To check whether a sensor's accuracy has degraded, systematic verification methods must be adopted. First, perform regular calibration comparisons using a standard source or a higher-accuracy-grade sensor of the same type as a reference. Select 3-5 typical points within the measurement range (such as zero, mid-scale, and full-scale) for simultaneous measurement; errors exceeding the allowable tolerance indicate accuracy degradation. Zero drift and span drift are core indicators—disconnect the input signal to check the zero output, then apply a standard full-scale signal. If deviations exceed the values specified in the technical datasheet, recalibration or replacement is necessary.
Long-term trend analysis is equally critical. Record the sensor's historical output under identical operating conditions via a data acquisition system, and use Statistical Process Control (SPC) methods to monitor data dispersion and mean shifts. Persistent unidirectional drift often signals aging. Environmental factor investigation cannot be overlooked—verify that temperature, humidity, vibration, and electromagnetic interference remain within the sensor's permissible limits, as these can cause temporary or permanent accuracy loss.
For smart sensors, internal status parameters can be read through self-diagnostic functions, such as bridge resistance in strain gauge sensors or dielectric constant changes in capacitive sensors. In field testing, employ the step response method for rapid assessment: apply an instantaneous standard input and observe the time to reach steady state and the overshoot amount. A slower response or increased oscillation both suggest performance degradation. It is recommended to establish a preventive maintenance cycle, calibrating critical sensors every 6-12 months, and formulate replacement schedules based on MTBF (Mean Time Between Failures) data.
