Based on the first principal direction and information remain rate, a condition identification method is proposed. The features set of multi-channel signals was calculated and the direction angel vector of the first principal direction was obtained. A new feature set was built by direction angel vector and the information remain rate. Then， a convergence rule and judging procedure of neural works were further proposed combining the anisomerous crossover genetic algorithm, and the training speed of the neural works was increased. The results show that the proposed method can extract the feature from the high dimension multivariable features-set, the calculation process is simple, and the accuracy of identification and the generali zation capability of the method are remarkable.