【作者】 张金萍；

【导师】 刘国贤；

【作者基本信息】 华北电力大学（北京） ， 电力系统及其自动化， 2004， 硕士

【摘要】 随着市场经济的不断发展和电力系统规模的扩大，电力设备的状态检修体制亟待建立。对设备的健康状态做出快速、科学的评估是实现状态检修的前提条件，本文对国内外电力设备健康状态评估的发展趋势及现状进行了广泛深入的调研，完成了基于预防性试验数据的电力设备健康状态评估系统的设计与开发工作。文中运用模糊数学理论，结合专家系统，针对在线监测数据、预防性试验数据和历史运行状况数据，提出了一种电力设备健康状态评估的新算法；它可将电力设备预防性试验数据及历史数据有效组织起来，对设备健康状态进行评估。现场工程数据评估结果显示：该算法可对设备的潜伏性故障，作出准确预测。随着该系统的工程应用和不断完善，它必将为状态检修的实现作出新的贡献。更多还原

【Abstract】 With increasing demand of economic and security operation of power systems, the implementation of condition-based maintenance of electric power equipments is expected strongly. In order to reach the goal, the key problem to be solved is how to evaluate the current health conditions of the equipments. In this paper, main attention is put on develop a evaluating algorism based of the preventive test data.By combining the fuzzy mathematics and expert acknowledge, a new algorism for evaluating health condition of electric power equipments is proposed. And more, a software package to implement the evaluating algorism is made. Field data tests have shown that evaluating results can describe health condition of the equipments satisfactory.更多还原