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Preprocess Data

Clean and label data in preparation for more advanced signal processing

In algorithm design for predictive maintenance, basic data preprocessing is often necessary to clean the data and perform other preliminary operations such as signal labeling prior to applying more specialized feature-focused processing. You can perform data preprocessing on arrays or tables of measured or simulated data that you manage with Predictive Maintenance Toolbox™ ensemble datastores. For an overview of some common types of data preprocessing, see Data Preprocessing for Condition Monitoring and Predictive Maintenance.

Apps

Data Cleaner	Preprocess and organize column-oriented data (Since R2022a)
Signal Labeler	Label signal attributes, regions, and points of interest, and extract features (Since R2019a)

Functions

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Basic Preprocessing

`fillmissing`	Fill missing entries
`filloutliers`	Detect and replace outliers in data
`smoothdata`	Smooth noisy data
`movmean`	Moving mean
`detrend`	Remove polynomial trend
`rescale`	Scale range of array elements

Topics

Data Preprocessing for Condition Monitoring and Predictive Maintenance
Use signal-processing techniques to preprocess data, cleaning it and converting it into a form from which you can extract condition indicators. Knowledge of your system can help you choose an appropriate preprocessing approach.