Overview of working with data

In this section we introduce various concepts and some of the terminology associated with data and data types. We discuss the various types of source data and data sources that Proficy CSense is able to use, we define what we understand to be real-time and historical data as well as monitored and independent variables.

In this section you can find out about:

Terminology

Continuous data - Data that flows in a time-series continuously, e.g. analogue values.
Data quality - Refers to the confidence (good or bad) or integrity of data. The flagging of the quality may be achieved in several ways. In Proficy CSense quality is set by performing limit checking and constructing crisp rules.
Data validation - A process used to determine if data is accurate, complete, and/or meets specified criteria. Proficy CSense performs validation by simple clipping in which data is truncated if it lies outside user-defined limits. If enabled, the quality of any data points that are clipped may be set to bad. Data may also be validated by formulating rules in the Architect script block.
Monitored variable - The variable that is tracked to identify when process deviation occurs; it is also known as a Key Performance Indicator (KPI).
Independent variable - This is a model input variable that influences the monitored variable or KPI; it is equivalent to a manipulated variable.
KPI - Key performance indicator, also known as the monitored variable within diagnostics of process deviations.
Historian - A component that keeps the history of fields usually in some file or database.
Analogue values - Electrical representation of temperature, flow rate, pressure etc. i.e. thermocouples, air flow rate, water flow rate, etc.

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