Import Data into Diagnostic Feature Designer
Diagnostic Feature Designeris an interactive tool for processing ensemble measurement data and extracting features that indicate the condition, such ashealthy
orfaulty
, of the machines that produced the data. The data can come from measurements on systems using sensors such as accelerometers, pressure gauges, thermometers, altimeters, voltmeters, and tachometers. The main unit for organizing and managing multifaceted data sets in the app is the data ensemble. Anensembleis a collection of data sets, created by measuring or simulating a system under varying conditions. Each row within the ensemble is amember. Each member of the ensemble contains the samevariables, such asVibration
orTacho
.
The first step in usingDiagnostic Feature Designeris to import source data into the app from your MATLAB®workspace. You can import data from tables, timetables, cell arrays, or matrices. You can also import an ensemble datastore that contains information that allows the app to interact with external data files. Your files can contain actual or simulated time-domain measurement data, spectral models or tables, variable names, condition and operational variables, and features you generated previously.Diagnostic Feature Designercombines all your member data into a single ensemble data set. In this data set, each variable is a collective signal or model that contains all the individual member values.
Before importing your data, it must already be clean, with preprocessing such as outlier and missing-value removal. For more information, seeData Preprocessing for Condition Monitoring and Predictive Maintenance.
During the import process, you select which variables you want to import, specify the variable types, and perform other operations to create the ensemble that you want to work with. When you click import, the app applies your specifications and creates an ensemble that contains your selected data. The following figure illustrates the overall import flow.
After you import your data once, you do not need to import it again for subsequent sessions. Save your session to store both the initial data ensemble and any derived variables and features you compute prior to saving. You can also export your data set to the MATLAB workspace, and save your data as a file that you can import in a subsequent session.
如果你有大量的乐团成员,有限公司nsider creating a representative subset of members when you first start exploring the data and potential features in the app. Because the app is interactive, importing a large number of members can result in slower performance. Instead, you can develop and rank features interactively with the smaller data set, and then generate code that repeats the computations on the original data set.
For more information on data sources, ensembles, and variable types in predictive maintenance, seeData Ensembles for Condition Monitoring and Predictive Maintenance.
Source Data Requirements
For signals, the app accepts individual membertable
arrays,timetable
arrays, cell arrays, or numeric matrices, each member containing the same independent variables, data variables, and condition variables. For spectral data, the app accepts individual membertable
arrays oridfrd
objects. This table describes the data requirements for variables within ensemble members.
Input Item | Content | Notes |
---|---|---|
Signal data | Timetables, tables, cell arrays, or numeric arrays | For time-based data, timetables are recommended. |
Signal independent variables (IVs) | Double,duration , ordatetime |
For each signal variable, all member IVs must be of the same type, whether your signal is based on time or on another IV such as consumption or duty cycles. 如果你的会员数据存储在一个矩阵,你亩t have only one IV that applies to the full set of signals that you are importing. If your data was uniformly sampled in time and you do not have recorded timestamps, you can construct a uniform timeline during the import process. |
Spectral data | Numeric (double) table oridfrd object |
Each You cannot import spectra from matrices. |
Condition variables (CVs) | Scalar — Numeric, string, cell, or categorical | You can import condition variables along with your data in tables, timetables, or cell arrays, but not in matrices. |
Features | Scalar — Numeric, string, or cell | You can import features that you computed previously, either externally or within the app itself. |
Matrices | Purely numeric array that contains columns representing a single IV and any number of signals that share that IV. Cannot accommodate spectra. Cannot generally accommodate condition variables or features. | Matrices cannot accommodate variable names. You can import condition variables and features from a matrix if your data set contains only scalars and does not contain signals. |
You can import data members individually or as an ensemble that contains all your data members. This ensemble can be any of the following:
An ensemble table containing
table
arrays, cell arrays, or matrices. Table rows represent individual members.An ensemble cell array containing tables, cell arrays, or matrices. Cell array rows represent individual members.
An ensemble datastore object such as a
fileEnsembleDatastore
orsimulationEnsembleDatastore
object that contains the information necessary to interact with files stored externally. Use an ensemble datastore object especially when you have too much data to fit into app memory. Reading and writing to external files during computations does impact performance, however. To create a representative subset of the ensemble datastore files to work with, seesubset
.An ensemble matrix that contains only condition variables and features. Matrix rows represent individual members.
A labeled signal set, which is a
labeledSignalSet
object, that contains labeled data for signals, condition variables, and features.
