Generator bar vibration optimization control system based on evolutionary algorithm and LSTM
An evolutionary algorithm and optimization control technology, applied to computer components, calculations, neural learning methods, etc., can solve problems such as reduced mechanical strength, reduced vibration frequency at the end of the stator winding, and lack of mathematical support at the historical data level to meet safety requirements. The effect of stable operation
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[0059] Such as Figure 1-3 As shown, this generator bar vibration optimization control system based on evolutionary algorithm and LSTM is characterized in that it includes the following steps:
[0060] Step 1. Data collection, collecting generator active power, generator reactive power, generator excitation current, temperature measurement points in each slot of the generator, temperature measurement points in each slot of the iron core, vibration measurement points at the end of the generator, and other relevant information. Historical data of measuring points related to generator end vibration;
[0061] Step 2. Data preprocessing and data set construction. Perform data cleaning, optimization, dimension expansion, and normalization on the historical data collected in step 1. After data preprocessing, build training sets, verification sets, and test sets with special data structures. Sets are divided according to the ratio of 7:2:1;
[0062] Step 3. Use the training set and ...
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