Leak detection in a subcritical boiler. (25th February 2021)

• Record Type: Journal Article
• Authors: Panday, Rupen; Indrawan, Natarianto; Shadle, Lawrence J.; Vesel, Richard W.
• Is Part Of: Applied thermal engineering. Volume 185(2021)
• Publication Date: 2021-02-25
• Subjects: Subcritical boiler -- Leak detection & isolation -- Upper control limit -- Exponential moving average filter -- Kalman filter -- Variable threshold; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2020.116371
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Only two standard flow measurements were used to detect the leak in a boiler section. A boiler tube leak was isolated using temperature measurement. Showed the equivalence between exponential moving average filter and Kalman filter. Optimal filter responded much quicker than a standard exponential filter, around 8 h earlier. A variable threshold balanced the tradeoff between the false alarm rate and leak detection rate. Abstract: Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coal-fired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.