Boiler Steam Leak Detection Using Makeup Water Prediction
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Solution Overview
Problem
Existing boiler steam leak detection technologies inaccurately identify leaks due to misinterpretation of phenomena caused by factors other than tube leaks.
Innovation Solution
An abnormality detection device and method that acquires operation data from boiler extraction devices, derives a predicted makeup water amount through statistical processing, and compares it with actual measurements to accurately detect steam leaks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If phenomena observation method is used to detect tube leaks, then detection capability is provided, but false positives occur due to phenomena caused by factors other than tube leaks
Solution Approach 1:
The invention segments the water circulation system into multiple monitoring points including extraction devices and makeup water supply points. By dividing the detection into separate measurement locations and comparing data from each segment, the system can identify anomalies specifically related to tube leaks rather than general system variations.
Solution Approach 2:
The invention implements a feedback mechanism where the detected anomaly information is fed back to adjust the detection thresholds and parameters. The system continuously monitors the relationship between extraction water amounts and makeup water amounts, and dynamically adjusts detection criteria based on accumulated operational data to reduce false positives.
2Adaptability or versatility
If multiple phenomena are monitored to improve detection coverage, then more leak scenarios can be detected, but false positives increase due to non-leak phenomena
Solution Approach 1:
The invention introduces makeup water amount as an intermediary parameter that mediates between extraction device operation and system water balance. By using this intermediate measurement point and analyzing the relationship between extraction water and makeup water, the system can indirectly detect tube leaks without directly monitoring all possible leak phenomena, thereby maintaining detection coverage while reducing false positives.
3Device complexity
If traditional observation methods are used, then detection system is simple, but detection accuracy is insufficient due to misinterpretation of non-leak phenomena
Solution Approach 1:
The invention replaces traditional mechanical observation methods with a data-driven detection system that uses sensors to measure extraction water amounts and makeup water amounts, then applies computational analysis to detect anomalies. This substitution of mechanical observation with electronic sensing and data processing improves detection precision while maintaining relatively simple system architecture.
Data Source
AI summary
Provided is an abnormality detection device, including: a data acquisition unit configured to acquire operation data of one or a plurality of extraction devices configured to extract water from a water circulation system in a boiler to an outside of the circulation system, and acquire an actually measured value of a makeup water amount supplied to the circulation system; a prediction unit configured to derive a predicted value of the makeup water amount based on the operation data acquired by the data acquisition unit; and a comparison unit configured to compare the actually measured value of the makeup water amount, which is acquired by the data acquisition unit, and the predicted value of the makeup water amount, which is derived by the prediction unit, with each other.