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    RCSA-Based Method for Tool Frequency Response Function Identification Under Operational Conditions Without Using Noncontact Sensor

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 006::page 61009
    Author:
    Yan, Rong
    ,
    Tang, Xiaowei
    ,
    Peng, Fangyu
    ,
    Li, Yuting
    ,
    Li, Hua
    DOI: 10.1115/1.4035418
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The stability lobe diagrams predicted using the tool frequency response function (FRF) at the idle state usually have discrepancies compared with the actual stability cutting boundary. These discrepancies can be attributed to the effect of spindle rotating on the tool FRFs which are difficult to measure at the rotating state. This paper proposes a new tool FRF identification method without using noncontact sensor for the rotating state of the spindle. In this method, the FRFs with impact applied on smooth rotating tool and vibration response tested on spindle head are measured for two tools of different lengths clamped in spindle–holder assembly. Based on those FRFs, an inverse receptance coupling substructure analysis (RCSA) algorithm is developed to identify the FRFs of spindle–holder–partial tool assembly. A finite-element modeling (FEM) simulation is performed to verify the validity of inverse RCSA algorithm. The tool point FRFs at the spindle rotating state are obtained by coupling the FRFs of the spindle–holder–partial tool and the other partial tool. The effects of spindle rotational speed on tool point FRFs are investigated. The cutting experiment demonstrates that this method can accurately identify the tool point FRFs and predict cutting stability region under spindle rotating state.
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      RCSA-Based Method for Tool Frequency Response Function Identification Under Operational Conditions Without Using Noncontact Sensor

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4234763
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    contributor authorYan, Rong
    contributor authorTang, Xiaowei
    contributor authorPeng, Fangyu
    contributor authorLi, Yuting
    contributor authorLi, Hua
    date accessioned2017-11-25T07:17:44Z
    date available2017-11-25T07:17:44Z
    date copyright2017/30/1
    date issued2017
    identifier issn1087-1357
    identifier othermanu_139_06_061009.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4234763
    description abstractThe stability lobe diagrams predicted using the tool frequency response function (FRF) at the idle state usually have discrepancies compared with the actual stability cutting boundary. These discrepancies can be attributed to the effect of spindle rotating on the tool FRFs which are difficult to measure at the rotating state. This paper proposes a new tool FRF identification method without using noncontact sensor for the rotating state of the spindle. In this method, the FRFs with impact applied on smooth rotating tool and vibration response tested on spindle head are measured for two tools of different lengths clamped in spindle–holder assembly. Based on those FRFs, an inverse receptance coupling substructure analysis (RCSA) algorithm is developed to identify the FRFs of spindle–holder–partial tool assembly. A finite-element modeling (FEM) simulation is performed to verify the validity of inverse RCSA algorithm. The tool point FRFs at the spindle rotating state are obtained by coupling the FRFs of the spindle–holder–partial tool and the other partial tool. The effects of spindle rotational speed on tool point FRFs are investigated. The cutting experiment demonstrates that this method can accurately identify the tool point FRFs and predict cutting stability region under spindle rotating state.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleRCSA-Based Method for Tool Frequency Response Function Identification Under Operational Conditions Without Using Noncontact Sensor
    typeJournal Paper
    journal volume139
    journal issue6
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4035418
    journal fristpage61009
    journal lastpage061009-11
    treeJournal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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