Application of Improved Genetic Algorithm in Network Fault Diagnosis Expert System

Knowledge acquisition is the “bottleneck” of building an expert system. Based on the optimization model, an improved genetic algorithm applied to knowledge acquisition of a network fault diagnostic expert system is proposed. The algorithm applies operators such as selection, crossover and mutation to evolve an initial population of diagnostic rules. Especially, a self adaptive method is put forward to regulate the crossover rate and mutation rate. In the end, a knowledge acquisition problem of a simple network fault diagnostic system is simulated, the results of simulation show that the improved approach can solve the problem of convergence better.

Design and Implementation of Urban-rural Power Grid Dispatching Fault Diagnosis Expert System

The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence method to analyze fault information and make fault diagnosis. The paper implements the core part of the fault expert system the design of knowledge base and fault inference engine.

A Simulation Study on Boiler Fault Diagnosis Expert System

The boiler is one of the key parts of power station. Monitoring the operation of the boiler automatically, continuously and accurately is very important. In case of malfunctions, an expert system might be helpful to find the sources of faults, and thereafter will assist the operator to act correctly and to prevent the fault from further development.In this paper, a simulation study of an expert system, which can diagnose the running faults of boiler system, is conducted. Shallow and deep two-layer knowledge base structure is used in this two layers of knowledge base. So. this kind of expert system can overcome the disadvantages of the old types of expert systems, which are only able to deal with experience rules base.A simulator of power boiler is used for the research on fault diagnose expert system. This boiler simulator gives all necessary information for the diagnosis. The knowledge base of expert system is built in hierarchies, so the speed of reasoning may be invreased. After the reasoning the

A Fault Diagnosis Expert System for a Heavy Motor Used in a Rolling Mill

A fault diagnosis expert system for a heavy motor used in a rolling mill is established in this paper. The fault diagnosis knowledge base was built, and its knowledge was represented by production rules. The knowledge base includes daily inspection system, brief diagnosis system and precise diagnosis system. A pull down menu was adopted for the management of the knowledge base. The system can run under the help of expert system development tools. Practical examples show that the expert system can diagnose faults rapidly and precisely.

STUDY OF A FAULT DIAGNOSIS EXPERT SYSTEM FOR SYNTHETIC MINING SYSTEM HYDRAULIC SUPPORT

Fault diagnosis expert system for hydraulic support is studied.The system is achieved by Turbo prolong Language, it summaries the experience of the domain expert and sets up a fault tree, knowledge base is developed by a productive rule.According to the feature of diagnosis, the system selects forward non determination inferring and limited depth first search strategy.It can accomplish expert diagnosis of more than 50 kinds faults in hydraulic support.

Research on the Algorithm of Avionic Device Fault Diagnosis Based on Fuzzy Expert System

Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.

Design and implementation of an expert system for remote fault diagnosis in ship lift

In this paper an expert system for remote fault diagnosis in the ship lift was developed by analysis of the fault tree and combination with VPN. The fault tree was constructed based on the operation condition of the ship lift. The diagnosis model was constructed by hierarchical classification of the fault tree structure, and the inference mechanism was given. Logical structure of the fault diagnosis in the ship lift was proposed. The implementation of the expert system for remote fault diagnosis in the ship lift was discussed, and the expert system developed was realized on the VPN virtual network. The system was applied to the Gaobaozhou ship lift project, and it ran successfully.

A Study on FMS's Real-time Fault Diagnosis Expert System

ＡＳｔｕｄｙｏｎＦＭＳ＇ｓＲｅａｌ－ｔｉｍｅＦａｕｌｔＤｉａｇｎｏｓｉｓＥｘｐｅｒｔＳｙｓｔｅｍＸＩＡＯＸｉａｎｇｓｈｅｎｇ；ＬＩＵＷｅｎｊｉａｎ；ＳＵＢａｏｈｕａ；ＭＡＹｕｌｉｎ（肖祥胜，刘文剑，苏宝华，马玉林）（ＦＭＳＲｅｓｅａｒｃｈＣｅｎｔｅｒ...

