Improved BP Algorithm in Vibration Failure Diagosis of Steam Turbine-Generator Set

A failure diagnosis model of neural networks for the vibration failure feature of steam turbine-generator set is established on the basis of the improved BP algorithm ,and used for diagnosing practical generator set,the results of verification show that the method is effective.     

A New Method of Diesel Engine Fuel System Fault Diagnosis

A method of diesel engine fuel system fault diagnosis based on wavelet transform and fuzzy C-means clustering is presented. Five characteristic parameters of reflecting fault state are distilled with wavelet transform of pressure wave of high-pressure oil pipe of diesel. The theory and generic approach of fuzzy C-means clustering algorithm (FCM) is given, and the validity of evaluating fuzzy clustering making use of partition coefficient, partition entropy and parting coefficient is pointed out. Identification of fault mode can be completed utilizing standard fault character modes established by FCM algorithm, and calculating and comparing the similarity degree between this standard mode and sample. The arithmetic is applied to all kinds of typical faults diagnose in the diesel engine fuel system. Measuring results indicate that the precision of fault diagnosis is increased with the analysis of wavelet and FCM.     

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.     

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.     

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.     

The Application of Fuzzy Neural Network in the Detection for Moving Object

A fuzzy neural network(FNN) of detection for moving object based on BP algorithm is described in this paper.The correctness of the FNN in signal detection for moving object and fault diagnosis for instrument is proved by experiments.     

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.     

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.     

Two-level Fuzzy Method for Evaluation of the Supplier''s System in Automobile Industry

This paper analyses the importance of the suppliers' evaluation in automobile industry. Based the conception of system, all the corporations' suppliers are regarded as an integer. On condition that the corporation has evaluated the single supplier's performance, the model for evaluate the performance of supplier's system is established, the performance by two-level fuzzy method is evaluated. Finally, the method sets with an example as the illustration.     

Application of Fuzzy Comprehensive Judge Method in Determining Supplying Risks in Automobile Parts Enterprises in an Uncertain Environment

Based on analyses of the main factors that influence the supplying risks in automobile parts enterprises within our country,a supplying risks judgment system is established. To determine the risks, a fuzzy comprehensive judge method is put forward with AHP method. In the end, with an example of a company, supply risks are analyzed, which provides a referential method for determining supplying risks in automobile parts enterprises.