Validation limits
- Last UpdatedNov 18, 2025
- 3 minute read
The Validation Limits window is a tool to assist you with defining reasonability limits. The window retrieves the historical meter data from the database and analyzes the data, based on the configured standard deviation.
Note: The information displayed on the Validation Limits window comes from raw meter data; it is not checked for validity prior to use.
This information is presented to you with the appropriate permission (Meas Object Modify Bulk), so that you can define the validation limits (reasonability limit checks) for that meter.
Note: This suggested validation limit can be meaningless if the data has a low kurtosis or is highly skewed. Consult the numbers in the Validation Limits window and view the histogram.
The Low/High information that is supplied by AVEVA Measurement Advisor as a suggested limit can be copied into the Current Limits column by selecting on the column of suggested values.
The Validation Limits for Meter window presents the statistical analyzes of 8 fields (volume, energy and more), including graphs (either trend or histogram). The Validation Limits for Meter window contains the following buttons and fields.
Validation Limits buttons and fields
|
Buttons and Fields |
Description |
|---|---|
|
Time Range |
Open the Select Date Range dialog. |
|
Start/End |
The system retrieves and analyzes the meter data between the start/end dates. |
|
Query |
Select Query to retrieve the data according to the set Time Range, analyze it, and suggest validation limits based on the meter data and the desired standard deviation. |
|
Meter Scroll |
Select the forward or backward Meter Scroll arrow to display the validation limits of the next/previous meter. |
|
% of data to fall in this range |
This corresponds to the Bell curve distribution of the sample data. Points that fall outside this range are excluded from the validation limits calculation. |
|
# Std Dev |
The standard deviation is equivalent to the % of data to fall in this range. |
|
The statistical information presented for each column. |
|
|
Min/Max |
The minimum value/ maximum value of the analyzed data. |
|
Average |
The average value. |
|
FWA |
The Flow Weighted Average. |
|
Std Dev |
The standard deviation in the respective units. For example, the volume is 7426 MCF and the standard deviation is 763 MCF. |
|
Kurtosis |
How peaked or flat the distribution is. If the data is 'peaked', it has a number of outliers, with the majority of the data forming a 'peak' on the graph. This makes it easy to identify the proper validation limit, as most of the data congregates within one area and the rest of it is likely to be invalid. In the event that the data is 'flat', this means that the data is more uniform with fewer outliers, appearing flatter. This makes it likely that the proper validation limits should be further apart. Additionally, a dataset that is extremely flat makes it difficult to differentiate between valid and invalid data. |
|
Skew |
How skewed the distribution is. Skew, in effect, measures symmetry. A skewed dataset will not appear symmetrical in any way, making the proper validation limits difficult to identify because they are not clustered together. |
|
Current Limits: Low/High |
The current (high/low) validation limits. Note: The current validation limits are editable. |
|
Low/High (read-only) |
The suggested (high/low) validation limit, based on the meter data and the configured standard deviation. |
|
Units |
The units of the value. |
|
Values based on N rows |
The number of rows that were included in the statistical calculation. |
|
Reset |
Saves the current validation limits. |
|
Save Limits |
Saves the suggested validation limits. |
|
Show Trend / Show Histogram |
Alternates between showing the trends to showing the histograms. The histograms are showing the distribution profiles for each of the columns. The histograms (graphs) are displayed at the bottom of the screen. |