Thermal turbine unit early warning method and system based on Mann-Kendall algorithm and LSTM neural network

• Main Authors: GE BING, CHI ZHONGRAN, ZHONG XINGHUA, LU MENGWEI
• Format: Patent
• Language: Chinese; English
• Published: 23.05.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention provides a thermal turbine unit early warning method and system based on a Mann-Kendall algorithm and an LSTM neural network. The thermal turbine unit early warning method comprises the steps of obtaining unit operation data in a power plant database; screening out data in a normal operation state from historical data of the power plant, and constructing a prediction library and a standard library neural network; inputting the real-time operation data of the power plant into the standard library and the prediction library for comparison, and giving an alarm if the thermal parameters exceed a set threshold value; and after an alarm is given, the change trend of each thermal parameter is identified through a Mann-Kendall algorithm. According to the method, the influence of the thermal capacity of the thermal turbine unit is considered by adopting the LSTM neural network, the thermal parameters are predicted, and a more advanced power plant operation prediction result is realized; a prediction resu