Steady-State Data Processing for Refrigerant Leak Detection Accuracy
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Solution Overview
Problem
Existing methods for detecting refrigerant leaks in air source air conditioners are prone to false determinations due to data collected during changing operation states, which can lead to inefficiencies, environmental pollution, and potential fines, as they do not accurately distinguish between steady-state and unsteady-state data.
Innovation Solution
A data processing method that resets cumulative changes and detection periods, adjusts data collection based on thresholds for compressor frequency, ambient temperature, and other parameters, determining data as steady-state or unsteady-state to ensure accurate analysis for refrigerant leak detection, system performance evaluation, and fault identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is collected during changing operation states, then data collection frequency is high and response time is fast, but determination accuracy deteriorates due to false positives from unsteady-state conditions
Solution Approach 1:
The system performs preliminary assessment by calculating the degree of change for multiple operation parameters (compressor frequency, ambient temperature, water temperatures) before conducting refrigerant leak determination. This preliminary action filters out unsteady-state data by comparing parameter changes against predefined thresholds, ensuring that only stable operation data is used for accurate refrigerant leak detection
Solution Approach 2:
The system dynamically adjusts data selection based on real-time operation state assessment. By continuously monitoring parameter changes and adapting the determination process to current steady-state or unsteady-state conditions, the system maintains high accuracy while responding to changing operational conditions
2Measurement precision
If data detection period is extended to ensure steady-state conditions, then determination accuracy improves, but response time deteriorates
Solution Approach 1:
The system performs preliminary change-degree assessment on multiple operation parameters before refrigerant leak determination. This preliminary action identifies steady-state conditions efficiently without requiring extended detection periods, as it evaluates parameter stability through calculated degree of change rather than prolonged monitoring
Solution Approach 2:
The system monitors multiple operation parameters (compressor frequency, ambient temperature, evaporator and condenser water temperatures) simultaneously. This partial monitoring of key parameters provides sufficient steady-state verification without requiring excessive detection time, as not all parameters need to be monitored at maximum frequency
Data Source
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AI summary
The present application provides a data processing method, a refrigerant leak detecting method, a system performance detecting method and a system fault detecting method. The steady-state data processing method includes: (i), resetting a cumulative change of target determination data and a data detection period as 0; (ii), obtaining the detected target data; (iii), calculating the cumulative change of the target data; (iv), when the calculated cumulative change of the target data is less than its preset threshold, adjusting the data detection period and returning to (ii); or recording a data detection period when a cumulative change of any of the target data is not less than its preset threshold; (v), when the recorded data detection period is less than its preset time threshold, determining a target data result obtained in the period as unsteady-state data of the device; or when the recorded data detection period is not less than the preset time threshold, determining the target data obtained in the data detection period as steady-state data. According to the method, the steady-state data can be obtained and subsequent analysis and processing can be performed.