Modeling and optimizing method of high-sulfur natural gas purification process oriented to energy saving and consumption reduction
A technology of purification process and optimization method, applied in neural learning method, gas fuel, petroleum industry, etc., can solve the problems of decreasing product gas flow rate and high acid component concentration, so as to overcome process interference, improve productivity and gas processing economy effect of benefit
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[0025] Glossary
[0026] ST-UKFNN: Strong track Unscented Kalman Fliter Neural Network, strong track unscented Kalman filter neural network.
[0027] The method for modeling and optimizing the purification process of high-sulfur natural gas for energy saving and consumption reduction provided by the present invention includes:
[0028] Step S1: Select the process parameters that affect the desulfurization efficiency and the performance indicators of the desulfurization unit; among them, the process parameters include the flow rate of lean amine liquid entering the tail gas absorption tower, the flow rate of lean amine liquid entering the secondary absorption tower, the processing capacity of raw material gas, and the exhaust gas unit The flow rate of the semi-rich amine liquid returning to the desulfurization unit, the temperature of the amine liquid entering the primary absorption tower, the temperature of the amine liquid entering the secondary absorption tower, the pressure...
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