Chasing the Cut: A Measurement Approach for Machine Tool Condition Monitoring

被引:14
|
作者
Huchel, Lukasz [1 ]
Krause, Thomas C. [1 ]
Lugowski, Tomasz
Leeb, Steven B. [1 ]
Helsen, Jan [2 ]
机构
[1] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA
[2] Vrije Univ Brussel, OWI Lab, B-1050 Brussels, Belgium
关键词
Cyclostationarity; diagnostics; integrated electronic piezoelectric (IEPE); Internet of things (IoT); spectral coherence; tool condition monitoring (TCM); WiFi;
D O I
10.1109/TIM.2020.3047939
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Often, the condition of a machine tool is detected indirectly in the reduced quality of manufactured parts upon visual inspection. Reliable and efficient machine tool condition monitoring is indispensable for manufacturing. Furthermore, issues affecting machine tools are closely related to pathologies associated with many other industrial electromechanical systems. An instrumentation and measurement solution for tool condition monitoring is presented in this article. A signal processing algorithm and instrumentation hardware are proposed to avoid intrusive sensor installations or modifications of the machine under test. The cyclostationary properties of machine vibration signals drive fault-detection approaches in the proposed sensing hardware and signal processing chain. A sample of end mills from an industrial facility is used to validate the tool condition monitoring system.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] A model approach for in-process tool condition monitoring in CNC turning using machine vision
    Sawangsri, Worapong
    Wattanasinbumrung, Pakanun
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2022, 16 (04): : 1439 - 1456
  • [22] Machine learning and IoT-based approach for tool condition monitoring: A review and future prospects
    Tran, Minh-Quang
    Doan, Hoang-Phuong
    Vu, Viet Q.
    Vu, Lien T.
    MEASUREMENT, 2023, 207
  • [23] Application of machine vision for tool condition monitoring and tool performance optimization–a review
    Tiyamike Banda
    Ali Akhavan Farid
    Chuan Li
    Veronica Lestari Jauw
    Chin Seong Lim
    The International Journal of Advanced Manufacturing Technology, 2022, 121 : 7057 - 7086
  • [24] Order bispectrum: A new tool for reciprocated machine condition monitoring
    Kocur, D
    Stanko, R
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2000, 14 (06) : 871 - 890
  • [25] Condition Monitoring in a Machine Tool Spindle using Wireless Sensor
    Ho, Chao-Ching
    Kuo, Tzu-Hsin
    Tsai, Tsung-Ting
    ADVANCES IN ABRASIVE TECHNOLOGY XIII, 2010, 126-128 : 678 - 683
  • [26] Sensorless machine tool condition monitoring based on open NCs
    Plapper, V
    Weck, M
    2001 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, 2001, : 3104 - 3108
  • [27] Machine tool condition monitoring using sweeping filter techniques
    Amer, W.
    Grosvenor, R.
    Prickett, P.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2007, 221 (I1) : 103 - 117
  • [28] Metacognitive learning approach for online tool condition monitoring
    Pratama, Mahardhika
    Dimla, Eric
    Lai, Chow Yin
    Lughofer, Edwin
    JOURNAL OF INTELLIGENT MANUFACTURING, 2019, 30 (04) : 1717 - 1737
  • [29] Metacognitive learning approach for online tool condition monitoring
    Mahardhika Pratama
    Eric Dimla
    Chow Yin Lai
    Edwin Lughofer
    Journal of Intelligent Manufacturing, 2019, 30 : 1717 - 1737
  • [30] A machine learning approach for the condition monitoring of rotating machinery
    Dimitrios Kateris
    Dimitrios Moshou
    Xanthoula-Eirini Pantazi
    Ioannis Gravalos
    Nader Sawalhi
    Spiros Loutridis
    Journal of Mechanical Science and Technology, 2014, 28 : 61 - 71