Patent ID: 11927944
Assignee: HONEYWELL INTERNATIONAL INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for monitoring and controlling flare operations of an industrial plant using a machine deep learning-based self-adaptive industrial automation system comprising:
(a) obtaining, from at least one camera, a sequence of real time images of the flare operation and obtaining data from a network of the industrial plant as to at least one flare parameter;
(b) applying, an optical flow algorithm on the sequence of real time images to separate the background information from useful information to generate motion information;
(c) inputting the real time images and the motion information to a machine deep learning configurable system module;
(d) analyzing the data by the machine deep learning configurable system module using machine learning models and algorithms to assign pixels of the images to categories selected from smoke, flame, and steam;
(e) generating a semantic segmentation map at a pixel level that categorizes segmented image frames indicating the smoke, flame, and steam based on the motion information of the pixels between frames of the sequence of real time images of the flare operation;
(f) displaying the results of the generated segmentation map by the machine deep learning configurable system module; and
(g) issuing a notice when the percentage of pixels in a specific category falls outside a predetermined range.