为实现井下落鱼高精度实时探测、保障油气田安全高效作业,攻克现有超声探测系统有线依赖、低信噪比下回波初至提取精度不足、高温适应性差的瓶颈,研制了基于现场可编程门阵列(Field-Programmable Gate Array,FPGA)的井下超声前视探测系...为实现井下落鱼高精度实时探测、保障油气田安全高效作业,攻克现有超声探测系统有线依赖、低信噪比下回波初至提取精度不足、高温适应性差的瓶颈,研制了基于现场可编程门阵列(Field-Programmable Gate Array,FPGA)的井下超声前视探测系统,集成超声发射、回波调理与数据采集电路;针对井下低信噪比、资源受限与高温工况,研究了面向边缘部署的赤池信息准则(Akaike Information Criterion,AIC)算法硬件加速架构,采用固定时窗约束缩小搜索范围、坐标旋转数字计算方法(COordinate Rotation DIgital Computer,CORDIC)迭代单元替代高开销对数运算、构建全流水并行方差计算通路,完成了算法轻量化与硬件协同优化。研究结果表明:①系统可清晰成像落鱼鱼顶形状,常温低信噪比环境下落鱼尺寸还原误差为3%,较阈值法精度提升1.33倍;②120℃高温条件下单点测距功能稳定,测距误差小于2.5 mm;③优化后的AIC硬件架构仅消耗9850个查找表(Look-Up Table,LUT)与116个数字信号处理器(Digital Signal Processor,DSP)资源,处理3001点数据延迟为6.8 ms,资源占用与处理效率显著优于传统查表法与平方法近似;④FPGA逻辑资源占用合理,LUT消耗占总资源39%,DSP消耗占78%,可满足井下实时处理需求。结论认为,该系统能够实现无缆化部署与实时成像,在精度、实时性与高温稳定性上达到井下探测要求,FPGA加速AIC算法可有效提升低信噪比下回波初至提取精度,为深井落鱼探测提供可靠技术方案。展开更多
This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, ...This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications.展开更多
在采用高斯径向基函数的相关向量机(RVM)回归模型中,核参数与模型性能之间关系复杂,针对如何确定RVM核参数的问题,提出一种基于AIC准则选择RVM的核参数的方法。首先基于Akaike Information Criterion(AIC)思想,得出一种新的统计量Q,同时...在采用高斯径向基函数的相关向量机(RVM)回归模型中,核参数与模型性能之间关系复杂,针对如何确定RVM核参数的问题,提出一种基于AIC准则选择RVM的核参数的方法。首先基于Akaike Information Criterion(AIC)思想,得出一种新的统计量Q,同时将Q作为适应度函数;然后利用微分进化算法(Differential Evolution Algorithm,DE)对核参数进行寻优,以此选择确定核参数;最后利用该算法建立RVM回归模型对黄金价格进行短期预测。实验结果表明,该模型较传统方法建立的预测模型具有更高的拟合精度和更好的泛化能力,进一步证明基于AIC准则选择RVM的核参数的方法的可行性和有效性。展开更多
地震波初至拾取是地震预警、地震定位等地震资料处理工作的重要基础,其实时性和准确性直接影响地震资料处理工作的效率.实际应用中,地震波初至拾取受日益增多的噪声干扰较大,传统地震波初至拾取算法很难兼顾实时性、准确性.针对上述问题...地震波初至拾取是地震预警、地震定位等地震资料处理工作的重要基础,其实时性和准确性直接影响地震资料处理工作的效率.实际应用中,地震波初至拾取受日益增多的噪声干扰较大,传统地震波初至拾取算法很难兼顾实时性、准确性.针对上述问题,本文提出一种基于Delaunay三角(简称为D三角)剖分的天然地震波初至实时拾取算法.首先,本文对STA/LTA-AIC(Short-Term Average/Long-Term Average-Akaike Information Criterion)算法特征函数进行参数分析,引用包含平方项和差分项的特征函数,增强算法的实时性;其次,通过改进时窗位置并加入取消时窗的方式,增加算法抗短时强噪声干扰的能力;最后,考虑到地震波在两台站间的最快传播速度,由台间距和地震波最大走时设置走时残差阈值,并依据D三角关系,提出D三角触发判别准则剔除部分干扰噪声.川渝地区现场数据验证表明,本文改进的STA/LTA-AIC算法提高了单台拾取地震波初至的抗短时强噪声能力,基于D三角剖分的天然地震波初至拾取算法能排除各台站误拾取信号,实时、准确、可靠拾取出实际地震波初至时刻.展开更多
