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The aviation engine is the heart of the airplane. Therefore, the research for its status recognition has been one of the hot issues which the industry studies attempts to solve. The paper take a real engine gas path system as the research object. The research collects a large number of test data through the test of the running condition in the professional test platform. And based on in-depth analysis for the large test data, the paper proposes to use the 8 main parameters for state recognition. The 8 main parameters contain the relative physical rotational speed of high pressure rotor, inlet temperature of aero engine, inlet pressure of aero engine, outlet pressure of compressor, 25 section of compressor inlet temperature, low pressure rotor speed, low relative temperature after turbine, low pressure turbine pressure etc. Firstly, the paper has been standardized treatment for these data. Second, the paper has been the principal component analysis, and this can calculate the number of principal components through the principal component contribution. Therefore, this can construct a state the recognition model, and can determine. Lastly, the paper takes the statistics of and statistics of SPE as the sign for the aero engine gas path system health status and anomaly recognition. So the paper uses the statistic of and statistic of SPE to finish the research of the aero engine gas path system health and no identification. The study result shows that the method can well identify the running state of the aero engine gas path system. And this method has important value and engineering guidance significance for the actual operation of the aero engine and the recognition of the state.