Meaning
Spurious signal deviations that do not reflect the physical reality of the measured process represent a common source of measurement error. A sensor artifact arises from hardware limitations, electrical interference, or environmental conditions that distort the output of a measuring device. These false readings can easily be mistaken for genuine system behaviors if they are not systematically identified and filtered out.
Recognizing these anomalies is necessary for maintaining the integrity of downstream data analysis.
Spurious Signal
Sudden spikes or dropouts in data streams often indicate electrical or mechanical disturbance rather than actual process changes. For example, a loose connection might cause a sensor artifact that manifests as an instantaneous jump to a maximum value. Such events are characterized by their extreme rate of change, which exceeds any physically possible behavior of the system.
Calibration Variance
Environmental factors such as temperature or vibration can introduce systematic distortions into sensor readings. This type of sensor artifact develops slowly over time as the device drifts from its calibrated state. Regular recalibration identifies and corrects these errors.
Signal Exclusion
Filtering techniques can automatically isolate and remove anomalous data points before they reach the main analytical models. By defining bounds based on the physical limits of the system, algorithms can flag a sensor artifact for exclusion. This preprocessing prevents false data from corrupting the calculated metrics and triggering incorrect operational decisions.
