用于风机疲劳寿命实时追踪的高阶峰谷识别方法

桂家彬; 李良星; 郭译文

doi:10.7652/xjtuxb202507010

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用于风机疲劳寿命实时追踪的高阶峰谷识别方法

—————————————————————— | 更新时间：2025-07-09

- 用于风机疲劳寿命实时追踪的高阶峰谷识别方法
- High-Order Peak-Valley Identification Method for Real-Time Tracking of Wind Turbine Fatigue Life
- 西安交通大学学报 2025年59卷第7期页码：99-107
- 作者机构：
  
  西安交通大学动力工程多相流国家重点实验室， 710049，西安
- 作者简介：
  
  桂家彬（2003—），男，硕士生；
  李良星，男，副教授，博士生导师。
- 基金信息：
- DOI：10.7652/xjtuxb202507010
  中图分类号： TK83
- 收稿：2024-12-19，
  
  网络首发：2025-02-27，
  
  纸质出版：2025-07-10
- 稿件说明：
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桂家彬, 李良星, 郭译文. 用于风机疲劳寿命实时追踪的高阶峰谷识别方法[J]. 西安交通大学学报, 2025,59(7):99-107.

GUI Jiabin, LI Liangxing, GUO Yiwen. High-Order Peak-Valley Identification Method for Real-Time Tracking of Wind Turbine Fatigue Life[J]. Journal of Xi’an Jiaotong University, 2025, 59(7): 99-107.
桂家彬, 李良星, 郭译文. 用于风机疲劳寿命实时追踪的高阶峰谷识别方法[J]. 西安交通大学学报, 2025,59(7):99-107. DOI： 10.7652/xjtuxb202507010.

GUI Jiabin, LI Liangxing, GUO Yiwen. High-Order Peak-Valley Identification Method for Real-Time Tracking of Wind Turbine Fatigue Life[J]. Journal of Xi’an Jiaotong University, 2025, 59(7): 99-107. DOI： 10.7652/xjtuxb202507010.

摘要

为了满足风电场中实时追踪风力发电机疲劳寿命以减少运维成本的需求，针对传统应力循环识别算法的实时性不足的缺点，提出一种新的高阶峰谷识别方法，通过对风机载荷的峰谷序列数据进行识别，引入半循环和高阶区间循环的概念，实现快速准确的疲劳寿命评估。研究结果表明：高阶峰谷识别方法的计算精度优于变程均值法，与雨流计数法相近；计算响应速度远远高于雨流计数法，与未采用该方法的计算性能相比，各风机的计算加速比超过5倍。利用高阶峰谷识别法对风机塔架推力与主轴力矩数据进行分析，计算了风机的等效疲劳载荷和累计疲劳损伤，结果表明，随着时间增加，损伤在初期增长较快，然后增速逐渐减缓，各风机累计疲劳损伤增长速度差异较大。高阶峰谷识别法可有效减少疲劳寿命评估的计算时间，对提高风电机场的安全性和经济性具有一定的意义。

Abstract

In order to meet the demand for real-time fatigue life tracking in wind farms and to reduce operation and maintenance costs

a novel high-order peak-valley identification method is proposed to address the insufficiency of real-time performance in traditional stress cycle identification algorithms. This method identifies peak-valley sequence data of wind turbine loads

introducing the concepts of half-cycles and high-order interval cycles to achieve fast and accurate fatigue life assessment. The research results indicate that the high-order peak-valley identification method achieves better computational accuracy than the variable range mean method and is comparable to the rain flow counting method. Furthermore

its computational response speed far exceeds that of the rain flow counting method

with a computational acceleration ratio of over 5 times compared to performance without this method for each wind turbine. The high-order peak-valley identification method is applied to analyze the tower thrust and main shaft torque data of wind turbines and to calculate the equivalent fatigue load and accumulative fatigue damage. As time increases

damage grows rapidly in the early stages and then gradually slows down

with significant differences in the growth rates of cumulative fatigue damage among different wind turbines. The high-order peak-valley identification method can effectively reduce the computation time for fatigue life assessment

which is significant for improving the safety and economic efficiency of wind farms.

关键词

Keywords

references

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