Position-varying surface roughness prediction method considering compensated acceleration in milling of thin-walled workpiece

Simultaneous Calibration of Multicoordinates for a Dual-Robot System by Solving the AXB = YCZ Problem

(2021) Gang Wang et al.   IEEE Transactions on Robotics

Machining vibration monitoring based on dynamic clamping force measuring in thin-walled components milling

(2020) Wuyang Sun et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Bayesian linear regression for surface roughness prediction

(2020) Dongdong Kong et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Optimization of varying-parameter drilling for multi-hole parts using metaheuristic algorithm coupled with self-adaptive penalty method

(2020) Ce Han et al.   APPLIED SOFT COMPUTING

Surface roughness prediction with new barrel-shape mills considering runout: Modelling and validation

(2020) G. Urbikain Pelayo et al.   MEASUREMENT

Position dependent vibration evaluation in milling of thin-walled part based on single-point monitoring

(2020) Zequan Yao et al.   MEASUREMENT

Analysis and modeling of surface roughness based on cutting parameters and tool nose radius in turning of AISI D2 steel using CBN tool

(2019) Vallabh D. Patel et al.   MEASUREMENT

Efficiency of vibration signal feature extraction for surface finish monitoring in CNC machining

(2019) E. García Plaza et al.   Journal of Manufacturing Processes

Chatter mitigation for the milling of thin-walled workpiece

(2018) Zhao Zhang et al.   INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

Optimization and improvement of stable processing condition by attaching additional masses for milling of thin-walled workpiece

(2018) Min Wan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

(2018) E. García Plaza et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

(2018) Carlos Quiterio Gómez Muñoz et al.   RENEWABLE ENERGY

Online monitoring of surface roughness and grinding wheel wear when grinding Ti-6Al-4V titanium alloy using ANFIS-GPR hybrid algorithm and Taguchi analysis

(2018) DuyTrinh Nguyen et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

Feature extraction using dominant frequency bands and time-frequency image analysis for chatter detection in milling

(2018) Yun Chen et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

Surface roughness monitoring by singular spectrum analysis of vibration signals

(2017) E. García Plaza et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An effective LS-SVM-based approach for surface roughness prediction in machined surfaces

(2016) Nian Zhang et al.   NEUROCOMPUTING

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

(2015) Anupam Agrawal et al.   APPLIED SOFT COMPUTING

Investigation on the influence of tool-tip vibration on surface roughness and its representative measurement in ultra-precision diamond turning

(2013) H. Wang et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE

Chatter detection in milling machines by neural network classification and feature selection

(2013) Mourad Lamraoui et al.   JOURNAL OF VIBRATION AND CONTROL

On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations

(2013) Zahia Hessainia et al.   MEASUREMENT

Kernel based regression and genetic algorithms for estimating cutting conditions of surface roughness in end milling machining process

(2012) Antoni Wibowo et al.   EXPERT SYSTEMS WITH APPLICATIONS

Rotational Machine Health Monitoring and Fault Detection Using EMD-Based Acoustic Emission Feature Quantification

(2012) Ruoyu Li et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

In-process prediction of surface roughness in turning of Ti–6Al–4V alloy using cutting parameters and vibration signals

(2012) Vikas Upadhyay et al.   MEASUREMENT

Surface roughness prediction through internal kernel information and external accelerometers using artificial neural networks

(2011) Guillem Quintana et al.   Journal of Mechanical Science and Technology

Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method

(2010) İlhan Asiltürk et al.   EXPERT SYSTEMS WITH APPLICATIONS

Natural roller bearing fault detection by angular measurement of true instantaneous angular speed

(2010) L. Renaudin et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results

(2009) Kunpeng Zhu et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE

Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process

(2008) M. Correa et al.   EXPERT SYSTEMS WITH APPLICATIONS

Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi-genetic learning algorithm

(2008) Wen-Hsien Ho et al.   EXPERT SYSTEMS WITH APPLICATIONS

In-process surface roughness prediction system using cutting vibrations in turning

(2008) D. R. Salgado et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models

(2007) J. Paulo Davim et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY