Diagnostic Feature Designer is an app that allows you to develop features and evaluate potential condition indicators using a multifunction graphical interface.
The app operates on data ensembles. An ensemble is a collection of data sets, created by measuring or simulating a system under varying conditions. An individual dataset representing one system under one set of conditions is a member. Diagnostic Feature Designer processes all ensemble members when executing one operation.
The following series of examples take you through the Diagnostic Feature Designer workflow, from your initial data inport to export of your chosen features.
This first example shows how to import data into Diagnostic Feature Designer and visualize your imported data.
This example uses data generated from a transmission system model in Using Simulink to Generate Fault Data. Outputs of the model include:
Vibration measurements from a sensor monitoring casing vibrations
Tachometer sensor, which issues a pulse every time the shaft completes a rotation
Fault code indicating presence of a modeled fault
Load the data. The data is a table containing variables logged during multiple simulations of the model under varying conditions. Sixteen members have been extracted from the transmission model logs to form an ensemble. Four of these members represent healthy data, and the remaining 12 members exhibit varying levels of sensor drift.
load dfd_Tutorial dataTable
View this table in your workspace.
dataTable = 16×3 table Vibration Tacho faultCode __________________ __________________ _________ [6000×1 timetable] [6000×1 timetable] 0 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 0 [6000×1 timetable] [6000×1 timetable] 0 [6000×1 timetable] [6000×1 timetable] 0 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1 [6000×1 timetable] [6000×1 timetable] 1
Tachoare each represented by a timetable, and all timetables have the same length. The third variable,
faultCode, is the condition variable.
faultCodehas a value of
0for healthy and
To open the Diagnostic Feature Designer, in your command window, type:
Import the dataset that you previously loaded into your workspace. In the Import Data menu, select Import Multi-Member Ensemble.
Confirm the selection for Ensemble variable, and click Next.
Review the list of imported variables and variable types.
The app has extracted the variable names from your member tables and embedded
timetables. For example, in your source table, the
variable is a
Data. The variable names resulting from the import are
The variables derived from the vibration and tacho signals have the correct variable types. These variables are unambiguous because they come from timetables.
faultCode has the incorrect variable type
Feature when it is a
Condition Variable. Both features and
condition variables can be numeric scalars. Update
faultCode, and click
Review the signals and the independent and condition variables that apply to the signals. Note the ensemble name. To complete the import process, click Import.
Your imported signals are now in the Signals & Spectra
area, and your imported ensemble
Ensemble1 is in the
The color code next to a signal represents that signal in plots. The icon to the
left of the signal indicates the variable type, which, for the variables you
Display information about your dataset by selecting its name in the Datasets area.
Now that your signals are loaded, plot them and view all your ensemble members together. To view your vibration signal, in the Signals & Spectra area, select Vibration. Selecting a signal variable enables the Signal Trace option in the plot gallery. Click Signal Trace.
The plotting area displays a signal trace plot of all 16 members. As you move the cursor over the data, an indicator in the lower right corner identifies the member your cursor is on. A second indicator provides the fault code value for that member.
Interact with the trace plot using standard MATLAB® plot tools, such as zoom and pan. Access these tools by hovering above the top right edge of the plot. You can also use the specialized options on the Signal Trace tab, which appears when you select the Signal Trace plot.
Explore the data in your plot using options in the Signal Trace tab.
Measure the distance between peaks for the one of the members with the high peaks.
Zoom in on the second clusters of peaks. Click Panner. In the panner strip, move the right handle to about 8. Then, move the panner window so that the left handle is at about 4. You should now have the second set of peaks within the window.
Hover over the first high peak, and note the member number. The second high peak is a continuation of the same member trace.
Click Data Cursors, and select
Vertical Cursor. Place the left
cursor over the first high peak and the right cursor over the second
peak for that member. The lower right corner of the plot displays
Select Lock Horizontal Spacing. Shift the cursor pair to the right by one peak for the same member. Is the right cursor aligned with the third member peak?
Restore the full window by moving the handles back to the edges of the panner.
Show which members have matching
faultCode values by using
color coding. Select Ensemble View Preferences > Group by
The resulting signal trace shows you that all the highest vibration peaks are associated with a data from faulty systems. However, not all the faulty systems have higher peaks.
Save your session data. You need this data to run the Process Data and Explore Features in Diagnostic Feature Designer example.
The next step is to explore different ways to characterize your data through features. The example Process Data and Explore Features in Diagnostic Feature Designer guides you through the feature exploration process.