Abstract Aiming at the problem that the traditional fault diagnosis methods cannot deal with the uncertain samples, this paper proposes an interval fault diagnosis method and its parameter optimization. First, the interval Gauss function is used to construct the kernel of the proposed interval fault diagnosis method. The weights and offsets of this interval method are calculated by solving the equality equation. Second, with the goal of maximizing the classification accuracy, the Glowworm swarm optimization algorithm is used to select the parameters of this method. Finally, the experimental results of the rotor crack interval fault samples and the University of California Irvine samples show that this method has higher classification accuracy than the traditional interval classification methods.

中文翻译：

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一种转子裂纹间隔故障诊断方法

摘要 针对传统故障诊断方法无法处理不确定样本的问题，提出一种区间故障诊断方法及其参数优化。首先，使用区间高斯函数构造所提出的区间故障诊断方法的内核。这种区间方法的权重和偏移量是通过求解等式方程来计算的。其次，以最大化分类精度为目标，采用萤火虫群优化算法选择该方法的参数。最后，转子裂纹间隔故障样本和加州大学欧文分校样本的实验结果表明，该方法比传统的间隔分类方法具有更高的分类精度。