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采用三维谱图提取放电指纹特征，并用人工神经网络来识别不同的放电类型。
The feature of discharge is extracted using the 3D pattern chart and the artificial neural networks is used to recognize the discharge models.
基于短时傅里叶变换形成的三维谱图，采用数字图像处理的方法提取信号的特征。
A Surface EMG signal identification method based on short time Fourier transform is presented in this paper.
声信号三维谱图丰富旋转机械碰摩故障诊断系统知识库中的特征信息，可以用于更准确地诊断转子中的碰摩故障。
The 3-d diagrams can enrich the feature information for the knowledge base of the rotating machinery rub fault diagnosis system and is of significance to diagnose rub faults in rotor more accurately.
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