Data points for SmartSCADA
This chapter describes the internal data point types and data points for SmartSCADA. The tables in this chapter contain a description of the specific data point elements. The descriptions contain a link to the corresponding description of panel/option in the UI.
SSC_KPI_Instance
The data point type SSC_KPI_instance specifies the structure of a KPI instance. A KPI represents an indicator in your system.
Note that the SSC_KPI_instance is not an internal data point type like the other types described in this chapter. You can create a KPI instance after creating a KPI (type) definition. See the data point type _SSC_KPI for the KPI definition.
In the UI KPI instances can be created in the Associate panel of the KPI wizard.
| Data point element | Type | Description |
| kpiKey | string | kpiKey is a unique identifier of a KPI instance. |
| result | float |
The result element contains the result of a KPI instance calculation. A calculation formula must be specified for a KPI before a KPI instance is created and calculated at runtime. For calculation formula, see data point type _SSC_KPI. In the UI a calculation formula must be created in the Definition panel of the KPI wizard before a KPI instance is created in the Associate panel and calculated at runtime. |
| comment | langstring |
Specifies the description of a KPI instance. The description can be used to describe the instance in more detail. In the UI descriptions are specified for KPI instances in the Associate panel of the KPI wizard.under "Description". |
| configuration | .kpiName (string) |
The configuration node contains the KPI instance configuration. The configuration node consists of a struct containing several elements. The elements and their types are described in the following. The types for each element can be found in the column on the left. The kpiName element contains the name of a KPI definition. The DP name used for the kpiName element is of the DP type _SSC_KPI. In the UI the KPI definition is specified in the "Definition" panel of the KPI wizard. |
| .parameterInstances (string) |
The element parameterInstances specifies the data point element names for the KPI parameters. The data point element names are assigned to the KPI parameters of a KPI instance. For parameters see the data point type _SSC_KPI. In the UI KPI instances are created in the Associate Panel of the KPI wizard and data point elements are assigned to parameters in the Associate panel under "configuration" |
|
| .trigger (string) |
The trigger element specifies a data point element name for the trigger or a list of DPE names when the * (asterisk) is used for the trigger. The trigger allows you to select how a KPI instance calculation is triggered. In the UI the trigger is selected in the Associate panel of the KPI wizard |
|
| .parameterTypes (dyn_int) |
The parameterTypes is a dyn element and contains an entry for each KPI parameter. Online = 1 means that the online value of the parameter is used. If the Online= 0, the parameter is a constant string. In the UI you can find the entries in the Associate panel of the KPI wizard. In the Associate panel check boxes are used for these entries. |
|
| .searchInContext (dyn_bool) |
The searchInContext element is dyn_bool and contains an entry for each KPI parameter of a KPI instance. If an entry of a searchInContext element is TRUE, it specifies that the KPI context is used for the parameter of a KPI instance. If the entry is FALSE, it specifies that the KPI context is not used. See also the element "context" below. In the UI the KPI context can be selected for the parameters in the Associate panel of the KPI wizard. See also the "context" element description below. |
|
| .context (string) |
The context element specifies the KPI context that is used for the parameters of a KPI instance. The context is used to search for the data points that were assigned to the parameters. Data point types, Data points as well as Plant model paths can be used for the context. In the UI the KPI context can be assigned to the parameters in the Associate panel of the KPI wizard |
|
| .parameterInputs(string) |
The parameterInputs element specifies the values of the KPI parameters. This means the data point elements that are assigned to the KPI parameters of a KPI instance. In the UI the data point elements are assigned to the parameters in the Associate panel of the KPI wizard. |
|
| enabled | bool |
The "enabled" element is set to TRUE if a KPI instance is enabled. Enabled means that the KPI instance is calculated at runtime. This means that the connection to the data points is built. In the UI the KPI instances are enabled in the Associate panel of the KPI wizard. |
| singleUpdated | bool |
The "singleUpdated" element is set to TRUE if the "Single edit option" is selected for a KPI instance. The "Single edit" mode selects the name of a KPI instance for the single edit mode. Thus, only this KPI instance is changed if you edit the KPI parameter values. In the UI the "Single edit option" is selected in the Associate panel of the KPI wizard. |
_SSC_Configuration
_SSC_Configuration is the global configuration data point type. It describes the configurations for the simulator and KPIs.
