Building Fault Event Snapshots for Retrospective BMS Diagnosis
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Solution Overview
Problem
Conventional building management systems (BMS) face challenges in identifying and analyzing faults, particularly due to the transient nature of alarm data, which often gets lost over time, making it difficult for operators to determine the cause of alarms, especially during non-working hours.
Innovation Solution
A method and system that capture a snapshot of data points related to faulty building equipment at the time of a fault, storing event data for later analysis via a graphical user interface, focusing on the specific data points relevant to the fault without storing unnecessary data, allowing for retrospective investigation and potential adjustments to equipment operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all data points are stored continuously for later analysis, then complete fault information is available, but storage requirements and data management complexity increase significantly
Solution Approach 1:
The system extracts and stores only the specific data points relevant to fault conditions at the moment they occur, rather than storing all continuous data. This selective extraction captures essential fault information while minimizing storage requirements.
Solution Approach 2:
The system pre-identifies and stores data points that are likely to be relevant for fault analysis before faults actually occur. By preparing the data capture framework in advance, the system ensures critical information is preserved when faults happen, without needing to store all possible data continuously.
2Measurement precision
If a comprehensive set of data points is captured for every fault, then thorough fault analysis is enabled, but processing time and computational resources increase
Solution Approach 1:
The system segments data points into specific categories relevant to different fault types. By organizing data into meaningful segments rather than processing a monolithic dataset, the system enables faster retrieval and analysis of only the pertinent information for each specific fault condition.
Solution Approach 2:
The system applies different data capture and storage strategies to different data points based on their specific relevance to fault conditions. Rather than uniformly processing all data, the system tailors the data handling approach to the local requirements of each data point, optimizing both accuracy and processing efficiency.
3Reliability
If data is stored for extended periods for retrospective analysis, then complete diagnostic information is available, but data relevance decreases and storage costs increase
Solution Approach 1:
The system pre-identifies and preserves critical fault data at the moment it becomes relevant, ensuring diagnostic accuracy is maintained without requiring long-term storage of all data. By capturing essential information proactively, the system eliminates the need to retain large volumes of data for extended periods.
Data Source
AI summary
A method for facilitating analysis of a fault in a building system. The method may include determining, by a processing circuit, occurrence of a fault, and capturing, by the processing circuit at a time of occurrence of the fault, a snapshot of conditions at the time by selecting a set of data points relating to the building equipment experiencing the fault and storing, by the processing circuit, event data comprising values of the set of data points at the time of occurrence of the fault. The method may also include facilitating analysis of the fault by providing, at a later time after the time of occurrence of the fault, the snapshot via a graphical user interface. The snapshot includes the event data.