An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals
Joint Authors
Dai, Lang
Liu, Tianyu
Liu, Zhongyong
Jackson, Lisa
Goodall, Paul
Shen, Changqing
Mao, Lei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Something like normal functionality of tools in a manufacturing process is typically designed to ensure reliability, where fast and accurate identification of tool abnormal operation plays a vital role in intelligent manufacturing.
In this study, a novel method is proposed to assess the cutting tool condition, which consists of a convolutional neural network with wider first-layer kernels (W-CONV), and long short-term memory (LSTM).
The analysis benefits from the use of output power signals from the cutting tool, since they can be obtained easily and efficiently, enabling the proposed method to be applicable in practical operation for online condition monitoring.
Moreover, effectiveness of the proposed method is investigated, using test data from cutting tools at various tool wear conditions.
Results demonstrate that with the proposed method, tool wear condition can be identified accurately and efficiently.
Furthermore, with test data collected at cutting tools with different sizes, the robustness of the proposed method can be further clarified.
American Psychological Association (APA)
Dai, Lang& Liu, Tianyu& Liu, Zhongyong& Jackson, Lisa& Goodall, Paul& Shen, Changqing…[et al.]. 2020. An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals. Shock and Vibration،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1212873
Modern Language Association (MLA)
Dai, Lang…[et al.]. An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals. Shock and Vibration No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1212873
American Medical Association (AMA)
Dai, Lang& Liu, Tianyu& Liu, Zhongyong& Jackson, Lisa& Goodall, Paul& Shen, Changqing…[et al.]. An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1212873
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212873