对Nakai拟合法的改进及实际应用

本文对Nakai拟合法作了改进并应用于计算井水固体潮和气压系数。利用该方法还可以计算井水位对固体潮和气压响应的滞后时间。以鲁06井为例,用本文的方法计算出其井水位的固体潮和气压系数分别为16.9mm/10~(-3)和5.58mm/hPa,滞后时间分别为18.8和22.4分钟。校正后的中误差由8.5mm下降到6.1mm。     

潮汐数字记录应用软件

文中较详细地介绍了重力潮汐数字记录系统应用软件,主要包括数字采集的控制部分、观测资料的日常处理、重力仪记录格值的标定等一系列与台站观测有关的处理功能。它实现了潮汐信息从采集到成果处理的自动化,首次将48小时的Nakai潮汐数据预处理方法引入PC-1500计算机。它能有效地剔除、修正数字采集器本身无法识别的错误数据或干扰信号,使观测人员能根据拟合参量的变化,及时了解仪器的工作状况及记录系统灵敏度的变化。实践表明:此软件配合数字采集系统使用后大大提高了重力固体潮观测的整体水平。对这一软件作部分的改进后,可用于固体潮其它分量的观测。     

河北形变观测资料映震能力浅析

采取Nakai拟合、振幅因子、调和分析和相对均方差等方法,对河北省数字化形变台站的形变观测进行计算和分析。结果表明,河北省形变观测资料中,怀来、易县和宽城的VS垂直摆倾斜仪、DSQ水管倾斜仪和SS-Y伸缩仪观测资料对河北范围内的中强以上地震有中、短期映震能力。     

承德地区形变资料前兆异常特征及映震能力分析

主要通过Nakai拟合、振幅因子以及非潮汐拟合常数3种方法对承德地区各个台站的各形变手段所得数据拟合处理,进行前兆异常分析,同时与该地区异常有效评价范围内的地震联系在一起,分析地震前兆异常与地震之间的关系.通过分台站、分手段、分拟合方法对各形变仪器映震能力进行R值评价,指出了形变异常观测在地震监测预报应用过程中存在的优...     

兰州十里店地震台连续重力观测资料分析

对兰州十里店地震台重力观测资料进行分析,发现重力资料受停电、仪器检修干扰较大,在剔除潮汐变化和人为干扰后,重力观测资料显示长期正向漂移趋势。利用Nakai拟合检验发现,2008—2013年的重力数据小于1×10-8/s2拟合残差的逐年增多,表明仪器观测噪声较小,观测资料状态稳定。对重力观测资料进行维尼狄可夫调和分析,确认兰州十里店地震台重力观测潮汐因子较稳定,精度高,映震效果较好。     

结合实地观测和STEREO/HI图像观测分析2010年CME事件

本文使用了基于单颗STEREO卫星日球层成像仪(Heliospheric Imager,HI)图像的固定Φ角拟合法(Fixed-Φ,FΦ)和调和均值拟合法(Harmonic-mean,HM),结合STEREO和ACE卫星的太阳风实地观测数据,深入分析了2010年15个日冕物质抛射(CME)事件,对比讨论了这两种方法在提取CME参数如太阳赤道平面的主传播方向、传播速度的效果,其中FΦ拟合法假设CME是固定方向传播的小质点,HM拟合法假设CME为具有球形前沿的通量绳结构,结果发现:(1)使用HM拟合法分析得到的CME主传播方向与太阳-实地观测点的夹角平均值是9.5°,小于FΦ拟合法的19.7°;(2)HM拟合法分析的预计到达时间与实测ICME起始时间的平均误差和最大误差分别为0.282天和0.805天,明显小于FΦ拟合法.本文也使用结合STEREO两颗卫星HI图像的直接三角法(Direct-triangulation,DT)和球面切线法(Tangent-to-a-sphere,TS),深入分析了5个朝向地球的CME事件,其中,DT和FΦ拟合法的假设相同,TS和HM拟合法的假设相同,结果发现:(1)这两种方法分析的CME主传播方向与日地连线的夹角最大值分别是13.2°和21.1°,明显小于单颗卫星观测的20.7°和27.5°;(2)其中4个CME事件使用方法得到的线性拟合加速度不超过0.4 m·s^-2,这说明CME在主传播方向上的速度变化在1AU内不超过100 km·s^-1;(3)使用TS方法得到的预计到达时间与实测ICME起始时间的绝对误差最小,平均值和最大值分别是2.3 h和5.8 h.可见,利用HI图像提取CME传播参数时,加入CME前沿结构假设和结合多角度观测都能够有效地减小拟合误差.     

