Building Device Relationship Discovery Through Test-Signal Correlation
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Solution Overview
Problem
Manually defining relationships between building systems, such as air handling units and variable air volume devices, is tedious and error-prone, leading to system-wide inefficiencies and missed optimization opportunities for energy efficiency and control.
Innovation Solution
A method and system that automatically define control relationships between building systems by activating control devices with test signals to generate sensor data, determining correlations using variance inflation factor or cross correlation, and storing these correlations for configuration and control purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual definition of relationships between building systems is used, then configuration accuracy can be ensured, but time consumption and labor intensity increase significantly
Solution Approach 1:
The system performs self-configuration by automatically discovering and defining relationships between building systems through data analysis and correlation algorithms, eliminating the need for manual configuration while maintaining accuracy through objective measurement of system interactions
Solution Approach 2:
Manual mechanical configuration processes are replaced with automated computational methods including correlation analysis, variance inflation factor calculation, and machine learning algorithms that objectively determine system relationships based on operational data
2Reliability
If manual definition of building system relationships is performed, then relationship accuracy can be achieved, but error rate increases due to human factors
Solution Approach 1:
Human manual configuration is replaced with automated computational analysis that uses correlation coefficients, variance inflation factors, and statistical methods to objectively determine system relationships, eliminating human errors while maintaining high accuracy
Solution Approach 2:
The system continuously monitors building system operations and uses feedback from sensor data to validate and refine relationship definitions, ensuring accuracy through iterative verification against actual system behavior
3Productivity
If automated configuration methods are used, then time efficiency improves, but system complexity increases
Solution Approach 1:
The automated configuration process is divided into distinct modular stages including data collection, correlation analysis, relationship definition, and validation, with each stage handling specific tasks to manage complexity while maintaining high overall efficiency
Solution Approach 2:
A building management system serves as an intermediary layer that coordinates between various building systems and the configuration process, managing complexity through standardized interfaces and centralized control logic
Data Source
AI summary
Systems and methods for automatically defining control relationships between building systems are disclosed. A system can identify a plurality of control devices and a plurality of plurality of building devices of a building. The system can activate the plurality of control devices using a plurality of test signals to generate a set of sensor data via the building devices, and determining one or more correlations between the plurality of control devices and the plurality of building devices using the set of sensor data. The system can store the one or more correlations for use in configuring the plurality of building devices or controlling the plurality of control devices. The one or more correlations include a variance inflation factor or a cross correlation.