Research and Application of Information Fusion Technology on Machinery Fault Diagnosis

Aiming at insufficiency exists in the process of machinery fault diagnosis at present, the paper takes consider of the application of information fusion technology in fault diagnosis to make fault diagnosis effectively. The applications of information fusion methods based on neural network, the Bayesian theory and the D-S theory are discussed in detail. Example is also given to explain the validity of information fusion technology in diagnosis analysis.     

The Development of Intelligent Fault Diagnosis System Based KBE Graph

Aimed at solving the insufficiency problem in the current intelligent fault diagnosis system, such as lack of development tools, inference oversimplification, and developed a kind of diagnosis system based on network and KBE graph. The system is simple and easy to establish, modify, expand and maintain and does not need further coding. In addition, it can significantly save time and reduce the chance of failure. The integration of expert rules, fuzzy logic and nerve network enables the system to adapt to those complicated systems which involve in multi-variable, multi-parameter, multi-object and multi-process. As an example, an on-line detection system for simulate-on rotor test bench has been established and typical faults were successfully diagnosed through it, which proved the validity and reliability of the system. Furthermore, the system has been declared national invention patent.     

Knowledge Representation for Rotative Machine Fault Diagnosis Based on Semantic Net

Aiming at knowledge representation problem of expert system for rotary machinery fault diagnosis, semantic net knowledge representation is discussed. Semantic net to represent expert knowledge of rotary machinery fault diagnosis is explored. Its realizing method is afforded in computer language, in addition, demostrating model is also developed in Visual C++. The result shows good validity of the knowledge representation.     

基于信息熵的农民信贷需求研究

以信息熵理论为基础,通过构建农民信贷决策的信息熵函数,以华北平原地区农村为例,探求了信息熵对农民家庭收入和支出两方面的影响及其对农民信贷需求的影响。研究发现,信息对农民家庭收支的影响存在差异;由于农村信息传播不畅通,致使农民家庭信贷需求是不完全有效的,并指出建立完善的农村信息传播机制,是提高农民信贷需求有效性的重要途径。     

Application on Extracting Feature in State Monitoring and Fault Diagnosis

With the development and application of information and internet and virtual instrument technology ,the virtual globular company based on internet arises .To study remote state monitoring, remote fault detection and diagnosis about large scale, complicated and integrative equipment become very important. In the whole fault diagnosis system , the detecting ,data acquisition is original ,processing; transform and extracting features with the signal detected is a key factor. The theories and methods used in mechanical fault diagnosis is stated. The application of signal process and its feature extracting methods is introduced which are time domain, frequency domain and time frequency domain analysis, in state monitoring and fault diagnosis with its signal analysis. The processing method of random time variant special signal is given also.     

A Multi-agent Fault Diagnosis System of Rotating Machinery Based on CBR

Recently,distributed intelligent systems based on multi-agent have been applied to many fields successfully.the multi-agent technique is introduced into the rotating machinery fault diagnosis system.With the combination of CBR technique,Basalstructure and development approach of the system are analyzed,and better cooperation among agents is realized.As a result,the system overcomes the limitation of single fault diagnosis method,and solves the contradictionbetween versatilityand adaptabilityof diagnosis software.Furthermore,a reference can be used for the research and development of multi-algorithmdiagnosis system of rotating machinery.The application in a factory's Networked Online Monitoring and Fault Diagnosis System for Turbine Fan shows that the system can diagnosefault rapidly and exactly.     

基于信息熵和灰色关联法的阿克苏地区建设用地动态变化研究

在城市化与工业化发展的背景下,建设用地进入快速扩张时期。为了加强阿克苏地区建设用地集约节约利用程度,合理进行土地资源配置。针对阿克苏地区土地利用特点,结合阿克苏地区2004-2013年土地利用现状调查和变更数据以及社会经济发展数据,采用土地利用结构信息熵判断阿克苏地区建设用地内部结构的有序性和均衡性,运用主成分分析法提取影响建设用地变化的外部因素,并将建设用地内部结构面积比例和外部因素与信息熵进行分别进行灰色关联分析。结果表明,阿克苏地区建设用地信息熵呈现波动性上升趋势,用地结构朝无序方向发展;建设用地外部影响因素中经济发展因素和耕地因素与信息熵呈现中度相关,是建设用地变化的主要推动力。     

基于信息熵和协整理论的新疆土地利用时空动态分析

土地利用结构信息熵可以综合反映某区域在一定时段内各种土地利用类型的动态变化及其转换程度,对于具体区域的土地利用结构调整、优化利用土地具有一定的指导意义。土地利用动态变化研究是全球性的课题,土地利用结构变化是土地利用动态变化的结果,笔者应用信息熵理论和协整理论及Granger因果检验,探究新疆土地利用时空动态变化。结果表明：①土地利用结构信息熵反映了新疆土地利用的时空情况,其信息熵随着时间的推移缓慢上升,其变化幅度较小,总体上土地利用结构趋于稳定,但南北疆土地利用差异明显;②土地利用变化与经济发展密切相关。土地利用结构与经济发展是非平稳的时间序列,经济发展与土地利用结构之间存在协整关系,经济发展是土地利用变化的单向Granger原因。新疆经济发展是土地利用结构及类型变化的主要原因,其特殊的自然生态环境,应在保护生态环境的前提下,统筹安排各业各类用地,协调好经济发展与土地利用之间的关系。因此,必须对该区域的土地利用结构进行调整与优化,以维护区域系统的稳定。     

