Abstract
This paper presents a method for monitoring machine tool spindle health based on multi-domain analysis and convolutional neural network. By extracting the characteristics of data from time domain, frequency domain and time frequency domain, the data information is fully excavated automatically. Meanwhile, Convolutional neural network is used to realize fault diagnosis and classification. As a result, the fault classification results reveal high accuracy by datasheet. It proves that the method in this paper which has strong practicability and application value.
Full Text
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call