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Cutting Tool Wear Monitoring in CNC Machines Based in Spindle-Motor Stray Flux Signals

Israel Zamudio-Ramírez, Jose A. Antonino‐Daviu, Miguel Trejo-Hernández, Roque A. Osornio‐Rios

2020IEEE Transactions on Industrial Informatics34 citationsDOI

Abstract

Tool condition monitoring (TCM) is one of the most relevant tasks during a machining process. The latest high-quality productivity standards make it essential to monitor the cutting tool wearing. Current TCM methodologies demand the installation of sensors near the working area, which in practical terms, it is not the most optimal solution since the final diagnosis can be disturbed by noisy signals and direct interferences with the machining process. This article proposes a novel noninvasive methodology based on the time–frequency analysis of the stray flux captured around the spindle-motor to detect and estimate the wearing level in cutting tools. Moreover, a new fault indicator based on this quantity is introduced through the application of the discrete wavelet transform. The results obtained are promising and demonstrates the effectiveness of the proposal to become a complementary source of information to classical approaches. This is validated with a Fanuc Oi mate computer numeric control turning machine for three different cutting tool wearing levels and different cutting depths.

Topics & Concepts

MachiningProcess (computing)Machine toolWaveletNumerical controlEngineeringFault (geology)Cutting toolTool wearCondition monitoringComputer scienceAutomotive engineeringControl engineeringMechanical engineeringArtificial intelligenceElectrical engineeringOperating systemSeismologyGeologyAdvanced machining processes and optimizationMachine Fault Diagnosis TechniquesAdvanced Machining and Optimization Techniques
Cutting Tool Wear Monitoring in CNC Machines Based in Spindle-Motor Stray Flux Signals | Litcius