EMI Data Validator gives you the ability to validate your PI Data and mark out the bad or questionable values so that other reporting applications can filter out unreliable data. The solution also provides a set of HTML5 interactive dashboards to pinpoint and analyze the locations and sources of bad data, giving users more insight into the authenticity of their data.
- Data Cleansing Service to mark un-trustful real-time data as Questionable directly in the PI Data Archive.
- Annotate Questionable Values in the PI Data Archive with the reason of marking.
- Calculate Hourly Averages for equipment or Assets excluding Bad and Questionable Values.
- Real time Synchronization of your AF Database with your Relational Data Store (SQL, Oracle, MongoDB …).
- Back filling tools.
- Real-time HTML5 Charts with zooming and panning support.
- Extra Fast Data Retrieval by MongoDB.
- Charts that support exporting, annotating and printing
- System Exposed as Rest Services for third party integration
Flagged Data will include:
- Below Range Values: Values that are below the “Zero” of the tag
- Above Range Values: Values that are above the (“Zero” +”Span”) of the tag
- Frozen Values: Values that get the same reading for more than a predefined number of times
- Noisy Values: Values whose standard deviation over a predefined period is larger than a configued threshold
- System Default Errors: Values that are in “System Default Errors” digital state
- Null Values: String tags that recieve empty string values
Questionable Data is then analysed and used to pinpoint at which level the problems originated. 5 screens will show the below data:
- Field Node Monitoring Bubble Chart: showing the magnitude of issues distributed among the fields and plants
- PI Servers Node Status Chart: showing the PI Servers statuses, with the ability to drill down from the PI Server level all the way to the tag level
- Data Reliability KPI: showing the overall data reliability KPI with error location and details chart
- Tags Reliability Heat map view: showing the reliability of the data over time, which can be used by the users to select the best period to conduct their field/reservoir/ well studies
- Detailed Field Equipment KPI View: showing the Field equipment status including installation, commissioning, connectivity, operational, configuration and reliability statuses
- Windows Server 2012 R2 or Later
- PI Server 2012 or Later
- PI AF Server 2012 or Later
- MongoDB V4.0.4