Heat Exchanger Dirt Detection Using Air Temperature Time Series
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Solution Overview
Problem
Existing air-conditioning apparatuses inaccurately detect dirt on air filters or heat exchangers due to temporary environmental changes, causing false alarms when temperature differences exceed predetermined thresholds.
Innovation Solution
An air-conditioning apparatus that determines dirt levels based on time-series data of temperature differences between suction air and cooled/heated air temperatures, using a set temperature zone and determination period to accurately assess dirt presence regardless of environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If temperature difference threshold method is used to detect dirt on heat exchanger, then detection simplicity is improved, but detection accuracy deteriorates due to false alarms from temporary environmental changes
Solution Approach 1:
The patent transitions from a static threshold comparison method to a dynamic time-series analysis method. Instead of simply comparing temperature difference against a fixed threshold, the system continuously monitors temperature differences over time and analyzes trends, enabling accurate detection that adapts to changing environmental conditions while maintaining operational simplicity.
Solution Approach 2:
The system implements continuous feedback by repeatedly measuring temperature differences and comparing current readings with historical data. This feedback mechanism allows the system to distinguish between temporary environmental fluctuations and actual dirt accumulation on the heat exchanger, improving detection accuracy without complicating the operational interface.
2Reliability
If frequent maintenance is performed to ensure accurate detection, then detection reliability is improved, but productivity deteriorates due to increased maintenance frequency
Solution Approach 1:
The system performs self-diagnosis by automatically monitoring its own operational parameters (temperature differences across the heat exchanger) and detecting anomalies that indicate dirt accumulation. This self-service capability ensures reliable detection without requiring frequent manual inspections or maintenance interventions, thereby maintaining productivity while ensuring detection reliability.
Solution Approach 2:
The system continuously accumulates and analyzes temperature difference data in advance, detecting dirt accumulation trends before they significantly impact performance. This preliminary detection allows for timely, targeted maintenance only when actually needed, reducing overall maintenance frequency while maintaining reliable detection capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach prevents erroneous detections caused by temporary environmental changes, allowing for accurate assessment of dirt levels and reducing maintenance frequency by optimizing operating capacity based on dirt degree.
Implementation Method 1
a heat exchange unit that causes heat exchange to be performed between air and a refrigerant
Data Source
Figure 1~2
Figure 3
AI summary
An air-conditioning apparatus includes: a suction-air temperature detection unit that detects the temperature of air that is sucked into a heat exchange unit or the temperature of space to be subjected to heat exchange as a suction air temperature; a cooled/heated-air temperature detection unit that detects the temperature of air blown from the heat exchange unit or the temperature of the heat exchange unit as a cooled/heated air temperature; and a control device that acquires data on a temperature difference between the suction air temperature detected by the suction-air temperature detection unit and the cooled/heated air temperature detected by the cooled/heated-air temperature detection unit at different times as time-series data, and determines whether the heat exchange unit is dirty or not based on the time-series data regarding the temperature difference.