Cognitive Prediction-Enabled Online Intelligent Fault Diagnosis and Prognosis for Wind Energy Systems

本研究的目的是研究使用认知预测范式进行在线故障诊断和预测，以实现风能系统基于状态的智能维护。该方法是：(1)研究利用时频域数据挖掘方法，从风力机状态监测系统采集的信号中有效提取风力机故障特征；(2)研究利用人工神经网络和机器学习进行故障智能诊断和预测，预测风机寿命，并利用提取的故障特征定量评估风机的物理状态。智力优势：该项目将创建创新的基于认知预测的模型和计算算法，以增强地理分布风能系统的状态意识。这项研究的结果是高度可转换的，并将为其他能源转换和工程系统提供基于状态的智能维护能力。更广泛的影响：该项目的结果将通过成功地降低成本和提高风能系统的可靠性，进一步利用风能的好处，因此，将使风能成为可靠的、具有成本竞争力的清洁电力来源。越来越多地使用风力发电将有利于国家经济的各个部门，并有助于社会的可持续发展。该项目涵盖的多个领域是美国预计人才短缺的地区，特别是中西部地区。拟议的活动将为年轻人提供一个独特的学习平台，使他们成为熟练的专业人士。

The objective of this research is to study the use of cognitive prediction paradigms for online fault diagnosis and prognosis to enable condition-based smart maintenance for wind energy systems. The approach is to: (1) study the use of time and frequency domain data mining methods to effectively extract the features of faults in a wind turbine from the signals acquired from the wind turbine condition monitoring system; and (2) study the use of artificial neural networks and machine learning for intelligently diagnosing and prognosing faults, predicting the lifetime, and quantitatively evaluating the physical condition of the wind turbine using the extracted fault features.Intellectual Merit: This project will create innovative cognitive prediction-based models and computational algorithms to enhance condition awareness of geographically distributed wind energy systems. The findings of this research are highly transformable and will provide capabilities for enabling condition-based intelligent maintenance for other energy conversion and engineered systems.Broader Impacts: The outcome of this project will further exploit the benefits of wind power by successfully reducing cost and improving reliability of wind energy systems and, therefore, will make wind energy a reliable, cost-competitive source of clean electricity. The increasing use of wind power will benefit various sectors of the nation's economy and contribute to sustainable development of society. Multiple fields covered by this project are areas where a talent shortage is projected in the United States, particularly in the Midwest. The proposed activities will provide a unique learning platform for young individuals to become skilled professionals.