风力发电机叶片故障诊断及裂纹损伤数值分析
发布时间：2018-07-25 21:06
【摘要】：随着社会经济的发展能源消耗以及污染问题的日渐严重,风能作为一种清洁能源受到全球各国政府的青睐。风力发电机叶片承载着旋转的主要任务,其目的就是将风能转换成电能。由于风力发电机组常常在一些偏远、自然环境极其恶劣的条件下工作,并且叶片在高空中处于悬空的状态,一旦发生故障会给整个风电机组造成停机,严重影响到了风力发电机的发电效率。因此,开展风力发电机叶片故障的研究,对保证风力发电机的安全和长时间运行具有非常重要的意义。本文对风电叶片故障诊断的国内外研究现状以及在生活中常见的风电叶片结构和制动进行了介绍,对叶片故障发生的主要原因、故障类型、故障产生的机理以及常用的故障监测方法进行了对比研究。通过对叶片等效悬臂梁结构的动、静频公式进行了推导,对比数值分析和理论推导的求解结果,表明有限元的方法对叶片分析的有效性。利用Wilson叶片优化方法,结合CATIA和Profili选型软件,完成对叶片三维模型的建立。根据叶片损伤前后的模态应变能变化率,作为诊断叶片是否发生损伤的依据;将模态应变能变化率和神经网络二者结合,该方法具有较高的辨识率、可准确的辨识叶片损伤。针对叶片可能存在的裂纹损伤进行不同方向、不同位置和不同深度的分析,通过引入叶片健康状况的评价指标RMSD(均方值),建立RMSD与裂纹损伤区域面积S的关系,在一定程度上实现了叶片裂纹损伤的量化。驱动器在故障检测中起着重要作用,而压电驱动器类型和激励频率的选择尤为重要,文中重点对驱动器的几何尺寸以及泊松比对共振频率的影响分析。分析结果表明利用有限元能够有效的模拟出发生在叶片上的损伤区域,对风力发电机叶片故障发生关注区域的选择提供了帮助,降低了人工劳动成本,提高故障发生的检测率,具有一定的现实意义。对影响故障检测的压电驱动器共振频率内、外部因素分析,这不仅仅为驱动器结构和激励频率的选择提供了帮助,还为压电驱动器的优化设计提供了理论指导。
[Abstract]:With the development of social economy, energy consumption and pollution problem become more and more serious, wind energy as a clean energy is favored by governments all over the world. Wind turbine blades carry the main task of rotation, the purpose of which is to convert wind energy into electricity. Since wind turbines often work in remote, extremely harsh natural conditions, and the blades are in a suspended state at high altitude, once a failure occurs, the whole wind turbine will be shut down. The efficiency of wind power generation is seriously affected. Therefore, it is very important to study the blade faults of wind turbine to ensure the safety and long time operation of wind turbine. This paper introduces the status quo of wind turbine blade fault diagnosis at home and abroad, and introduces the structure and braking of wind turbine blade, the main cause and type of blade fault. The mechanism of fault generation and common fault monitoring methods are compared. Through the derivation of the dynamic and static frequency formula of the equivalent cantilever beam structure, the results of numerical analysis and theoretical derivation show that the finite element method is effective for blade analysis. Using Wilson blade optimization method and CATIA and Profili software, the three dimensional model of blade was established. According to the change rate of modal strain energy before and after blade damage, the method can be used as the basis for diagnosing blade damage, and combining modal strain energy change rate with neural network, the method has higher identification rate and can accurately identify blade damage. According to different directions, different positions and different depth of crack damage, the relationship between RMSD and crack damage area S was established by introducing the evaluation index RMSD (mean square value) of leaf health. To some extent, the quantification of blade crack damage is realized. The actuator plays an important role in fault detection, and the choice of the type and excitation frequency of the piezoelectric actuator is particularly important. This paper focuses on the analysis of the geometric size of the actuator and the influence of Poisson's ratio on the resonance frequency. The results show that the finite element method can be used to simulate the damage area on the blade effectively, which can help the wind turbine blade to select the focus area, reduce the labor cost, and improve the detection rate of the fault. Has certain realistic significance. The analysis of external factors in the resonant frequency of piezoelectric actuator, which affects the fault detection, not only provides help for the choice of actuator structure and excitation frequency, but also provides theoretical guidance for the optimal design of piezoelectric actuator.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM315
[Abstract]:With the development of social economy, energy consumption and pollution problem become more and more serious, wind energy as a clean energy is favored by governments all over the world. Wind turbine blades carry the main task of rotation, the purpose of which is to convert wind energy into electricity. Since wind turbines often work in remote, extremely harsh natural conditions, and the blades are in a suspended state at high altitude, once a failure occurs, the whole wind turbine will be shut down. The efficiency of wind power generation is seriously affected. Therefore, it is very important to study the blade faults of wind turbine to ensure the safety and long time operation of wind turbine. This paper introduces the status quo of wind turbine blade fault diagnosis at home and abroad, and introduces the structure and braking of wind turbine blade, the main cause and type of blade fault. The mechanism of fault generation and common fault monitoring methods are compared. Through the derivation of the dynamic and static frequency formula of the equivalent cantilever beam structure, the results of numerical analysis and theoretical derivation show that the finite element method is effective for blade analysis. Using Wilson blade optimization method and CATIA and Profili software, the three dimensional model of blade was established. According to the change rate of modal strain energy before and after blade damage, the method can be used as the basis for diagnosing blade damage, and combining modal strain energy change rate with neural network, the method has higher identification rate and can accurately identify blade damage. According to different directions, different positions and different depth of crack damage, the relationship between RMSD and crack damage area S was established by introducing the evaluation index RMSD (mean square value) of leaf health. To some extent, the quantification of blade crack damage is realized. The actuator plays an important role in fault detection, and the choice of the type and excitation frequency of the piezoelectric actuator is particularly important. This paper focuses on the analysis of the geometric size of the actuator and the influence of Poisson's ratio on the resonance frequency. The results show that the finite element method can be used to simulate the damage area on the blade effectively, which can help the wind turbine blade to select the focus area, reduce the labor cost, and improve the detection rate of the fault. Has certain realistic significance. The analysis of external factors in the resonant frequency of piezoelectric actuator, which affects the fault detection, not only provides help for the choice of actuator structure and excitation frequency, but also provides theoretical guidance for the optimal design of piezoelectric actuator.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM315
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相关期刊论文 前10条
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