CAJ | 학술논문

为了提高风电机组电动变桨系统运行状态评估的准确性，提出电动变桨系统状态重要参量挖掘及其异常识别方法的研究。论文在阐述风电机组电动变桨系统的结构及控制原理和监测参数特点的基础上，基于特征参数选择的 Relief方法，建立变桨系统特征参量挖掘的数学模型，获取了叶片桨距角、发电机转速及变桨电机驱动电流及其IGBT温度的特征参量，并对其故障状态的漏检率指标进行分析。提出基于多特征参量距离的变桨系统运行状态异常识别方法，建立基于风速输入的变桨系统特征参量的支持向量机回归模型，并对距离阈值进行探讨。最后，对实际变桨系统故障状态的异常识别进行实例验证。实验证明，建立的电动变桨系统状态特征参量挖掘模型的有效性，相比单参数绝对阈值评估方法，基于多特征参量距离的电动变桨系统异常识别方法更能及时、准确地识别其异常状态。
위료제고풍전궤조전동변장계통운행상태평고적준학성，제출전동변장계통상태중요삼량알굴급기이상식별방법적연구。논문재천술풍전궤조전동변장계통적결구급공제원리화감측삼수특점적기출상，기우특정삼수선택적 Relief방법，건립변장계통특정삼량알굴적수학모형，획취료협편장거각、발전궤전속급변장전궤구동전류급기IGBT온도적특정삼량，병대기고장상태적루검솔지표진행분석。제출기우다특정삼량거리적변장계통운행상태이상식별방법，건립기우풍속수입적변장계통특정삼량적지지향량궤회귀모형，병대거리역치진행탐토。최후，대실제변장계통고장상태적이상식별진행실례험증。실험증명，건립적전동변장계통상태특정삼량알굴모형적유효성，상비단삼수절대역치평고방법，기우다특정삼량거리적전동변장계통이상식별방법경능급시、준학지식별기이상상태。
In order to accurately assess the operating condition of an electric pitch system (EPS) of a wind turbine generator system, methods of characteristic parameter mining and outlier identification for an EPS were studied. After presenting its structure, control principle and monitoring parameters, mathematical model for characteristic parameters mining for an EPS was presented by using a characteristic parameters selection of the Relief method. Characteristic parameters including pith angle, generator rotational speed, current and IGBT temperature of the pitch drive motor system were acquired by using the presented model, and the results are demonstrated by using an index of undetected error rate for its fault condition. Then, an outlier identification method of operational condition of the EPS was proposed based on a distance method of the selected multi-characteristic parameters. Moreover, support vector machine (SVM) based regression model of characteristic parameters was presented by using wind speed variable as input, and the threshold of the distance was also investigated. Finally, the proposed outlier identification method was demonstrated by using the real operating condition of a practical EPS. The results show thatthe proposed model of characteristic parameter mining for EPS is effective, and compared with the condition assessment method using the single parameter and the absolute threshold, the proposed method based on multi-characteristic parameters distance can more quickly and accurately identify the abnormal condition of the EPS.