A Novel Approach to Condition Monitoring of the Cutting Process Using Recurrent Neural Networks

Feature evaluation and selection for condition monitoring using a self-organizing map and spatial statistics

(2018) Rui G. Silva et al.   AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING

Predicting tool life in turning operations using neural networks and image processing

(2018) T. Mikołajczyk et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Condition monitoring of turning process using infrared thermography technique – An experimental approach

(2017) Balla Srinivasa Prasad et al.   INFRARED PHYSICS & TECHNOLOGY

Artificial neural network based tool condition monitoring in micro mechanical peck drilling using thrust force signals

(2017) K. Patra et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

A survey of randomized algorithms for training neural networks

(2016) Le Zhang et al.   INFORMATION SCIENCES

Tool condition classification in turning process using hidden Markov model based on texture analysis of machined surface images

(2016) Nagaraj N. Bhat et al.   MEASUREMENT

Multi-sensor data fusion framework for CNC machining monitoring

(2016) João A. Duro et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Tool wear assessment based on type-2 fuzzy uncertainty estimation on acoustic emission

(2015) Qun Ren et al.   APPLIED SOFT COMPUTING

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Tool life prediction using Bayesian updating. Part 1: Milling tool life model using a discrete grid method

(2013) Jaydeep M. Karandikar et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

A review of flank wear prediction methods for tool condition monitoring in a turning process

(2012) A. Siddhpura et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring

(2009) T. Warren Liao   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Tool wear condition monitoring using a sensor fusion model based on fuzzy inference system

(2008) Cuneyt Aliustaoglu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Expert system development for vibration analysis in machine condition monitoring

(2006) Stephan Ebersbach et al.   EXPERT SYSTEMS WITH APPLICATIONS