metadata

license: apache-2.0
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: Timestamp
      dtype: timestamp[ns, tz=+09:00]
    - name: DcDiffAvg
      dtype: int64
  splits:
    - name: train
      num_bytes: 1600752
      num_examples: 100047
  download_size: 1452329
  dataset_size: 1600752
tags:
  - ethercat
  - dcdiff
  - anomaly
pretty_name: wmx_master_stat_dcdiff_norma

Dataset Card for Dataset Name

This dataset card aims to train an LSTM autoencoder model to detect anomalies of DC diff statistics calculated by the WMX Ethercat master.

Dataset Details

The data frame has two columns consisting of "Timestamp" and "DcDiffAvg".

Every cycle is done, the average time interval to the next DC clock for each cycle is cacluated in ns, and this value shows a peculiar sawtooth pattern as follows. Using this dataset the autoencoder model can be trained to detect anomalies in case of unstable communication between the master(Main device) and sub-devices.

For detail information and source code, find the following link. https://github.com/kyoungje/WMXAnomalyDetection/tree/main

Dataset Description

Uses

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