Fault Diagnosis Expert System of Combustion Engine with Rough Set Theory

On the basis of fault diagnosis expert system, the rough set theory is introduced. Knowledge representation system table is taken as a major tool to reduce the rules of expert system in which unnecessary properties are eliminated. The redundancy of fault diagnosis information is revealed. The complexity of fault diagnosis expert system's structure is also reduced. The decision making rules are given finally.     

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.     

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 diagnosis of rotating machinery based on self-learning fuzzy spiking neural network

For fuzziness classific boundry of fault diagnosis of rotating machinery and traditional neural network algorithms difficulted to solve contradiction between application problems example scale and netwok scale,a methord of self-learning fuzzy spiking neural network is put forward. The methord overcomes unavailability of cluster analysis on classific boundry of fault diagnosis of rotating machinery by species encoding of pulse sequence and unsupervised learning. The method shows that it effectively solves boundary fuzziness problem on fault diagnosis of rotating machinery,and greatly improves efficiency of fault diagnosis.     

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.     

Application of Object-oriented Representation in the Motorcycle Designed Expert System

Knowledge representation is one of the key technologies in the designed expert system.According to the requirement of total design of motorcycle, this paper researches the classificationof knowledgeand experienceof the motorcycle, analyses the points of knowledge representationmethod such as production rule, frameworkand object-oriented and so on, and puts forward the object-oriented knowledge representation method which is combined with abstraction, encapsulationand inheritanceof object-oriented technique. At last the authors realizes the knowledge representation of motorcycle designing under the language environmentof C++ and givesthe knowledge representationexamples of motorcyclebodywork designing.     

A Vovel Constracture of Combinatorial Knowledge Base for the Expert System of Eletrical Switching

By comparing the techniges of the production and the logic predicate for knowledge representation, this paper presents a kind of constructure of combinatorial knowledge base applied to the expert system for switch operation in electric power system . This constructure of knowledge base to be expanded and revised easily,and it is cinvenitnt to build the general shell of the expert system.     

Fault diagnosis of rotating machinery based on fuzzy clusteringoptimized by chaos embedded particle swarm optimization

A method of weighted fuzzy clustering optimized by chaos embedded particle swarm algorithm(CPSO) is put forward and applied in vibration fault diagnosis of rotating machinery. In the method, CPSO is used to displace the traditional stochastic-gradient algorithm to optimize parameters of weighted fuzzy C-means (WFCM). The best clustering num and clustering centers are automatically attained according to clustering validity function. The experimental results show that the method effectively increases the convergence velocity and precision of WFCM and so does the correctness rate of fault diagnosis for rotating machinery.     

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.     

A model of a hall for a workshop of metasynthetic engineering

A hall for a workshop of metasynthetic engineering (HWME) is constructed based on network services, in which the expert, machinery and knowledge systems are combined with services. This hall is an expansion of the traditional workshop hall. The     

Petri网逆网在主轴故障诊断中的应用

比较了成熟期27个梨品种的果胶含量、半乳糖醛酸含量、果肉硬度和可溶性固形物含量,并分析果胶含量与果实品质特性的相关性。结果表明,不同梨品种间的果肉硬度、可溶性固形物、果胶、半乳糖醛酸含量4个指标的差异性都达到极显著水平(P0.01),果肉硬度均值为2.76 kg·cm-2,F值为47.03;半乳糖醛酸含量为0.64%~1.73%,F值为89.24,品种间差异最大;可溶性固形物含量为9.41%~15.19%,F值为17.66,品种间差异最小;果胶含量为0.23%~1.02%,与可溶性固形物和半乳糖醛酸含量呈极显著正相关(P0.01),Pearson相关系数分别为0.618和0.680。     

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.     

Parsimonious Covering Probability Model for Turbogenerator Vibration Faulty Diagnosis

The turbogenerator vibration faults have the character of variety. Many faults often occur synchronously. This paper introduces a diagnosing model based on parsimonious covering theory and probability. A model for turtogenerator's fault diagnosis is proposed. The availability of this method is proved by two fault diagnosis examples of turbogenerator. The results show that the model proposed can be used for multi_fault diagnosis together. It may make up shortage for some of expert systems and neural networks in some aspect. From the practice,this model has higher reliability and practicability.     

实用型荔枝虫害诊断专家系统设计方法研究 实用型荔枝虫害诊断专家系统设计方法研究

针对大型检索表为表示的专家知识体系，研究提出了一套可重用的、实用性强的系统设计方法，建立了荔枝虫害诊断专家系统（LDS）。经生产示范应用表明：实现了人机操作界面直观、明了，降低了客户端的专业要求，提高了系统的实用性。还对系统所构造的人机界面、知识存储结构设计和控制策略给出实践示例。     

Analysis of Information Flow Based on Entropy of Fault Diagnosis

Under the pointview of epistemology and generalized information theory, fault diagnosis can be regarded as the state identification process by dint of various cognitive tools. Therefore, information Entropy can be employed to explain the transfer of information during identifying the faults. The mathematical deduction of information Entropy is given and the idea of Multi-Symtom Domains Comprehensive Feature Knowledge to solve fault diagnosis problems caused by insufficient knowledge and lower cognitiving ability for complex knowledge system is presented.     

实用型荔枝虫害诊断专家系统设计方法研究

针对大型检索表为表示的专家知识体系,研究提出了一套可重用的、实用性强的系统设计方法,建立了荔枝虫害诊断专家系统(LDS)。经生产示范应用表明:实现了人机操作界面直观、明了,降低了客户端的专业要求,提高了系统的实用性。还对系统所构造的人机界面、知识存储结构设计和控制策略给出实践示例。     

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.     

专家系统在果树中的应用及研究进展

专家系统是一种模拟人类专家解决领域问题的计算机系统,它主要分为知识库、综合数据库、推理机、解释器、接口等几部分。现今,国内果树专家系统的应用类型主要分为果树栽培生产专家系统和果树营养、病虫害诊断防治决策系统两类;在果树专家系统上的应用研究最多的计算机理论主要是：人工神经网络、模糊神经网络、多媒体技术、Web技术等;果树专家系统的开发手段主要是利用现成的农业专家系统平台直接进行二次开发,还有少数是直接利用程序语言进行原型系统开发。今后随着信息技术的不断发展,利用果树学的特点结合先进的计算机理论和技术,将开发出动态的、更具智能化的果树专家系统。     

A Uncertain Reasoning Machine

This paper firstly discusses some problem about the uncertain reasoning machine in the agricultural expert system based on HPC, such as the knowledge representation, the certainty factor, the representation of evidence uncertainty, the calculation of multi evidence uncertainty, the update of uncertainty and so on. Secondly, the control strategy of this uncertain reasoning machine is discussed. This control strategy adopts a converse reasoning strategy based on target, and it adopts a conflict removing strategy based on certainty factor. The arithmetic to realize the uncertain reasoning machine is also given in detail. At last, this paper stats the example of malnutrition diagnosing of grape as the application of the reasoning machine.     

The Design and Implementation of An Expert Control System

This paper proposes an expert control system for industrial processes on-line control and supervision by combining expert system techniques with computer process control techniques, introduces the fundamental design principles,basic structure and engineering implementation of this real time expert control system and gives the field operation results concerning the processing of a sodium chromate rotary kiln controlled by this expert control system as an application example.