Przetwarzanie sygnałów w diagnostyce stanu narzędzia i procesu skrawania

[1]  Amin Al-Habaibeh,et al.  A new approach for systematic design of condition monitoring systems for milling processes , 2000 .

[2]  Krzysztof Jemielniak,et al.  Catastrophic Tool Failure Detection Based on Acoustic Emission Signal Analysis , 1998 .

[3]  Krzysztof Jemielniak,et al.  Detection of Cutting Edge Breakage in Turning , 1992 .

[4]  Krzysztof Jemielniak,et al.  Some aspects of acoustic emission signal pre-processing , 2001 .

[5]  P. S. Heyns,et al.  WEAR MONITORING IN TURNING OPERATIONS USING VIBRATION AND STRAIN MEASUREMENTS , 2001 .

[6]  Krzysztof Jemielniak,et al.  Tool condition monitoring in micromilling based on hierarchical integration of signal measures , 2008 .

[7]  Geok Soon Hong,et al.  Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results , 2009 .

[8]  Romero-Troncoso René de Jesús,et al.  FPGA based on-line tool breakage detection system for CNC milling machines , 2004 .

[9]  Yusuf Altintas,et al.  Dynamic Compensation of Spindle-Integrated Force Sensors , 2004 .

[10]  Amiya R Mohanty,et al.  Bayesian-inference-based neural networks for tool wear estimation , 2006 .

[11]  Zhenhu Liang,et al.  Complexity measure of motor current signals for tool flute breakage detection in end milling , 2008 .

[12]  D. R. Salgado,et al.  In-process surface roughness prediction system using cutting vibrations in turning , 2009 .

[13]  T. I. El-Wardany,et al.  Tool condition monitoring in drilling using vibration signature analysis , 1996 .

[14]  Jemielniak.  Some aspects of AE application in tool condition monitoring , 2000, Ultrasonics.

[15]  Dragos Axinte,et al.  A time–frequency acoustic emission-based monitoring technique to identify workpiece surface malfunctions in milling with multiple teeth cutting simultaneously , 2009 .

[16]  Krzysztof Jemielniak,et al.  Chip form monitoring through advanced processing of cutting force sensor signals , 2006 .

[17]  Krzysztof Jemielniak,et al.  Application of Wavelet Transform of Acoustic Emission and Cutting Force Signals for Tool Condition Monitoring in Rough Turning of Inconel 625 , 2011 .

[18]  D. R. Salgado,et al.  Tool wear detection in turning operations using singular spectrum analysis , 2006 .

[19]  Dongfeng Shi,et al.  Tool wear predictive model based on least squares support vector machines , 2007 .

[20]  David Dornfeld,et al.  A study of tool wear using statistical analysis of metal-cutting acoustic emission , 1982 .

[21]  P. S. Heyns,et al.  An industrial tool wear monitoring system for interrupted turning , 2004 .

[22]  Yonghong Peng,et al.  Empirical Model Decomposition Based Time-Frequency Analysis for the Effective Detection of Tool Breakage , 2006 .

[23]  Christopher A. Suprock,et al.  Directionally Independent Failure Prediction of End-Milling Tools During Pocketing Maneuvers , 2007 .

[24]  W. Grzesik,et al.  An Investigation of the Cutting Process for Chip Breaking Monitoring in Turning of Steels , 1998 .

[25]  Sagar Kamarthi,et al.  FOURIER AND WAVELET TRANSFORM FOR FLANK WEAR ESTIMATION — A COMPARISON , 1997 .

[26]  Bernhard Sick,et al.  ON-LINE AND INDIRECT TOOL WEAR MONITORING IN TURNING WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW OF MORE THAN A DECADE OF RESEARCH , 2002 .

[27]  Sohyung Cho,et al.  achine ensemble approach for simultaneous detection of transient and radual abnormalities in end milling using multisensor fusion , 2009 .

[28]  Krzysztof Jemielniak,et al.  Diagnosis of tool wear based on cutting forces and acoustic emission measures as inputs to a neural network , 1998, J. Intell. Manuf..

[29]  Krzysztof Jemielniak,et al.  Advanced monitoring of machining operations , 2010 .