| 史玉升,梁书云.神经网络实时诊断与优化模型建模法——人工智能在钻井工程中的应用之二[J].地质与勘探,1999,(3):49-53 |
| 神经网络实时诊断与优化模型建模法——人工智能在钻井工程中的应用之二 |
| REAl TIME DIAGNOSIS AND MODELING FOR OPTIMIZATION MODEL USING NEURAL NETWORK——THE SECOND PART OF APPLICATION OF ARTIFICIAL INTILLIENCE TO DRILLING ENGINEERING |
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| DOI： |
| 中文关键词: 神经网络 实时诊断 钻压优化 自动送钻 |
| 英文关键词: neural network,real-time diagnosis,optimizing model for the weight on bit(WOB),automatic bit feed, |
| 基金项目:中国博士后科学基金? |
| 史玉升 梁书云 |
：史玉升(华中理工大学 武汉 430074)
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| 摘要点击次数: 2080 |
| 全文下载次数: 1453 |
| 中文摘要: |
| 提出了一些新的实时诊断和钻压优化模型建模方法———神经网络法，它们可以克服传统方法需要建立数学模型的缺陷，满足钻进过程控制对实时性的要求。给出了利用反向传播神经网络（ＢＰ网络） 进行实时诊断和建立钻压优化模型的方法。实际应用和计算机仿真研究表明：采用这些新方法可以实时地实现钻进过程的事故诊断，建立的模型不但能够满足自动送钻实时优化钻压的要求，而且也可以用于离线的钻压参数优选 |
| 英文摘要: |
| Sone new real-time diagnosis and modeling methods for optimizing the weight on bit(WOB)based on BP neural network were presented .These methods can overcome the shortcomings that the traditional methods need to build up mathematical model ,and meet the repuirements that the drilling control demands good real time.These methods that then real-time diagnosis is carried out and optimizing model for WOB is built up by use of BP neural network were given.The practical application and computer simulation research show that the application of BP neural network to real-time diagnosis and modeling for optimizing WOB is practicable and efficacious. |
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