CONTEMPORARY CHALLENGES IN TOOL CONDITION MONITORING | Zendy

Krzysztof Jemielniak | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

CONTEMPORARY CHALLENGES IN TOOL CONDITION MONITORING

Author(s) -

Krzysztof Jemielniak

Publication year - 2019

Publication title -

journal of machine engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.588

H-Index - 7

eISSN - 2391-8071

pISSN - 1895-7595

DOI - 10.5604/01.3001.0013.0448

Subject(s) - computer science , signal (programming language) , feature (linguistics) , condition monitoring , feature extraction , segmentation , artificial intelligence , signal processing , feature selection , data mining , industrial engineering , control engineering , engineering , digital signal processing , computer hardware , philosophy , linguistics , electrical engineering , programming language

Implementation of robust, reliable tool condition monitoring (TCM) systems in one of the preconditions of introducing of Industry 4.0. While there are a huge number of publications on the subject, most of them concern new, sophisticated methods of signal feature extraction and AI based methods of signal feature integration into tool condition information. Some aspects of TCM algorithms, namely signal segmentation, selection of useful signal features, laboratory measured tool wear as reference value of tool condition – are nowadays main obstacles in the broad application of TCM systems in the industry. These aspects are discussed in the paper, and some solutions of the problems are proposed.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research