华电技术 ›› 2018, Vol. 40 ›› Issue (10): 4-7.

• 研究与开发 • 上一篇    下一篇

基于随机抽样一致性算法的风电机组塔筒倾斜度检测方法

  

  1. 1.杭州职业技术学院 友嘉机电学院,杭州〓310018; 2.华电电力科学研究院有限公司,杭州〓310030;3.浙江省工程物探勘察院,杭州〓310005
  • 出版日期:2018-11-26 发布日期:2018-12-13

Measuring method for wind turbine tower slope based on random sample consensus algorithm

  1. 1.Fair Friend Institute of Electromechanics, Hangzhou Vocational and Technical College,Hangzhou 310018,China; 2.Huadian Electric Power Research Institute Company Limited, Hangzhou 310030,China; 3.Zhejiang Engineering Geophysical Prospecting Academy, Hangzhou 310005, China
  • Online:2018-11-26 Published:2018-12-13

摘要:

随着风电行业的快速发展,由于设计缺陷、制造问题以及检查和维护不充分导致风电事故频繁发生。机组倒塌是典型的事故之一,检测塔筒倾斜度是避免机组倒塌事故的重要措施。为解决利用最小二乘法无法剔除检测数据的局外点和噪声而导致检测精度低的问题,提出了一种基于随机抽样一致性的算法,可以剔除不良数据,并具有较强的抗噪声和异常点干扰能力。依托甘肃瓜州某风电场进行试验,结果表明,该算法能够较好地应用于塔筒倾斜度检测。

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Abstract:

With the rapid development of wind power industry, there are frequent accidents of wind turbines since design defects, manufacturing problems and inadequate maintenance. Collapse of units is one of the typical accidents, which can be avoided by measuring the inclination of the tower. In order to improve the low detection accuracy caused by the detection outliers and noise that cannot be eliminated by the least squares method, it proposes a random sample consensus algorithm which has a better immunity to noises and outliers. According to the testing results from a wind farm in Guazhou, Gansu, it is proved that the algorithm can be applied well in tower barrel inclination detection.

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