherein a color of the sampling frame is derived from a comparison between the scaled deviation value and the scaled deviation thresholds.
Dependencies are inferred from the claim text.