HVAC Fault Detection Using Existing Temperature and Power Data
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Solution Overview
Problem
Traditional non-communicating HVAC systems are unable to effectively display faults without increasing costs and installation time due to the need for multiple sensors.
Innovation Solution
An HVAC system with a system controller, indoor and outdoor temperature sensors, and a power measuring device that tracks performance data and generates fault signals based on changes in power consumption and temperature data, which can be communicated wirelessly or via a wired connection, allowing for fault detection without the need for extensive additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If accessory systems with multiple sensors are retrofitted on HVAC units to display faults, then fault detection capability is improved, but system cost and installation time increase
Solution Approach 1:
The patent makes existing HVAC components perform multiple functions. The outdoor unit's existing temperature sensor and power consumption measurements are used not only for their primary purposes but also for fault detection by comparing actual performance against expected performance based on outdoor temperature data. This eliminates the need for separate dedicated fault detection sensors.
Solution Approach 2:
The system uses the HVAC unit's own existing data (temperature sensor readings and power consumption measurements) to perform self-diagnosis and fault detection. The controller compares actual performance data against expected performance curves stored in memory, allowing the system to detect faults without external monitoring equipment.
2Reliability
If accessory systems with multiple sensors are retrofitted on HVAC units to display faults, then fault detection capability is improved, but installation time increases
Solution Approach 1:
The patent makes existing HVAC components perform multiple functions. The outdoor unit's existing temperature sensor and power consumption measurements are used not only for their primary purposes but also for fault detection by comparing actual performance against expected performance based on outdoor temperature data. This eliminates the need for separate dedicated fault detection sensors.
Solution Approach 2:
The system uses the HVAC unit's own existing data (temperature sensor readings and power consumption measurements) to perform self-diagnosis and fault detection. The controller compares actual performance data against expected performance curves stored in memory, allowing the system to detect faults without external monitoring equipment.
3Ease of manufacture
If traditional non-communicating HVAC systems are used, then system cost is reduced, but fault display capability is lost
Solution Approach 1:
The system implements feedback by continuously monitoring performance data (outdoor temperature, power consumption) and comparing it against expected performance curves. When actual performance deviates from expected performance, the system generates fault indicators. This feedback mechanism enables fault detection using only existing system components without requiring additional expensive communication infrastructure.
Solution Approach 2:
The patent replaces complex mechanical sensor systems with a computational approach. Instead of using physical sensors to directly detect faults, the system uses the controller to process existing temperature and power data, compare it against stored performance curves, and generate fault indicators through algorithmic analysis. This substitution reduces hardware complexity and cost.
Data Source
AI summary
A system and method for monitoring performance of an HVAC unit by receiving outdoor temperature data from an outdoor temperature source and indoor temperature data from an indoor temperature source, tracking performance data of the HVAC unit based at least in part on the outdoor temperature data and the indoor temperature data, receiving power consumption data from the power measuring device, tracking the power consumption data based at least in part on the outdoor temperature data, determining whether there is a change in the performance data and the power consumption data, and generating a fault signal based at least in part on the change in the performance data and the power consumption data.


