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基于RBF神经网络的故障诊断,简单讲述了RBF神经网络的设计与应用-RBF neural network based fault diagnosis, a brief descr iption of the RBF neural network design and application of
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本文对旋转机械振动故障预
测方法进行了初步研究，分析了传统预测参数的不足，提出了以分时尺度矩为预测故
障参数的两种故障预测模型:分时尺度矩趋势预测模型和分时尺度矩波动预测模型。
根据分时尺度矩的变化不仅能够判断是否发生了故障，而且能够判断故障的种类。典
型故障实测数据的预测结果验证了基于分时尺度矩预测参数的灰色模型故障预测算
法的有效性。
-This paper the grey correlation analysis method and the probabilis
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这是一篇关于，基于小波分形和神经网络的滚动轴承故障诊断，的学位论文，希望对大家有帮助-This is an on ball bearing fault diagnosis based on wavelet fractal and neural network, dissertations, and we hope to
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模拟电路故障诊断，建立模型，设计诊断算法那，神经网络方法-Analog circuit fault diagnosis based on neural network method
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an excellent book providing an introduction to artificial neural network for modeling and fault diagnosis
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基于BP神经网络的发电机故障诊断程序，较全面，适合初学者和中级学员。-Generator based on BP neural network fault diagnosis procedures, more comprehensive, suitable for beginners and intermediate learners.
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一种新的基于遗传算法的模糊C-均值聚类的RBF神经网络-A New RBF Neural Network with GA-based Fuzzy C-Means Clustering Algorithm for SINS Fault Diagnosis
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滚动轴承多部位多类别故障诊断属于大规模或者较复杂分类问题，利用智能方法诊断时需
要设计结构合理的神经网络才能实现高精度诊断 -Rolling multi-site multi-class fault diagnosis are more complex or large-scale classification problems, the need for the rational design of neural network structure in order to achieve
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小波变换提取特征信号用bp神经网络进行故障诊断(Bp neural network is used for fault diagnosis of feature signal extracted by wavelet transform)
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