Building Digital Twin Graph for Flexible Equipment Diagnostics
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Solution Overview
Problem
Existing building systems face challenges in efficiently managing and processing data due to time-consuming development and lack of flexibility in analytic and control algorithms, which hinder adaptation to changing circumstances.
Innovation Solution
Implementing a digital twin system that includes a virtual representation of building equipment, enabling diagnostics through communication with the equipment, operation, and generating reports on its performance based on diagnostic message responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional analytic and control algorithms are used for building equipment diagnostics, then the system can detect equipment issues, but the development and deployment process is time-consuming and requires significant software development
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the building equipment that replicates the equipment's behavior, parameters, and operational characteristics. This digital twin can be used for diagnostics, testing, and analysis without requiring physical equipment modification or complex software development on the actual equipment, thereby reducing development time while maintaining detection reliability
Solution Approach 2:
The digital twin is populated with equipment data, parameters, and operational models in advance. Diagnostic algorithms and test scenarios can be pre-configured and validated in the digital twin environment before deployment, eliminating the need for time-consuming on-site algorithm development and testing
2Reliability
If traditional analytic and control algorithms are used for building equipment diagnostics, then the system can operate equipment monitoring, but the algorithms lack flexibility to adapt to changing circumstances or deployment situations
Solution Approach 1:
The digital twin is designed as a dynamic system that can be updated and reconfigured based on changing equipment conditions, operational scenarios, or diagnostic requirements. New parameters, test scenarios, or diagnostic algorithms can be introduced into the digital twin without modifying the physical equipment, enabling flexible adaptation to various deployment situations
Solution Approach 2:
The digital twin serves multiple functions including equipment monitoring, diagnostic testing, algorithm validation, and scenario simulation. This multi-functional platform can accommodate different diagnostic approaches and adapt to various equipment types and operational contexts, enhancing both reliability and versatility
Data Source
AI summary
A building system operates to store a digital twin comprising a building graph, the building graph comprising a plurality of nodes representing a plurality of entities of a building and a plurality of edges between the plurality of nodes representing relationships between the plurality of entities. The instructions cause the one or more processors to determine a value for a functionality indicator for a piece of building equipment based on data received from the piece of building equipment, identify a first node of the plurality of nodes representing the functionality indicator by identifying an edge of the plurality of edges relating a second node of the plurality of nodes representing the piece of building equipment to the first node, and cause the first node to store the value for the functionality indicator, or a link to the value for the functionality indicator.