Non-linear Sensitivity
Non-linear temperature sensitivity behavior describes second-order non-linearities in sensor scale factors across wide operating thermal envelopes. Quantifying thermal coefficient curvature allows sensor correction algorithms to eliminate quadratic sensitivity drift in precision pressure and acceleration transducers. Application boundaries cover static and quasi-static thermal states, excluding dynamic thermal transient effects.
Polynomial Modeling
Sensor sensitivity changes non-linearly with ambient temperature due to semiconductor piezoresistance or physical expansion properties. Accounting for thermal coefficient curvature requires second-order or third-order polynomial modeling of sensor output across temperature ranges. High-precision sensors fitted with simple linear temperature compensation exhibit residual parabolic errors at temperature extremes.
Mathematical model terms fit quadratic parabolic curves to measured sensitivity data collected during environmental chamber sweeps. Microcontroller-based signal conditioners apply real-time polynomial evaluation to neutralize non-linear temperature response.
Compensation Logic
Embedded lookup tables or polynomial engines apply corrective gain factors based on continuous temperature sensor inputs. Uncompensated second-order curvature causes full-scale span errors exceeding 0.5 percent without polynomial correction.
Characterization Method
Qualification testing measures sensor full-scale output at five distinct temperature points within environmental test chambers. Reference pressure or acceleration inputs are maintained within 0.01 percent accuracy during characterization sweeps. Calibration certificates list quadratic coefficient terms alongside standard linear temperature coefficients.