Virtual sensing method and system for variable inlet guide vane control fluid device operating frequency based on metamodel

A virtual sensing system for sensing a variable IGV control fluid device operating frequency based on a metamodel, the virtual sensing system comprising:

• a communication unit configured to collect input characteristic data from a fluid device system;
• and
• a processor configured to predict output characteristic data by applying the input characteristic data to a metamodel which is a machine learning model,
• wherein the input characteristic data is two or more of a fluid pressure (P), a fluid flow rate (Q), and an IGV angle (β),
• wherein the output characteristic data is an operating frequency (N) of the fluid device.

A virtual sensing method for sensing a variable IGV control fluid device operating frequency based on a metamodel, the virtual sensing method comprising:

• collecting, by a communication unit, input characteristic data from a fluid device system;
• and
• predicting, by a processor, output characteristic data by using a metamodel which is used for predicting an operating frequency of a fluid device,
• wherein the metamodel is configured by a P-Q-N prediction model which uses a fluid pressure (P), a fluid flow rate (Q), and an operating frequency (N) of the fluid device as characteristic data, and a P-Q-β prediction model which uses the fluid pressure (P), the fluid flow rate (Q), and an IGV angle (β) as characteristic data.