一种基于时序分析的大型重载支承轴隐蔽部位疲劳裂纹诊断方法

大型重载支承轴隐蔽部位因发生不可观测的突发性疲劳断裂事故,严重影响生产的正常进行,给企业带来重大的经济损失.在分析支承轴振动特性的基础上,通过在机械结构外部便于检测部位提取反映结构疲劳裂纹状态的特征信号,编写相应的MAT-LAB程序构建时序模型,然后模拟支承轴实际工况,将裂纹产生、发展、断裂过程划分为5种状态,建立标准故障模式特征向量空间.运用模糊聚类分析方法,结合Euclide距离判别函数,找出与标准故障模式特征向量中隶属度最大的特征向量,从而有效诊断支承轴隐蔽部位疲劳裂纹状态的程度.最后通过实例验证了该方法的正确性和可行性.图2,参5.

A method based on time series of diagnosing fatigue crack in ulterior place of large-scale overloaded supporting shaft

Because of the unobserved sudden fatigue cracking of the large-scale overloaded supporting shafts, the normal product line is affected seriously and the economic loss of enterprise is very big. Based on analyzing the vibration characteristics of supporting shafts, the characteristic signal reflected the state of structure' fatigue crack was distilled in the part of exterior machine structure, the time series model was established by the relevant MATLAB procedure, and then, the actual working condition of supporting shafts was imitated to divide the crack process of producing, developing, spliting into 5 kinds of state, established the space characteristic vector of standard failure mode. To make use of the method of fuzzy clustering analysis, and combine discriminant function of Euclide distance, the characteristic vector of the biggest membership grade in the space characteristic vector of standard failure mode was found, consequently, the degree of fatigue crack in concealment part of supporting shafts was diagnosed effectively. This method of accuracy and feasibility is verified by the example finally. 2figs.,5refs.