Air Conditioner Learning Baselines for Fault State Detection
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Solution Overview
Problem
Single-package air conditioner units face challenges in identifying when they are operating outside their intended state, making it difficult to determine if maintenance is needed or if the unit is appropriately sized for its environment, due to variations in building types, geographic locations, and user preferences.
Innovation Solution
A method and system for a single-package air conditioner that includes detecting a learning condition, initiating a learning event, measuring and recording performance, comparing baseline and operational variables, and determining fault states to adapt to environmental conditions and identify atypical performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If single-package air conditioner units are installed in various buildings and environments, then the unit can serve diverse applications and locations, but it becomes difficult to identify when the unit is operating outside its intended state or needs maintenance
Solution Approach 1:
The system performs preliminary action by establishing a baseline performance profile during an initial learning period before normal operation begins. This baseline serves as a reference point for future fault detection, allowing the system to proactively identify deviations from expected performance rather than waiting for failures to manifest
Solution Approach 2:
The system implements continuous feedback by monitoring operational parameters and comparing them against the established baseline performance profile. This feedback mechanism enables real-time detection of performance deviations that may indicate maintenance needs or malfunctions, adapting to the unit's specific installation environment
2Adaptability or versatility
If the air conditioner unit operates in different rooms or locations, then the unit can be moved and reused, but the typical or desirable performance changes with each location making fault identification difficult
Solution Approach 1:
Before the air conditioner operates in a new location, the system performs a learning event during which it collects operational data and establishes a location-specific baseline performance profile. This preliminary characterization of the installation environment enables accurate fault detection specific to that location's conditions
Solution Approach 2:
The system adapts to different locations by changing the baseline performance parameters specific to each installation environment. By storing and comparing location-specific operational characteristics, the system maintains measurement precision across diverse locations rather than using fixed universal thresholds
3Adaptability or versatility
If different users occupy the same room, then the unit can accommodate varying user preferences, but the widely different temperature preferences make it difficult to identify atypical performance
Solution Approach 1:
The system accommodates different user preferences by establishing baseline performance profiles that capture the range of normal operational variations under different user settings. By learning the specific operational characteristics associated with each user's temperature preferences and usage patterns, the system can distinguish between intentional parameter changes and actual performance faults
Data Source
AI summary
An air conditioner, as provided herein, may include a cabinet, an outdoor heat exchanger, an indoor heat exchanger, a compressor, an internal temperature sensor, and a controller. The controller may be configured to initiate a conditioning operation. The conditioning operation may include detecting a learning condition at the air conditioner, identifying a first operating mode, and initiating a learning event at the first operating mode. The conditioning operation may further include measuring performance during the learning event, recording a baseline variable based on the measured performance during the learning event, and measuring performance at the first operating mode. The conditioning operation may still further include recording an operational variable based on the measured performance at the first operating mode, comparing the operational variable of the first operating mode to the baseline variable of the first operating mode, determining a fault state based on the comparison, and recording the fault state.