Fault Diagnosis in Hydraulic Turbine Governor Based on BP Artificial Neural Network

The governing system of hydraulic turbine generator plays an important role in power system. It is significant to find out the faults of governing system and remove them quickly. This paper sets up a new fault diagnosis model of the hydraulic turbine generator governing system with the advanced ANN (artificial neural net). This 17-in-13-out model consists of three layers. It is proved that this model can find the fault accurately.     

Artificial Neural Network Fault Diagnosis System Based on Rough Set Theory

On the basis of fault diagnosis neural network model, in this paper, knowledge representation system of rough set theory is taken as a major tool to delaminate the complex neural network and in which unnecessary properties are eliminated. This method overcomes some shortcomings, such as network scale is too large and the rate of classification is slow. The good effect that reduces the matching quantity of pattern search in classification course is gotten. The structure and algorithm of layered-mining neural network model based on rough set theory are also given. The example shows that this system has higher reference value in practical application.     

Study on the Method of Intelligence Fault Diagnosis System for Drill

It is very difficult to simulate the motion process of drill by accurate mathematics model for the complexity and invisibility of stratum. The fault of drill is usually identified and disposed by personal experience so far. This means it can not estimate the trend of the equipment running good or not and the reason conduced the fault or location and degree of fault by data measured. Farther, it can not give the expert suggestions. Based on the studying of drill fault, artificial intelligence and expert system have been used in the petroleum drilling engineering, the theory and method of fault diagnosis intelligence system for drill have been studied. It also constitutes the expert knowledge database of graphic Fuzzy Neural Network for the familiar fault of drill. The intelligence reasoning machine which consists of expert rule, Fuzzy logic and artificial Neural Network have been bring forward. And the fault diagnosis system it makes for drill can be applied in complex system which includes multi-variable, multi-parameter and multi-process.     

Fault Section Diagnosis Algorithm of Distribution Networks Based On Topology Identification

An algorithm of fault section diagnosis based on topology identification for distribution networks is presented. By decomposing the topologic matrix which describing the distribution network into two parts,one part only contain the complex coupling factor ,and the other ignore the complex coupling factor. Using this method, the fault zones in distribution network can be identified and isolated efficiently, and the vertexes of the zones can also be identified automatically. This approach adapts to the changefully network structures.     

基于信息熵的庄浪县土地利用结构变化及其驱动力分析

为研究庄浪县土地利用结构动态变化情况,促进土地资源的合理利用和可持续发展,基于庄浪县1997—2012年土地利用变更数据以及经济社会统计数据,采用信息熵、均衡度和优势度原理,分析庄浪县土地利用结构的动态演变特征,并运用主成分分析方法对影响庄浪县土地利用结构动态演变的驱动力进行分析。结果表明：1997—2012年,庄浪县土地利用结构信息熵总体呈先上升后下降再上升的波浪式趋势变化,表明各区域的土地利用系统仍处于较大程度的开发中。耕地、林地及未利用地面积所占比例的高低,是影响庄浪县土地利用结构信息熵的主要因素。人口经济发展状况、城市化、产业结构是庄浪县土地利用结构变化的主要驱动力。     

Analysis of the Modulation Phenomenon of Complex Vibration in Gearbox Fault Diagnosis

This paper presents a modulation phenomenon of complex vibration which occured when gear teeth broke or shaft seriously bent in gearbox. Based on the mechanism of gear vibration and modulation sideband,the peper analyzes this complex modulation phenomenon.     

State and Prospects of Diesel Engine Fault Diagnosis Technique

As a kind of complex power machinery, diesel engine is being paid more and more attention to its condition monitoring and fault diagnosis technology. In the fault diagnosis field of diesel engine, the technique of signal process, character abstraction and identification method have formed a system, but there is a certain distance away from practical. This paper analyzes the common faults and influencing factor of diesel engine. The principle, characteristic and disadvantage of modern fault diagnosis technology, such as various time-frequency methods based on vibration signal, speed fluctuation method, iron content and spectrometry, grey system theoretical diagnosis method, artificial neural network and expert system fault diagnosis method, were reviewed. The difficulties and the development direction of diesel engine fault diagnosis were put forward in the end.     

A Three Valued Model of System Level Fault Diagnosis

We propose a three valued model of system level fault diagonsis,define a class of diagnosable systems,give a characterization of them,and study their optimal design.     

The Application of Fuzzy Neural Networks for Power Transformer Fault Diagnosis

This paper presents the application of fuzzy neural networks (FNN) in power transformer faults diagnosis.A FNN model is builded,in which input is transformer oil color spectrum analysis and output is fault type.The test results of fault examples show its effectiveness and potential applicable worthiness.