Novel Method for Processing the Dynamic Calibration Signal of Pressure Sensor

Area of Science:

• Sensor Technology
• Signal Processing
• Dynamic Systems Analysis

Background:

• Dynamic calibration is crucial for obtaining accurate dynamic performance parameters of pressure sensors.
• Extracting true step response signals from noisy sensor outputs presents a significant challenge.

Purpose of the Study:

• To develop an effective method for processing pressure sensor output to extract true step response information under strong interference noise.
• To establish a dynamic model that accurately characterizes the dynamic performance of a calibrated pressure sensor.

Main Methods:

• A dynamic calibration system using a shock tube was employed to generate time-domain response signals.
• Difference modeling and fusion of generating sequences were applied to extract true signal information.
• QR decomposition was utilized to establish a dynamic model from the processed signal data.

Main Results:

• The proposed method successfully filtered strong interference noise from the pressure sensor output.
• The established dynamic model effectively characterized the dynamic performance of the pressure sensor.
• Validation through calibration tests and frequency-domain experiments confirmed the method's efficacy.

Conclusions:

• The developed signal processing technique enhances the accuracy of dynamic performance parameter acquisition for pressure sensors.
• This research provides a robust approach for dynamic calibration and modeling of pressure sensors in noisy environments.