Sensor Calibration Using Temperature Humidity Compensation
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Solution Overview
Problem
Existing sensor calibration methods fail to account for influences such as humidity, leading to systematic errors in sensor readings, especially after production when sensors are dry and later exposed to moisture, making post-calibration adjustments economically unfeasible due to the slow absorption process.
Innovation Solution
A method that records sensor characteristics at different temperatures to determine the influence of humidity and other factors, using a functional relation to compensate for these influences by calculating and storing correction coefficients, allowing for accurate conversion of digital equivalent values into correct output values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensor calibration is performed in dry state directly after production, then calibration time is reduced and production efficiency is improved, but systematic errors occur after humidity absorption leading to reduced measurement precision
Solution Approach 1:
The patent applies preliminary action by pre-determining the humidity influence characteristics of sensors during manufacturing. Correction values are calculated in advance based on the relationship between humidity and sensor output, allowing the sensor to be calibrated quickly in dry state while compensating for future humidity effects through stored correction data.
Solution Approach 2:
The patent uses parameter changes by introducing temperature as a variable to characterize humidity influence. By measuring sensor output at different temperatures and establishing a functional relationship, the system can predict and compensate for humidity effects based on temperature measurements, maintaining precision without requiring actual humidity exposure during calibration.
2Measurement precision
If calibration is performed after humidity absorption to ensure accuracy, then measurement precision is improved, but calibration time increases significantly due to slow saturation process
Solution Approach 1:
The patent determines humidity influence characteristics in advance during manufacturing by measuring sensor behavior at different temperatures. This preliminary characterization allows the system to calculate correction values beforehand, eliminating the need to wait for humidity saturation during calibration while still achieving accurate compensation.
Solution Approach 2:
The patent replaces the physical process of humidity absorption (which takes days) with a mathematical model based on temperature measurements. By using a functional relationship between temperature and sensor output to represent humidity influence, the system achieves the same calibration accuracy instantly without the time-consuming physical saturation process.
3Ease of manufacture
If standard calibration methods are used without considering humidity influence, then calibration process is simple and fast, but systematic errors occur after humidity exposure reducing reliability
Solution Approach 1:
The patent introduces temperature as an additional measurement parameter to characterize humidity influence. By measuring sensor output at multiple temperatures and establishing a functional relationship, the system can predict humidity effects and apply corrections, maintaining both simplicity and reliability.
Solution Approach 2:
The patent implements feedback by using temperature measurements to determine the current humidity influence state and applying corresponding correction values. The system continuously monitors temperature and adjusts the compensation based on the established functional relationship, ensuring reliable operation under varying environmental conditions.
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 ensures that sensor output values remain within tolerance ranges by compensating for humidity and temperature-related deviations, enabling precise measurements even after exposure to moisture, thus improving the accuracy and reliability of sensor data.
Implementation Method 1
The sensor element can for example be a piezoresistive element, by which the vibrations can be detected
Implementation Method 2
a sensor characteristic is recorded by determination of at least one measurand at at least two different temperatures
Data Source
AI summary
In a method for calibrating at least one sensor having at least one signal-conducting connection to at least one signal converter, a sensor characteristic is recorded by the determination of at least one measurand at at least two different temperatures, the extent of the influence of a further value influencing the sensor is determined from the sensor characteristic by means of a functional relation, the extent of the influence of the further influencing value is considered in the calibration and the influence of the further influencing value is balanced in the calibration. As a result, the influence of a further influencing value acting on the sensor is corrected. The sensor can be a structure borne sound sensor which may have a membrane with a sensor element arranged on the membrane. Vibrations on the membrane can be captured by the sensor element, such as a piezoresistive element.