For more information about organizing your data for import, seeOrganize System Data for Diagnostic Feature Designer.
Typical Workflows for Data Import
The following sections describe typical workflows for different types of data import. The first workflow describes the overall import process and the subsequent workflows focus on variations that are specific to the import data format. The following table summarizes the cases for the workflows.
Import Type | Summary |
---|---|
Ensemble table | Core workflow that describes the import of an ensemble table, including ensemble specification, configuration, import, and confirmation in the app |
Individual Ensemble Members | Use of the filtering capability within the import dialog process to quickly select and import individual ensemble members that are represented by tables or timetables |
Matrices | Use of matrix column indices for variable identification. Alternative specification of matrix as feature rather than signal. |
Spectral Data | Import of spectral data inidfrd object or in a table with columns that contain frequency or order values and corresponding data values |
Signal with no IV | Import of signal with no explicit time stamps by generating virtual IV |
Signal with multiple IVs | Specification of an alternative IV so that the signal can be analyzed in the app using either IV |
Ensemble Datastore | Specification of an ensemble datastore that contains information on interacting with external files. |
Import Labeled Signal Set (LSS) | Import of signal, condition variable, and feature information from alabeledSignalSet object. |
Core Workflow—Import Ensemble Table
This workflow illustrates the steps for importing an ensemble table into the app.
Load Ensemble Table intoMATLABWorkspace
合奏表加载到MATLAB工作区. You can preview the data in the workspace variable browser, as this example shows. In this case, the data set contains two time-based signals and a scalar condition variable namedfaultCode
.
Open App and Start New Session
Open the app by enteringdiagnosticFeatureDesigner
at the command line. Then, clickNew Session. This action opens the import dialog box.
Select Ensemble Table from Source Variables
In theSelect dataset from workspacepane, select your ensemble table as theSource.
View Source Variable Components and Change Variable Type and Units
TheSelect source variablespane displays the variables from your ensemble. In the following example figure, the app identifies theVibration
andTacho
variables as time-based signals that each containTime
andData
variables. The third variable in the variable set for each signal,Sample (Virtual)
, is not checked.Sample (Virtual)
allows you to generate an IV, especially when your source data set does not contain an explicit IV. For more information onSample (Virtual)
, seeImport Signal with No Time Variable.
The icons identify the variable type that the app assumes. The icon next tofaultCode
, which illustrates a histogram, represents a feature. Both features and condition variables are scalars, and the app cannot distinguish between the two unless the condition variable is categorical. To change a variable type, click the variable name to open the variable properties in theConfigure source variable propertiespane. Then, inVariable type, changeFeaturetoCondition Variable.
The icon forfaultCode
now illustrates a label, which represents a condition variable.
For signal and spectrum variables, you can also change the units that the app uses for plotting and for other operations within the app. To do so, in the lower level variable list of the signal or spectrum variable, click the name of the IV or data variable. TheConfigure source variable propertiespane provides a menu of options for each property that you can modify. In the following example figure,Configure source variable propertiesdisplays properties for theTime
variable of theVibration
signal. The figure illustrates the selection ofMinutesfrom the menu ofUnitsoptions.
Preview Data Variables
In addition to providing options for variable properties such asType
, theConfigure source variable propertiespane displays a preview of your import data when you click the name of a signal or spectrum variable. The following example figure shows the preview of theVibration
data. The preview pane in the figure displays source data for the first tenVibration
samples of the first ensemble member, and includes values for IV, data, and the sample index.
The preview pane displays source properties only. The preview pane does not reflect any property modifications that you make in the pane. For example, if you change the units of theVibration
signal from seconds to minutes, the preview pane still displays source units of seconds. When you complete the import, the app converts the time data to minutes for use in the app.
Confirm Ensemble Specification and Execute Import
Confirm the ensemble specification in the Summary pane at the bottom of the dialog box. ClickImportto execute the data import.
Confirm Successful Import into App
Confirm the import in the variables pane. In this example, the two signals appear in theSignalslist. The condition variableFaultCode
appears in theCondition Variableslist. Beneath the variables pane is theDetailspane, which provides additional information about the selected variable.
SelectVibration/Data
and clickSignal Traceto plot the data and view the imported signals, as the following example figure shows. For more information on plotting data, seeImport and Visualize Ensemble Data in Diagnostic Feature Designer.
Import Individual Members
This workflow describes the steps associated with importing ensemble members individually.
