Prognosis of Bearing and Gear Wears Using Convolutional Neural Network with Hybrid Loss Function

Prognosis of Bearing and Gear Wears Using Convolutional Neural Network with Hybrid Loss Function

This study aimed to propose a prognostic method based on a one-dimensional convolutional neural network (1-D CNN) with clustering loss by classification training. The 1-D CNN was trained by collecting the vibration signals of normal and malfunction data in hybrid loss function (i.e., classification...

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Bibliographic Details
Main Authors: Chang-Cheng Lo, Ching-Hung Lee, Wen-Cheng Huang
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
wear prognosis
deep learning
convolutional neural network
vibration signal
Online Access:https://www.mdpi.com/1424-8220/20/12/3539

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