Data-driven based research on anomaly detection for high-pressure heaters in thermal power units

doi:10.3969/j.issn.1674-1951.2021.08.010

Abstract

Abstract:

To ensure the safe and economic operation of high-pressure heaters in thermal power units,data-driven research was made on anomaly detection for high-pressure heaters.The research took the performance and state of the high-pressure heater into consideration,and chose five parameters including upper end difference,lower end difference,temperature rise,water level and normal opening of drain valves as the characteristic parameters to establish a model for anomaly detection.Then,driven by the real historical operation data under steady-state condition,Principal Component Analysis was used to solve the "Curse of Dimensionality" in high-dimensional data analysis,and Mahalanobis distance and PauTa criterion were taken to determine the parameters' threshold.This method can realize the anomaly detection for high-pressure heating system.Finally,verified by a group of real historical operation data,the model can capture the early abnormalities of the high-pressure heating system effectively.By providing effective abnormal information for high-pressure heaters in thermal power units,this method can ensure the safe and economic operation of the units.

Key words: thermal power units, high-pressure heating system, data driven, anomaly detection, Principal Component Analysis

CLC Number:

TK267:TM621

HAN Xudong. Data-driven based research on anomaly detection for high-pressure heaters in thermal power units[J]. Huadian Technology, 2021, 43(8): 67-73.

Figures/Tables 10

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