arXiv 1702.050472017-02stat.AP

Data-driven online monitoring of wind turbines

Thomas Kenbeek, Stella Kapodistria, Alessandro Di Bucchianico

英文摘要：

Condition based maintenance is a modern approach to maintenance which has been successfully used in several industrial sectors. In this paper we present a concrete statistical approach to condition based maintenance for wind turbine by applying ideas from statistical process control. A specific problem in wind turbine maintenance is that failures of a certain part may have causes that originate in other parts a long time ago. This calls for methods that can produce timely warnings by combining sensor data from different sources. Our method improves on existing methods used in wind turbine maintenance by using adaptive alarm thresholds for the monitored parameters that correct for values of other relevant parameters. We illustrate our method with a case study that shows that our method is able to predict upcoming failures much earlier than currently used methods.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

阅读原文

阅读 PDF ↗

arXiv 页面 ↗HTML 原文 ↗

本文内容

英文摘要相关论文

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

继续探索

相关论文

Probabilistic computation of wind farm power generation based on wind turbine dynamic modeling

This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including cut-off and cut-in behaviours. The wind turbine is modeled as a stochastic hybrid system with three operation modes. Numerical results, obtained using Monte-Carlo simulations, provide the annual distribution of a wind farm's active power generation. For different numbers of wind turbines, we compare the numerical results obtained using the dynamic model with…

2008-04-13stat.AP

Phase I analysis of hidden operating status for wind turbine

Data-driven methods based on Supervisory Control and Data Acquisition (SCADA) become a recent trend for wind turbine condition monitoring. However, SCADA data are known to be of low quality due to low sampling frequency and complex turbine working dynamics. In this work, we focus on the phase I analysis of SCADA data to better understand turbines' operating status. As one of the most important characterization, the power curve is used as a benchmark to represent normal performance. A powerful distribution-free control chart is applied after the power generation is adjusted by an accurate power…

2020-07-08stat.AP

A Case Study of Space-time Performance Comparison of Wind Turbines on a Wind Farm

This paper presents an academia-industry joint case study, which was conducted to quantify and compare multi-year changes in power production performance of multiple turbines scattered over a mid-size wind farm. This analysis is referred to as a space-time performance comparison. One key aspect in power performance analysis is to have the wind and environmental inputs controlled for. This research employs, in a sequential fashion, two principal modeling components to exercise tight control of multiple input conditions -- a covariate matching method, followed by a Gaussian process model-based f…

2021-02-19stat.AP

A surrogate model for estimating extreme tower loads on wind turbines based on random forest proximities

In the present paper we present a surrogate model, which can be used to estimate extreme tower loads on a wind turbine from a number of signals and a suitable simulation tool. Due to the requirements of the International Electrotechnical Commission (IEC) Standard 61400-1, assessing extreme tower loads on wind turbines constitutes a key component of the design phase. The proposed model imputes tower loads by matching observed signals with simulated quantities using proximities induced by random forests. In this way the algorithm's adaptability to high-dimensional and sparse settings is exploite…

2020-04-30stat.AP

Bayesian spline method for assessing extreme loads on wind turbines

This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine structure that the turbine would experience during its service lifetime. A wind turbine should be designed to resist such a high load to avoid catastrophic structural failures. To assess the extreme load, turbine structural responses are evaluated by conducting field measurement campaigns or performing aeroelastic simulation studies. In general, data obtained in either case are not sufficient to represent various loa…

2014-01-13stat.AP

Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity

Wind energy makes a significant contribution to global power generation. Predicting wind turbine capacity is becoming increasingly crucial for cleaner production. For this purpose, a new information priority accumulated grey model with time power is proposed to predict short-term wind turbine capacity. Firstly, the computational formulas for the time response sequence and the prediction values are deduced by grey modeling technique and the definite integral trapezoidal approximation formula. Secondly, an intelligent algorithm based on particle swarm optimization is applied to determine the opt…

2019-10-19stat.AP

更多相关论文收起更多论文

The latent state hazard model, with application to wind turbine reliability

We present a new model for reliability analysis that is able to distinguish the latent internal vulnerability state of the equipment from the vulnerability caused by temporary external sources. Consider a wind farm where each turbine is running under the external effects of temperature, wind speed and direction, etc. The turbine might fail because of the external effects of a spike in temperature. If it does not fail during the temperature spike, it could still fail due to internal degradation, and the spike could cause (or be an indication of) this degradation. The ability to identify the und…

2016-01-29stat.AP

基于Copula变分推断的序列不完整风电曲线定向监测方法

A Directional Monitoring Approach of Sequential Incomplete Wind Power Curves with Copula-based Variational Inference