Learning Fault Diagnosis Knowledge for a FCC Expert System by Genetic Algorithms

This paper introduces a GA-based Fault Matrix Learning System(GAFMLS) which applies Genetic Algorithms to a FCC expert system (FCCES) to learn a near-optimal fault matrix used in the fault diagnosis of an oil catalytic and cracking unit. The practical running results show that more effective fault matrixes can be generated by GAFMLS, and the reliability and precision of FCC expert system are improved.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

STUDY OF REAL-TIME EXPERT SYSTEM TOOL FOR INDUSTRIAL FAULT MONITORING AND DIAGNOSIS

From the requirements of industrial production,an integrated fault monitoring,diagnosis and repairing system is suggested in this paper. This new scheme of fault monitoring and diagnosis system is realized by a master-slave real-time expert system,and a real-time expert system tool for this system is also developed accordingly. As an example of application of this tool ,a realtime expert system for fault monitoring and diagnosis on DC mine hoist is developed. Experiments show that this tool possesses better supporting environment, strong knowledge acquisition ability, and convenience for use. The system developed by this tool not only meets the real-time requirement of DC hoist,but also can give correct diagnosis results.

Expert fault diagnosis system for leaching process in zinc hydrometallurgy

Leaching process is the first step in zinc hydrometallurgy, which involves the complex chemical reactions for dissolving zinc bearing material in dilute sulfuric acid. Ensuring the safe running of the process is a key point in the operation. An expert fault diagnosis system for the leaching process was proposed, which has been implemented in a nonferrous metals smeltery. The system architecture and the diagnosis procedure were presented, and the rule models with the certainty factor were constructed based on the empirical knowledge, empirical data and statistical results on past fault countermeasures, and an expert reasoning strategy was proposed which employs the rule models and Beyes presentation and combines forward chaining and backward chaining. [

RESEARCH ON EXPERT SYSTEM OF FAULT DETECTION AND DIAGNOSING FOR PNEUMATIC SYSTEM OF AUTOMATIC PRODUCTION LINE

Fault detection and diagnosis for pneumatic system of automatic productionline are studied. An expert system using fuzzy-neural network and pneumatic circuit fault diagnosisinstrument are deigned. The mathematical model of various pneumatic faults and experimental deviceare built. In the end, some experiments are done, which shows that the expert system usingfuzzy-neural network can diagnose fast and truly fault of pneumatic circuit.

An Equipment Fault-tolerant Control Expert System and its Application

This paper presents an expert system that can automatically monitor, diagnose and fault-tolerant control by combining fault diagnosis with fault-tolerant technology. The features of the structure of this expert system, knowledge acquisition and organization, and the strategies and realized methods of fault-tolerant control are introduced. An applied example is given.

Knowledge Processing Method of Fault Diagnosis Expert Systems for Letter Sorting Equipment

Based on the analysis of fault diagnosis knowledge of letter sorting machine, this paper proposes a processing method by which the fault diagnosis knowledge is divided into exact knowledge, inadequate knowledge and fuzzy knowledge. Then their presenting and implementing form in fault diagnosis expert system is discussed and studied. It is proved that the expert system has good feasibility in the field of the diagnosis of letter sorting machine.

Integrated automatic HAZOP analysis and fault diagnosis based on Petri net

Based on systematically analyzing the procedure of hazard and operability (HAZOP) study, the author introduces a method of modeling fault diagnosis with the Petri net with fuzzy colors, in which the fuzzy information can be represented effectively in the process of analysis. The author proposes the architecture of a knowledge base, which integrates HAZOP analysis and fault diagnosis, and provides the conditions for constructing the knowledge-based expert system. The author also presents a method of knowledge representation for on-line HAZOP analysis and on-line fault diagnosis is presented based on the technology of Petri net with fuzzy colors, which establishes a technological fundamental for integrating the automatic HAZOP analysis and fault diagnosis.

REALIZATION OF OBJECT-ORIENTED RULE-TYPE EXPERT SYSTEM TEMPLATE

Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.

Fault Diagnosis of Mechanical Equipments Through Spectrometric oil Analysis for Worn Off Metallic Elements

In the fault prediction of mechanical equipments through spectromectric oil analysis for worn off debris, a method for the determination of the limiting value of wear is proposed and discussed. In order to diagnose the impending failure and to predict the fault modes and locate the fault spots, a comprehensive approach is studied and outlined on the basis of methods of discriminative analysis and fuzzy logic. A fault diagnosis expert system OAFDS developed by the authors for the nonitoring of working conditions of the ND5 locomotive diesel engine Nd5 is briefly introduced.

Intelligent Fault Diagnosis in Lead-zinc Smelting Process

According to the fault characteristic of the imperial smelting process （ISP）, a novel intelligent integrated fault diagnostic system is developed. In the system fuzzy neural networks are utilized to extract fault symptom and expert system is employed for effective fault diagnosis of the process. Furthermore, fuzzy abductive inference is introduced to diagnose multiple faults. Feasibility of the proposed system is demonstrated through a pilot plant case study.

The development of a knowledge base in an expert system based on the four-layer perceptron neural network

Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differential function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.