张新宇,陈建钧,潘勋平,杨成,袁伟杰,吴文超.车用高强钢酸洗数学模型的研究[J].表面技术,2017,46(11):276-281.
ZHANG Xin-yu,CHEN Jian-jun,PAN Xun-ping,YANG Cheng,YUAN Wei-jie,WU Wen-chao.Mathematical Model for Pickling of Automotive High Strength Steel[J].Surface Technology,2017,46(11):276-281 |
| 车用高强钢酸洗数学模型的研究 |
| Mathematical Model for Pickling of Automotive High Strength Steel |
| 投稿时间：2017-03-22 修订日期：2017-11-20 |
| DOI：10.16490/j.cnki.issn.1001-3660.2017.11.038 |
| 中文关键词: 高强钢 酸洗 导数近零 线性拟合 正交试验 模型 |
| 英文关键词:high strength steel pickling derivative near zero linear fitting orthogonal experiment model |
| 基金项目:国家自然科学基金（51375164，51675182） |
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| Author | Institution |
| ZHANG Xin-yu | School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China |
| CHEN Jian-jun | School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China |
| PAN Xun-ping | Baosteel Nscarcelor Automotive Steel Plate Co., Ltd, Shanghai 200237, China |
| YANG Cheng | School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China |
| YUAN Wei-jie | School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China |
| WU Wen-chao | School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China |
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| 中文摘要: |
| 目的 研究酸液浓度、温度和氧化皮厚度对车用高强钢酸洗时间的影响，建立关于酸液浓度、温度和氧化皮厚度的综合酸洗模型。方法 引入电位导数近零法判断酸洗结束时间，通过进一步酸洗实验研究酸液温度、浓度变化对不同厚度氧化皮酸洗时间的影响，对实验数据进行多元拟合，最后利用正交试验对三种影响因素进行相关性分析。结果 当酸洗液电位导数值达到0.0025 V/s时，氧化皮已去除干净；当酸液浓度提升到10%时，酸洗时间大大减少，而继续提高酸液浓度对缩短酸洗时间的帮助不大。酸液温度在达到80 ℃时，酸洗效率值达到最高，再提高温度，不仅浪费能源，而且会增加盐酸挥发，反而可能延长酸洗时间。建立了综合酸洗模型并将实际高强钢酸洗数据带入检验，发现酸洗时间误差在8%以内。氧化皮厚度对酸洗时间的影响超过酸液温度和浓度。结论 带钢酸洗有适宜的酸液浓度和温度，不能一味地通过增加酸液浓度和温度来提高酸洗效率。通过正交实验发现，建立包含氧化皮厚度影响因素在内的综合酸洗控制模型，对预测酸洗结束时间有较好的准确性和有效性，在工程上具有重要意义。 |
| 英文摘要: |
| The work aims to study effects of pickling solution concentration, temperature and oxide scale thickness on pickling time of high strength steel, and establish an integrated pickling model involving pickling solution concentration, temperature and oxide scale thickness. End time of pickling was determined by introducing the near zero method of electropotetial derivative. The effects of pickling solution temperature and concentration variation on pickling time of different thickness of oxide scales were studied by further performing experiments. Multicomponent fitting was applied to experimental data, and finally orthogonal experiment was performed to analyze correlation among the three factors. The oxide scale was completely removed when electropotential derivative of pickling solution reached 0.0025 V/s. Pickling time reduced dramatically when concentration of pickling solution increased to 10%, and further increasing the pickling solution concentration did little to help shorten the pickling time. The pickling efficiency reached the maximum when the pickling solution temperature reached 80 ℃. Further temperature increase would not only waste energy, but also increase volatilization of hydrochloric acid and prolong pickling time. An integrated pickling model was established, actual high strength steel pickling data was introduced into the test. Error of acid pickling time was less than 8%. The effect of oxide scale thickness on the pickling time was higher than that of pickling solution temperature and concentration. The pickling of strip steel shall be completed at appropriate pickling solution concentration and temperature. Pickling efficiency shall not be improved by increasing pickling solution concentration and temperature blindly. Orthogonal experiment shows that building an integrated pickling control model allowing for factors affecting oxide scale thickness exhibits excellent accuracy and validity in predicting end time of pickling, and is of great importance in engineering. |
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