In some DeltaV installations, lab data may be collected and recorded either manually or in a lab system that is not connected to the DeltaV system. Also, historical data may have been saved in the historian of another control system that is being replaced by the DeltaV system. In these cases, it may save time to use this historical data to create a virtual sensor that is being implemented in the DeltaV system. The Neural application can use data from a file to determine input sensitivity and train the neural network. This section describes how DeltaV Neural uses data files, the required data file format, and the utilities included in the DeltaV system to export data from the Continuous Historian into a file.
DeltaV Neural normally uses data from the Continuous Historian to perform network input sensitivity analysis and training. However, DeltaV Neural can use historical data saved in data files as well. The data file must contain historical values for all inputs and outputs used in the neural network and the data must be formatted correctly for DeltaV Neural to use.
To use historical data from a file, you must first create a module that contains a Neural Network function block. The NN block must reference the DeltaV inputs the neural network uses. Download this module to a controller or Application Station and then start DeltaV Neural. Connect DeltaV Neural to the NN block. From the DeltaV Neural main menu, select either or (to determine sensitivity and train in one step). The Sensitivity Analysis from File option is grayed out unless you are in Expert mode.
When you select either of these options, a dialog appears in which you specify the data file to use. After you select the file and click OK, DeltaV Neural performs the sensitivity analysis or autogeneration using the data file and presents the results as if you had used data from the Continuous Historian.
You can create models and verify models using data files. For best results, the values contained in the data file should reflect normal conditions over the operating range of the process. Any input or output sample values that represent abnormal conditions should be replaced by a non-numeric string in the data file. Use a tool, such as Microsoft Excel, to format and edit the file as required.
The data files must be saved as .dat files and formatted in a particular way for DeltaV Neural to use them. The data files must contain the following information formatted as described:
Line 1 - Must contain the phrase DeltaV_NN_Data <eol> Note The above header specifies to DeltaV Neural that this is a historical data file.
Line 2 - Lists the Number of Input references<tab>The number of Outputs <eol>
Line 3 - Lists the Number of samples in the file <tab> The sampling period in seconds <eol>
The sampling period must be the sampling period of the data in the file. It may be different than the Historian Sampling Rate configured in Control Studio for the block.
Line 4 - An empty line <eol>
Line 5 - Lists the identifiers of the Input references separated by tabs <eol>
The identifier names should match those that you configured in the associated Neural Network function block.
Line 6 - An empty line <eol>
Line 7 through the end of data - The data in the following order: index of the sample<tab>output value<tab>first input reference value<tab>second input reference value<tab>… last input reference value<tab>delay value (in seconds)<eol>
If the data contains values that do not reflect normal operating conditions, replace those values with non-numeric strings. The delay value is the time elapsed between sampling and lab analysis or sampled analyzer output becoming available. The Neural application shifts the output value by the delay value so that the inputs and the output are time coincident.
Last Line - An empty line <eol>
The following is an example neural network data file for a network considering three inputs and one output. The example shows only the first 15 and the last three sample input and output values out of the 389 total. Note that some of the output and input data values have been flagged as bad (the values have been replaced by BAD, but could have been replaced by any non-numeric string).
DeltaV_NN_Data 3 1 389 5 FI101 PI102 FI103 1 298.91198730 49.74733734 51.41758347 50.12039566 15.00000000 2 301.14556885 49.94604492 49.38345337 47.68234253 15.00000000 3 301.80010986 49.73253632 49.77395248 52.39353561 15.00000000 4 299.38861084 49.79014206 49.88610840 52.50535202 15.00000000 5 299.79846191 49.22924423 48.94361115 49.54271698 19.00000000 6 299.30975342 50.15618515 49.98815918 50.34877396 19.00000000 7 299.12210083 50.06230545 49.96276093 50.90197754 19.00000000 8 BAD 49.96342850 49.37252426 BAD 19.00000000 9 299.73184204 49.27413177 50.75104904 49.83951950 19.00000000 10 299.44027710 50.51338577 50.38288498 52.36296082 22.00000000 11 298.68725586 50.11240768 50.38404083 50.63307190 22.00000000 12 298.38619995 50.08751297 51.27215958 48.14796066 22.00000000 13 298.92086792 BAD 50.98120117 50.59751511 22.00000000 14 299.72399902 50.84034729 49.70337296 48.73555756 22.00000000 15 300.00738525 49.81303406 48.52415848 52.84468842 22.00000000 . . . . . . . . . . . . . . . 387 300.87734985 50.02370071 49.43601227 48.33786011 17.00000000 388 301.19873047 50.53816605 50.74356842 48.55810928 17.00000000 389 301.05834961 50.28169250 49.73216248 51.49454498 17.00000000