Burn in Hours That Remove the Steepest Early Drift
Thermal burn-in under active electrical bias removes early non-linear drift, locking in long-term calibration stability before sensors reach the field.
Sensor Aging Kinetics
Aging Rate
Time-and-temperature dependent material degradation mechanisms dictate the rate at which transducer parameters drift over extended operational lifespans. Understanding sensor aging kinetics allows calibration engineers to forecast long-term drift bounds and establish recalibration intervals for critical measurement hardware. Degradation modes include lattice relaxation, package stress relief, and contact oxidation.
Arrhenius Modeling
Thermal stress accelerates chemical and physical degradation processes within sensing elements and encapsulating polymers. Mathematical models for sensor aging kinetics rely on Arrhenius rate equations to transform high-temperature accelerated life test data into predicted operational drift curves. Long-term baseline drift typically follows logarithmic or square-root time dependencies.
Drift Extrapolation
Qualification protocols subject sample batches to continuous elevated temperature operating tests for thousands of hours to map drift trajectories. Analyzing sensor aging kinetics enables manufacturers to guarantee end-of-life accuracy specifications under stated environmental conditions. Parameter shifts outside statistical limits indicate unintended degradation mechanisms like intermetallic compound growth at bond wire interfaces.
Periodic field recalibration or automated software drift compensation restores baseline accuracy over product lifespans.
Reliability Life
Environmental humidity and electrical stress interact with thermal acceleration to modify overall degradation velocity. Characterizing sensor aging kinetics ensures system designs maintain required measurement margins throughout target service lives.