Compressed Air System Modeling for Failure Prediction and Optimization
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Solution Overview
Problem
Existing compressed air systems face challenges in efficiency, energy consumption, and optimization, particularly in predicting component failures and optimizing system performance.
Innovation Solution
A system and method for modeling, simulating, optimizing, and generating quotes for compressed air systems, utilizing a computer with a modeling module, simulation module, analytics module, and recommendations module to analyze system parameters, predict failures, and provide optimization recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If compressed air systems are designed to provide compressed air at desired flow rate, pressure, temperature and quality, then system performance is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary simulation and analysis before actual system operation to predict performance and optimize design parameters. The modeling module creates virtual representations of compressed air systems to evaluate different configurations and operating conditions, allowing optimization to be done in advance rather than through trial-and-error operation, thereby reducing actual energy consumption while maintaining performance.
Solution Approach 2:
The system implements feedback mechanisms where simulation results and performance data are continuously analyzed to refine system operation. The analytics module processes system data and provides feedback for optimization, allowing the system to adjust operating parameters to minimize energy consumption while maintaining desired performance levels of flow rate, pressure, temperature and quality.
2Reliability
If existing systems are used without advanced modeling and simulation, then device complexity is reduced, but ability to predict component failures and optimize performance deteriorates
Solution Approach 1:
The system creates virtual copies or digital twins of the compressed air system components through modeling. These virtual representations allow for simulation and analysis of component behavior, failure prediction, and optimization without requiring physical modifications or complex additional hardware. The modeling module generates these digital copies that mirror the physical system's characteristics and operating parameters.
3Productivity
If comprehensive system modeling and simulation is implemented, then optimization capability is improved, but computational time and resources increase
Solution Approach 1:
The system implements partial modeling and simulation approaches, focusing computational resources on critical components and parameters that have the greatest impact on system performance. Rather than modeling every aspect of the compressed air system in full detail, the system identifies and analyzes only the most influential factors, thereby achieving effective optimization with reduced computational time and resources.
Data Source
AI summary
A computer may display on a graphical user interface (GUI) a component library including a set of components relating to a compressed air system. The GUI may have a modeling interface for configuring a virtual model using the set of components. The computer may simulate the virtual model to determine one or more optimizations to the compressed air system. The computer may also determine the cost of implementing the compressor system optimization.