Initiate Import Process
Load the individual member variables into your MATLAB workspace, open the app, and clickNew Session. In theSelect dataset from workspacepane, theSourcemenu displays a list of the files in your workspace. The following example figure shows 10 member files and one additional file,sens2
, that is not an ensemble member.
Select Ensemble Members
Select one of the variables that represents an ensemble member. In this example, selectd1
. The app opens a list of all compatible workspace variables that contain the same internal variables. You can select any combination of these variables or clickSelect Allto select all of them at once.
Import Individual Timetables
If your individual members are packaged as timetables with a scalar value for each time point, specifyUse as signalto have the app interpret the timetable variable as a signal rather than as a feature.
Complete Import Process
Once you select your variables, the remaining import steps are the same as inCore Workflow—Import Ensemble Table. The app combines the members you import into a single ensemble.
矩阵数据导入
This workflow describes the import of signals from individual member matrices. When you import data in matrices, each signal in the ensemble must share one independent variable, such as a time variable, with all signals in the ensemble. You cannot import condition variables, features, or spectral data in matrices.
Select and Preview Matrices to Import
Load your matrices into the MATLAB workspace, and then initiate the import process by clickingNew Session. In theSelect dataset from workspacepane, select one of your matrices and clickSelect All. For matrices, this pane also displays aUse as featureoption. This option applies to the special case where a matrix contains only scalar condition variables and features, and no signal data.
Because matrices are numeric, the app identifies each variable column by its column index. The following example figure shows four member matrices. The first column of each matrix contains the IV representing time, and the second and third columns contain the data values for vibration and tacho data. To preview the contents of the ensemble, in theSelect Source variablespane, select theMatrix
row.
Confirm Variable Types
The app interpretsCol1
as the IV because it is monotonic, andCol2
andCol3
as signal data variables.
If you cannot accurately represent your signals with a single time variable, convert your matrices into tables before import.
Complete and Confirm Import
ClickImportto complete the import. Confirm that the variables pane contains the signals you want, as shown in the following example figure.
The app merges the matrices into an ensemble data set that contains the four matrices.
This workflow demonstrates that you can import matrices, but only with limitations. If you want to identify your variables by name, import condition variables or features, or use independent timelines for independent signals, convert your matrices to tables or cell arrays prior to import. For an example of converting a set of matrices to an ensemble table, seePrepare Matrix Data for Diagnostic Feature Designer.
Import Spectral Data
This workflow illustrates how to import spectral data. You can import spectral data in two forms:
An
idfrd
object that contains frequency and spectrum data for a single spectrum in theFrequency
andSpectrumData
properties, respectivelyA table that contains columns with the frequency and spectral data
When you import anidfrd
object, the app recognizes that the data source is spectral, and defaults to theSpectrumvariable type, as the following example figure shows.
When you import spectral data in a table, the app defaults to theSignalvariable type, but provides additional options for theSpectrumandOrder Spectrumvariable types. The following example figure illustrates the import of spectral data in a table.
You can also import order spectra that contain order rather than frequency information. Order spectra are useful for analyzing rotating machinery. Each order is a multiple of a reference frequency, such as the primary-shaft rotational frequency. The following example figure illustrates the import of an order spectrum.
When you complete the import, theVariablespane displays the spectra, as the following example figure shows.
Import Signal with No Time Variable
This workflow illustrates how to generate a virtual IV if your data set includes signals that contain no IV. For instance, you might have a signal that was measured or generated in uniform time samples, but which does not include a vector of the actual time stamps. The app can generate a virtual timeline that contains the same sample rate.
Select Data Source and View Source Variables
Initiate the import process and select workspace variables to import. In the following example figure, the data source is a table that containsVibration
andTacho
variables. However, these variables contain only measurement data and no time information. As always, the app provides aSample (Virtual)
option. In this case, since the data has no IV, the app automatically selects this variable.
View Virtual IV Properties
The default unit for a virtual IV is the sample index. You can modify this default setting by selecting theSample (Virtual)
name, which opens the source properties. The following example figure displays the default properties.
Reconstruct Signal Time Variable Using Sample Time
If you know the sample time of the signal, you can reconstruct the time variable. To do so, changeIndependent variable nameto the name you want,IV typetoTime,Unitto the time units you want, andSampling intervalto the sample time. For example, consider that you know the sample time for bothVibration
andTacho
is 0.001 seconds. The following figure shows how to set this sample time forVibration
. Note that these settings do not affectTacho
.
