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    <identifier>10.57760/sciencedb.07238</identifier>
    <datestamp>2023-02-07T14:41:29Z</datestamp>
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  <dc:date>2023-02-07</dc:date>
  <dc:title>Statistical perception of chaotic fabrication error and self-adaptive processing decision in ultra-precision optical polishing</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.07238</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>An ultra-precision surface with equivalent accuracy can be stably realised via proper tool influence function (TIF) selection and modification, even for low-deterministic level tools. Experimental results indicated that the average prediction error in each convergence cycle was reduced to 6.14%. Without manual participation, the root mean square(RMS) of the surface figure of a ϕ100-mm flat mirror was converged to 1.788 nm with only robotic small-tool polishing, and that of a ϕ300-mm high-gradient ellipsoid mirror was converged to 0.008 &amp;lambda;. Additionally, the polishing efficiency was increased by 30% compared with that of manual polishing. The proposed SCP model offers insights that will help achieve advancement in the subaperture polishing process.</dc:description>
  <dc:subject>chaotic error; self-adaptive processing decision ;  ultra-precision optical polishing</dc:subject>
  <dc:creator>Hanjie Li</dc:creator>
  <dc:creator>Songlin Wan</dc:creator>
  <dc:creator>Zhenqi Niu</dc:creator>
  <dc:creator>Lanya Zhang</dc:creator>
  <dc:creator>Hao Guo</dc:creator>
  <dc:creator>Qing Lu</dc:creator>
  <dc:creator>Chaoyang Wei</dc:creator>
  <dc:creator>Jianda Shao</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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