HVAC Fault Detection Using Normalized Load Ratio Pattern Analysis
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Solution Overview
Problem
Current HVAC fault detection methods are complex, expensive, and have limited acceptance for small to medium-sized installations, necessitating a simpler and more economical approach to identify faults using readily available data with minimal additional equipment.
Innovation Solution
A computer-implemented system that analyzes load enabled utilization value data from HVAC units by comparing their energy consumption patterns with historical data and peer units, using normalized load ratios and thresholds to automatically detect fault conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional HVAC fault detection methods are used, then measurement precision and reliability are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts and analyzes only the most critical parameter - energy consumption patterns - from the complex HVAC system. By focusing solely on power usage data rather than monitoring all system parameters simultaneously, the method achieves reliable fault detection with minimal additional equipment, resolving the contradiction between detection accuracy and system complexity
Solution Approach 2:
The patent creates a virtual model of normal HVAC operation by collecting and analyzing historical energy consumption data. This digital copy of normal behavior patterns enables fault detection through comparison without requiring physical copies or redundant sensing equipment, thereby maintaining high detection precision while minimizing added system complexity
2Reliability
If comprehensive fault detection is implemented, then reliability is improved, but loss of information and data processing complexity increase
Solution Approach 1:
The patent performs preliminary data processing by collecting and analyzing historical energy consumption patterns before actual fault detection begins. This pre-processing establishes baseline expectations for normal operation, enabling more reliable real-time fault detection with simpler data requirements, thus improving reliability without overwhelming data processing demands
3Ease of operation
If simple fault detection methods are used, then ease of operation and cost are improved, but measurement precision and reliability decrease
Solution Approach 1:
The patent enables the HVAC system to self-diagnose faults by automatically comparing its own energy consumption patterns against historical baselines and peer group data. This self-service approach eliminates the need for complex manual monitoring or expert intervention, maintaining high detection precision while dramatically simplifying operation and reducing costs
Data Source
AI summary
Methods and systems are described for detecting a wide variety of fault conditions in a HVAC system based on analysis of current and historical energy consumption patterns, and on comparison with energy consumption patterns of other similarly situated RTUs. Energy consumption comparisons are preferably made in regard to a normalized load ratio or NLR or more preferably to a daily maximum normalized load ratio or MDNLR, which provide more robust and reliable bases for comparison of faulty and fault-free RTUs, and hence for generalized fault detection, than other previously known metrics or criteria.