对自相似扩展(SSE)模型的改进和研究

自相似扩展拟合法(Self-Similar Expansion,SSE)假设日冕物质抛射(CME)具有恒定角宽度、沿径向向外传播的、自相似扩展的球形前沿,由日心出发的、与这个球形前沿相切的圆锥的圆锥角就是通常所说的CME角宽度,半角宽度取值范围是[0°,90°],固定Φ角拟合法(Fixed-Φ,FΦ)和调和均值拟合法(Harmonic-mean,HM)分别对应SSE模型的半角宽度为0°和90°的特殊情况.本文中修改后的自相似扩展拟合法(MSSE)假设CME具有自相似扩展的半球形前沿,能够提取的CME参数包括由日心出发的、圆锥截面过球心的圆锥的半圆锥角和CME的主传播方向、传播速度,其中半圆锥角取值范围是[0°,90°],FΦ和HM分别对应MSSE模型的半圆锥角为0°和45°的特殊情况,半圆锥角为90°时,CME前沿是以日心为圆心的半圆.MSSE拟合法扩大了SSE模型对CME前沿形态的描述范围,将半圆锥角作为判断CME是否能够到达、何时到达某颗卫星的重要参数.基于单颗STEREO卫星日球层成像仪(Heliospheric Imager,HI)图像,结合STEREO和ACE卫星的太阳风实地观测数据,本文深入分析了2010年23个CME事件,结果发现:在用于预报CME事件是否能到达某颗卫星、何时到达时,MSSE拟合法相比FΦ、HM和SSE拟合法,不但可以更准确地拟合CME主传播方向和传播速度,也可以缩小预计到达时间和到达速度的误差.     

中国固体潮向量空间分布特征的研究

本文对中比合作和我们独立获得的共10个台站17个仪器架次2890天的固体潮观测资料采用卡特莱特(Cartwright)的完全展开和维尼迪可夫(Venedikov)方法统一地进行了调和分析,并用中井(Nakai)方法对观测资料进行了拟合预处理以提高分析结果的信噪比,同时用线性内插方法处理了仪器灵敏度以资对比.本文着重讨论了分析结果所提供的我国大陆固体潮矢量空间分布的区域性特征及其与海洋负荷的关系.结果表明:中国大陆固体潮空间分布受到海洋负荷的明显控制.O1波尤为显着.文中讨论了仪器流变模型对观测矢量的影响.根据流变模型改正后的结果,所得到的地球对引潮力的实际响应的相位滞后,大多数发站都接近于-1,它论证了理论原则的正确性.文中还讨论了残差矢量与海洋负荷矢量的关系,它们的一致性最概括地说明了海洋负荷对固体潮的影响.文中用误差矢量的方法研究了分析结果的精度,它说明目前海潮改正的精度仍然是不够的.在上述工作基础上,文中最后得到了经海潮改正后的 M2波和 O1波的观测矢量.      

江苏地磁观测受高压直流输电干扰现状及预处理

随着我国经济全面、迅速发展,高压直流输电线路的建设和运行越来越多,从而对江苏地磁观测环境造成严重影响或干扰。介绍了江苏地磁观测受高压直流输电干扰的现状,分析了高压直流输电干扰的判定、数据表现形态,还介绍了地磁观测数据的预处理及预处理后数据的检验结果。     

兰州地震台PET重力潮汐参数分析

用维尼迪科夫(Vinedikov)调和分析方法,计算2008年1月1日至2010年12月31日兰州地震台PET重力仪观测资料,获得几个主要潮波的潮汐参数.对日均值采用最小二乘拟合法,分析非潮汐重力变化信息.基于一元线性回归,分析气压对重力观测的影响,结果表明:气压对重力观测具有一定影响.     

