CN 41-1243/TG ISSN 1006-852X
Volume 42 Issue 2
May  2022
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FU Tingbin, ZHU Zhenwei, ZHANG Rui, ZHAO Huadong. On-line discrimination of radial runout state during diamond roller trimming[J]. Diamond & Abrasives Engineering, 2022, 42(2): 233-239. doi: 10.13394/j.cnki.jgszz.2021.0119
Citation: FU Tingbin, ZHU Zhenwei, ZHANG Rui, ZHAO Huadong. On-line discrimination of radial runout state during diamond roller trimming[J]. Diamond & Abrasives Engineering, 2022, 42(2): 233-239. doi: 10.13394/j.cnki.jgszz.2021.0119

On-line discrimination of radial runout state during diamond roller trimming

doi: 10.13394/j.cnki.jgszz.2021.0119
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  • Received Date: 2021-06-21
  • Rev Recd Date: 2021-09-24
  • The performance of diamond roller when dressing grinding wheel was affected by its radial runout, but the intelligent degree of judging its radial runout state was low. Therefore, an on-line detection method based on wavelet decomposition and SVM was proposed for the grinding acoustic emission signal of radial runout under the trimming state of diamond roller. The grinding acoustic emission signal was transformed and decomposed by wavelet transform, and the three characteristic parameters of wavelet decomposition coefficients were extracted, which were effective value, variance value and energy spectrum coefficient. The results show that the accuracies of combining the three feature parameters into SVM for state recognition are more than 96.0%. When the three characteristic parameters are input at the same time, the accuracy is the highest, reaching 98.3%. The detection method has practical application value.

     

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  • [1]
    龚子维. 磨削砂轮钝化识别与声发射特征参数研究 [D]. 南京: 南京大学, 2020.

    GONG Ziwei. Identification of blunting state of grinding wheel and study on characteristic parameters of acoustic emission [D]. Nanjing: Nanjing University, 2020.
    [2]
    吕长飞, 吴小玉, 王茵, 等. 外圆磨削颤振监测方法设计 [J]. 机床与液压,2019,47(8):166-168, 66. doi: 10.3969/j.issn.1001-3881.2019.08.036

    LYU Changfei, WU Xiaoyu, WANG Yin, et al. Design of chatter detection in external cylindrical grinding [J]. Machine Tool & Hydraulics,2019,47(8):166-168, 66. doi: 10.3969/j.issn.1001-3881.2019.08.036
    [3]
    LIU G J, WANG Q, KANG R K. Study on the wavelet transform based monitor signal processing method for grinding wheel dull [J]. Key Engineering Materials,2008,375/376:598-602. doi: 10.4028/www.scientific.net/KEM.375-376.598
    [4]
    徐水竹, 杨京, 张仲宁, 等. 基于小波变换的磨削噪声在线监测方法 [J]. 声学技术,2011,30(3):275-279. doi: 10.3969/j.issn.1000-3630.2011.03.014

    XU Shuizhu, YANG Jing, ZHANG Zhongning, et al. On-line grinding state monitoring with wavelet transform of noise signal [J]. Acoustical Technology,2011,30(3):275-279. doi: 10.3969/j.issn.1000-3630.2011.03.014
    [5]
    巩亚东, 吕洋, 王宛山, 等. 基于多传感器融合的磨削砂轮钝化的智能监测 [J]. 东北大学学报,2003(3):248-251.

    GONG Yadong, LYU Yang, WANG Wanshan, et al. Intelligent monitoring for grinding wheel passivation based on multi-sensor fusion [J]. Journal of Northeastern University,2003(3):248-251.
    [6]
    陈俊奇. 基于磨削声音信号特征的砂带磨损状态监测方法研究 [D]. 上海: 上海交通大学, 2018.

    CHEN Junqi. Acoustic signal based grinding belt wear condition monitoring [D]. Shanghai: Shanghai Jiao Tong University, 2018.
    [7]
    王起硕. 基于多传感器融合的微晶刚玉砂轮磨削性能在线检测系统的研究 [D]. 济南: 山东大学, 2017.

    WANG Qishuo. Online detection system of grinding performance of microcrystalline corundum grinding wheel based on multi-sensor fusion [D]. Jinan: Shandong University, 2017.
    [8]
    丁宁, 段景淞, 石建, 等. 基于声发射砂轮磨损监测系统的研究 [J]. 南京航空航天大学学报,2020,52(1):48-52.

    DING Ning, DUAN Jingsong, SHI Jian, et al. Research on grinding wheel wear monitoring system based on acoustic emission [J]. Journal of Nanjing University of Aeronautics & Astronautics,2020,52(1):48-52.
    [9]
    朱欢欢, 迟玉伦, 闻章, 等. 断续磨削表面烧伤机理与在线监测方法研究 [J]. 表面技术,2021(9):379-389.

    ZHU Huanhuan, CHI Yulun, WEN Zhang, et al. Research on burn mechanism of intermittent grinding surface and online monitoring method [J]. Surface Technology,2021(9):379-389.
    [10]
    CHEN X, OPOZ T T. Effect of different parameters on grinding efficiency and its monitoring by acoustic emission [J]. Production & Manufacturing Research,2016,4(1):190-208.
    [11]
    郭力, 郭君涛, 霍可可. 金刚石砂轮与氧化锆磨削接触的声发射监测 [J]. 制造技术与机床,2019(5):94-98.

    GUO Li, GUO Juntao, HUO Keke. Acoustic emission monitoring on grinding contact between diamond grinding wheel and zirconia [J]. Manufacturing Technology and Machine Tool,2019(5):94-98.
    [12]
    郑敏敏, 高小榕, 谢海鹤. 心电信号小波去噪的改进算法研究 [J]. 中国生物医学工程学报,2017,36(1):114-118. doi: 10.3969/j.issn.0258-8021.2017.01.015

    ZHENG Minmin, GAO Xiaorong, XIE Haihe. Research on an improved algorithm for wavelet denoising of ECG [J]. Chinese Journal of Biomedical Engineering,2017,36(1):114-118. doi: 10.3969/j.issn.0258-8021.2017.01.015
    [13]
    李鹏瑞. 基于贝叶斯分类器的煤层底板破坏程度预测 [D]. 济南: 山东科技大学, 2016

    LI Pengrui. Prediction of failure degree of coal seam floor based on bayesian classifier [D]. Jinan: Shandong University of Science and Technology, 2016.
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