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机构地区:[1]中国水利水电科学研究院,北京100044 [2]北京中水科工程总公司,北京100044
出 处:《水利与建筑工程学报》2017年第5期32-38,共7页Journal of Water Resources and Architectural Engineering
基 金:中国水利水电科学研究院科研专项项目(EM0145C152016)
摘 要:海上风机所处环境恶劣,基础与塔架等支撑结构在使用阶段受到荷载和非荷载因素,会产生累积损伤和性能退化。为了实时掌握基础与塔架体系的运行状态及安全性,进行合理的检修与维护,提出了一种基于神经网络的实时安全评估方法。结果表明:结合风况、风机运行等信息,仅在风机基础及塔架关键部位设置少量监测设备即可满足安全实时评估的数据要求;考虑限值比较、单点误差分析、总体误差分析后,可对基础与塔架局部及整体安全性进行实时评价。经实例论证,预测结果与监测数据较为接近,具有较好的实用性,可为类似工程提供参考。The base-tower of offshore wind turbines could have cumulative damage and performance degradation affected due to the load and non-load factors in the harsh environment. In order to understand the operation status and security of the base-tower in real time and to arrange reasonable maintenance,a real-time security assessment method based on neural network was proposed. The results show that with the information of wind condition and wind turbine operation status,as long as a small amount of monitoring equipment which was set on the key parts could meet data requirements of real-time assessment of the safety,and considering the limit value comparison,single point error analysis,the overall error analysis,the method could evaluates the local/overall safety of base-tower in real time. The prediction results in case study also agreed well with the monitoring data,therefore,the method has good efficiency and can provide reference for similar projects.
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