针对风速波动导致不同时段功率曲线难以比较的问题，提出基于Copula变分推断的序列不完整风电曲线定向监测方法，经英国风电场数据验证，可提升建模精度与退化监测效果。

2023-11-04stat.AP

基于代理模型的浮式海上风力机长期疲劳损伤估算研究

On long-term fatigue damage estimation for a floating offshore wind turbine using a surrogate model

本研究针对浮式海上风力机长期疲劳损伤估算效率低的问题，提出基于高斯过程回归的代理模型框架，通过少量代表性海况结合补充海况实现高效收敛，经5-MW半潜式风机验证，可在保证精度的同时减少大量响应仿真。

2024-03-07stat.AP

用于从稀疏气象数据中估计未监测站点风力机高度风速的两步时空框架

A Two-Step Spatio-Temporal Framework for Turbine-Height Wind Estimation at Unmonitored Sites from Sparse Meteorological Data

University of Limerick（利默里克大学）；INRAE（法国国家农业、食品与环境研究院）

本文提出了一种两步时空框架，利用稀疏气象数据实时估计风电场风速，提升风能资源评估精度。

2026-02-23stat.AP

Measuring Wind Turbine Health Using Drifting Concepts

Warsaw University of Technology（华沙理工大学）；Hasselt University（哈瑟尔特大学）；Tilburg University（蒂尔堡大学）；Universidad de Talca（塔尔卡大学）

Time series processing is an essential aspect of wind turbine health monitoring. Despite the progress in this field, there is still room for new methods to improve modeling quality. In this paper, we propose two new approaches for the analysis of wind turbine health. Both approaches are based on abstract concepts, implemented using fuzzy sets, which summarize and aggregate the underlying raw data. By observing the change in concepts, we infer about the change in the turbine's health. Analyzes are carried out separately for different external conditions (wind speed and temperature). We extract …

2021-12-09cs.LGstat.AP

用于风电分布的双机制统计框架：从风速波动到涡轮机控制

A Two-Regime Statistical Framework for Wind-Power Distributions: From Wind-Speed Fluctuations to Turbine Control

OIST Graduate University（冲绳科学技术大学院大学）；MINES ParisTech（巴黎高等矿业学院）；London Mathematical Laboratory（伦敦数学实验室）；Exus Renewables North America（Exus可再生能源北美公司）

研究风电变异性挑战，开发双机制统计框架。在空气动力学运行状态下推导风电分布解析表达式，在控制主导的近额定状态下表征功率亏缺，为风力涡轮机全运行范围的风电波动提供物理解释统计描述。

2026-07-29physics.ao-phphysics.data-anphysics.flu-dyn

风力涡轮机 SCADA 数据相关矩阵的非平稳性及其对故障检测的启示

Non-stationarity in correlation matrices for wind turbine SCADA-data and implications for failure detection

该研究分析 Thanet 海上风电场高频 SCADA 数据，利用移动窗口 Pearson 相关矩阵与聚类识别由风速和控制系统决定的运行状态，为故障检测提供考虑非平稳性的自动化预处理框架。

2023-08-17physics.app-phphysics.data-anstat.AP

Reconstructing the intermittent dynamics of the torque in wind turbines

We apply a framework introduced in the late nineties to analyze load measurements in off-shore wind energy converters (WEC). The framework is borrowed from statistical physics and properly adapted to the analysis of multivariate data comprising wind velocity, power production and torque measurements, taken at one single WEC. In particular, we assume that wind statistics drives the fluctuations of the torque produced in the wind turbine and show how to extract an evolution equation of the Langevin type for the torque driven by the wind velocity. It is known that the intermittent nature of the a…

2014-04-08physics.data-anstat.APstat.CO

设备健康评估：用于风力涡轮机性能的时间序列分析

Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance

Hitachi America, Ltd., R&D（日立美国有限公司研发部）；Atria University（阿特里亚大学）；Atria Brindavan Power Private Limited（阿特里亚布林达万电力私人有限公司）

本文基于多台风机 SCADA 数据，融合 FNN 与 LSTM 进行功率预测和性能退化检测，证明集成模型及按风机自动定制建模的优越性与跨设备推广价值。

2024-03-01cs.AIcs.LGmath.FA

自动化拟合数据集的危险：风力涡轮机成本模型的案例

The perils of automated fitting of datasets: the case of a wind turbine cost model

Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences（自然资源与生命科学大学可持续发展经济研究所）

本文研究了自动化回归分析在风力涡轮机成本模型中的应用问题，提出了一个针对特定地点的投资成本模型，但认为通用成本模型存在缺陷，可能导致其他应用场景中出现不合理结果。

2021-12-28cs.SYecon.GNeess.SY