Instance Tag Field Descriptions

Analytic Instance Tag Field Descriptions

This topic describes the fields that can be viewed in a SmartSignal Maintenance deployment.

FieldDescription
Tag AliasThe display name of the tag. This value is inherited from the analytic template and cannot be modified.
Tag TypeIf the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.
Sensor Health MonitoringAllows you to enable or disable Sensor Health Monitoring. If you enable this option, you can configure the Sensor Health Monitoring parameters. This option is available for numeric input tags.
Source TagThe time series ID of the tag. This value can be modified.
DecimalsThe number of decimal places included in the tag readings. This value is inherited from templates imported from Classic SmartSignal Blueprint Center. It is not used in APM and cannot be modified.
DescriptionThe description of the tag.
ActiveThe collection of deployment-specific settings and data for this tag are collectively referred to as a deployment tag. If selected, this tag will be included as part of the deployment.
Last Changed DateDate the tag was last modified.
UnitsThe units of measure for the source data of the tag, such as degrees (C) or percentage (%). This is used only as an identifying label and is displayed on the y-axis when the tag is used in model training data charts.
Actual HighThreshold used in rules to determine whether data is outside of expected limits.
Actual LowThreshold used in rules to determine whether data is outside of expected limits.
Deployment IDThe ID for the deployment.
Standard UnitsThe units of measurement for the source data for the tag.
Step HighThreshold used for step-change rules.
Step LowThreshold used for step-change rules.
Tag Template IDThe ID for the tag template.
Adaptation HighUpper threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Adaptation LowLower threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Source Tag AliasThe display name of the source tag.
Analytic Template Display NameThe name of the analytic template.
Created ByThe ID of the user who created the tag.
Created DateDate the tag was created.
Data TypeThe data format of the tag. The options are Float, Integer, Boolean, String, or Date. This value is inherited from the analytic template and cannot be modified.
Tag IDAutomatically generated unique ID for the tag. This value cannot be modified.
Last Changed ByThe ID of the user who last modified the tag.
NoteNotes about the tag.

Model Tag Field Descriptions

Model tag data is used to predict equipment behavior under various operating conditions. This topic provides a list and description of the fields that exist for model tags and appear on the grid for a selected model.

FieldDescription
Tag AliasThe display name of the tag. This value is inherited from the analytic template and cannot be modified.
Tag TypeIf the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.
Active in DeploymentDepending on whether the tag is an input tag or an output tag, if this check box is selected, one of the following will occur:
  • For an input tag, data will be collected at every data collection interval.
  • For an output tag, data will be produced at every data collection interval.
The collection of deployment-specific settings and data for this tag are collectively referred to as a deployment tag.
Source TagThe time series ID of the tag. This value can be modified.
DescriptionThe description of the tag.
UnitsThe units of measure for the source data of the tag, such as degrees (C) or percentage (%). This is used only as an identifying label and is displayed on the y-axis when the tag is used in model training data charts.
Standard UnitsThe units of measurement for the source data for the tag.
Actual HighThreshold used in rules to determine whether data is outside of expected limits.
Actual LowThreshold used in rules to determine whether data is outside of expected limits.
Active in ModelIf selected, this tag is included as part of the model and is used in predictions and data modeling. If it is deactivated, it is not used in predictions and data modeling. The collection of model-specific settings and data for this tag are collectively referred to as a model tag.
Alarm TypeDefines the algorithm used to trigger residual indications.
AlgorithmDescription
NoneDisables residual indications for the residual signal for the tag.
SPRTThis is a specialized decision algorithm called the Sequential Probability Ratio Test (SPRT). The system can apply it when the residuals are normally distributed and serially uncorrelated. The algorithm uses a statistical hypothesis testing technique to determine if the mean of the residual has shifted in the positive or negative direction.
Residual ThresholdThis is the default value. It triggers a residual indication if the residual signal of the tag exceeds the value in the Positive Residual Threshold column or falls below the value in the Negative Residual Threshold column.
Smoothed Residual Threshold Triggers a residual indication if the smoothed residual signal of the tag exceeds the value in the Residual + Threshold column or falls below the value in Residual – Threshold column. This method is used to remove spike data and noise from the residuals.
Residual (Positive)The maximum absolute value allowed for a positive residual (that is, when the estimate is above the actual for a signal). See details in the Alarm Type description.
Residual (Negative)The maximum absolute value allowed for a negative residual (that is, when the estimate is below the actual for a signal). See details in the Alarm Type description.
Actual MeanThe mean of the actual values for a tag included in the reference values. This attribute is automatically evaluated when creating a state matrix.
Actual Standard DeviationThe standard deviation of the actual values for a tag included in the reference values. This attribute is automatically evaluated when creating a state matrix.
Adaptation HighUpper threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Adaptation LowLower threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Data TypeThe data format of the tag. The options are Float, Integer, Boolean, String, or Date. This value is inherited from the analytic template and cannot be modified.
DecimalsThe number of decimal places included in the tag readings. This value is inherited from templates imported from Classic SmartSignal Blueprint Center. It is not used in APM and cannot be modified.
Filter HighThe upper filtering threshold. This field sets the upper threshold value for filtering of tag signals to remove data outside the normal operating range. Any tag data greater than this value is considered an outlier. Outliers will be filtered out of training data.
Filter LowThe lower filtering threshold. This field sets the lower threshold value for filtering of tag signals to remove data outside the normal operating range. Any tag data less than this value is considered an outlier. Outliers will be filtered out of training data.
Flatline NumberIf the data for this tag remains at the same level for more than this number of data points, the data will be considered to be flatlined, and will be filtered out of training data.
Instance Tag IDAutomatically generated unique ID for the tag. This value cannot be modified.
Is DriverAny tags with this selected will be looked at to determine if a new operating state is occurring to trigger auto adaptation. At least one tag must be checked to enable auto-adaptation.
Is IndependentInferential models use an observation of measured signal values to generate one or more estimated signal values not present in the observation of measured signal values. When using this method, this field indicates whether the independent variables should represent all of the drivers for the dependent output variables.
Model Tag IDAutomatically generated unique ID for the tag. This value cannot be modified.
Notes in InstanceNotes about the analytic instance.
Notes in TemplateNotes about the analytic template. This value is inherited from the analytic template and cannot be modified.
Notes in ModelNotes about the configuration of the tag for the selected model.
Outlier (Negative)Threshold used for outlier rules. Data outside of Outlier limits appear as NaNs in charts.
Outlier (Positive)Threshold used for outlier rules. Data outside of Outlier limits appear as NaNs in charts.
Residual VarianceThe variance of the residual values for a tag included in the reference values. This attribute is automatically evaluated when creating a state matrix. Residual values are calculated by modeling the reference values not included in the state matrix.
Spike SensitivityThe sensitivity of the spike detection algorithm used to detect spikes in tag signals. A lower value will detect more spikes, but may also generate false positives. Spike data will be filtered out of training data.
SPRT (Negative)The negative values for the sensitivity of the SPRT. This value is multiplied by the standard deviation of the residual, which in turn defines the amount of negative change in the residual mean that must occur to constitute an alarm.
SPRT (Positive)The positive values for the sensitivity of the SPRT. This value is multiplied by the standard deviation of the residual, which in turn defines the amount of positive change in the residual mean that must occur to constitute an alarm.
Step HighThreshold used for step-change rules.
Step LowThreshold used for step-change rules.
Tag OrderThe order of the tags in the deployment. This value is inherited from the analytic template and cannot be modified.