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
  • 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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