CNC machine tool monitoring by AE sensors: Difference between revisions

Revision as of 17:56, 13 June 2020

Revision as of 03:51, 24 July 2020

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{{Orphan|date=September 2015}}}}

'''CNC machine tool monitoring by AE sensors'''. Machine Tool monitoring system is flow of [[Information processing|information]] and system processing in which the information selection, obtaining data, processing of information and decision making on the refined information are integrated. The aim of tool condition monitoring is to detect early the disturbances in the machining process and wear of machine tool components.<ref>{{Cite book|url=https://books.google.com.eg/books?id=uAi8NH6XH2MC&printsec=frontcover&dq=CNC+machine&hl=en&sa=X&ved=0ahUKEwiut83Crv_pAhVqCWMBHc23A5oQ6AEIMDAB|title=Preparing and Proving CNC Machine Tool Programs|publisher=Benchmark Media Limited|language=en}}</ref>

The condition of tool has been researched extensively in the past and have focused on detection of [[tool wear]], tool breakage and the estimation of remaining tool life.It is very important for on-line identification of tool condition in machining process for enhanced productivity, better quality of parts and lower costs for unmanned, automated manufacturing systems.<ref>{{cite web|url=http://www.eng.nus.edu.sg/EResnews/0310/rd/rd_7.html|website=www.eng.nus.edu.sg}}</ref>

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The Machine tool monitoring systems commonly use sensors for measuring cutting force components or quantities related to cutting force (power, [[torque]], distance/[[Displacement (geometry)|displacement]] and strain). AE sensors are relatively easy to install in existing or new machines, and do not influence machine integrity and stiffness. All systems suppliers also use acoustic [[emission sensors]], especially for monitoring small tools and for grinding.

All sensors used in Machine tool monitoring systems are well adjusted to harsh machine tool environments. The difficulties in designing reliable Machine tool monitoring can be related to the complexity of the machining process itself, which may have one or more of the following characteristics, apart from the changes of the machine tool itself.<ref>{{cite journal|last1=Dimla|first1=Dimla E|title=Sensor signals for tool-wear monitoring in metal cutting operations–a review of methods|journal=International Journal of Machine Tools and Manufacture|date=2000|volume=8|issue=40|page=1073}}</ref>

==References==