IAQ Sensor Drift Calibration Using Mitigation Device Feedback
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Solution Overview
Problem
Indoor air quality sensors in HVAC systems face calibration challenges due to measurement drift and variability among sensors, leading to user distrust in accuracy and effectiveness in maintaining air quality within predetermined limits.
Innovation Solution
An indoor air quality (IAQ) sensor module that includes sensors for particulate matter, VOCs, and carbon dioxide, with features for determining initial and drift offsets, and adjusting measurements to normalize data across multiple sensors, ensuring accurate and consistent readings by averaging sensor data and accounting for sensor drift over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple IAQ sensors are deployed to monitor air quality, then measurement coverage is improved, but measurement precision deteriorates due to sensor drift and variability
Solution Approach 1:
The system continuously monitors sensor readings and compares them against expected ranges. When drift is detected, the system automatically adjusts calibration factors to correct the readings, creating a closed-loop feedback mechanism that maintains measurement precision across multiple sensors over time
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting calibration factors and offset values for each sensor based on environmental conditions and historical data. This allows the system to adapt sensor readings to maintain accuracy despite variations in sensor characteristics and drift over time
2Measurement precision
If sensor calibration is performed frequently to maintain accuracy, then measurement precision is improved, but loss of time increases due to calibration operations
Solution Approach 1:
The system implements periodic calibration at scheduled intervals rather than continuous calibration, combining this with real-time drift detection that triggers adaptive adjustments. This periodic action with intelligent triggering reduces overall calibration time while maintaining measurement precision through both scheduled and event-driven calibration events
Solution Approach 2:
The system performs self-calibration by automatically detecting drift patterns and adjusting its own calibration factors without requiring manual intervention. This self-service capability significantly reduces the time loss associated with calibration operations while maintaining measurement accuracy through automated corrective actions
Data Source
AI summary
An IAQ sensor module includes: a sensor configured to measure an amount of an item in air, the item being one of particulate matter, volatile organic compounds, and carbon dioxide; a minimum module configured to selectively store the amount of the item as a minimum value of the amount when a mitigation device has been on for at least a predetermined period, the mitigation device being configured to decrease the amount of the item in the air when on; a storing module configured to selectively store the minimum value as an initial minimum value; an offset module configured to determine a drift offset for the sensor based on a difference between the minimum value and the initial minimum value; and an adjustment module configured to determine an adjusted amount of the item in the air at the IAQ sensor module based on the amount and the drift offset.