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Development of vibrational diagnosis system and creation of fault mode in rotating machinery

旋转机械振动诊断系统开发及故障模式创建

基本信息

批准号：
03452140
负责人：
IWATSUBO Takuzo
金额：
$ 3.39万
依托单位：
Kobe University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1991
资助国家：
日本
起止时间：
1991 至 1992
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-03452140/
关键词：
Rotating machinery Failure mode Diagnosis method Fuzzy logic Neural network 故障モ-ドニュ-ラルネット

项目摘要

It is a most effective way to protect the power plants or chemical plants from the big accidents that we predict the accident theoretically or find the accident at the initial stage of the faults. In order to achieve the above matters, the investigations were performed for the following objects. (1) Establishment of predicting method of fault modes from the viewpoints of function and stracture of rotating machinery. (2) Establishment of precise estimating technique by using the Bay's theory, in which the discrepancy of measurement vibrational data by the difference of measuring points of the rotating machinery are made clear. (3) Development of automatic diagnostic algorithm by using the expart system or neural network theory.As the results, the data base for the cause of the fault are established and the expart diagnostic systems by using the matrix counting method, fuzzy theory, Bay's theory and the neural network system are built up. That is, the analysis of diagnostic process by the specialist and the development of the modeling of the diagnostic process are built up by using the expart system technique. In practical case, main diagnostic computer program are finished, in which subsystem for different types of diagnostic algorithm, these are, the matrix counting method, fuzzy theory, Bay's theory and neural network theory can be added in order to compare with each other.In the diagnostic method, creation of fault modes and its relation to the vibration phenomena are clarified from the engineering point of view. Moreover realizations of Bay's diagnostic technique and the neural network technique to the precise diagnosis are accomplished.

从理论上预测事故或在故障初期发现事故，是保护发电厂或化工厂免遭重大事故的最有效方法。为了实现上述目的，进行了以下目的的研究。 (1)从旋转机械的功能和结构角度建立故障模式预测方法。 (2)利用Bay理论建立精确估算技术，明确了旋转机械测量点不同导致的测量振动数据的差异。 (3)利用外部系统或神经网络理论开发自动诊断算法。据此，建立了故障原因数据库，并建立了利用矩阵计数法、模糊理论、Bay理论和神经网络系统的外部诊断系统。即专家对诊断过程的分析和诊断过程建模的开发是利用外部系统技术来建立的。在实际情况中，完成了主诊断计算机程序，其中针对不同类型的诊断算法的子系统，可以添加矩阵计数法、模糊理论、贝氏理论和神经网络理论，以便相互比较。在诊断方法中，从工程角度阐明了故障模式的产生及其与振动现象的关系。并实现了Bay诊断技术和神经网络技术的精确诊断。