| Data point element | Type | Description |
| simulator | string | Contains the name of the SmartSCADA simulator configuration DP. |
| kpi | string | Contains the name of the KPI configuration DP of the type _SSC_KPI_Configuration: "_ssc_kpi_std_configuration". |
_SSC_KPI
The data point type _SSC_KPI specifies a KPI. In the UI KPIs are created via the Definition panel of the KPI wizard.
| Data point element | Type | Description |
| parameters | dyn_string |
Specifies the KPI parameters that are added to a KPI. In the UI parameters are added to a KPI in the Definition panel of the KPI wizard. The data point element "parameters" possesses by default the auth config with the authorization bits set for the configs _address, _default, dp_fct and _original . |
| displayName | langString |
Specifies the name of a KPI (type) such as "Electric_Power". In the UI names are created via the Definition panel of the KPI wizard. |
| kpiFunc | string |
Specifies a KPI Calculation formula that is specified for a KPI. KPI calculation formula is used to calculate a KPI instance at runtime. In the UI KPI calculation formulas are specified in the Definition panel of the KPI wizard. The data point element "kpiFunc" possesses by default the auth config with the authorization bits set for the configs _address, _default, dp_fct and _original . |
_SSC_KPI_Configuration
The data point type _SSC_KPI_Configuration specifies general settings for the KPI framework. The KPI framework allows you to define, configure and calculate KPIs.
| Data point element | Type | Description |
| unsubscribeFilters | dyn_string | For internal use only. |
| blockingTime | unsigned |
The blockingTime element can be used to block a KPI calculation. This is useful when an * (asterisk) is used as a trigger and the KPI instance contains several parameters that would trigger the KPI calculation almost simultaneously. A KPI calculation is not triggered several times almost simultaneously for as long as the set blockingTime. The blocking time is specified in milliseconds. For the data point element "trigger", see SSC_KPI_Instance For the description of the "Trigger" in the UI, see chapter KPI Wizard - Associate. |
| kpiFunctions | dyn_string |
Specifies the KPI functions that can be used for KPI calculation formulas in order to calculate KPI instances. There are two predefined functions (formulas): ssc_kpi_histSum and ssc_predictCondition. In the UI you can find the KPI functions in the "Definition" panel of the KPI wizard as well as create your own functions, see chapter KPI Wizard - Definition |
| activeKPIs | unsigned | For internal use only. |
_SSC_Model
Contains the model data of a random forest model.
Random forests are an ensemble learning method that uses decision tree models and can be used for classification or regression. The WinCC OA SmartSCADA Online help does not provide detailed information on "what a random forest model is", since a random forest model is a common term in the machine learning. You can find detailed information on the Internet.
A random forest model is created via the Classification wizard of SmartSCADA. See the chapter Classification Wizard - Selection.
| Data point element | Type | Description |
| model | blob | Contains the actual random forest model. |
| metadataRef | string | Refers to a data point that contains the data of the random forest model. |
| modelName | string | Name of the model. rf = Random Forest |
_SSC_Labelset
Contains the labels of a label set. Labels are used to designate different states to clusters. In other words clusters specify which states are assigned to which data point values in a WinCC OA system by using labels. For more information on clusters, see chapter Classification Wizard - Clustering.
| Data point element | Type | Description |
| labels | dyn_string |
Specifies the labels of a label set. In the UI, you can specify and assign labels in the Clustering panel of the classification wizard. |
_SSC_METADATA_DM
Contains the data of the Data Mining wizard. The data mining wizard is used to detect correlations between data points. In the Data Mining wizard you select data point elements for a session and also configure settings for the selected data point elements such as the time range and equidistant time intervals. The data point elements as well as the settings are saved in the _SSC_METADATA_DM data point type and described in the following table.
