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Microseismic source location using the Log-Cosh function and distant sensor-removed P-wave arrival data 被引量:6
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作者 PENG Kang GUO Hong-yang SHANG Xue-yi 《Journal of Central South University》 SCIE EI CAS CSCD 2022年第2期712-725,共14页
Source location is the core foundation of microseismic monitoring.To date,commonly used location methods have usually been based on the ray-tracing travel-time technique,which generally adopts an L1 or L2 norm to esta... Source location is the core foundation of microseismic monitoring.To date,commonly used location methods have usually been based on the ray-tracing travel-time technique,which generally adopts an L1 or L2 norm to establish the location objective function.However,the L1 norm usually achieves low location accuracy,whereas the L2 norm is easily affected by large P-wave arrival-time picking errors.In addition,traditional location methods may be affected by the initial iteration point used to find a local optimum location.Furthermore,the P-wave arrival-time data that have travelled long distances are usually poor in quality.To address these problems,this paper presents a microseismic source location method using the Log-Cosh function and distant sensor-removed P-wave arrival data.Its basic principles are as follows:First,the source location objective function is established using the Log-Cosh function.This function has the stability of the L1 norm and location accuracy of the L2 norm.Then,multiple initial points are generated randomly in the mining area,and the established Log-Cosh location objective function is used to obtain multiple corresponding location results.The average value of the 50 location points with the largest data field potential values is treated as the initial location result.Next,the P-wave travel times from the initial location result to triggered sensors are calculated,and then the P-wave arrival data with travel times exceeding 0.2 s are removed.Finally,the aforementioned location steps are repeated with the denoised P-wave arrival dataset to obtain a high-precision location result.Two synthetic events and eight blasting events from the Yongshaba mine,China,were used to test the proposed method.Regardless of whether the P-wave arrival data with long travel times were eliminated,the location error of the proposed method was smaller than that of the L1/L2 norm and trigger-time-based location method(TT1/TT2 method).Furthermore,after eliminating the Pwave arrival data with long travel distances,the location accuracy of these three location methods increased,indicating that the proposed location method has good application prospects. 展开更多
关键词 seismic source location log-cosh function data field theory location stability
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基于BP神经网络的HPPC低温SOC优化估计 被引量:2
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作者 唐豪 张振东 吴兵 《计算机系统应用》 2021年第6期293-299,共7页
鉴于在低温状态下锂电池实时容量可估计性难度高,低温环境下瞬时电流电压对瞬态电池容量变化影响效果大.对Dense全连接层为主体的深度前馈BP网络模型进行了研究,进行了不同添加层对模型预测值与实际值的影响分析,采用了[11-9-12]的3层... 鉴于在低温状态下锂电池实时容量可估计性难度高,低温环境下瞬时电流电压对瞬态电池容量变化影响效果大.对Dense全连接层为主体的深度前馈BP网络模型进行了研究,进行了不同添加层对模型预测值与实际值的影响分析,采用了[11-9-12]的3层隐藏层BP网络模型以达到较高的精度,采用了基于SGD扩展的使用动量和自适应学习率来加快收敛速度Nadam优化算法以及Log-cosh损失函数优化模型,并且采用正则化方法降低过拟合,提高网络泛化能力.基于HPPC工况下0度低温实验测试数据进行模型的训练以及测试,经实验测试实现了在不同电压电流条件下所预测的soc误差在0.04左右. 展开更多
关键词 BP神经网络 ADAM log-cosh DENSE 正则化
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融合深度残差网络和注意力机制的3D目标检测 被引量:1
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作者 赵瑞 陶兆胜 +2 位作者 宫保国 李庆萍 吴浩 《齐齐哈尔大学学报(自然科学版)》 2023年第1期31-41,共11页
针对Frustum-PointNets的实例分割网络结构单一且卷积深度较深、易出现特征丢失和过拟合,检测准确率较低的问题,提出了一种改进的Frustum-PointNets网络。该网络首先构建深度残差网络并融入实例分割网络,提高特征提取能力,解决深层网络... 针对Frustum-PointNets的实例分割网络结构单一且卷积深度较深、易出现特征丢失和过拟合,检测准确率较低的问题,提出了一种改进的Frustum-PointNets网络。该网络首先构建深度残差网络并融入实例分割网络,提高特征提取能力,解决深层网络的退化问题;引入双重注意力网络以增强特征,提高分割效果;运用Log-Cosh Dice Loss解决样本不均衡,加快网络训练;使用Mish激活函数保留特征信息;最后基于Kitti和SUN RGB-D两个数据集进行实验验证本文算法的有效性。实验结果表明,本文算法相对于Frustum-PointNets,在Kitti数据集中,3D框检测精度提高了0.2%~13.0%;鸟瞰图的3D框检测精度提高了0.2%~11.3%。在SUN RGB-D数据集中,本文算法的3D框检测精度提高了0.6%~16.2%,平均检测精度(m AP)提高了4.4%。实验验证,本文算法在室外和室内场景中获得较好的目标检测及分割效果。 展开更多
关键词 3D目标检测 实例分割网络 深度残差网络 双重注意力模块 log-cosh Dice Loss
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基于全变差正则化的电力系统惯量评估方法
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作者 杨灵睿 郭成 +2 位作者 郭圳 代瑞 戴景 《电力自动化设备》 2026年第3期178-185,共8页
针对惯量常数评估过程中存在的计算精度和运算时间问题,提出一种基于log-cosh函数全变差正则化的电力系统惯量评估方法。通过全变差正则化得到频率量测数据的泛化函数,结合L曲线得到正则化参数的曲率函数,并利用log-cosh函数更新正则化... 针对惯量常数评估过程中存在的计算精度和运算时间问题,提出一种基于log-cosh函数全变差正则化的电力系统惯量评估方法。通过全变差正则化得到频率量测数据的泛化函数,结合L曲线得到正则化参数的曲率函数,并利用log-cosh函数更新正则化参数;构建Hessian近似矩阵和梯度表达式,通过迭代得到最佳频率变化率(RoCoF);结合功率量测量的差值法,通过摇摆方程得到系统惯量评估值。所提方法通过引入全变差正则化算法获取系统RoCoF,提高了RoCoF的计算精度,加快了计算速度,可以有效提高电网惯量评估的准确度。将IEEE 3机9节点系统和10机39节点系统算例的数值模拟结果与带外生输入的自回归滑动平均模型的结果进行对比,验证了所提方法的有效性和优越性。 展开更多
关键词 高比例新能源电力系统 全变差正则化 惯量评估 log-cosh 频率变化率
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