预测性维护

利用预测性维护应用程序扩展深度学习工作流

通过将 Deep Learning Toolbox™ 与 Predictive Maintenance Toolbox™ 结合使用，将深度学习应用于预测性维护。您可以训练深度神经网络来执行各种预测性维护任务，如故障检测和剩余使用寿命估计。

主题

Generate Synthetic Signals Using Conditional GAN
Use a conditional generative adversarial network to produce synthetic data for model training.
Chemical Process Fault Detection Using Deep Learning
Use simulation data to train a neural network than can detect faults in a chemical process.
Rolling Element Bearing Fault Diagnosis Using Deep Learning
This example shows how to perform fault diagnosis of a rolling element bearing using a deep learning approach.
Remaining Useful Life Estimation Using Convolutional Neural Network
This example shows how to predict the RUL of engines using deep convolutional neural networks (CNN).
Anomaly Detection in Industrial Machinery Using Three-Axis Vibration Data
Detect anomalies in industrial-machine vibration data using machine learning and deep learning.
Battery Cycle Life Prediction Using Deep Learning
Predict the remaining cycle-life of a fast charging Li-ion battery by training a deep neural network.