基于LabVIEW的旋转机械远程故障诊断系统研究

针对北京燕山石化炼油厂某烟气轮机进行旋转机械远程故障诊断的研究,设计并开发了远程故障诊断系统原型.首先通过转子实验台模拟烟机的振动信号,以LabVIEW为平台对转子振动信号进行获取和分析;然后利用BP神经网络的方法对其进行故障诊断;最后通过B/S结构网络体系的构建,完成整个远程故障诊断原型系统的开发.     

基于LabVIEW的罗茨鼓风机转子振动测试系统

开发一套基于LabVIEW的罗茨鼓风机转子振动测试系统,利用PCI采集风机振动信号,以振动信号的频域特征作为主要的故障征兆,运用频谱分析方法实现风机状态监测,为设备安全运行提供技术保障.     

具有模式识别功能的焊接自动跟踪系统

所研制的焊接自动跟踪系统,通过对不同焊道的模式自动识别,很好地实现了对多道埋弧焊的自动跟踪。     

A new hybrid pattern recognition scheme for automatic discrimination of power quality disturbances

In this paper an intelligent method for automatic detection of Power Quality Disturbances (PQDs) is presented. The proposed automatic scheme is noticed to retaining informative features or eliminating redundant features simultaneously. This paper presents an effective method, for extracting features, so-called “integrated approach”, using integration of Discrete Wavelet Transform and Hyperbolic S Transform. Moreover, a new efficient feature selection method namely Orthogonal Forward Selection by incorporating Gram Schmidt procedure and forward selection is applied for selection of the best subset features. Some different classifiers are empirically compared in order to determine the best classifier. In this automatic scheme, the variable parameters of classifiers are optimized using a powerful method namely Particle Swarm Optimization. The sensitivity of the proposed method under noisy conditions has been investigated. The average rate of correct classification using the proposed hybrid scheme for automatic discrimination of PQDs in various noise conditions 99.55% is obtained.     

Evaluation of principal component analysis and neural network performance for bearing fault diagnosis from vibration signal processed by RS and DF analyses

In this work, signal processing and pattern recognition techniques are combined to diagnose the severity of bearing faults. The signals were pre-processed by detrended-fluctuation analysis (DFA) and rescaled-range analysis (RSA) techniques and investigated by neural networks and principal components analysis in a total of four schemes. Three different levels of bearing fault severities together with a standard no-fault class were studied and compared. Signals were acquired from bearings working under different frequency and load conditions. An evaluation of fault recognition efficiency was performed for each combination of signal processing and pattern recognition techniques. All four schemes of classification yielded reasonably good results and are thus shown to be promising for rolling bearing fault monitoring and diagnosing.     

机电设备故障诊断中的模式识别技术

模式识别技术广泛地应用于复杂系统的故障诊断中.简述了复杂机电设备故障诊断中的模式识别技术,建立了一个模式识别故障诊断通用平台.最后以H-L32型卧式数控车床转子为对象,对其各种故障应用模式识别技术进行了诊断,并取得了较好的效果,从而充分证明了模式识别技术在故障诊断中的应用价值.     

一种新型车型自动识别系统

提出了一种新型超声波车型自动识别系统,该系统集超声波回波测距原理和现代计算机技术于一体,实现对车辆高度、长度、速度的自动检测,并进行车型自动识别与分类。本文详细介绍了超声波测距原理,利用超声波发射电路、接收电路和单片机实现车型自动识别的方法。     

A novel procedure for diagnosing multiple faults in rotating machinery

In analyzing signals from a wind turbine gearbox this paper suggests a new signal processing procedure named as CMF-EEMD method which is formed by applying conventional EEMD to a new type of combined mode function (CMF). This CMF consists of a low frequency CMF, denoted as C_L, and a high frequency CMF, denoted as C_h. Then it optimizes the amplitude of the added noise in decomposing C_h and C_L using EEMD. Finally, it calculates cyclic autocorrelation function (CAF) for every characteristic IMF from EEMD. The proposed procedure is applied to analyze the multi-faults of a wind turbine gearbox and the results confirm better performances in resolving different signal components by the proposed method than that from the cyclic autocorrelation function (CAF) of a direct EEMD analysis.     

Packaging machine for “Mozartkugeln” controlled by a position recognition system

This paper explores some of the critical issues in the development of a picture position recognition system. The system uses an on-line correlation procedure. Its output is used to control a positioning and packaging machine, the design of which is described in some detail.     

Experimental validation of impact energy model for the rub-impact assessment in a rotor system

An experimental setup which can simulate the rotor-to-stator rub in a rotor system is installed. A rub screw is used to simulate the condition of local rub-impact fault. Based on the theory of elastic collision and energy conservation, an Impact Energy Model (IEM) is proposed to evaluate the probability or severity of rub-impact fault. To prove this model, the paper conducts the experiment in two steps i.e. hammer test and rub-impact fault validation. The wave signal, spectrum and axis orbit are used to analyze the severity of the rub-impact fault when it occurs. The analysis result shows that the proposed Impact Energy Model (IEM) is effective in the assessment of rub-impact fault. Furthermore, the proposed IEM can also provide a reference for the design and operation of a rotor system.     

智能化故障诊断系统在双环减速机中的应用

介绍智能化诊断系统原理和组成 ,分析环式减速器可能存在的故障及减速器齿轮箱故障特征 ,并以中心输入式双环减速器为对象 ,介绍智能诊断系统在环式减速机故障诊断中的应用。利用该系统对环式减速器故障数据进行分析、处理 ,进而推理、诊断 ,获得了满意的效果     

基于高阶谱分析的转子裂纹的诊断

研究了基于高阶谱特性的转子裂纹的诊断 ,分析和实验表明无裂纹轴和有裂纹轴的高阶谱具有显著的差别 ,不同的裂纹深度、位置的转子裂纹的高阶谱 (主要是三阶谱 )也有较大的差别 ,利用高阶谱对转子裂纹的诊断具有良好的应用前景