Model-transfer-based large-sized new compressor performance prediction rapid-modeling method

Abstract

The invention discloses a model-transfer-based large-sized new compressor performance prediction rapid-modeling method, which comprises the following steps: determining a rated value of each parameter and a stable running interval on the basis of a performance prediction model for an existing similar compressor by utilizing the prior experience knowledge of a new / old compressor; designing an experiment to acquire a small number of experimental data samples, performing normalization processing on the acquired samples according to rated running parameters of a new compressor, establishing a performance prediction model for the new compressor by utilizing an ELM (Extreme Learning Machine) neural network, performing transfer learning, and performing model transfer training by using experimental sample input data and a predicted output value of the basic model as input variables of the new model and using experimental sample output data as the output of the new model; testing the effectiveness of the new model by using the experimental samples. According to the method, the performance prediction model for the new compressor can be rapidly developed under the condition of less experimental data information by virtue of the performance prediction model for the existing similar compressor and the prior knowledge of the new compressor, so that the modeling efficiency and accuracy are improved.

Description

technical field [0001] The invention relates to a modeling method for a performance prediction model of a large compressor, in particular to a fast modeling method for performance prediction of a large new compressor based on model migration, and belongs to the technical field of large compressor performance prediction model modeling. Background technique [0002] As a pressure boosting device, the compressor has been widely used in the fields of industry and agriculture. It mainly uses the interaction between the blades and the gas to increase the pressure and kinetic energy of the gas, and decelerates the air flow through the action of successive flow elements, so that Its pressure is further increased. Existing large-scale compressors have the advantages of high exhaust pressure, large delivery flow and high efficiency, and can meet the requirements of large-scale industrial production such as steel mills and power plants. Ideal and other issues, such as large centrifuga...

AI Technical Summary

Problems solved by technology

As long as there is enough reliable data information, the prediction accuracy of the model is very high; but because this modeling method usually requires a large number of data samples for learning, it is very sensitive to the noise of the training data and changes in working conditions, especially For a new compressor, due to the short running time and lack of reliable process data information, if the above-mentioned modeling method is used to develop a new compressor performance prediction model, the prediction accuracy of the model will be low. And waste a lot of manpower and cost, low efficiency

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