Response Signal
Measurement error defines the deviation where an output signal fails to maintain a linear ratio against an increasing input stimulus within an inertial sensor. Non-linear acceleration bias occurs when the internal architecture of a transducer produces a non-proportional response as the inertial load exceeds the calibrated range of the device. This discrepancy arises from mechanical hysteresis or internal stress concentrations within the proof mass suspension system.
Sensor manufacturing standards designate these deviations as second order or higher terms in the characteristic transfer function.
Error Characterization
Complex polynomial models define the correction factors required to isolate the influence of non-linear acceleration bias from total sensor noise. Engineers apply a least squares regression to characterize the error across the operational temperature range and dynamic input spectrum. Calibration benches measure the voltage output against a known gravity vector to identify the specific coefficients for each sensor unit.
Static testing fails to reveal the magnitude of this effect because the dynamic stress states depend on the instantaneous magnitude of the input force.
Metrological Boundary
Hardware limitations dictate the threshold where non-linear acceleration bias invalidates the primary measurement signal. High frequency vibration environments force the internal structure of the sensing element to oscillate outside the elastic regime of the material. Saturation of the signal processor usually coincides with the point where the non-linear term exceeds the primary sensitivity parameter.
Design specifications provided by the manufacturer detail the specific g-force level at which the error term becomes dominant.
Control Consequence
Mathematical compensation routines remove the non-linear acceleration bias during the final stage of data processing. Algorithms subtract the quadratic or cubic product of the input signal from the raw measurement stream to restore linearity. Successful removal depends on the temporal stability of the sensor components over the service life of the hardware.
Residual errors remain if the sensor geometry changes due to prolonged exposure to high shock loads.
