Part-Specific Sensor Diagnosis for Tolerance-Robust Self-Calibration
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Solution Overview
Problem
Existing sensor systems face challenges in achieving accurate self-diagnosis and self-calibration due to high dependence on manufacturing tolerances and varying environmental conditions, particularly in micromechanical rotation rate sensors with negative frequency splits, leading to non-satisfactory results from identical evaluation of test signals.
Innovation Solution
A method involving part-specific ascertaining of a mathematical relationship between test and response signals, allowing for precise recalibration and self-monitoring by using a processing specification that accounts for manufacturing tolerances and environmental factors, implemented in software or hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional identical evaluation of test signals is used for diagnosis, then manufacturing simplicity is maintained, but measurement precision deteriorates due to high dependence on further variables and manufacturing tolerances
Solution Approach 1:
The patent applies local quality by creating part-specific processing specifications tailored to individual sensor characteristics. Instead of using a universal evaluation method, the system determines specific mathematical relationships (including sensitivity factors and offset values) for each sensor based on its unique manufacturing tolerances and characteristics. This allows accurate diagnosis adapted to local sensor properties while maintaining overall system simplicity through automated determination of these specifications.
2Measurement precision
If manufacturing tolerances are reduced to improve diagnosis accuracy, then measurement precision improves, but manufacturing cost and complexity increase
Solution Approach 1:
The patent employs parameter changes by adjusting the processing specification parameters (sensitivity factors, offset values, mathematical relationships) based on the actual manufacturing tolerances of each sensor. Rather than tightening manufacturing tolerances, the system adapts the evaluation parameters to match the actual sensor characteristics. This allows maintaining standard manufacturing tolerances while achieving accurate diagnosis through customized parameter sets determined during sensor characterization.
3Measurement precision
If part-specific processing specifications are determined for each sensor, then measurement precision improves, but device complexity and calibration time increase
Solution Approach 1:
The patent applies preliminary action by determining the part-specific processing specifications during an initial characterization phase before the sensor enters normal operation. The system performs test signal evaluations and determines mathematical relationships, sensitivity factors, and offset values in advance. These pre-determined specifications are then stored and used for rapid self-diagnosis and self-calibration during operation, eliminating the need for time-consuming recalibration while maintaining high measurement precision.
Solution Approach 2:
The patent implements self-service through automated determination and application of part-specific processing specifications. The system automatically performs test signal evaluations, determines the mathematical relationships, and applies the customized processing specifications without requiring manual calibration or intervention. This self-calibrating capability reduces calibration time and enables the sensor to maintain accuracy autonomously throughout its operational life.
Data Source
AI summary
A method for carrying out a diagnosis of a sensor system. The method including: (i) ascertaining a processing specification of a test signal and/or of a characteristic physical variable and/or its respective change as a function of at least one part-specific property of the sensor system; and (ii) carrying out a subsequent diagnosis of a sensor element of the sensor system, using the processing specification ascertained in (i).