Deploy Predictive Maintenance Algorithms
Implement and deploy condition-monitoring and predictive maintenance
algorithms
Deployment or integration of a predictive maintenance algorithm is typically the final stage of the algorithm-development workflow. How you ultimately deploy the algorithm can also be a consideration in earlier stages of algorithm design. MATLAB® products support several phases of the process for developing, deploying, and validation process for predictive maintenance algorithms.
Functions
Topics
Deployment Basics
- Deploy Predictive Maintenance Algorithms
Understand the phases of deployment and implementation of your predictive-maintenance algorithm.
Deploy RUL Prediction Algorithms
- Generate Code for Predicting Remaining Useful Life
Deploy an algorithm for predicting remaining useful life (RUL). Such code generation is useful when you have trained an RUL model and are ready to deploy the prediction algorithm to another environment. - Generate Code That Preserves RUL Model State for System Restart
Generate code that preserves the state of the RUL model when the prediction algorithm is stopped and restarted.
Generate Streaming Code from Diagnostic Feature Designer
- Export Feature Extraction Function and Simulink Model for Streaming Data
From Diagnostic Feature Designer, export feature-extraction code formatted for streaming data that is MATLAB Coder™ compliant and a Simulink® model that contains that code.