Datasets:

Jake5
/

wmx_normal_data

Timestamp timestamp[ns, tz=+09:00]	DcDiffAvg int64 695k 801k
2024-10-31T19:13:46.454000	780,472
2024-10-31T19:13:46.584000	783,309
2024-10-31T19:13:46.693000	785,026
2024-10-31T19:13:46.803000	786,223
2024-10-31T19:13:46.913000	787,620
2024-10-31T19:13:47.022000	789,378
2024-10-31T19:13:47.130000	791,095
2024-10-31T19:13:47.240000	792,853
2024-10-31T19:13:47.350000	794,250
2024-10-31T19:13:47.460000	795,808
2024-10-31T19:13:47.569000	697,485
2024-10-31T19:13:47.678000	699,122
2024-10-31T19:13:47.788000	700,640
2024-10-31T19:13:47.897000	701,797
2024-10-31T19:13:48.005000	703,155
2024-10-31T19:13:48.115000	705,512
2024-10-31T19:13:48.224000	706,709
2024-10-31T19:13:48.332000	708,426
2024-10-31T19:13:48.444000	710,304
2024-10-31T19:13:48.553000	711,941
2024-10-31T19:13:48.662000	713,059
2024-10-31T19:13:48.772000	715,016
2024-10-31T19:13:48.881000	716,534
2024-10-31T19:13:48.990000	717,771
2024-10-31T19:13:49.100000	719,769
2024-10-31T19:13:49.209000	721,325
2024-10-31T19:13:49.318000	722,603
2024-10-31T19:13:49.429000	724,000
2024-10-31T19:13:49.537000	725,918
2024-10-31T19:13:49.646000	727,475
2024-10-31T19:13:49.756000	729,233
2024-10-31T19:13:49.866000	730,950
2024-10-31T19:13:49.975000	732,148
2024-10-31T19:13:50.084000	733,945
2024-10-31T19:13:50.193000	735,263
2024-10-31T19:13:50.303000	737,059
2024-10-31T19:13:50.412000	738,977
2024-10-31T19:13:50.522000	740,214
2024-10-31T19:13:50.632000	741,812
2024-10-31T19:13:50.741000	743,209
2024-10-31T19:13:50.850000	744,967
2024-10-31T19:13:50.960000	746,684
2024-10-31T19:13:51.068000	748,122
2024-10-31T19:13:51.179000	749,919
2024-10-31T19:13:51.288000	751,516
2024-10-31T19:13:51.397000	752,993
2024-10-31T19:13:51.506000	754,671
2024-10-31T19:13:51.615000	756,068
2024-10-31T19:13:51.725000	757,826
2024-10-31T19:13:51.834000	759,503
2024-10-31T19:13:51.944000	760,941
2024-10-31T19:13:52.051000	762,658
2024-10-31T19:13:52.161000	764,176
2024-10-31T19:13:52.271000	765,733
2024-10-31T19:13:52.380000	767,330
2024-10-31T19:13:52.490000	768,567
2024-10-31T19:13:52.600000	770,605
2024-10-31T19:13:52.709000	771,722
2024-10-31T19:13:52.821000	773,120
2024-10-31T19:13:52.932000	775,437
2024-10-31T19:13:53.042000	776,515
2024-10-31T19:13:53.153000	778,512
2024-10-31T19:13:53.261000	779,590
2024-10-31T19:13:53.372000	781,746
2024-10-31T19:13:53.482000	783,384
2024-10-31T19:13:53.606000	785,221
2024-10-31T19:13:53.716000	786,938
2024-10-31T19:13:53.842000	788,256
2024-10-31T19:13:53.968000	790,332
2024-10-31T19:13:54.092000	795,689
2024-10-31T19:13:54.203000	793,407
2024-10-31T19:13:54.313000	795,124
2024-10-31T19:13:54.423000	796,402
2024-10-31T19:13:54.533000	698,079
2024-10-31T19:13:54.644000	699,516
2024-10-31T19:13:54.754000	700,674
2024-10-31T19:13:54.865000	703,031
2024-10-31T19:13:54.975000	704,269
2024-10-31T19:13:55.083000	705,986
2024-10-31T19:13:55.190000	707,664
2024-10-31T19:13:55.302000	709,140
2024-10-31T19:13:55.412000	710,618
2024-10-31T19:13:55.523000	712,296
2024-10-31T19:13:55.633000	713,693
2024-10-31T19:13:55.740000	715,371
2024-10-31T19:13:55.849000	716,448
2024-10-31T19:13:55.960000	718,845
2024-10-31T19:13:56.068000	720,243
2024-10-31T19:13:56.178000	721,679
2024-10-31T19:13:56.289000	723,317
2024-10-31T19:13:56.396000	724,915
2024-10-31T19:13:56.506000	726,712
2024-10-31T19:13:56.615000	728,069
2024-10-31T19:13:56.726000	729,947
2024-10-31T19:13:56.835000	731,624
2024-10-31T19:13:56.947000	733,182
2024-10-31T19:13:57.056000	735,099
2024-10-31T19:13:57.165000	736,256
2024-10-31T19:13:57.276000	739,853
2024-10-31T19:13:57.384000	739,571

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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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Downloads last month: 7

Size of downloaded dataset files:

1.45 MB

Size of the auto-converted Parquet files:

1.45 MB

Number of rows:

100,047