In order to improve aerodynamic performance of the counter-rotating compressor in an all-round way

overall working conditions optimization design was carried out on the Rotor 2 of a two-stage counter-rotating compressor in multistage environment based on artificial neural network and genetic algorithm. The changes of geometry

overall performance and flow field were compared and analyzed. Results show that: after the optimization

the overall isentropic efficiency and pressure ratio of the counter-rotating compressor are both improved

meanwhile the range of mass flow is widened. The isentropic efficiency of the counter-rotating compressor increases by 0.3% on the design point

increases by 1.5% near the stall point

and the surge margin increases by 6.37%. After the optimization

the overall isentropic efficiency and pressure ratio of the Rotor 1 are almost unchanged

but those of Rotor 2 are raised much. The isentropic efficiency of Rotor 2 improves by 1% on the design point

and the isentropic efficiency is improved by 2.5% near the stall point. Also

the flow fields of Rotor 1

Rotor 2 and outlet guide vane (OGV) at the tip are improved remarkably near the stall point.