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Time dependency of the anomaly detection module

LR_9796586
11-Garnet

Time dependency of the anomaly detection module

I’m interested in predict anomalies in a process that works 24/7, but for training, I only have data of two days for each week, as depicts in the image below: 

LR_9796586_0-1623945012823.png

Considering that I have several months of data and the timestamps for each sample, is this data enough to properly train an anomaly detection model? 

ACCEPTED SOLUTION

Accepted Solutions

@LR_9796586 ,

 

Thank you for posting your question to the PTC Community.

 

The typical suggestion for training is to have 5 full cycles of the data to obtain a good training set.

 

Details on this can be found in this Knowledge Article: https://www.ptc.com/en/support/article/CS248761

 

Should be note, Anomaly Detection has a max period of 23 hours and 59 Minutes for its monitoring, and is not capable of multi day monitoring at this time.

 

Regards,

 

Neel

 

View solution in original post

4 REPLIES 4

@LR_9796586 ,

 

Thank you for posting your question to the PTC Community.

 

The typical suggestion for training is to have 5 full cycles of the data to obtain a good training set.

 

Details on this can be found in this Knowledge Article: https://www.ptc.com/en/support/article/CS248761

 

Should be note, Anomaly Detection has a max period of 23 hours and 59 Minutes for its monitoring, and is not capable of multi day monitoring at this time.

 

Regards,

 

Neel

 

@nsampat  Regarding the max period of 24 hours does that mean that the sum of all 5 full cycles must be less than 24 hours, or that each individual cycle must be of 23h59m at much?

@LR_9796586 ,

 

The 5 cycles must be within the 23 hours and 59 minutes, otherwise its considered a new training window.

 

Ideally you would want your cycles to be periodic and cyclical, Anomaly Detection does not handle acyclical data very well.

 

Regards,

 

Neel

slangley
23-Emerald II
(To:LR_9796586)

Hi @LR_9796586

 

If you feel your question has been answered, please mark the appropriate response as the Accepted Solution for the benefit of others with the same question.

 

Regards.

 

--Sharon

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