基于GA-BP算法的旋转控制头轴承温度预测  

A Rotary Control Head Bearing Temperature Prediction Model Based on GA-BP Algorithm in Underbalanced Drilling

作　　者：莫丽[1] 王军[1] 王俊[2] 王禄友 

机构地区：[1]西南石油大学机电工程学院,四川成都610500 [2]成都理工大学地学核技术四川省重点实验室,四川成都610059

出　　处：《西南石油大学学报（自然科学版）》2016年第1期164-169,共6页Journal of Southwest Petroleum University(Science & Technology Edition)

基　　金：国家科技重大专项(2011ZX05037-002)

摘　　要：旋转控制头轴承组件要承受很大的动载荷,由于摩擦力的作用,使轴承发热和磨损非常严重,极易发生轴承温度过高而导致轴承失效。针对旋转控制头轴承温度影响因素多、精确计算困难、不易测量等特点,提出了一种基于遗传算法优化的神经网络(the optimized algorithm of BP neural network based on genetic algorithm,GA-BP)进行旋转控制头轴承温度预测的方法,利用某无外挂冷却润滑泵站式旋转控制头台架实验数据进行训练和测试,并与传统神经网络模型(BP)进行对比。结果表明,GA-BP预测模型实现了控制头轴承温度预测过程的自适应控制,预测得到的轴承温度与期望值之间的线性相关度达到0.991 48;通过95%置信区间以及平均、最大、最小绝对百分比误差的对比得到,GA-BP模型在逼近能力、收敛和泛化能力上都要优于BP预测模型。GA-BP预测模型预测精度高、稳定性好,对掌握轴承运行状态,优化旋转控制头冷却润滑方式和结构。提高旋转控制头的整体性能有重要指导意义.Rotary contol head （RCH） bearing assembly withstands great dynamic load, and severe heat and abrasion resulting from the friction force. Shorter equipment life may arise because of bearing failure caused by excessive bearing temperature. Aiming to overcome the difficulty in precise calculating and measuring, due to various influence factors on RCH bearing temperature, a method based on GA-BP （the optimized algorithm of BP neural network based on genetic algorithm, GA-BP） is proposed to predict RCH bearing temperature. The bench test data of an outboard cooling and lubrication pump station RCH was used for training and testing, and traditional neural network model （BP） was used for comparison. Results show that, the GA-BP prediction model can realize adaptive control for RCH bearing temperature prediction process. The linear correlation between prediction value and the expectative output comes up to 0.991 48. 95% confidence interval and mean, max, min absolute percentage error were contrasted between GA-BP and BP, and the result shows that the approximation capability, convergence and generalization ability of GA-BP are better than BP. With high prediction accuracy and good stability, GA-BP model can help monitor the bearing running state, and optimization of the cooling and lubrication stuctures. The GA-BP model has an important guiding significance in improving the overall performance of RCH.

关 键 词：旋转控制头 轴承温度 遗传算法 神经网络 置信区间 

分 类 号：TE921[石油与天然气工程—石油机械设备]