关于(超)高压输变电系统地震安全性评价工作的认识

通过对(超)高压输变电系统在社会经济中的地位及其地震破坏情况的简要分析,确认了(超)高压输变电系统工程属于"重大建设工程"的范畴,必须开展相应的地震安全性评价工作。输变电系统具有远距离,长跨越的特点,其抗震设防标准应分段作评定。     

低温雨雪过程的粒子群-神经网络预报模型

利用逐日气温和降水量数据、NCEP/NCAR再分析资料以及预报场资料,通过分析提取我国南方区域持续性低温雨雪过程及其预报因子,使用粒子群-神经网络方法建立非线性的统计集合预报模型 (PSONN-EPM),对我国南方区域持续性低温雨雪过程进行预报试验。结果表明:以过程的冷湿程度及影响范围为标准,将低温雨雪过程分为一般过程和严重过程,并建立不同的预报模型效果较好。通过10 d独立样本预报试验看,基于粒子群-神经网络方法建立的集合预报模型比基于逐步回归方法建立的预报模型的预报平均相对误差小,对严重过程预报能力高于对一般过程预报,且这种非线性统计集合建模方法在建模过程中不需要调整神经网络参数,在实际预报业务中值得尝试。     

基于Datist的测震分析月报自动产出技术研发

针对四川测震台网运行月报中关于测震分析章节编写过程中的程序化工作流程,依托于数据专家(Datist)自动化流程实现了数据源读取、数据清洗、目录统计、绘制震中分布图、计算速报结果自评和报告自动产出等功能,辅助完成月报生成。实践证明该成果可有效减轻地震监测人员的工作负担,提高工作效率。     

Attenuation of coda waves and Q c value beneath the Chengdu telemetered seismic network

Based on the single scattering model of coda power spectrum analysis, digital waveform data of 50 events recorded by the real-time processing system of the Chengdu telemetry network are analyzed to estimate the Q _c values of earth medium beneath the Chengdu telemetry network for several specified frequencies. It is found that the Q _c shows the frequency dependency in the form of Q _c = Q ₀ f ⁿ in the range of 1.0 to 20.0Hz. Estimated Q ₀ ranges from 60.83 to 178.05, and n is found to be 0.713 to 1.159. The average value of Q ₀ and n are 117 and 0.978 respectively. This result indicates the strong frequency dependency of the attenuation of coda waves beneath the Chengdu telemetry network. Comparing with the results obtained in other regions of the world, it is found that Q ₀ ⁻¹ value and its change with frequency are similar to those in regions with strong tectonic activity. This subject is supported by the Ministry of Personnel, China for partly sponsoring.     

Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms

Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region.     

基于测站信息自动构建导线网

为解决导线网条件平差自动组网问题,提出了程序设计的方法和流程,程序依据导线网的野外观测信息自动构造出导线网的拓扑结构,在此基础上提取必要的平差参数和供平差用的观测数据,实现了从观测到平差结果输出全过程的自动化。     

区域重力场相对基准的建立

针对地震系统各区域重力网的现状,提出了一种在没有绝对重力测量资料的情况下,利用网区多年积累的观测资料,建立区域重力场相对基准的方法。实验证明,采用该方法建立的区域重力场相对基准,精度优于５０ｎｍ·ｓ－２,不仅有利于地震重力前兆信息的提取,而且能优化和评定区域重力网的质量,标定和检测重力仪参数及其变化。     

引汉济渭黄三段控制网布设及数据处理研究

针对引汉济渭工程控制网布设、观测和数据处理等具体问题,该文结合引汉济渭黄三段施工控制网的建立,研究了大型复杂工程施工控制网的布设方案、观测和数据处理方式以及验证控制网可靠性的做法,阐述了项目的作业流程、主要方法、关键技术和成果精度,对类似项目的生产具有指导意义和推广价值。     

大规模GNSS基准站网快速同步处理方法研究

目前我国GNSS连续运行基准站网已基本建设完毕,全国范围内建设完成约2000个GNSS连续运行基准站。随着站点规模的加大,数据计算的效率也迫切需要提高,采用传统的高精度数据处理软件已适应不了大规模GNSS网的数据解算要求。本文基于BERNESE5.2软件研究了我国“陆态网络工程”260个基准站的大规模GNSS网同步数据处理方法,通过修改源程序及利用并行计算技术,成功实现了陆态网络基准站快速、高效、高精度的数据计算能力。实例验证表明,陆态网络单天260个站的数据在无需分区的情况下,可在1 h内获得全球框架下的约束解,解算的框架点坐标精度在毫米量级,大大提高了国家数据中心的大规模GNSS网数据处理能力。     

专用方位控制网形变检测方案的设计

为检测专用方位控制网是否发生了明显变形 ,本文作者提出了方位边夹角灵敏度的概念 ,并推导了相应的公式。