Advanced Serial Data Logger

Process data from the HMI scale indicator

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Problem scenario:

I'm doing a Project for a pecan farm in New Mexico that wants to capture the weight of the bags of pecans as they are processed and save that data to an Excel file.

I'm using the Rice Lake 920i HMI scale indicator with a WLAN card, and I'm sending the data to the network each time the user presses the "print" button on the indicator. My goal is to transfer this data to Excel, such that each time the user hits "print," a new row is appended to an existing Excel file that contains the data.

Currently, when the user presses "print," the following data shows up in the Advanced Serial Data Logger main window:

Largest Pecan Farm
1 HMI 1, La Scala, NM   88111
Date/Time: 01.24.14:08:14.51
Superbag ID: 12312
Gross Weight: 2103lbs
Variety: Wichita
Grade: No. 1
Farm: Murano

I would like this data to appear in Excel as follows:

DATE             BAG ID               WEIGHT                VARIETY             GRADE              FARM
01/24/14         12312                2103                  Wichita             No. 1              Murano
01/24/14         12313              1994                  Wichita             No. 1            Murano
01/24/14         12314              2068                  Wichita             No. 1              Murano


It is assumed that:

You've configured communication parameters (baud rate, the number of data bits, flow control, etc.) in the data logger and can receive any data without communication errors.


The image above shows that the data flow is very simple, but we should extract data variables from a report with multiple rows.

It is clear from the data example above that the data block starts with "Date/Time:" and ends with "Farm: " with some letters.

We are now ready to configure modules. First, select the "ASCII data query and parser" plugin (fig.1, pos.1) from a drop-down list. Then, enable a parsing option for data received (fig.1, pos.2) and select the necessary data export plugins. The DDE server (fig.2) will help us to check that the data packet is parsed and exported. The "Excel Export Pro" plugin will write data directly to the XLS file without Microsoft Excel installed.

Data parser plug-in
Fig.1.Data parser plugin.

Data export plug-ins
Fig.2.Data export plugins.

Now, please, open the ASCII parser and query configuration window by clicking the "Setup" button near a drop-down box (fig.1, pos.1). The dialog window below will appear on the desktop (fig.3).

The parser configuration window
Fig.3.The parser configuration window.

The configuration process should be straightforward if you have examined your data flow in the data logger window (fig.3). You should type in the same as in the data logger window in fields 1 and 2. Field #1 marks the beginning of the data block, and field #2 marks the end. In this example, our data block contains both markers. Therefore, all fields are not empty. The values to be typed in here are as underlined in red in fig.3 above. Because the end marker is not constant, we'll use a regular expression as the end marker. The expression "\bFarm: [A-Za-z0-9]+[\x0D\x0A]+" means any string that begins with the "Farm" word and following by any characters from the specified range. The "RE" checkbox near the expression field instructs the parser to search the signature using a regular expression (not plain text).

Because the report in this example is rather short, we should set the "Timeout" value (fig.3 pos.#3) to a corresponding value to prevent data loss. The option at pos.4 allows you to use the start marker in the parsing process.

The next tab is a significant part of the parser configuration. The data parser uses this information for data extraction from the data block. In the example, the data block contains 6 data items (look at the data example above), namely: DATE, BAGID, WEIGHT, VARIETY, and so on, that should be separated out to different variables. Later, these variables will be used in the data export and placed in different columns of our Excel file. The file with all variables you can download here (right-click → Save As) and load it on the "Data parsing" page (fig.4 pos.#8).

Parser items
Fig.4. Parser items.

Any new items may be added by clicking the "Add item" button (fig.4, pos.7). Before adding an item, the program will ask you about an item description. You can type any characters here, which will help you to remember a variable's content. For this example, all six variables with their corresponding descriptions have been added.

Each parser item has several properties:

  1. Item name. This name will be bound to a column in a data export plugin. It is a limited text description and cannot contain spaces and a few other characters;
  2. Parser's type. It is a method which the program use for data extraction. Our parser has a few methods from simple to the most powerful. In this example, where data items are placed in a variable place, we should use the most powerful method - regular expressions. This method allows you to extract data from any position of the report by a mask. This mask can be widely transformed and adapted to characters in the report;
  3. Data type. It is the data type of the characters extracted. For example, you can specify FLOAT, DATE, TIME, or STRING data types. The data will be converted to the selected data type. The plugin uses the format settings for the selected data type from the "Data formats" tab. In the example, we use the FLOAT data type for all numbers, the DATETIME type for date and time, the STRING for other parser items;
  4. Default value. The value specified here is to be used when data cannot be extracted from a data block. In this example, some numbers may not exist in the report. Therefore we should define a default value for all variables;
  5. Regular expression. In this example, we need numbers or strings, which follow by a dot or the ":" character in several places of the report. For example, a regular expression will look lile Date\/Time: ([\d\.\:]+). Here, the expression in parenthesis is our date and time, which we should extract to a variable. Please, search in Google for a detailed description of regular expressions;
  6. Entrance position. All our values are present in the report once only. Therefore an entrance position for each variable is 1.

All other items have identical parameters, except a data type and a regular expression.

Name Expression Meaning
DATE Date\/Time: ([\d\.\:]+) sequence of any combination of digits, dots and colons
BAGID Superbag ID: (\d+) any digits
VARIETY Variety: ([^\x0D\x0A]+) any characters before a line ending characters (\x0D and \x0A mean ASCII codes for CR and LF)
WEIGHT Weight: ([\d\.]+) any digits (the units will not be included)
GRADE Grade: ([^\x0D\x0A]+) any characters before a line ending characters
FARM Farm: ([^\x0D\x0A]+) any characters before a line ending characters

On the next tab, you can specify basic format options as per (fig.5). In this example, one variable has the "datetime" data type. Therefore the first option (fig. 5, pos. #1) allows you to convert the date string to a field with the "datetime" data type. We specified MM"."DD"."YY":"HH":"NN"."SS here, according to the data example above. For a detailed description of formatting characters, please, see the help file.

Date/time format
Fig.5. Date/time format.

Therefore the second option (fig. 5, pos. #2) allows you to trim unnecessary spaces from left and right from "string" values.

Click the "OK" button and close the parser configuration window. Then click the "OK" button in the options window.

Now our parser is ready, it is time for testing it. Connect your device and power it on if necessary. Check to see if you can receive a data block from the specified port. If the parser had been correctly set up, you should see all parser items and their values (fig. 6) in the DDE server window below.

Testing parser. DDE server window.
Fig.6. Testing parser. DDE server window.

All parser variables are now ready for export to an Excel spreadsheet. You can read about it in the second part.

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