With the increasing demand for electricity in modern society and the increasing complexity of advanced thermal power generation systems,improving system performance and reliability has become increasingly important.The fault diagnosis system can automatically compensate for adverse effects under noise measurement conditions.To improve the process monitoring capability and accuracy of fault diagnosis of DC boilers,a data-driven fault diagnosis method based on six ANFIS is proposed based on the strong correlation between various measurement sensors.Each ANFIS classifier can diagnose a specific boiler system fault.The effectiveness and performance of the proposed ANFIS in diagnosing six main faults of boilers under noise measurement conditions were verified through testing and simulation in different scenarios.
NETL
NSTL
万方数据
