CombustionGuard
AI safety interlock application for combustion control systems that monitors abnormal data, out-of-range operator actions, and communication or AI failures to prevent unsafe operation and equipment risk.
The Problem
“Safety interlock for AI-driven combustion control in energy operations”
Organizations face these key challenges:
AI controllers can act on corrupted, drifting, frozen, or delayed sensor data
Operators may place equipment in modes or ranges not represented in AI training data
Communications loss between DCS, PLC, edge gateway, and AI service can create unsafe ambiguity
AI model failures or inference latency can leave control loops without valid supervision
Impact When Solved
The Shift
Human Does
- •Review combustion alarms, trends, and operator actions during routine operation
- •Verify sensor readings and equipment status before changing combustion modes or setpoints
- •Apply procedures or conservative control adjustments when instability or abnormal conditions appear
- •Escalate burner trips, flame instability, or communication issues and decide on manual fallback
Automation
- •No AI-based supervision or anomaly detection is used
- •No automated validation of AI control recommendations is performed
- •No learned operating envelope checks are available for operator actions
- •No AI-driven communication health or service availability triage is performed
Human Does
- •Approve safety envelope policies, fallback modes, and operating limits for each combustion asset
- •Review and act on high-risk alerts, blocked actions, and repeated abnormal condition escalations
- •Decide when to keep equipment in manual, conventional control, or AI-assisted operation after exceptions
AI Handles
- •Continuously monitor sensor validity, operator actions, actuator commands, and communication health
- •Evaluate AI-generated control recommendations against approved safe operating envelopes before execution
- •Detect abnormal process patterns, unseen operating states, and rising combustion risk conditions
- •Block unsafe actions and trigger predefined safe fallback modes when risk, communication loss, or AI failure is detected
Operating Intelligence
How it works
AI runs the operating engine in real time.
Humans govern policy and overrides.
Measured outcomes feed the optimization loop.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Sense
Step 2
Optimize
Step 3
Coordinate
Step 4
Govern
Step 5
Execute
Step 6
Measure
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI senses, optimizes, and coordinates in real time. Humans set policy and override when needed. Measurements close the loop.
The Loop
6 steps
Sense
Take in live demand, capacity, and constraint signals.
Optimize
Continuously compute the best next allocation or action.
Coordinate
Push those actions into systems, channels, or teams.
Govern
Humans set policies, objectives, and overrides.
Authority gates · 1
The system must not change approved safety envelopes, operating limits, or fallback policies without human approval [S1].
Why this step is human
Policy decisions affect the entire operating envelope and require organizational authority to change.
Execute
Run the approved operating loop continuously.
Measure
Measured outcomes feed back into the optimization loop.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in CombustionGuard implementations: