Getting Started with MATLAB and Predictive Maintenance - MATLAB & Simulink

Predictive Maintenance

Getting Started

Learn how to use MATLAB for predictive maintenance by exploring examples, articles, and tutorials.

Workflow and Concepts

Overview of the Algorithm Development Workflow

Overview of Preprocessing Techniques for Cleaning up Data - Documentation
Overview of Feature Extraction Methods for Designing Condition Indicators - Documentation
Overview of Decision Models for Fault Detection and Diagnosis - Documentation
Overview of Predictive Models for Estimating Remaining Useful Life - Documentation

Gearboxes and Bearings

Remaining Useful Life Estimation for a Wind Turbine Bearing

Fault Diagnosis in an Oil Pump Bearing - Example
Generating Failure Data for a Transmission System - Example
Gear Tooth Fault Analysis using Vibration Data - Example

Pumps, Motors, and Batteries

Fault Classification in a Reciprocating Pump

Fault Detection in a DC Motor using Kalman Filters - Example
Residual Analysis of Centrifugal Pumps - Example
Estimating Battery Degradation using Kalman filters - Example
Onboard Diagnostics for Pumps Using Simulink and Machine Learning (49:35) - Video

Aircraft and Helicopters

Remaining Useful Life Estimation of a Jet Engine Using Similarity Methods

Process Plants and Power Systems

Mondi Implements Statistics-Based Health Monitoring and Predictive Maintenance for Manufacturing Processes with Machine Learning

Apps for Signal Preprocessing, Feature Extraction, and Predictive Modeling

Signal Analyzer App for Visualizing, Preprocessing, and Comparing Data

Wavelet Signal Denoiser App for Denoising Time-Series Data - Documentation
Classification Learner App for Training and Validating Classification Models - Documentation
Regression Learner App for Training and Validating Regression Models - Documentation

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