In-process detection of grinding burn using machine learning

Scaling tree-based automated machine learning to biomedical big data with a feature set selector

(2019) Trang T Le et al.   BIOINFORMATICS

An intelligent grinding burn detection system based on two-stage feature selection and stacked sparse autoencoder

(2019) Weicheng Guo et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A survey of methods for detecting metallic grinding burn

(2018) Baofeng He et al.   MEASUREMENT

Online evaluation of metal burn degrees based on acoustic emission and variational mode decomposition

(2017) Zheyu Gao et al.   MEASUREMENT

Traceability of acoustic emission measurements for micro and macro grinding phenomena—characteristics and identification through classification of micro mechanics with regression to burn using signal analysis

(2015) James Marcus Griffin   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A review of the application of acoustic emission technique in engineering

(2015) S. Gholizadeh et al.   STRUCTURAL ENGINEERING AND MECHANICS

Variational Mode Decomposition

(2014) Konstantin Dragomiretskiy et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

A non-destructive surface burn detection method for ferrous metals based on acoustic emission and ensemble empirical mode decomposition: from laser simulation to grinding process

(2014) Zhensheng Yang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Advanced monitoring of machining operations

(2010) R. Teti et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Multiple classification of the acoustic emission signals extracted during burn and chatter anomalies using genetic programming

(2009) James Marcus Griffin et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY