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Manage System Data

Import measured data, generate simulated data, organize data for use at the command line and in the app

Data analysis is the heart of condition monitoring and predictive maintenance. Designing algorithms for predictive maintenance requires organizing and analyzing large amounts of data while keeping track of the systems and conditions the data represents.

Predictive Maintenance Toolbox™ provides tools for managing sensor data stored locally and remotely, as well as for generating simulated data by running a Simulink® model. The main unit for organizing and managing multifaceted data sets in Predictive Maintenance Toolbox is an ensemble. An ensemble is a collection of data sets, created by measuring or simulating a system under varying conditions. You can store smaller ensembles in forms such as tables, timetables, and cell arrays. Manage larger ensembles using ensemble datastore objects. For more information about how ensembles work and how to use them, see Data Ensembles for Condition Monitoring and Predictive Maintenance.

The Diagnostic Feature Designer app includes interactive tools for processing data and extracting features. The app accepts data sets in various forms, consolidates the data within the app, and manages that data internally during a session. For more information on the app, see Explore Ensemble Data and Compare Features Using Diagnostic Feature Designer.


fileEnsembleDatastoreManage ensemble data in custom file format
simulationEnsembleDatastoreManage ensemble data generated by generateSimulationEnsemble or by logging simulation data in Simulink
workspaceEnsembleManage ensemble data stored in the MATLAB workspace using code generated by Diagnostic Feature Designer (Since R2020a)


generateSimulationEnsembleGenerate ensemble data by running a Simulink model
readRead member data from an ensemble datastore
writeToLastMemberReadWrite data to member of an ensemble datastore
hasdataDetermine if data is available to read
resetReset datastore to initial state
subsetCreate new ensemble datastore from subset of existing ensemble datastore (Since R2021a)
summary Return or plot condition variable distribution in an ensemble datastore (Since R2024a)
numpartitionsNumber of datastore partitions
partitionPartition a datastore
progress Determine how much data has been read
tallCreate tall array


Ensemble Datastore Basics

Data Management in the Diagnostic Feature Designer