Humidity Sensor Calibration for Low RH Accuracy
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Solution Overview
Problem
Commercial humidity sensors, such as capacitive and resistive hygrometers, face challenges in achieving high accuracy, especially at low relative humidity (RH) levels and are sensitive to temperature and pressure variations, making precise measurements below 1% RH costly and complex.
Innovation Solution
A method involving calibration processes to improve humidity sensor accuracy, which includes receiving measurements from known humidity samples, determining calibration parameters based on temperature and pressure, and applying these parameters to correct measurements from unknown samples, thereby reducing the influence of temperature and pressure variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If commercial humidity sensors (capacitive or resistive hygrometers) are used, then the device complexity and cost are reduced, but the measurement precision deteriorates especially at low RH levels and under temperature/pressure variations
Solution Approach 1:
The patent applies preliminary action by performing calibration measurements before actual use. The system measures humidity at known reference conditions (first gas sample with known humidity level) to determine calibration parameters, which are then stored and applied to subsequent measurements. This preliminary calibration action enables the simple commercial sensor to achieve high measurement precision without increasing device complexity.
Solution Approach 2:
The patent implements feedback by using the calibration parameters derived from known humidity samples to correct and adjust subsequent humidity measurements. The system continuously refines measurements by comparing actual sensor readings against calibrated values, thereby improving measurement precision while maintaining simple device architecture.
2Measurement precision
If measurements are taken at fixed temperature and pressure, then the measurement precision is improved, but the adaptability deteriorates because the sensor cannot accurately measure across varying environmental conditions
Solution Approach 1:
The patent applies parameter changes by adjusting calibration parameters based on temperature and pressure conditions. The system determines calibration parameters at specific reference conditions and then modifies these parameters to account for actual measurement conditions. This enables the sensor to maintain high measurement precision across varying environmental conditions, thereby improving adaptability without sacrificing precision.
Solution Approach 2:
The patent implements dynamics by making the calibration parameters adaptable to changing environmental conditions. Rather than using fixed calibration values, the system dynamically adjusts calibration parameters based on temperature and pressure measurements, allowing the sensor to maintain accuracy across different operating conditions while preserving measurement precision.
3Adaptability or versatility
If calibration measurements are performed at multiple temperatures and pressures, then the adaptability is improved, but the loss of time increases due to the additional calibration process
Solution Approach 1:
The patent applies preliminary action by performing comprehensive calibration measurements at multiple temperatures and pressures before actual use. These time-consuming calibration measurements are conducted in advance to establish a comprehensive set of calibration parameters, which are then stored and applied to subsequent measurements. This eliminates the need for repeated time-consuming calibration during actual operation, thereby reducing time loss while maintaining high adaptability.
Solution Approach 2:
The patent implements self-service by enabling the system to automatically retrieve and apply appropriate calibration parameters based on current environmental conditions without requiring manual intervention or repeated calibration measurements. The system self-adjusts by selecting from pre-computed calibration data, thereby maintaining high adaptability while minimizing time consumption during actual measurements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enhances the accuracy of humidity sensors to measure less than 5% RH with improved precision and reduces the impact of temperature and pressure fluctuations, allowing for more reliable and cost-effective low-RH measurements.
Implementation Method 1
in capacitive hygrometers, the effect of humidity on the dielectric constant of a polymer or metal oxide material is measured
Implementation Method 2
In resistive hygrometers, the change in electrical resistance of a material due to humidity is measured
Implementation Method 3
determining calibration parameters based on temperature and pressure, and applying these parameters to correct measurements
Implementation Method 4
determining calibration parameters based on temperature and pressure, and applying these parameters to correct measurements
Data Source
AI summary
A method for increasing the accuracy of a humidity sensor is disclosed. The method comprises: receiving one or more first sets of humidity measurements from a humidity sensor over a period of time, when the humidity sensor is exposed a to a first gas sample having a known humidity level; determining a calibrating humidity measurement from the first sets of humidity measurements; receiving one or more second sets of humidity measurements from the humidity sensor over a period of time, when the humidity sensor is exposed to a second gas sample having an unknown humidity level; and for each second set, subtracting the calibrating humidity measurement from the humidity measurements.