Temperature Compensation Method for Piezoresistive Pressure Sensors Based on Gated Recurrent Unit.

Area of Science:

• Sensor Technology
• Materials Science
• Data Science

Background:

• Piezoresistive pressure sensors are widely used but suffer from accuracy issues caused by temperature-induced drift.
• Existing compensation methods often fail to account for thermal hysteresis, limiting their effectiveness.

Purpose of the Study:

• To develop an advanced temperature compensation model for piezoresistive pressure sensors that addresses thermal hysteresis.
• To improve the accuracy and stability of pressure sensor measurements under varying temperatures.

Main Methods:

• A novel RF-IWOA-GRU model was proposed, combining Random Forest (RF) for data interpolation, Gated Recurrent Unit (GRU) networks for sequence-dependent drift, and an Improved Whale Optimization Algorithm (IWOA) for optimization.
• Experiments were conducted under continuous temperature and pressure variations to validate the model's performance.

Main Results:

• The RF-IWOA-GRU model demonstrated superior temperature compensation capabilities compared to traditional methods.
• Post-compensation, the standard deviation of pressure decreased from 10.18 kPa to 1.14 kPa.
• Mean absolute error and root mean squared error were reduced by 75.10% and 76.15%, respectively.

Conclusions:

• The proposed RF-IWOA-GRU model effectively compensates for temperature drift and hysteresis in piezoresistive pressure sensors.
• This advanced compensation strategy significantly enhances sensor accuracy and stability, outperforming conventional techniques.