Sensor Calibration System Reducing Power Consumption
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Solution Overview
Problem
MEMS devices face errors due to undesirable movements from large external acceleration or shock, leading to false measurements and the need for frequent recalibration, which consumes significant power in host devices.
Innovation Solution
A system and method that utilize multiple sensors to generate and compare orientation signals, initiating calibration only when the output exceeds a threshold, thereby reducing unnecessary recalibration and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are re-calibrated periodically to eliminate spurious errors, then measurement accuracy is improved, but power consumption of the host device increases significantly
Solution Approach 1:
The system performs preliminary actions by continuously monitoring sensor outputs and comparing them against threshold values to predict when calibration will be needed. This allows the system to prepare for calibration only when necessary, rather than performing it periodically regardless of actual sensor drift conditions, thereby reducing unnecessary power consumption while maintaining measurement accuracy.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring sensor outputs and using this information to determine when calibration is actually needed. The sensor output is compared against threshold values, and this feedback loop allows the system to dynamically adjust calibration timing based on real-time sensor performance, eliminating unnecessary recalibration cycles and associated power consumption.
2Measurement precision
If all sensors in a device are re-calibrated, then measurement accuracy is maintained, but power consumption increases significantly
Solution Approach 1:
The system segments the calibration process by treating each sensor individually rather than recalibrating all sensors simultaneously. The method determines whether each specific sensor needs calibration based on its own output characteristics and threshold comparisons, allowing selective calibration of only the affected sensor(s) rather than the entire sensor array, thereby significantly reducing power consumption.
Solution Approach 2:
The system applies local quality by customizing the calibration approach for each individual sensor based on its specific performance characteristics. Instead of applying a blanket recalibration to all sensors, the system evaluates each sensor's output against its own threshold and calibrates only those sensors that actually require it, optimizing power consumption while maintaining overall measurement accuracy.
3Reliability
If calibration is performed frequently to ensure accuracy, then measurement reliability is improved, but device operation time decreases due to repeated calibration cycles
Solution Approach 1:
The system performs preliminary monitoring of sensor outputs against threshold values to predict calibration needs before they actually affect measurement reliability. This allows the system to schedule calibration only when necessary, rather than performing frequent unnecessary calibration cycles that would reduce device operation time while providing no additional reliability benefit.
Solution Approach 2:
The system uses feedback from continuous sensor output monitoring to determine actual calibration needs. By comparing sensor outputs against threshold values and using this feedback to trigger calibration only when necessary, the system maintains measurement reliability while avoiding unnecessary calibration cycles that would reduce device operation time.
Data Source
AI summary
A method and system to determine orientation of a device is disclosed. The device includes a plurality of sensors. A first signal indicative of an orientation of the device is generated using at least a first subset of sensors, with at least one sensor. A second signal indicative of the orientation of the device is generated using at least a second subset of sensors, with at least one sensor. The first signal and the second signal is compared to determine if indicated orientation is acceptable. If the orientation is not acceptable, one or more sensors are calibrated.