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adap

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This is python package used detect different types of anomalies in compressors' sensors time series data.

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Direct dependencies0From release 0.0.1
Last observed20 Oct, 19:03 UTC

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Version 0.0.1 documentation

Anomaly Detection and Prediction (ADAP) Package

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Anomaly typeType codeDescriptionExample in the literature and/or alternative terminologyImportance ranking (with respect to time series visualization in this case study)Potential end-user and application
Impossible valuesAValues 6666 are highly impossible in compressor sensor data and consider as out of range value of the sensors.-Important, but it can be deleted easily using simple rule-
Constant values within the acceptable region for long time periodBConstant values within the acceptable region for long time period (more than one day)-Important can be detected using rate of change-
Large sudden spikeCThe spikes are larger than the surrounding data points but less than 6666. Example one or two values much higher than previous or next values-At any point in the time series, used 3 times standard deviation as threshold-
DriftDGradual change in values in positive to zero-High priority (Emergency shutdown, ESD)-
Sudden zeroEValue suddenly shifts in values in positive to zero-High priority (Emergency shutdown, ESD)-

Table 1: Load current related anomaly types

Anomaly typeType codeDescriptionExample in the literature and/or alternative terminologyImportance ranking (with respect to time series visualization in this case study)Potential end-user and application
Impossible valuesAValues 6666 are highly impossible in compressor sensor data and consider as out of range value of the sensors.-Important, but it can be deleted easily using simple rule-
Constant values within the acceptable region for long time periodBConstant values within the acceptable region for long time period (more than one day)-Important can be detected using rate of change-
Large sudden spikeCThe spikes are larger than the surrounding data points but less than 6666. Example one or two values much higher than previous or next values-At any point in the time series, used 3 times standard deviation as threshold-
DriftDGradual change in values in positive to zero-High priority (Emergency shutdown, ESD)-
Sudden zeroEValue suddenly shifts in values in positive to zero-High priority (Emergency shutdown, ESD)-
Step up (sudden shift)FIncrease the mean while keeping the variance constant-High priority (Emergency shutdown, ESD)-
Step down (sudden shift)GDecrease the mean while keeping the variance constant-Normal, indicate motor flips from OFF to ON-

Table 2: Suction pressure related anomaly types

Anomaly typeType codeDescriptionExample in the literature and/or alternative terminologyImportance ranking (with respect to time series visualization in this case study)Potential end-user and application
Impossible valuesAValues 6666 are highly impossible in compressor sensor data and consider as out of range value of the sensors.-Important, but it can be deleted easily using simple rule-
Constant values within the acceptable region for long time periodBConstant values within the acceptable region for long time period (more than one day)-Important can be detected using rate of change-
Large sudden spikeCThe spikes are larger than the surrounding data points but less than 6666. Example one or two values much higher than previous or next values-At any point in the time series, used 3 times standard deviation as threshold-
DriftDGradual change in values in positive to zero-High priority (Emergency shutdown, ESD)-
Sudden zeroEValue suddenly shifts in values in positive to zero-High priority (Emergency shutdown, ESD)-
Step up (sudden shift)FIncrease the mean while keeping the variance constant-Normal, indicate motor flips from OFF to ON-
Step down (sudden shift)GDecrease the mean while keeping the variance constant-High priority (Emergency shutdown, ESD)-

Table 2: Discharge pressure related anomaly types

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VersionPublishedDirect dependenciesOpen version
0.0.123 Mar 20240

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wickramanayaka/adap

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Observed since 20 Oct, 19:03 UTC

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package:6102cf3f609e48aaf813d315ac471461c08df9ab82317bca37141274764f1289