Accelerometer Scale Factor Non-Linearity

Polynomial Characterization

Mathematical models for this phenomenon often use second or third order coefficients to describe the curvature of the response. Engineers identify accelerometer scale factor non-linearity by collecting data points across the full dynamic range of the instrument and calculating the residuals against a linear regression. These residuals indicate how the sensitivity of the proof mass assembly changes under different loading conditions.

The characterization process involves high precision centrifuges or tilt tables that can repeatably apply known gravitational vectors to the sensing element. By isolating the non-linear component, software compensation can mitigate the effect in real-time processing.

Error Distribution

Error patterns typically show the largest magnitude at the extremes of the operational envelope. If the accelerometer scale factor non-linearity is poorly characterized, the resulting data introduces errors into velocity and position calculations that grow over time. Manufacturers specify this value in parts per million of the applied acceleration squared to provide a normalized metric for comparison across different sensor grades.

Thermal Sensitivity

Changes in ambient temperature often alter the internal mechanical stresses of the sensor housing. This fluctuation impacts the accelerometer scale factor non-linearity by shifting the spring constants or the capacitive gap distances within the micro-structure. Calibration cycles must therefore account for thermal gradients to ensure the non-linear components remain within specified tolerances during field operations.