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对模糊支持向量机中的传统隶属度确定函数进行了改进,得到了紧密度隶属函数的模糊隶属度确定方法;针对航空发动机整机振动中多类故障诊断的特点,引入模糊隶属度函数建立了更有效的FSVM融合诊断的数学模型,并将该模型应用到航空发动机整机振动故障诊断中。计算结果显示:该方法不但具有较高的正确诊断率,而且也具有很强的抗噪声能力,从而为航空发动机整机振动故障分析提供了一种新方法。
The traditional membership degree determination function in fuzzy support vector machine is improved and the fuzzy membership degree of the close degree membership function is determined. Aiming at the characteristics of multi-class fault diagnosis in the whole machine vibration of aeroengine, the fuzzy membership function is introduced More effective FSVM fusion diagnosis mathematical model, and the model is applied to aeroengine machine vibration fault diagnosis. The results show that this method not only has a higher correct diagnosis rate but also has a strong anti-noise ability, which provides a new method for vibration analysis of aeroengine vibration.