| 王梓齐,张书瑶,刘长良.基于增量式相对熵的风电机组实时状态监测[J].电子测量与仪器学报,2020,34(12):125-132 |
| 基于增量式相对熵的风电机组实时状态监测 |
| Real-time condition monitoring of wind turbine based on incremental relative entropy |
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| DOI： |
| 中文关键词: 增量式相对熵 风电机组 状态监测 残差分析 |
| 英文关键词:incremental relative entropy wind turbine condition monitoring residual analysis |
| 基金项目:北京市自然科学基金(4182061)、中央高校基本科研业务费(2020JG006, 2020MS117)资助项目 |
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| 中文摘要: |
| 针对风电机组的实时状态监测问题,提出了一种基于增量式相对熵的残差分析方法。 首先,通过分析滑动窗口数据特
点,推导了适用于实时运算的增量式相对熵的计算公式,其时间复杂度为 O(1),要低于常规计算方法的 O( n)。 接下来,提出
了一种基于数据驱动和正常行为建模的风电机组实时状态监测方法,并将增量式相对熵作为实时残差分析的指标。 最后,用某
2 MW 风电机组的实际齿轮箱故障数据为算例,验证了该方法的有效性。 结果表明,相对熵残差分析能够至少提前 8 ~ 10 d 实
现故障预警,优于常规的统计量;增量式相对熵的计算时间仅相当于常规方法的 0. 4% ~ 1. 9%,在实时性上有显著优势。 |
| 英文摘要: |
| Aiming at the problem of real-time condition monitoring of wind turbine, a real-time monitoring method based on incremental
relative entropy was proposed. Firstly, based on the analysis of the characteristics of sliding window data, the formula of incremental
relative entropy which is suitable for real-time calculation was derived. And the time complexity of incremental relative entropy is O(1),
which is lower than O(n) of conventional calculation method. Next, a real-time wind turbine condition monitoring method based on datadriven and normal behavior modeling was proposed and the incremental relative entropy was used as the index of real-time residual
analysis. The effectiveness of the proposed method was verified by the actual gearbox fault data of a 2 MW wind turbine. The results
show that relative entropy residual analysis can realize fault warning at least 8~ 10 days in advance, which is better than the conventional
statistics. The calculation time of incremental relative entropy was only 0. 4% ~ 1. 9% of the conventional calculation method, which has
significant advantages in real-time performance. |
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