Once you have reconstructed the IVs that you want, complete the import process. You can view your reconstructed timelines by plotting your imported signals in the app. The following figure shows plots forVibration
, which has the reconstructed timeline, andTacho
, which retains the default IV ofSample
.
Specify Sample Index as Alternative IV
This workflow describes the steps for specifying the signal sample index as an alternative IV when you also import a time variable or some other signal IV.
Specify Sample Index as IV
Initiate the import and select the data to import. In theSelect source variablespane, selectSample (Virtual)
and view the properties. The following example figure illustrates this step. In this figure,Vibration
now has all three lower level variables selected. TheConfigure source variable propertiespane displays the default IV type and unit forSample (Virtual)
, which areIndexandsamples, respectively.
Perform the same operation on all variables for which you want to include the sample index. Complete the import process.
Switch to Sample Index the App
The app defaults to the IV type that you imported with the data. To switch to the sample index, inOptions, selectIndex, as the example figure illustrates.
All signals that includeIndexas an alternative IV type now use the sample indices rather than the time values. When you plot the data, the signal trace uses the sample data, as the following example figure shows.
Import Ensemble Datastore
This workflow describes the steps for importing afileEnsembleDatastore
object or asimulationEnsembleDatastore
object. Ensemble datastore objects provide information that allows the app to interact with external files. They include specifications for the variables you want to read, the variable types, and the source file locations. When you import an ensemble datastore, you can choose whether to store results within the app memory or write the results back to the ensemble datastore. For more information about ensemble datastores, seeData Ensembles for Condition Monitoring and Predictive Maintenance.
Select Data Source and View Source Variables
Initiate the import process. In theSelect dataset from workspacepane, select the ensemble datastore. The app uses the ensemble datastore properties forSelectedVariables
to select the variables to display. The app also uses theDataVariables
,IndependentVariables
, andConditionVariables
properties to determine which variables belong to which of these variable types. The example figure illustrates the import of asimulationEnsembleDatastore
objectens
.
在前面的示例图,应用解释sens
as follows:
The data variables
Flow
andPressure
appear identical in form to timetable-based variables extracted from tables.ens
includes the standardsimulationEnsembleDatastore
variableSimulationInput
in theSelectedVariables
property. However, the app does not support theSimulationInput
data format and displays an orange warning icon. The app also automatically clears the selection and deletesSimulationInput
fromens.SelectedVariables
.CombinedFlag
appears as a condition variable in accordance withens.ConditionVariables
.
Choose How App Interacts with External Files
You can choose whether the app interacts with the external files referenced in your ensemble datastore. In the Select more variables pane, useAppend data to file ensembleto specify your choice.
如果你选择这个选项,应用国际米兰acts directly with the external files and writes results, such as derived variables or features, to the same folder as the original data. If you are using a
fileEnsembleDatastore
object, the object must include a reference to awrite
function that is specific to your data structure. You do not need awrite
function if you are using asimulationEnsembleDatastore
object.If you clear this option, the app stores results in local app memory for the duration of the session. Select this option if, for example:
You want to keep your source files pristine at least until you have finalized your processing and feature generation.
You do not have write permission for your source files.
You do not have a
write
function, and you are using afileEnsembleDatastore
.The process of writing the results back to the source files is slow.
To retain your local results at the end of the session, useSave Session. You can also export your results as a
table
MATLAB的工作区。从工作空间,您can store the results in the file, or integrate results selectively using ensemble datastore commands.
Import Labeled Signal Set (LSS)
This workflow describes the steps for importing an LSS, orlabeledSignalSet
object, fromSignal Labelerin Signal Processing Toolbox™. The signals you import must be full signals and not framed (segmented) signals.
Select Data Source and View Contents
Initiate the inport process. In theSelect dataset from workspacepane, select the LSS. The app retains the LSS labels and interprets the variables as signals, condition variables, and features, according to the variable roles in the LSS and their data type.
View Imported Variables and Features in Variables Pane
View the imported variables and features in the variables pane. The imported data retains the labels and the variable and feature designations.
See Also
Diagnostic Feature Designer|table
|timetable
|simulationEnsembleDatastore
|fileEnsembleDatastore
|idfrd
|subset
|labeledSignalSet
Related Topics
- Data Ensembles for Condition Monitoring and Predictive Maintenance
- Organize System Data for Diagnostic Feature Designer
- Import and Visualize Ensemble Data in Diagnostic Feature Designer
- Prepare Matrix Data for Diagnostic Feature Designer
- Data Preprocessing for Condition Monitoring and Predictive Maintenance