摘要为实现井下落鱼高精度实时探测、保障油气田安全高效作业,攻克现有超声探测系统有线依赖、低信噪比下回波初至提取精度不足、高温适应性差的瓶颈,研制了基于现场可编程门阵列(Field-Programmable Gate Array,FPGA)的井下超声前视探测系统,集成超声发射、回波调理与数据采集电路;针对井下低信噪比、资源受限与高温工况,研究了面向边缘部署的赤池信息准则(Akaike Information Criterion,AIC)算法硬件加速架构,采用固定时窗约束缩小搜索范围、坐标旋转数字计算方法(COordinate Rotation DIgital Computer,CORDIC)迭代单元替代高开销对数运算、构建全流水并行方差计算通路,完成了算法轻量化与硬件协同优化。研究结果表明:①系统可清晰成像落鱼鱼顶形状,常温低信噪比环境下落鱼尺寸还原误差为3%,较阈值法精度提升1.33倍;②120℃高温条件下单点测距功能稳定,测距误差小于2.5 mm;③优化后的AIC硬件架构仅消耗9850个查找表(Look-Up Table,LUT)与116个数字信号处理器(Digital Signal Processor,DSP)资源,处理3001点数据延迟为6.8 ms,资源占用与处理效率显著优于传统查表法与平方法近似;④FPGA逻辑资源占用合理,LUT消耗占总资源39%,DSP消耗占78%,可满足井下实时处理需求。结论认为,该系统能够实现无缆化部署与实时成像,在精度、实时性与高温稳定性上达到井下探测要求,FPGA加速AIC算法可有效提升低信噪比下回波初至提取精度,为深井落鱼探测提供可靠技术方案。
基金supported by the National Natural Science Foundation of China(61172159)
摘要This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications.
摘要在采用高斯径向基函数的相关向量机(RVM)回归模型中,核参数与模型性能之间关系复杂,针对如何确定RVM核参数的问题,提出一种基于AIC准则选择RVM的核参数的方法。首先基于Akaike Information Criterion(AIC)思想,得出一种新的统计量Q,同时将Q作为适应度函数;然后利用微分进化算法(Differential Evolution Algorithm,DE)对核参数进行寻优,以此选择确定核参数;最后利用该算法建立RVM回归模型对黄金价格进行短期预测。实验结果表明,该模型较传统方法建立的预测模型具有更高的拟合精度和更好的泛化能力,进一步证明基于AIC准则选择RVM的核参数的方法的可行性和有效性。
摘要地震波初至拾取是地震预警、地震定位等地震资料处理工作的重要基础,其实时性和准确性直接影响地震资料处理工作的效率.实际应用中,地震波初至拾取受日益增多的噪声干扰较大,传统地震波初至拾取算法很难兼顾实时性、准确性.针对上述问题,本文提出一种基于Delaunay三角(简称为D三角)剖分的天然地震波初至实时拾取算法.首先,本文对STA/LTA-AIC(Short-Term Average/Long-Term Average-Akaike Information Criterion)算法特征函数进行参数分析,引用包含平方项和差分项的特征函数,增强算法的实时性;其次,通过改进时窗位置并加入取消时窗的方式,增加算法抗短时强噪声干扰的能力;最后,考虑到地震波在两台站间的最快传播速度,由台间距和地震波最大走时设置走时残差阈值,并依据D三角关系,提出D三角触发判别准则剔除部分干扰噪声.川渝地区现场数据验证表明,本文改进的STA/LTA-AIC算法提高了单台拾取地震波初至的抗短时强噪声能力,基于D三角剖分的天然地震波初至拾取算法能排除各台站误拾取信号,实时、准确、可靠拾取出实际地震波初至时刻.