预测性维护

通过并行计算加速预测性维护应用

通过将 Parallel Computing Toolbox™ 与 Predictive Maintenance Toolbox™ 结合使用，利用并行计算来加速预测性维护应用。

主题

Accelerate Fault Diagnosis Using GPU Data Preprocessing and Deep Learning (Predictive Maintenance Toolbox)
This example shows how to use GPU computing to accelerate data preprocessing and deep learning for predictive maintenance workflows. (自 R2025a 起)
Detect Anomalies in Industrial Machinery Using Three-Axis Vibration Data (Predictive Maintenance Toolbox)
Detect anomalies in industrial machine vibration data using machine-learning and deep-learning models trained with data representing only nominal behavior.
Detect Aging Severity in Power Converters (Predictive Maintenance Toolbox)
Generate synthetic semiconductor degradation data from a power converter model, and use that data to build a predictive maintenance algorithm that can detect aging severity in a power converter.
Remaining Useful Life Estimation Using Convolutional Neural Network (Predictive Maintenance Toolbox)
This example shows how to predict the RUL of engines using deep convolutional neural networks (CNN).