Development of real-time damage estimation system of lifeline facilities using neural networks

主要研究结果如下：1.对1991年9月27-28日的9119号台风和1993年1月的钏路冲地震这两次自然灾害进行了现场调查。研究了9119号台风期间停电对生命线系统和城市生活的影响。为了评估生命线系统的可靠性和可用性，通过模拟地震地面运动的时空变化，从理论上研究了生命线系统的物理破坏程度与功能服务率之间的关系，分析了生命线系统的可靠性和可用性。（3）编制了计算机程序ILAS（Integrated Lifeline Analysis System）.为了探测和定位关东及其周边地区发生的地震，开发了一个实时强震数据处理系统。它已被证明与真实的到达时间数据为4秒 关于我们 台站地震台阵表明，自动化系统计算的震源位置和发震时间是相当可靠的.利用地震监测数据和土壤分区数据，模糊推理，使我们能够进行燃气管网的损害估计。决策分析也采用模糊集理论。通过比较实际损伤数据和模糊推理结果，对建议的隶属函数进行了检验。并对整个系统进行了抽样计算.提出了一种基于神经网络的生命线系统震害预测方法。建议的网络估计使用地震烈度作为输入的结构损伤。通过监督学习训练的网络在回忆测试中很好地估计了观察到的损伤程度.提出了一种利用神经网络优化地震后电话业务恢复过程的有效方法。结果表明，神经系统可以有效地确定受损设备的修复顺序和修复路径，是一种非常有用的确定修复过程的工具。少

The main results of this may be summarized as follows :1. Site investigations were conducted for the recent two natural disasters, the typhoon 9119 on September 27-28, 1991 and the Kushiro-oki earthquake on January , 1993. Effects of power Outage to lifeline systems and urban life were investigated for the typhoon 9119. Soil effect to structural damage was confirmed for the Kushiro-oki earthquake.In order to evaluate the reliability and serviceability of the lifeline system, 1) the space-time variation of earthquake ground motion was simulated ; 2) the relationship between the degree of physical damage to the lifeline system and the functional service ratio was theoretically investigated; and 3) an outline of the computer program ILAS (Integrated Lifeline Analysis System) was developed.3. A real-time strong-motion data processing system was developed to detect and locate earthquake occurring in and around the Kanto area. It has been demonstrated with real arrival time data for a four-s … More tation seismic array that hypocenter location and origin time calculated by the automatic system are quite reliable.4. Using earthquake monitoring data and soil zoning data, fuzzy reasoning enables us to perform damage estimation of gas networks. Decision analysis also employs fuzzy set theory. Proposed membership functions were examined by comparing actual damage data and the results of fuzzy reasoning . A sample calculation was also conducted as a total system.5. A use of neural networks was proposed for earthquake damage estimation of lifeline systems. The proposed network estimates the structural damage using seismic intensities as inputs. The network trained by supervised learning well estimated the observed damage extent in a recall test.6. An effective procedure was presented for optimization of post-earthquake restoration process of telephone service using neural networks. Results show that the repair sequencing of damaged equipment and the restoration route can be effectively determined and that the neural system may be a very useful tool for determining restoration process. Less