Название: Matlab Predictive Maintenance Toolbox User’s Guide
Автор: MathWorks
Издательство: The MathWorks, Inc
Год: 2018
Страниц: 354
Язык: английский
Формат: pdf (true)
Размер: 10.19 MB

Data analysis is the heart of any condition monitoring and predictive maintenance activity. Predictive Maintenance Toolbox provides tools for labeling data, designing condition indicators, and estimating the remaining useful life (RUL) of a machine. You can analyze and label machine data imported from local files, cloud storage, and distributed file systems. You can also label simulated failure data generated from Simulink models.

Signal processing and dynamic modeling methods that build on techniques such as spectral analysis and time series analysis let you preprocess data and extract features that can be used to monitor the condition of the machine. To estimate a machine's time to failure, you can use survival, similarity, and trend-based models to predict the RUL.

The toolbox includes reference examples for motors, gearboxes, batteries, and other machines that can be reused for developing custom predictive maintenance and condition monitoring algorithms.