Cooling System Degradation Detection Under Steady-State Operation
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Solution Overview
Problem
Cooling systems experience degradation over time, leading to inefficiencies and potential downtime due to issues like refrigerant leakage, condenser fouling, and compressor wear, which existing detection methods fail to address effectively.
Innovation Solution
A method for detecting component degradation in cooling systems by evaluating operating parameters using rule-based and distance-based methods, generating degradation evaluation values, and triggering alarms or countermeasures based on predefined criteria, without requiring a server for historical data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing detection methods are used to monitor cooling system components, then system operation continues without interruption, but component degradation is not detected early leading to inefficiencies and downtime
Solution Approach 1:
The cooling system performs self-diagnosis by using its existing sensors and controller to monitor its own operational parameters. The controller evaluates parameters like suction superheat, discharge temperature, and power consumption against predefined criteria to detect degradation, eliminating the need for external detection equipment.
Solution Approach 2:
The system continuously monitors operational parameters and provides feedback to the controller, which compares actual values against expected ranges. When parameters deviate from normal operation patterns, the system generates alerts or adjusts operation to address degradation before it causes failure.
2Measurement precision
If multiple operational parameters are monitored continuously to detect degradation early, then detection accuracy improves, but false alarms increase
Solution Approach 1:
The system establishes baseline operational parameters and degradation thresholds in advance during normal operation. By pre-defining criteria for what constitutes normal versus degraded operation, the system can accurately detect degradation without generating false alarms, as the thresholds are calibrated to account for normal variations.
Solution Approach 2:
The system monitors multiple parameters simultaneously (suction superheat, discharge temperature, power consumption, refrigerant flow) and evaluates them in combination rather than isolation. This multi-parameter approach improves detection accuracy while reducing false alarms, as degradation typically manifests as a pattern across multiple parameters rather than isolated anomalies.
Data Source
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AI summary
A method including: determining whether a cooling system is operating in a cooling mode, such that the cooling system is not operating in a reheat mode, a humidification mode or a dehumidification mode; determining whether the cooling system is operating in a compressor mode, such that the cooling system is not operating in a pump refrigerant economization mode; determining whether the cooling system is at steady-state; and if the cooling system is operating in the cooling mode and the compressor mode and is at steady-state, evaluating one or more rules to determine if a degradation symptom exists for the cooling system. The method further includes: subsequent to the evaluation, generating a degradation evaluation value to indicate whether the one or more rules are satisfied; and based on the degradation evaluation value, generating an alarm signal or performing a countermeasure.