motor-defect-detector-python:预测制造设备电机的性能问题。 对发现的问题执行本地或云分析,然后在用户界面上显示数据以确定何时可能出现故障-源码

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电机缺陷检测仪 细节 目标操作系统: Ubuntu * 16.04 LTS 程式语言 Python 完成时间: 30分钟 它能做什么 制造设备的监视对于任何工业过程都是至关重要的。 有时至关重要的是,必须实时监视设备的故障和异常,以防止损坏并将设备行为故障与生产线问题相关联。 故障检测是预测性维护的先兆。 本参考实现涵盖FFT,逻辑回归,K均值聚类,GMM的基本实现。 它还显示了FFT在机器振动数据特征工程中的帮助。 这个怎么运作 从最基本的(FFT)到最复杂的(高斯混合模型),有几种方法不需要训练神经网络就能检测到故障。 它们的优点是可以在不同的数据流上进行较小的修改就可以重复使用,并且不需要大量已知的先前分类的数据(与神经网络不同)。 实际上,其中一些方法可用于对数据进行分类,以训练DNN。 要求 硬体需求 经过测试 软件需求 Ubuntu * 16.04 带有以下库的Py

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