Industrial Flare Smoke Level Detection Using Video Image Analysis
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Solution Overview
Problem
Operators in industrial plants face the tedious task of continuously monitoring live flare videos to detect smoking conditions, which is inefficient and may lead to non-compliance with EPA regulations, requiring an automated system for real-time smoke detection and control.
Innovation Solution
A system that automatically detects smoking conditions in industrial flares using video cameras, generating a Smoke Level value from 0 to 10, which can trigger alarms and control override actions, integrated with a computer system for historical data analysis and reporting, allowing for real-time monitoring and compliance with EPA regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators manually monitor live flare videos continuously, then smoke events can be detected, but operator workload and time consumption increase significantly
Solution Approach 1:
The patent replaces the mechanical system of manual video monitoring by operators with an automated computer-based smoke detection system that uses image processing algorithms to automatically analyze flare videos and detect smoke events, thereby eliminating operator time consumption while maintaining detection reliability
Solution Approach 2:
The system enables self-service smoke detection by implementing automatic analysis capabilities within the flare monitoring system itself, where the computer system independently processes videos, detects smoke conditions, and generates alerts without requiring human intervention for continuous monitoring
2Productivity
If automated smoke detection is implemented, then operator workload is reduced, but system complexity increases
Solution Approach 1:
The patent applies universality by designing the computer system to perform multiple functions including video acquisition, image processing, smoke detection, alert generation, and data logging within a single integrated platform, thereby improving monitoring efficiency while managing system complexity through functional consolidation
Solution Approach 2:
The system uses an intermediary computer-based image processing layer between the video cameras and the final detection output, which mediates the complex analysis tasks and provides standardized smoke detection results to the control system, thereby managing complexity through abstraction
3Reliability
If real-time smoke detection is implemented, then compliance with EPA regulations is ensured, but energy consumption increases
Solution Approach 1:
The patent implements periodic action by analyzing video frames at optimized intervals rather than continuously processing every frame, allowing real-time smoke detection for EPA compliance while reducing overall system energy consumption through pulsed processing cycles
Data Source
AI summary
A method and system is disclosed that can automatically detect smoking conditions for industrial flares. It can analyze live or historical video images to identify smoking conditions and generate a “Smoke Level” value in the range of 0 to 10 to represent the seriousness of the smoking events. The Smoke Level data can be sent to the plant distributed control system (DCS) or other control devices so alarms can be generated and automatic or manual control actions can be taken to stop the flare from smoking quickly. The Smoke Level data can also be saved in historical files for reporting and smoke event tracking purposes. Using the described method and system, industrial plants can comply with EPA regulations at all times, improve flare control and monitoring, be better prepared for EPA reporting and auditing, and save energy and manpower.