| Data point element | Type | Description |
| inputDPs | dyn_string |
Specifies the data point elements for a session. In the UI the data point elements are selected in the Selection panel of the Data Mining wizard. The data mining wizard is then used to detect correlations between these selected data point elements. |
| startTime | time |
Specifies the start time for the data point elements selected for a session (see above). This means the start time of the time range when the DPE values are queried. In the UI the data point elements are selected in the Selection panel of the Data Mining wizard. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC |
| endTime | time |
Specifies the end time for the data point elements selected for the session (see above). This means the end time of the time range when the DPE values are queried. In the GUI the data point elements are selected in the Selection panel of the Data Mining wizard The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC |
| equiTimeInterval | int |
Specifies the time for the "equidistant time intervals" for the data point elements selected for the session (see above) . "Equidistant time intervals" allow you to generate values every [specified] second. This is useful if the selected data points do not contain the same amount of DPE values. By using "Equidistant time intervals" you can generate values at intervals of the specified [time]. Depending on the specified time, values are, for example, generated every 2 seconds. For the data points - see the element inputDPs above. In the UI the equidistant time intervals can be set via the check box "equidistant" time intervals. |
| maxLagDetection | int |
Specifies the time maxLagDetection. maxLagDetection contains the maximum time (delay) between all values of different data points. Several values are often needed to calculate a correlation. By using the maxLagDetection you can specify the maximum time that is allowed between all values of different data points. In other words between the two values when two data points are compared. For the data points - see the element inputDPs above. In the UI you can set the value by using the check box Enable lag detection of the Selection panel. |
| quality | bool |
The element "quality" is set to TRUE when the calculate quality metrices check box is activated in the UI. The "Calculate quality metrices" check box is shown when you check box "Equidistant time intervals". When you check the "Calculate quality metrices" check box, the average value in the interval (argValInt), the mean absolute error (MAE) and the normalized mean absolute error (NMAE) are calculated. |
| selectedDPs | dyn_string |
Specifies the data point elements that are selected for the correlation. In the UI the data point elements are selected for the correlation in the Correlation panel of the Data Mining wizard. |
| lastSaved | time |
Contains the time when the selected time range and the selected data point elements were saved via the "Save" button for the session in the Selection panel of the Data Mining wizard. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC |
_SSC_METADATA_KM
Contains the data of the Classification wizard. The classification wizard is used to generate clusters. Clusters specify which states are assigned to which data point values in a WinCC OA system by using labels. The classification wizard is then used to create a random forest model for detection of root causes
For more information on the classification wizard, see Overview of the Classification Wizard.
| Data point element | Type | Description |
| clusterVector | dyn_uint | Contains the cluster vector. |
| centers | dyn_float |
Specifies the data point element values of clusters. In the UI the values are shown in the Clustering panel of the classification wizard. The data points whose values are shown for clusters are selected in the first step in the Selection panel of the Classification wizard. |
| numClusters | int |
Specifies the number of clusters. In the UI the number of clusters is specified in the Clustering panel of the classification wizard. |
| inputDPs | dyn_string |
Specifies the data point elements for the clustering. In the UI the data point elements are selected in the Selection panel of the classification wizard. |
| startTime | time |
Specifies the start time for the selected data point elements (see inputDPs above). This means the start time of the time range when the DPE values are queried. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC In the UI the startTime is specified in the selection panel of the classification wizard. |
| endTime | time |
Specifies the end time for the selected data point elements (see inputDPs above). This means the end time of the time range when the DPE values are queried. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC In the UI the endTime is specified in the selection panel of the classification wizard. |
| labelsetRef | string |
Specifies the name of the label set that is used for the clusters .A label set contains the labels that are used to assign states to data point element values in a WinCC OA system In the UI the label set is selected in the clustering panel of the classification wizard |
| labelMapping | dyn_int |
