• Acta Optica Sinica
  • Vol. 39, Issue 12, 1206003 (2019)
Lei Jiang1、2, Xuezhi Zhang1、2, Jin Wang1、2, Xiaojun Fan1、2, Yuqing Li1、2, Yue Chu1、2, Bangtian Xu1、2, and Tiegen Liu1、2、*
Author Affiliations
  • 1School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
  • 2Key Laboratory of Opto-Electronic Information Technology, Ministry of Education, Tianjin 300072, China
  • show less
    DOI: 10.3788/AOS201939.1206003 Cite this Article Set citation alerts
    Lei Jiang, Xuezhi Zhang, Jin Wang, Xiaojun Fan, Yuqing Li, Yue Chu, Bangtian Xu, Tiegen Liu. Real-Time Online Detection of Cutter Wear Based on Fiber Bragg Grating Array[J]. Acta Optica Sinica, 2019, 39(12): 1206003 Copy Citation Text show less
    References

    [1] Wang X C, Wang W S, Wu Q[J]. The present situation and prospect of future development of tool wear detection system in China Science and Technology Wind, 2017, 12.

    [2] Kishida M[J]. Optical fiber contact wire wear detection system Peng H M, Transl. Foreign Locomotive & Rolling Stock Technology, 2006, 43-45.

    [3] Cook N H, Subramanian K. Micro-isotope tool wear sensor[J]. Annals of the CIRP, 21, 67-72(1978).

    [4] Kassim A A, Mannan M A, Jing M. Machine tool condition monitoring using workpiece surface texture analysis[J]. Machine Vision and Applications, 11, 257-263(2000). http://link.springer.com/article/10.1007/s001380050109

    [5] Xiong S C. Research on cutting tool wear condition monitoring based on computer vision[D]. Hangzhou: Zhejiang University(2003).

    [6] Anandakrishnan V, Mahamani A. Investigations of flank wear, cutting force, and surface roughness in the machining of Al-6061-TiB2in situ metal matrix composites produced by flux-assisted synthesis[J]. The International Journal of Advanced Manufacturing Technology, 55, 65-73(2011).

    [7] Shi J, Ding N. On-line detection of the state of grinding wheel wear based on acoustic emission technique[J]. Journal of Changchun University, 23, 931-936, 950(2013).

    [8] Venkata Rao K. Murthy B S N, Mohan Rao N. Prediction of cutting tool wear, surface roughness and vibration of work piece in boring of AISI 316 steel with artificial neural network[J]. Measurement, 51, 63-70(2014).

    [9] Cheng G. Research on cutting temperature and tool wear of Cr12MoV die steel in high-speed milling[D]. Lanzhou: Lanzhou University of Technology(2016).

    [10] Li K, Huang M, Wu G X et al[J]. Design and implementation of tool wear condition monitoring system based on inverter input current Modular Machine Tool & Automatic Manufacturing Technique, 2017, 90-92, 96.

    [11] Yang F, Li Y. Research on tool wear prediction based on Fitnet neural network[J]. Machine Tool & Hydraulics, 46, 50-51, 49(2018).

    [12] Xiao Z Y, Zhang W M, Liu Z H. Detection technology of tool wear based on maximum entropy and cross entropy theory[J]. Machine Tool & Hydraulics, 46, 89-93(2018).

    [13] Shang W, Wang B Q. Research on the ultrasonic testing technology of shield tool wear based on wireless communication[J]. Construction Mechanization, 39, 56-59(2018).

    [14] Cao W Q, Fu P, Li X H. The diagnosis of tool wear based on EMD and GA-B-spline network[J]. Sensors & Transducers, 156, 195-202(2013).

    [15] Geramifard O, Xu J X, Zhou J H et al. Multimodal hidden Markov model-based approach for tool wear monitoring[J]. IEEE Transactions on Industrial Electronics, 61, 2900-2911(2014). http://ieeexplore.ieee.org/document/6566096/

    [16] Guo Y X, Xiong L, Kong J Y et al. Sliding type fiber Bragg grating displacement sensor[J]. Optics and Precision Engineering, 25, 50-58(2017).

    [17] Tan Z, Liao C R, Liu S et al. Simultaneous measurement sensors of temperature and strain based on hollow core fiber and fiber Bragg grating[J]. Acta Optica Sinica, 38, 1206007(2018).

    [18] Zhu Y S, Gui L, Zhu Y X. Temperature sensing for wavelength demodulation based on recognition by maximum intensity of radio frequency[J]. Acta Optica Sinica, 39, 0728003(2019).

    [19] Gu Z T, Ling Q. Theoretical analysis for long-period fiber grating strain sensor based on dual-peak resonance near PMTP[J]. Acta Optica Sinica, 36, 0106005(2016).

    [20] Wang G D, Yang Y L. Two kinds of tension in fiber Bragg gratings with cladding etched as the sinusoidal function[J]. Optoelectronics letters, 6, 48-50(2010). http://www.cqvip.com/QK/88368X/201001/32607219.html

    [21] Sun X M, Sun H Y, Yan X S. Application of FBG sensor to internal displacement monitoring of surrounding rock[J]. Chinese Journal of Rock Mechanics and Engineering, 27, 3847-3851(2008).

    [22] Liu B, Niu W C, Yang Y F et al. A novel fiber Bragg grating accelerometer[J]. Chinese Journal of Scientific Instrument, 27, 42-44(2006).

    [23] Kashyap R[M]. Fiber Bragg gratings, 130-142(2010).

    [24] Ou J P, Zhou Z, Wu Z J et al. Intelligent monitoring of Heilongjiang Hulan river bridge based on FBGs[J]. China Civil Engineering Journal, 37, 45-49, 64(2004).

    [25] Li C[M]. Fiber grating: principle, technology and sensing applications, 87-88(2005).

    Lei Jiang, Xuezhi Zhang, Jin Wang, Xiaojun Fan, Yuqing Li, Yue Chu, Bangtian Xu, Tiegen Liu. Real-Time Online Detection of Cutter Wear Based on Fiber Bragg Grating Array[J]. Acta Optica Sinica, 2019, 39(12): 1206003
    Download Citation