Drain Pump Clog Prediction Using Image-Based Object Detection
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Solution Overview
Problem
When the drain pump in an air conditioner becomes clogged, water can overflow from the drain pan, even after the cooling operation is stopped, due to the heat exchanger remaining in a cooled state, leading to potential water overflow issues.
Innovation Solution
A drain pump clog prediction device that uses image capture technology to obtain information about objects in the drain pan, calculates the object amount, size, and inflow amount, and predicts clogging based on these metrics, adjusting its prediction cycle and period according to the air conditioner's operating load and environment to provide accurate clogging occurrence rates and times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image capturing is used to monitor the drain pan continuously, then the prediction accuracy of clogging is improved, but the energy consumption and device complexity increase
Solution Approach 1:
The system performs image capturing at periodic intervals rather than continuously, with the capture cycle dynamically adjusted based on operating conditions. The control unit determines appropriate capture intervals based on the operational state of the air conditioner, reducing energy consumption while maintaining adequate monitoring coverage for clogging detection
Solution Approach 2:
The image capture cycle is made dynamic rather than fixed. The control unit adjusts the capture interval based on real-time operating conditions, such as the operational state of the air conditioner and environmental factors. This allows the system to capture images more frequently when clogging risk is higher and less frequently when conditions are stable, optimizing both accuracy and energy efficiency
2Measurement precision
If multiple parameters (object amount, size, inflow amount) are calculated from images, then the clogging prediction accuracy is improved, but the calculation complexity and processing time increase
Solution Approach 1:
The clogging prediction process is divided into separate calculation modules, each handling a specific parameter (object amount, object size, object inflow amount). The control unit independently calculates each parameter based on image data, allowing for modular processing and easier implementation of complex calculations without overwhelming the system at once
Solution Approach 2:
The system calculates multiple parameters beyond what might be strictly necessary for basic clogging detection. By computing object amount, object size, and object inflow amount simultaneously, the system gathers comprehensive data that improves prediction accuracy and provides more information for maintenance planning, even though this increases calculation complexity
3Measurement precision
If the image capture cycle is shortened to monitor objects flowing into the drain pan, then the object inflow amount calculation accuracy is improved, but the energy consumption and processing load increase
Solution Approach 1:
The system uses periodic image capturing with dynamically adjusted intervals to monitor objects flowing into the drain pan. The capture cycle is optimized to provide sufficient data for accurate inflow amount calculation while avoiding excessive processing. The control unit determines appropriate intervals based on operational conditions, balancing measurement accuracy with processing efficiency
Data Source
AI summary
A drain pump clog prediction device predicts the clogging of a drain pump, which is configured to drain water out of a drain pan of an air conditioner. The drain pump clog prediction device includes an obtaining portion that obtains information related to an object in the drain pan and a prediction portion calculates at least one of an object amount, an object size, and an object inflow amount based on information obtained by the obtaining portion and predicts occurrence of the clogging of the drain pump based on at least one of the object amount, the object size, and the object inflow amount.