Specifies a mapping of labels and their values. This is a dyn_int element and a value is added for each label that is used for the clusters. This means that if there are, e.g., three labels: "Too high", "Too low" and "OK", the dyn_int contains the numbers 1,2 and 3. The dyn_int contains the numbers one or several times depending on the number of clusters and how many times a label is assigned to a cluster. If, e.g. the label "OK" is used for two clusters, the labelMapping element contains the number 3 (OK) two times. In the UI the labels are assigned to clusters in the clustering panel of the classification wizard. |
| equiTimeInterval | int |
Specifies the time for the "Equidistant time intervals". "Equidistant time intervals" allow you to generate values every [specified] second. This is useful if the selected data points do not contain the same amount of DPE values. By using "Equidistant time intervals" you can generate values at intervals of the specified [time in seconds]. Depending on the specified time, values are, for example, generated every 2 seconds. In the UI the equidistant time intervals can be set via the check box in the selection panel of the classification wizard. |
_SSC_METADATA_RF
Contains the data for a random forest model when a model is created via the classification wizard
| Data point element | Type | Description |
| confusionMatrix | .elements (dyn_string) |
The confusionMatrix node consists of a struct containing several elements. The elements and their types are described in the following. The types for each element can be found in the column on the left. The elements element specifies the individual values of an error matrix. The error rate of the error matrix shows how accurate the prediction of a state in a model is. In the UI the error matrix is shown in the quality panel of the classification wizard |
| .rowHeaders (dyn_string) | For internal use only. | |
| .columnHeaders (dyn_string) | For internal use only. | |
| importanceMatrix | .elements (dyn_string) |
The importanceMatrix node consists of a struct containing several elements. The elements and their types are described in the following. The types for each element can be found in the column on the left. The elements element specifies the individual values of the importance Matrix. The importance matrix shows how important each data point variable is for the prediction model. In the UI the importance matrix is shown in the quality panel of the classification wizard |
| .rowHeaders (dyn_string) | For internal use only. | |
| .columnHeaders (dyn_string) | For internal use only. | |
| headers | dyn_string | Specifies the data point element headers for the importance matrix. These are required in order to show the importance of the individual data point element variables. |
| clusterModel | string |
Specifies the model name of the random forest model. The name for the model is created in the UI when a session is created in the Selection panel of the Classification wizard. The model is then created in the Training panel. |
| inputDPs | dyn_string | Specifies the data point elements that are used for the random forest model as well as later for the classification test in the quality panel of the classification wizard |
| outOfBagError | float |
Contains the OOB error rate. The OOB Error rate specifies the expected percentage of elements that cannot be classified correctly. This means the percentage of the data point elements that were selected for the prediction model and cannot be labeled. In the UI you can find the OOB error rate in the quality panel of the classification wizard |
| startTime | time |
Specifies the start time for the model. This means the start of the time range when the DPE values are queried. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC In the UI you select the start time in the Selection panel of the classification wizard. |
| endTime | time |
Contains the end time for the model. This means the end time of the time range when the DPE values are queried. The time format is: YYYY.MM.DD.HH.MINMIN.SECSEC.MSEC In the UI you select the end time for the model in the Selection panel of the classification wizard. |
| labelVector | dyn_string |
Contains a vector of the defined labels. This is a dyn_string element and a value is added for each label that is used for the clusters. This means that if there are, e.g., three labels: "Too high", "Too low" and "OK", the dyn_string contains the numbers 1,2 and 3 in a vector. In the UI the labels are assigned to clusters in the clustering panel of the classification wizard. |
| labelsetRef | string |
Specifies the name of the label set that contains the labels that are used for the clusters. In the UI the label set is created and selected in the clustering panel of the classification wizard. |
| equiTimeInterval | int |
Specifies the time for the "Equidistant time intervals". "Equidistant time intervals" allow you to generate values every [specified] second. This is useful if the selected data points do not contain the same amount of DPE values. By using "Equidistant time intervals" you can generate values at intervals of the specified [time in seconds]. Depending on the specified time, values are, for example, generated every 2 seconds. In the UI the equidistant time intervals can be set via the check box in the selection panel of the classification wizard. |
| feedbackData | dyn_float | For internal use only. |
| feedbackDataLabel | dyn_int | For internal use only. |
