METHODS FOR ON-LINE DIRECTIONALLY INDEPENDENT FAILURE PREDICTION OF END MILLING CUTTING TOOLS

Autor:	Christopher A. Suprock, John T. Roth
Rok vydání:	2007
Předmět:	Engineering Signal processing Mathematical model Cutting tool business.industry Mechanical Engineering Autocorrelation Variance (accounting) Industrial and Manufacturing Engineering Autoregressive model Machining General Materials Science Tool wear business Algorithm Simulation
Zdroj:	Machining Science and Technology. 11:1-43
ISSN:	1532-2483 1091-0344
DOI:	10.1080/10910340601174806
Popis:	Tracking the health of cutting tools under typical wear conditions is advantageous to the speed and efficiency of many manufacturing processes. Although techniques exist to monitor tool performance, most are dependent on cutting direction, sensor orientation, cutting procedure, or the use of computationally intensive mathematical models. In this work, several solutions are proposed such that real-time analysis of signal variance and frequency magnitudes is possible through the identification of trends in the transient behavior of tri-axial force dynamometer signals. Moreover, the nature of both the transient variance (the temporal change in signal variance) and the frequency magnitude trends are shown to be independent of direction through the observation of both linear and pocketing mill sequences. Ten autonomous methods for failure prediction are discussed, tested, and presented. Analysis methods are demonstrated through the implementation of procedures derived from autocorrelation, FFT type, and Autore...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::57795b0a3b3eed51bd02729c09093b17 https://doi.org/10.1080/10910340601174806 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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