Vision-Based Closed-Loop Control for Non-Sensible Process Conditions
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Solution Overview
Problem
Traditional thermodynamic sensors are unreliable for accurately measuring non-sensible process conditions in complex industrial processes, requiring manual intervention and heuristic judgments by trained operators, especially during transient conditions.
Innovation Solution
A system that captures images of non-sensible process conditions using an image capture device, converts them into numeric values with a machine learning model, and adjusts the process using a closed-loop controller to maintain optimal conditions, allowing for autonomous control and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional thermodynamic sensors are used to measure process conditions, then the measurement system is simple and reliable, but the sensors cannot accurately represent certain characteristics or properties of non-sensible process conditions
Solution Approach 1:
The patent introduces an intermediary machine learning model that translates visual information from cameras into sensor-like numeric values. This intermediary layer bridges the gap between visual data and traditional sensor inputs, enabling accurate measurement of non-sensible process conditions without directly modifying the physical sensing mechanism.
Solution Approach 2:
The patent replaces traditional thermodynamic sensors with a computer vision-based measurement system. Instead of using physical sensors to directly detect process conditions, the system uses cameras to capture visual information and machine learning models to interpret it, substituting mechanical/physical sensing with optical and computational approaches.
2Extent of automation
If manual intervention with trained operators is employed to monitor and control non-sensible process conditions, then measurement judgments can be made based on experience, but the system requires continuous human involvement and is not autonomous
Solution Approach 1:
The patent implements a self-service control system where the machine learning model autonomously translates visual data into control decisions without requiring continuous human intervention. The system serves itself by automatically processing camera feeds, generating sensor values, and triggering control actions based on predetermined logic, eliminating the need for ongoing manual monitoring.
Solution Approach 2:
The patent establishes a closed-loop feedback system where the machine learning model continuously monitors visual conditions, compares them against target values, and automatically adjusts process parameters. This feedback mechanism ensures consistent and reliable control by maintaining a continuous cycle of measurement, comparison, and correction without human intervention.
3Productivity
If real-time video feed with manual monitoring is used during transient conditions, then operational flexibility is maintained, but productivity decreases due to the need for continuous manual oversight
Solution Approach 1:
The patent replaces manual visual monitoring with an automated computer vision system. The machine learning model processes video feeds and generates control decisions automatically, substituting human cognitive processing with computational algorithms. This increases productivity by eliminating the need for continuous manual oversight while maintaining operational simplicity through automated decision-making.
Data Source
AI summary
A method of monitoring and controlling an industrial process includes capturing images of a non-sensible process condition of the industrial process with an image capture device, receiving the images of the non-sensible process condition with a computer system, and converting each image into a corresponding numeric value with a machine learning model stored in and operable by the computer system. The corresponding numeric value is then received and compared to a predetermined numeric value for the non-sensible process condition with a closed-loop controller, and an actuator operates with the closed-loop controller to adjust operation of the industrial process when the corresponding numeric value fails to match the predetermined numeric value or is outside of a defined threshold near the predetermined numeric value.