Data Scaling
Data Scaling is a generic data-processing layer available for YuDash variables. It can be applied to values acquired from different interfaces, including Analog Inputs, Modbus, SDI-12, weather sensors, and other supported data sources. The feature performs a configurable two-point linear transformation on an existing variable and can optionally apply minimum and maximum clipping limits before the value is used for logging, display, calculations, or telemetry.
Data Scaling operates on the variable itself. The Variable Name entered in the DataScale configuration must exactly match the variable name created by the corresponding input configuration. When a match is found, YuDash applies the scaling rule and updates that same variable with the processed value. DataScale does not create a separate output variable automatically.
If a DataScale entry refers to a variable that does not exist among the active input variables, that scaling rule is simply ignored. This allows DataScale configurations to coexist with different sensor configurations without affecting unrelated variables.
For example, a variable named temperature may originate from an analog input, while another variable such as water_level may originate from Modbus and soil_moisture from SDI-12. Data Scaling can be applied independently to any of them, provided the variable name in the DataScale rule matches the input variable name.
How Data Scale Works
Data Scale works on a two-point linear scaling model, with optional minimum and maximum clipping. The user defines two input-to-output reference points:
Min In → Min Out
Max In → Max Out
These two points define the linear relationship between the raw input value and the required engineering value.
The diagram below illustrates the concept. Point A represents the lower reference point and Point B represents the upper reference point. YuDash calculates the corresponding output for values between these points, and also continues the same linear relationship for values outside the defined input range.
Optional Min Cutoff and Max Cutoff values can then be used to restrict the final output. In other words, scaling determines the converted value, while clipping limits the final value if required.
Important Notes
The variable name in the Data Scaling table must match an existing YuDash input variable exactly.
Data Scaling updates the same variable; it does not create a separate output variable automatically.
If the configured variable name is not found in the active inputs, that Data Scaling row is ignored.
The input value does not have to remain strictly inside the Min In / Max In range. YuDash still applies the linear equation, and the final value may then be limited by the optional cutoff values.
The same Data Scaling feature can be used for analog, Modbus, SDI-12, and other YuDash variables.
Example: Converting 4–20 mA to Temperature
A typical use of Data Scale is to convert a standard 4–20 mA transmitter signal into an engineering value. In this example, a Novus TxBlock-USB converts a Pt100 temperature measurement of −50 to 100 °C into 4–20 mA.
Configure the Analog Input
Go to Sensor Settings → Open Analog Wizard.
Configure Channel 1 as:
Setting
Value
Topology
A1: 0–20 mA
Input
0 to 20
Output
0 to 20
Multiplier
1
Variable
Temperature
Backup Variable
Temperature_Raw_mA
The channel therefore retains the signal in mA before Data Scale is applied. Temperature_Raw_mA keeps a copy of the raw current for diagnostics.
Configure the scaling
Add a Data Scale rule for Temperature:
Setting
Value
Variable Name
Temperature
Min In
4
Max In
20
Min Out
−50
Max Out
100
The variable name must match the input variable exactly. Data Scale therefore converts the existing Temperature variable from 4–20 mA to −50 to 100 °C.
For this example, the optional cutoff fields are left blank.
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