Model-Based Measurement Calibration for Sensor Drift and Nonlinearity
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Solution Overview
Problem
Existing measurement systems face challenges in achieving high accuracy due to design flaws that prevent owner-users from performing reliable recalibration, leading to costly and time-consuming recalibration processes. Additionally, these systems are limited by nonlinear physical phenomena, requiring complex correction factors and restricting their accuracy and utility.
Innovation Solution
The development of high-accuracy measurement systems that incorporate a model-based approach, allowing for explicit representation and configuration of models by the owner-user. This includes calibration methods using reference devices and adaptive systems that account for sensor drift and nonlinearity, enabling dynamic reconfiguration and improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If factory calibration and sealing are used to maintain accuracy, then measurement accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The measurement system performs self-calibration using stored reference data and environmental sensors. The microcontroller automatically adjusts calibration parameters based on sensed conditions without requiring external laboratory equipment or manufacturer intervention, eliminating the need for sealed factory calibration
Solution Approach 2:
Reference calibration data for multiple environmental conditions is pre-stored in memory during manufacturing. The system retrieves and applies the appropriate calibration data based on currently sensed environmental conditions, performing calibration preparation in advance rather than requiring real-time laboratory calibration
2Measurement precision
If frequent recalibration is performed to maintain accuracy, then measurement accuracy is improved, but loss of time and productivity decrease
Solution Approach 1:
The system continuously performs calibration adjustments in the background based on real-time environmental sensing and stored reference data. This continuous self-calibration eliminates the need to take the device out of service for periodic recalibration, maintaining uninterrupted measurement capability
Solution Approach 2:
The measurement system autonomously performs calibration without requiring external intervention or removal from service. The microcontroller automatically senses environmental conditions, retrieves appropriate calibration data from memory, and adjusts calibration parameters in real-time, eliminating time loss associated with traditional recalibration schedules
3Measurement precision
If correction factors are used to account for nonlinearity, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
Correction factors for nonlinear effects are pre-calculated and stored in memory during manufacturing for various environmental conditions and measurement ranges. The system automatically retrieves and applies the appropriate correction factors based on current conditions, eliminating the need for complex real-time calculations
Solution Approach 2:
Complex mechanical or manual correction procedures are replaced by digital storage and retrieval of correction factors in memory. The microcontroller automatically applies stored correction algorithms based on sensed conditions, replacing what would otherwise require complex user intervention or additional hardware
4Measurement precision
If high-accuracy laboratory equipment is used, then measurement accuracy is improved, but cost increases
Solution Approach 1:
The measurement system performs its own calibration using internally stored reference data and environmental sensors, eliminating the need for expensive external laboratory calibration services. The microcontroller automatically manages calibration without requiring costly professional intervention
Solution Approach 2:
The system uses inexpensive non-volatile memory to store reference calibration data that would otherwise require expensive laboratory equipment to maintain. By storing multiple sets of calibration data for different conditions in cheap memory, the system replaces the need for ongoing expensive laboratory calibration services
Data Source
AI summary
Systems and methods for measurement and management provide complex measurements cost-effectively at very high accuracy. These methods and systems in some cases achieve measurement accuracy exceeding the accuracy of the reference standards they rely on, and eliminate expensive and disadvantageous recalibration procedures. The accurate measurements are integrated with management functions, applying the measurement data to meet objectives of the integrated system and workflow goals of its user. The disclosed systems and methods comprise an explicit or expressly represented model both of themselves and of candidate external systems to be measured and managed. The models may be configured and reconfigured by the owner-user through either local or remote means. The system intelligently reconfigures itself to adapt dynamically to the conditions of measurement and the user's and system's goals at each moment. In an embodiment, the system includes high-accuracy and reconfigurable components including a meter or control head adapted for user precision assembly and maintenance that computes and displays or communicates the measurements, displaying measurements in desired units, grouping functions according to ergonomic and cognitive principles based on the activity and workflow of a user in relation to the internal model. The use of models permits the system to compute and provide complex and inferred measurements of ultimate interest to the user, including quantities that cannot be directed measured and only can be determined through reasoning or computation by applying models to raw measurement data. The precision-assembly modular electromechanical design further permits an owner-user to precisely assemble, maintain, modify the apparatus and calibrate the equipment for accuracy.