Research on Fault Diagnosis and Early Warning of Power Plant Boiler Reheater Temperature Deviation Based on Machine Learning Algorithm

2020 
Based on the machine learning algorithm, the fault diagnosis and early warning research of the temperature deviation of the power plant boiler reheater is studied. Real-time and offline data of the power plant boiler is collected. The data is processed through expert experience and mathematical algorithms. Using PCA fault diagnosis technology, the influencing factors of the temperature deviation of the left and right sides of the reheater are found and the weight is given. Based on the machine learning regression algorithm, the temperature deviation of the left and right sides of the power plant boiler reheater is predicted. When the deviation exceeds the threshold, the system alarms. The results show that the model can find the influencing factors of the temperature deviation of the left and right sides of the reheater, and can predict the deviation value and give early warning, so as to provide reference guidance for the operation of power plant boilers.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    4
    References
    0
    Citations
    NaN
    KQI
    []