Development of a superordinate model for controlling and/or monitoring a compressor installation
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Solution Overview
Problem
Existing compressor systems lack a universally applicable structure, and higher-level station controllers often use standard control and analysis procedures without considering the specific conditions and interrelationships of individual components, limiting the ability to analyze and evaluate their behavior effectively.
Innovation Solution
A method and system that utilizes initial models based on P&I diagrams to create derived models accounting for the causal relationships between compressors and peripheral devices, allowing for precise control, monitoring, and diagnostic routines using aspect-specific analysis algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standard control and analysis procedures are used in station controllers, then the system is easier to operate and implement, but the ability to analyze and evaluate specific compressor system behavior is limited
Solution Approach 1:
The patent segments the compressor system into individual components (compressors, dryers, filters, tanks) and creates separate models for each. This allows the system to maintain ease of operation through standardized procedures while improving analysis precision by evaluating each component's specific behavior and interrelationships.
Solution Approach 2:
The patent introduces an intermediary modeling layer that sits between the standard control procedures and the actual system behavior. This intermediary layer captures causal relationships and component interdependencies, enabling precise analysis without complicating the operational interface.
2Adaptability or versatility
If compressor systems are designed individually for specific on-site conditions, then the system adapts better to specific conditions, but a universally applicable structure cannot be established
Solution Approach 1:
The patent creates a universal modeling framework that can represent any compressor system configuration. The standardized component models and causal relationship structures can be applied universally, while the ability to customize interconnections and parameters maintains adaptability to specific on-site conditions.
Solution Approach 2:
The patent employs dynamic modeling that can adapt to different operating conditions and system configurations. The models can be configured for specific on-site conditions while maintaining a consistent universal structure, allowing the system to be both adaptable and structurally consistent.
3Measurement precision
If knowledge of system structure and component interrelationships is required for analysis, then analysis precision improves, but the complexity of implementing control procedures increases
Solution Approach 1:
The patent creates simplified representations (models) of the actual compressor system components and their relationships. These model copies capture the essential causal relationships and interdependencies, enabling precise evaluation without requiring direct complex analysis of the physical system's full complexity.
Data Source
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AI summary
A method for controlling and/or monitoring a compressor system comprising one or more compressors (11, 12, 13) and one or more peripheral devices (14 to 21) is proposed, wherein the compressors (11, 12, 13) and peripheral devices (14 to 21) are arranged or connected in a predetermined configuration, and wherein the compressor system is controlled and/or monitored via a control/monitoring unit (22). The method is characterized by the fact that, based on one or more initial models (M1, M2, ...) of the compressor system, which is based, for example, on a P&ID diagram, possibly including the specification of the compressors (11, 12, 13) and the peripheral devices (14 to 21), one or more derived models (M̃a, M̃b, ...) are generated, which represent the interactions between the individual compressors (11, 12, 13) and peripheral devices (14 to 21) and possibly other components.dynamic processes are also taken into account, and one or more derived models (M̃a, M̃b, ...) are used as the basis for subsequent control, monitoring, diagnostic or evaluation routines.