工业CT图像亚体素表面检测算法研究

针对ICT图像序列,研究了基于Facet模型和基于矩的亚体素表面检测算法,并通过引入基于Otsu的阈值分割预处理环节,大大减少了待处理体素的数目,在很大程度上提高了原始算法的处理速度.最后在对航空发动机叶片仿真数据的实验中,对比了算法处理效果,结果表明两算法检测精度均可达1/5个像素以内,预处理环节的引入可将原始算法速度提高约4倍.     

Hybrid denoising-jittering data pre-processing approach to enhance multi-step-ahead rainfall–runoff modeling

Successful modeling of stochastic hydro-environmental processes widely relies on quantity and quality of accessible data and noisy data might effect on the functioning of the modeling. On the other hand in training phase of any Artificial Intelligence based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole population. Accordingly in the present article first, wavelet-based denoising method was used in order to smooth hydrological time series and then small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smoothed time series to form different denoised-jittered training data sets, for Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling of daily and multi-step-ahead rainfall–runoff process of the Milledgeville station of the Oconee River and the Pole Saheb station of the Jighatu River watersheds, respectively located in USA and Iran. The proposed hybrid data pre-processing approach in the present study is used for the first time in modeling of time series and especially in modeling of hydrological processes. Furthermore, the impacts of denoising (smoothing) and noise injection (jittering) have been simultaneously investigated neither in hydrology nor in any other engineering fields. To evaluate the modeling performance, the outcomes were compared with the results of multi linear regression and Auto Regressive Integrated Moving Average models. Comparing the achieved results via the trained ANN and ANFIS models using denoised-jittered data showed that the proposed data pre-processing approach which serves both denoising and jittering techniques could improve performance of the ANN and ANFIS based single-step-ahead rainfall–runoff modeling of the Milledgeville station up to 14 and 12% and of the Pole Saheb station up to 22 and 16% in the verification phase. Also the results of multi-step-ahead modeling using the proposed data pre-processing approach showed improvement of modeling for both watersheds.     

一种工业CT点云数据的NURBS曲面重构算法

虽然CT技术已经发展得相当成熟,但保证检测数据重构的精度还存在较大困难.本文将工业CT图像转化为三维散乱点云数据,研究数据预处理算法;对处理后数据进行NURBS曲面插值,完成了对NURBs曲面的董构.以某工件工业CT图像为例,通过VG软件转化为点云数据,利用VC++和OpenGL编程实现数据预处理算法和NURBS曲面拟...     

An improved constraint method in optimal estimation of CO_2 from GOSAT SWIR observations

We propose an algorithm that combines a pre-processing step applied to the a priori state vector prior to retrievals,with the modified damped Newton method(MDNM),to improve convergence.The initial constraint vector pre-processing step updates the initial state vector prior to the retrievals if the algorithm detects that the initial state vector is far from the true state vector in extreme cases where there are CO_2 emissions.The MDNM uses the Levenberg-Marquardt parameter y,which ensures a positive Hessian matrix,and a scale factor a,which adjusts the step size to optimize the stability of the convergence.While the algorithm iteratively searches for an optimized solution using observed spectral radiances,MDNM adjusts parameters y and a to achieve stable convergence.We present simulated retrieval samples to evaluate the performance of our algorithm and comparing it to existing methods.The standard deviation of our retrievals adding random noise was less than 3.8 ppmv.After pre-processing the initial estimate when it was far from the true value,the CO_2 retrieval errors in the boundary layers were within 1.2 ppmv.We tested the MDNM algorithm's performance using GOSAT L1b data with cloud screening.Our preliminary validations comparing the results to TCCON FTS measurements showed that the average bias was less than 1.8 ppm and the correlation coefficient was approximately 0.88,which was larger than for the GOSAT L2 product.     

