| 基于遗传算法的凿岩钻进系统自寻最优控制 |
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| 引用本文： | 郑惠斌,范茹军,闵金才,罗春雷.基于遗传算法的凿岩钻进系统自寻最优控制[J].井冈山大学学报（自然科学版）,2015(5):89-93. |
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| 作者姓名： | 郑惠斌 范茹军 闵金才 罗春雷 |
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| 作者单位： | 中南大学机电工程学院, 湖南, 长沙 410083,中南大学机电工程学院, 湖南, 长沙 410083,中南大学机电工程学院, 湖南, 长沙 410083,中南大学机电工程学院, 湖南, 长沙 410083 |
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| 基金项目： | 河南省企业项目(143010100) |
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| 摘 要： | 现有凿岩台车大多不具备自寻最优凿岩参数功能,凿岩钻进速度难以达到理论设计的最大值。为获取最大凿岩钻速,分析了多种影响因素,从中筛选出主要的可控变量。根据其难以构建准确的数学模型、非线性、时变性的特点,引入遗传算法作为自寻优核心思想,并设计了相应的控制系统。经验证,这种控制方法可以使钻进速度较快收敛至最大值。与传统的控制方法相比,该控制方法可根据岩石硬度自动匹配最优凿岩参数,有效地提高凿岩速度,大大减少凿岩施工所需时间。对于同类的凿岩设备自寻优控制同样具有参考价值。
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| 关 键 词： | 遗传算法 凿岩台车 钻进系统 自寻优 控制系统 |
| 收稿时间： | 2015/6/24 0:00:00 |
| 修稿时间： | 2015/7/13 0:00:00 |
THE SELF-OPTIMIZING CONTROL OF DRILLING SYSTEM BASED ON GENETIC ALGORITHM |
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| ZHENG Hui-bin,FAN Ru-jun,MIN Jin-cai and LUO Chun-lei.THE SELF-OPTIMIZING CONTROL OF DRILLING SYSTEM BASED ON GENETIC ALGORITHM[J].Journal of Jinggangshan University(Natural Sciences Edition),2015(5):89-93. |
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| Authors: | ZHENG Hui-bin FAN Ru-jun MIN Jin-cai and LUO Chun-lei |
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| Institution: | School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan 410083, China,School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan 410083, China,School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan 410083, China and School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan 410083, China |
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| Abstract: | Most of drill rig at present can't automatically adjust drilling parameters to make the drilling speed reach to theoretical maximum. In order to obtain the fastest drilling speed, we analyzed the factors affecting drilling speed and screened the controllable variables among them. As rock drilling speed is difficult to build accurate mathematical model, nonlinear and time variation, we introduced genetic algorithm as self-optimizing central idea and designed the corresponding control system. This control method has been applied to experiment and proved that it can effectively improve the drilling speed, greatly reduce the time required for drilling construction compared with the traditional control method. This method also has reference value for similar drilling equipment. |
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| Keywords: | genetic algorithm drill rig drilling system self-optimizing control system |
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