模糊诊断法在风机故障诊断中的研究与应用

发布时间：2018-01-16 11:54

本文关键词：模糊诊断法在风机故障诊断中的研究与应用　出处：《辽宁科技大学》2012年硕士论文　论文类型：学位论文

【摘要】：风机广泛应用于国民生产的各个部门,对国家经济发展起重要作用,因此对风机开展故障诊断和状态监测工作,保证风机良好的运行,具有重大的理论意义和现实意义本论文将模糊理论应用到风机故障诊断中,依据风机故障的模糊症状进行状态识别并进行模糊推理,从而做出诊断。此方法克服了传统诊断法需要获取精确信息的困难,适应了风机在连续运行过程中,由于受到工艺参数、温度变化、周围环境等因素影响,导致其运行状态和故障表象的随机性和模糊性。通过对风机故障机理的研究,确定以振动烈度和倍频峰值作为待检故障的征兆库,利用Matlab曲线拟合法和模糊分布法得出隶属函数。参考专家经验与大量诊断实例结果,初步建立模糊矩阵,选择加权平均型模型完成模糊方程。使用大连理工大学研制的PDM2000数据采集分析仪对故障风机进行振动信号采集,然后进行时域和频域分析,得出所需数值进行模糊故障诊断。经实例诊断结果对比,此方法是可行的。采用C++语言开发出风机模糊故障诊断系统,辅助求解隶属函数和模糊方程并实现模糊矩阵的自学习功能,不断对模糊诊断矩阵加以修正,逐步提高模糊诊断矩阵的适应能力和准确性。使用该模型对某钢厂内引风机和鼓风机进行测试诊断,经信号采集、数据提取、参照选定、模糊诊断系统诊断等步骤,确定引风机正常,鼓风机为转轴裂纹故障。停机进行检修,显示诊断结果正确,证明了此模型的实用性。
[Abstract]:The fan is widely used in various departments of national production and plays an important role in the development of national economy . Therefore , it is of great theoretical and practical significance to carry out fault diagnosis and state monitoring on the fan so as to ensure the good operation of the fan . In this paper , the fuzzy theory is applied to the fault diagnosis of the fan , the state recognition is carried out according to the fuzzy symptom of the fan fault and fuzzy reasoning is carried out , so that the diagnosis is made . The method overcomes the difficulty that the traditional diagnosis method needs to acquire accurate information , and the method overcomes the influence of the factors such as process parameters , temperature changes and the surrounding environment in the continuous operation process of the fan , and leads to the randomness and the ambiguity of the operation state and the fault appearance . By studying the mechanism of fan failure , it is determined that the vibration intensity and the frequency doubling peak are used as the symptom database of the fault to be detected . The fuzzy matrix is obtained by using the Matlab curve fitting method and the fuzzy distribution method . The fuzzy matrix is established by using the PDM2000 data acquisition analyzer developed by Dalian University of Technology . The fuzzy fault diagnosis is carried out by using the PDM2000 data acquisition analyzer developed by Dalian University of Science and Technology . In this paper , the fuzzy fault diagnosis system of the fan is developed by using C ++ language , the membership function and the fuzzy equation are solved , the self - learning function of the fuzzy matrix is realized , the fuzzy diagnosis matrix is corrected , and the adaptability and the accuracy of the fuzzy diagnosis matrix are gradually improved . This model is used to diagnose the induced draft fan and blower in a steel plant . After signal acquisition , data extraction , reference selection and diagnosis of the fuzzy diagnosis system , it is determined that the fan is normal and the blower is the crack fault of the rotating shaft . The shutdown is repaired , the diagnosis result is correct , and the practicability of the model is proved .

【学位授予单位】：辽宁科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH165.3

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