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DC竞赛轴承故障检测

Python 100.00%

bearing-fault-detection-by-keras's Introduction

基于轴承振动信号的轴承故障诊断

使用方法

python装好以下依赖库:

  1. keras
  2. matplotlib
  3. pandas

然后直接运行main.py即可开始训练,最终训练模型保存为finishModel.h5文件

将第90行改为False即可使用测试数据进行分类测试,测试完成后分类标签保存为submit.csv

数据介绍

训练数据是由792组样本组成,每组样本包含6000个采用数据和一个分类标签,总共有9个故障类和1没有故障的类

实验使用生成器,每次使用20组数据进行训练

课题组修改方案

把Bear_data/train.csv文件的数据按照格式替换为我们实验所得的数据

例如:每行数据为1000秒采样的电信号数据,没有故障的数据采样100组,敲打故障的数据采样100组,轴不对中的数据采样100组,然后修改main.py中相关参数即可开始训练我们课题组的模型

bearing-fault-detection-by-keras's People

Contributors

sherry-roar avatar

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