Computer Model for Heat Transfer Fluid Life Estimation
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Solution Overview
Problem
Existing hardware and sensor-based systems for assessing heat transfer fluid quality are inaccurate, costly, and time-consuming, providing only real-time assessments without predicting fluid life, leading to detrimental effects on machinery and unnecessary resource consumption.
Innovation Solution
A computer-implemented method that generates an estimate of fluid life and quality score using historical data and machine learning models, analyzing parameters such as molecular weight, moisture content, and conductivity to predict fluid condition and life expectancy, improving user interfaces and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If sensor-based systems and hardware measurement systems are used to assess heat transfer fluid quality, then real-time assessment capability is improved, but measurement precision and predictive accuracy deteriorate
Solution Approach 1:
The patent creates a virtual copy of the physical measurement system through a computer model that replicates fluid degradation patterns. Instead of relying on direct sensor measurements that provide only real-time snapshots, the model uses historical data to create a virtual representation of fluid condition, enabling both real-time assessment and predictive accuracy simultaneously
Solution Approach 2:
The system performs preliminary analysis by establishing baseline fluid conditions and degradation patterns before actual failure occurs. Historical data is used to pre-determine fluid life expectancy and quality thresholds, allowing the system to predict future fluid conditions rather than merely measuring current state, thus improving measurement precision while maintaining real-time capability
2Reliability
If conventional fluid quality measurement systems are used, then hardware infrastructure is maintained, but productivity and resource efficiency deteriorate
Solution Approach 1:
The computer model performs self-service by automatically analyzing historical data and generating fluid life predictions without requiring continuous manual intervention or expensive hardware infrastructure. The system uses pre-established algorithms and historical records to autonomously assess fluid quality and predict failures, improving productivity while maintaining reliability
Solution Approach 2:
The patent transforms the assessment approach by changing from physical measurement parameters to computational parameters. Instead of relying on continuous hardware monitoring that consumes resources, the system uses discrete historical data points and computational models to determine fluid condition, reducing resource consumption while maintaining or improving reliability through more comprehensive data analysis
3Measurement precision
If extensive historical data analysis is performed to improve prediction accuracy, then measurement precision is improved, but device complexity and computing resources increase
Solution Approach 1:
The patent segments the complex historical data into distinct degradation patterns and key parameters (such as molecular weight changes, moisture content, acid number). By dividing the complex fluid degradation process into manageable segments and focusing on the most influential parameters, the model achieves high prediction accuracy without requiring analysis of every possible variable, thus controlling device complexity
Solution Approach 2:
The system extracts only the most critical historical data elements and patterns needed for accurate fluid life prediction, filtering out redundant information. By taking out and focusing on key degradation indicators rather than processing all available data, the model maintains high measurement precision while reducing the computational burden and model complexity
Data Source
AI summary
Various embodiments are directed to improving the accuracy of existing hardware-based fluid quality measurement systems and particular computer applications. For instance, some embodiments improve the accuracy of these technologies by generating, via a computer model, an estimate of a fluid life for a heat transfer fluid and/or a score that indicates a quality of the heat transfer fluid, among other things. Additional embodiments also improve human-computer interaction, user interfaces, and computer resource consumption relative to existing technologies.