大型风电机组主传动链同频干扰状态下复合故障信息流漂变及传递规律研究

It is of great importance to analyze the characteristic flow drift mechanism of frequency coupling fault in improving the accuracy of compound fault diagnosis of main drive chain for large wind turbine. Due to the blur of the relationship between the nature and source of the frequency-coupled fault signal of wind turbine main drive chain in the same frequency interference state, multidimensional features coupled by multiple single fault features cross, merge together in the process of vertical and horizontal transfer , are difficult to separate. Based on virtual-real synthesis of the mechanical modeling and practical verification, by introducing gene genetic theory, this project aims to study the connection between essence and source of the signal, and analyzes the drift and transfer mechanism of characteristic flow of frequency-coupled fault. The specific research contents are as follows:(1) Establish the dynamic model; Analyze the relationship between the nature and source of composite fault in transmission chain;(2) Research multi-level, multi-source signal test system to verify the signal source correlation mechanism；(3)Study the multi-feature evaluation criteria of frequency-coupled fault, searching for features that best characterize faults, and solving the law of fitness in inheritance of fault features; (4)study the drift mechanism of the frequency-coupled fault feature flow in the process of compounding and transmission. explain the basic point offsets and the crossover and fusion rules of the base features in the process of forming the complex characteristic. Reveal the composite principle of frequency-coupled faults. The project aims to solve the problem of separation of the characteristics of frequency-coupled faults in mechanical transmission chains and provides theoretical and technical support for group failure diagnosis of mechanical equipment.

同频带耦合故障的特征流漂变机理解析对提高大型风电传动链复合故障诊断的准确率具有重要意义。针对风电机组主传动链同频干扰状态下复合故障质源关系不明确，多维特征纵横向传递表现为多个单故障特征交叉、融合在一起而难以分离的特性，项目将动力学分析和实践验证虚实结合，引入基因遗传理论，研究故障与信号间的质源关联特性，解析频耦故障特征流漂变、传递机理。包括：（1）建立系统动力学模型，研究传动链复合故障信号的质源关系；（2）研究多级、多源故障信号测试系统，验证信号质源关联机制；（3）研究故障特征的多重特征评价准则，搜索最优故障表征特征，解析故障特征传承中的适应度变化规律；（4）研究频耦故障复合、传递历程中特征流漂变机理，明确基特征构成复合特征时基特征的基点偏移及基特征间的交叉、融合规律，揭示频耦故障的复合特性。项目旨在解决机械传动链频耦故障特征分离的难题，为机械设备群故障诊断提供理论和技术支撑。

风能作为一种清洁的永续能源，已经成为我国可持续发展战略的重要组成部分。伴随着风电机组增速传动链结构日趋复杂，多种激励源相互干扰，加之传动系统中柔性构件的存在，导致传动部件的故障都是多种故障因素耦合的结果，以单一故障诊断方法对风电齿轮箱传动结构做诊断会造成漏判甚至误判。因此项目以风电机组健康维护为目标，探索解决了风电机组主传动链同频干扰状态下复合故障特征解耦难的问题。首先，针对风力机主传动链中的二级齿轮传动部分，本研究建立了含不同类型故障的二级齿轮传动系统有限元模型，研究了在转轴裂纹影响下的传动系统动力学特性，研究了不同类型齿轮故障影响下的传动系统动态特性，研究了多源激励耦合的传动系统动态特性；其次，针对传动链中的行星传动部分，建立了含不同类型故障的行星轮系动力学模型，研究了行星传动系统柔性齿圈行波振动特性，研究了行星轮系柔性内齿圈在动态啮合力作用下的疲劳损伤规律，研究了时变路径行星齿轮箱太阳轮故障响应周期特性，分析了考虑信号传递路径下太阳轮裂纹故障响应；然后，针对频耦故障特征评价准则及其表征能力问题，提出了相对应的频耦故障特征评价准则并分析了其表征能力；接着，针对不同类型故障的损伤程度评估问题，提出了VMD-Lempel-Ziv方法，实现了轴裂纹损伤程度评估，提出了SVD-MMSE方法,实现了齿轮故障损伤程度评估；最后，针对传动系统中不同故障的诊断问题，提出了一种自适应VMD-FSK诊断方法，提出了一种双优化MCKD-VMD诊断方法，实现了转轴裂纹故障诊断，提出了三阶段混合式特征选择方法，实现了特征集中冗余或无关的特征的剔除以及关键特征的提取，提出了一种具有更加优越的解耦性能的基于MOMEDA和并行参数优化的RSSD的复合故障诊断方法。本项目的研究成果可以用于大型风电增速传动设备健康状态的评价和复合故障的诊断，有重要的科学价值和工程应用前景。