Sensor Calibration Adjustment System for Energy-Constrained Accuracy
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Solution Overview
Problem
Existing sensor systems face inefficiencies in recalibrating calibration parameters due to increased computational effort and energy consumption, particularly in response to temperature fluctuations and aging effects, which can lead to reduced accuracy over time.
Innovation Solution
An apparatus and method for adjusting calibration parameters that monitor sensor accuracy, activate recalibration only when necessary, and utilize temperature modeling to minimize energy consumption by deactivating components unless new calibration is required, ensuring high accuracy while reducing energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recalibration is performed frequently to maintain accuracy, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
The system continuously monitors the accuracy of calibration parameters and uses this feedback to determine when recalibration is necessary. The control device evaluates whether current calibration parameters still meet accuracy criteria, and only triggers recalibration when degradation is detected, creating a closed-loop control system that balances accuracy maintenance with energy conservation.
Solution Approach 2:
The recalibration frequency and intensity are made dynamic rather than static. The system adapts the recalibration process based on actual sensor performance, environmental conditions, and detected accuracy degradation. This dynamic approach allows the system to perform minimal necessary recalibration rather than following a fixed schedule, optimizing the balance between accuracy and energy consumption.
2Reliability
If recalibration components are continuously active to ensure readiness, then reliability is improved, but energy consumption increases
Solution Approach 1:
Instead of continuous operation, the control device and calibrator operate periodically based on detected needs. The system enters low-power states between monitoring cycles and only activates full recalibration functions when accuracy degradation is detected. This periodic activation pattern maintains system reliability while significantly reducing average energy consumption compared to continuous operation.
Solution Approach 2:
The sensor system performs self-diagnosis to determine when recalibration is needed. The control device automatically monitors calibration parameter accuracy and triggers recalibration only when necessary, without requiring continuous external control or intervention. This self-service approach ensures the system remains reliable while minimizing energy expenditure on monitoring and control functions.
3Measurement precision
If computational checks are performed continuously to ensure data suitability, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The system performs partial computational checks rather than complete exhaustive analysis. The measurement-data evaluation module checks only critical suitability criteria for recalibration data rather than performing comprehensive validation of all possible parameters. This partial action approach maintains sufficient accuracy assurance while significantly reducing computational overhead and improving processing speed.
Data Source
AI summary
Adjusting of calibration parameters for a sensor. The adjusted calibration parameters may be used to correct the raw data of the sensor. It is provided to calculate new calibration parameters only when accuracy of the calibration parameters currently available is no longer adequate, and suitable measurement data are available for a recalibration of the sensor. Otherwise, the components necessary for calibrating the sensor data may be deactivated in order to reduce energy consumption.