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Image recognition technology in rotating machinery fault diagnosis based on artificial immune

机译:基于人工免疫的旋转机械故障诊断图像识别技术

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By using image recognition technology, this paper presents a new fault diagnosis method for rotating machinery with artificial immune algorithm. This method focuses on the vibration state parameter image. The main contribution of this paper is as follows: firstly, 3-D spectrum is created with raw vibrating signals. Secondly, feature information in the state parameter image of rotating machinery is extracted by using Wavelet Packet transformation. Finally, artificial immune algorithm is adopted to diagnose rotating machinery fault. On the modeling of 600MW turbine experimental bench, rotor's normal rate, fault of unbalance, misalignment and bearing pedestal looseness are being examined. It's demonstrated from the diagnosis example of rotating machinery that the proposed method can improve the accuracy rate and diagnosis system robust quality effectively.
机译:通过图像识别技术,提出了一种基于人工免疫算法的旋转机械故障诊断新方法。该方法着重于振动状态参数图像。本文的主要贡献如下:首先,利用原始振动信号创建3-D频谱。其次,利用小波包变换提取旋转机械状态参数图像中的特征信息。最后,采用人工免疫算法对旋转机械故障进行诊断。在600MW汽轮机实验台的建模中,研究了转子的正常速度,不平衡故障,未对准和轴承座松动。从旋转机械的诊断实例证明,该方法可以有效提高准确率,提高诊断系统的鲁棒性。

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