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CNC Tool Health Assessment @2019 PyCon

設備連網是工業4.0重要的一環,設備連網後我們如何讀得懂設備的語言?面對大量的高頻數據如何處理?怎麼將數據應用在工業現場?這次的演講將為大家介紹如何使用Python實作上述的課題,以CNC為範例,利用信號處理方法解析高低頻數據,並比較Supervised、Unsupervised方法的應用等,同時分享sample code。

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CNC Tool Health Assessment @2019 PyCon

  1. 1. 報告人 張楦涵 徐仕杰 | PyCon Taiwan 2019
  2. 2. Edge Server Database
  3. 3.  
  4. 4. from nptdms import TdmsFile tdms_file = TdmsFile(path) obj=tdms_file.object(‘vibration_X’) data = obj.data 震動 X 震動Y 震動Z 0.5047 -0.938 1.156 … … … -1.717 -0.286 1.759
  5. 5. 日期 時間 毫秒 … X軸座標 Y軸座標 Z軸座標 進給 轉速 主軸負載 2018/5/26 08:13:15 481 … 0.8501 -239.158 -254.203 0 1999.969 4.257332 2018/5/26 08:13:15 496 … 0.8501 -239.158 -254.203 0 1999.969 4.257332 2018/5/26 08:13:15 512 … 0.8501 -239.158 -254.203 0 1999.969 4.257332
  6. 6. • • •
  7. 7. 10/24/11 05/11/12 11/27/12 06/15/13 01/01/14 07/20/14 02/05/15 0 0.5 1 1.5 2 2.5 3 x 10 4 Time Energy(mJ) 09/23/13 11/12/13 01/01/14 02/20/14 04/11/14 05/31/14 07/20/14 09/08/14 5600 5800 6000 6200 6400 6600 6800 7000 7200 Time Energy(mJ) 256,908,800 155,456,000
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  10. 10. 1 x 155,456,000 342,968 x 7,680
  11. 11. 342,968 x 7,680 342,968 x 281
  12. 12. • • The Mann-Kendall Test is used to determine whether a time series has a monotonic upward or downward trend. It does not require that the data be normally distributed or linear. It does require that there is no autocorrelation. • • Kolmogorov–Smirnov test is a nonparametric test of the equality of continuous (or discontinuous), one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution • • A type of statistical significance test in which the distribution of the test statistic under the null hypothesis is obtained by calculating all possible values of the test statistic under rearrangements of the labels on the observed data points.
  13. 13. • • XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. • • • • •
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