Enhancing streamflow forecasting using the augmenting ensemble procedure coupled machine learning models: case study of Aswan High Dam

ABSTRACT

The potential of the most recent pre-processing tool, namely, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), is examined for providing AI models (artificial neural network, ANN; M5-model tree, M5-MT; and multivariate adaptive regression spline, MARS) with more informative input–output data and, thence, evaluate their forecasting accuracy. A 130-year inflow dataset for Aswan High Dam, Egypt, is considered for training, validating and testing the proposed models to forecast the reservoir inflow up to six months ahead. The results show that, after the pre-processing analysis, there is a significant enhancement in the forecasting accuracy. The MARS model combined with CEEMDAN gave superior performance compared to the other models – CEEMDAN-ANN and CEEMDAN-M5-MT – with an increase in accuracy of, respectively, about 13–25% and 6–20% in terms of the root mean square error.     

The Background Variation of Natural Source ELF and Its EM Abnormal Phenomena in Yunnan Earthquakes

In order to add earthquake monitoring methods and develop new method research, the ELF Network for Earthquake Monitoring selected 30 stations in the Capital Circle and the Sichuan-Yunnan region. Finding electromagnetic field background variation is the basis of distinguishing the seismic electromagnetic anomalies. This paper introduces the data acquisition and selection of the Shexian, Anqiu, Lijiang and Dali stations which have recorded for longer time with better data and are located on the similar latitude. Then we use the natural source electromagnetic field''s auto-power spectrum to express the intensity of the electromagnetic field. By using power spectral data of many frequencies in the observation frequency band, after the data pre-processing and sliding average noising, the background variation of extremely low frequency stations and the range ability were acquired. Taking the Baoshan M5.1 earthquake on October 30, 2015 and Dali M5.0 earthquake on May 18, 2016 as examples, the authors analyzed the earthquake electromagnetic anomaly characteristic of ELF stations around the earthquakes.     

井间弹性波CT中初至波自动提取转换及后处理优化应用

CT技术在地球物理主要应用中分为电磁波CT和弹性波CT，基于射线追踪理论的弹性波层析成像技术是重要的工程物探方法之一，在工程质量检测、工程勘察等领域得到了广泛的应用。该研究经过实践总结了一整套较为高效的后处理流程，开发了数据预处理软件，使得后处理工作量得到降低，给其他研究人员提供一种处理思路和方法。      

Quality control for ocean observations: From present to future

The quality control(QC) of ocean observational data, essential to establish a high-quality global ocean database, is one of the basic data pre-processing steps in oceanography research, marine monitoring, and forecasting. With the introduction of various advanced instruments in recent decades, oceanographic surveys have expanded from coastal regions to open oceans.However, as ocean in-situ observations are obtained using different instruments that offer heterogeneous data qualities, it is paramount that bad data could be accurately and efficiently identified via QC to provide a reliable global ocean database. In this review, we briefly summarize the latest progress of QC for oceanic in-situ observations, and mainly focus on temperature and salinity data. The similarities and differences between QC schemes developed by various ocean organizations are introduced. We also discuss the performances of the various QC schemes and identify the key challenges. Based on the discussions, several recommendations are proposed for future improvements in the QC for ocean observations.     

地震频发区域背景噪声提取格林函数的反褶积方法研究

针对云南这一地震频发区域记录到的地震背景噪声数据,设计了一种"最大值均一化"算法,该算法能有效地消除背景噪声中的地震信号、畸变信号及其它干扰信号。应用此算法对记录到的背景噪声数据进行预处理,对处理后的数据利用多窗谱反褶积计算方法可获得其具有较高信噪比和保留了相对幅值信息的格林函数。     

采用不同预处理方法的GPR图象去噪效果分析

探讨了多小波预处理方法对信号去噪性能的影响,选取不同的多小波函数和不同的预处理方法,利用改进的阈值函数,对实际的探地雷达（GPR）图像进行阈值化处理和对比分析,结果表明选取合适的预处理方法,采用DGHM多小波对GPR图象去噪可获得比其他方法更好的效果.