HVAC Equipment Performance Mapping for Fault Detection and Diagnostics
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Solution Overview
Problem
Existing HVAC systems, particularly chilled water plants, face difficulties in identifying and addressing malfunctions and performance degradation due to the complexity of their components and interrelated operations, leading to inefficiencies and inaccurate monitoring and maintenance.
Innovation Solution
Performance mapping is achieved by generating maps that outline expected equipment performance based on operating conditions, using model values and coefficients to capture and compare performance data, enabling more accurate monitoring, diagnostics, and maintenance through a parameterization system that includes a device, memory, and controllers for continuous commissioning and energy optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple devices and parts are used to achieve common cooling function, then the cooling capability is improved, but the difficulty of identifying malfunction source increases
Solution Approach 1:
The patent segments the complex HVAC system into individual device-level performance models, where each device (chiller, pump, fan, valve) has its own performance map and health indicators. This segmentation allows independent monitoring and diagnosis of each component, making it easier to identify malfunction sources while maintaining overall system cooling capability.
Solution Approach 2:
The patent introduces performance maps and health indicators as intermediary elements between system components and monitoring systems. These intermediaries translate complex multi-device interactions into measurable performance parameters, enabling easier identification of malfunction sources without reducing the system's cooling capability.
2Loss of information
If performance monitoring is implemented in existing HVAC systems, then operational awareness is improved, but measurement accuracy is insufficient
Solution Approach 1:
The patent performs preliminary action by establishing device-level performance maps during manufacturing or commissioning, before actual operation begins. These pre-established maps serve as reference benchmarks that enable accurate measurement and comparison of actual performance during operation, improving both operational awareness and measurement precision.
Solution Approach 2:
The patent changes the monitoring approach from system-level aggregate parameters to device-level specific parameters. By tracking individual device performance parameters against their unique performance maps, the system achieves higher measurement accuracy and more detailed operational awareness.
3Productivity
If traditional monitoring methods are used, then system operation is maintained, but fault detection and diagnostics accuracy is poor
Solution Approach 1:
The patent implements feedback mechanisms by continuously comparing actual device performance against pre-established performance maps and health indicators. This feedback loop enables real-time fault detection and diagnostics, allowing the system to maintain operation while accurately identifying and responding to malfunctions.
Solution Approach 2:
The patent replaces traditional mechanical monitoring methods with data-driven performance modeling and analysis. By substituting physical inspection and simple sensors with computational performance maps and health indicator algorithms, the system achieves superior fault detection accuracy while maintaining continuous operation.
Data Source
AI summary
Performance mapping of equipment performance parameters by capturing, mapping, and/or structuralizing equipment performance data of a device for installation in a system. This includes generating performance maps which outline the expected feature performance parameter behavior of the equipment based on a set of operating parameters that capture the operating conditions. Each performance parameter on the map is representative of an operating point of specific operating conditions taken at a particular point in time. In one example, a performance parameter can be defined by an individualized set of parameter coefficients which in turn are dependent on instantaneous operating conditions. With the performance maps determined individually for devices as part of the system, and stored along with a time of testing, activities such as continuous commissioning, monitoring and verification, preventative maintenance, fault detection and diagnostics, as well as energy performance benchmarking and long term monitoring can be performed.