共查询到20条相似文献，搜索用时 93 毫秒
1.
《保鲜与加工》2003,(10):97-100
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. 相似文献
2.
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. 相似文献
3.
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. 相似文献
4.
Building management control systems (BMCS) are widely employed in modern buildings. The huge amount of data available on central stations and outstations provide rich information for fault diagnosis of HVAC systems. An online fault diagnosis method for variable air volume air handling units was presented using self-tuning HVAC component models. The model parameters are tuned online by using a genetic algorithm (GA) which minimizes the error between measured and estimated performance data, so high modeling accuracy is assured. If the error between measured and estimated performance data exceeds preset thresholds, it means the occurrence of faults or abnormalities in the air handling unit system. The statistical method of selecting thresholds also is presented. The fault detection method was tested and validated using data collected from real HVAC systems. The results of validation show that the fault detection method can be integrated in BMCS systems to detect faults in air handling unit systems efficiently. 相似文献
5.
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. 相似文献
6.
This paper discuses the method with which the corrosion of the grounding grid can be diagnosed .A grounding grid can handled as a circuit network. With the application of circuit network graph theory and the fault diagnosis theory of analog circuit and optimization, the fault diagnosis equations can be set up. This equations is figured out by Matlab, and the corrosion status of the grounding grid can be deduced from the result. 相似文献
7.
The Crossing Entropy is defined to scale the similar level of two probability distribution. In many papers on learning BN structure,the Crossing Entropy was used as an indicator of measuring the learning accuracy of an algorithm.The known scoring metrics for learning BN structure is analyzed in this paper,then a new scoring metrics Sum of Mutual Information is proposed based on the information theory.At last,two algorithm for learning BN structure by SIM is represented. 相似文献
8.
Application of higher density wavelet transform to composite fault diagnosis of rolling bearing 
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下载免费PDF全文 Aiming at the difficulties in accurate reorganization of several weak faults currently, a composite fault diagnosis method based on higher density discrete wavelet transform and envelope spectrum is proposed. Firstly, the higher density discrete wavelet transform is used to decompose acquired vibration signals of rolling bearings. Then, the single-subband reconstruction is performed on the wavelet coefficients and scaling coefficients at each scale in order to solve frequency aliasing. Finally, the envelope spectra of all subband signals are calculated, and all faults can be recognized according to the characteristic frequencies of the typical faults. The proposed method is applied to the diagnosis of the rolling bearings with composite faults, and is compared with other common fault diagnosis method. The results show that the proposed method can be effectively used for the early composite fault diagnosis of rolling bearings. 相似文献
9.
DENG Guo-hong~ 《保鲜与加工》2004,(10):8-13
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. 相似文献
10.
CAI Jing zhi 《保鲜与加工》2003,(4):93-95
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. 相似文献
11.
A new principle and scheme of a Feeder Automation based system protection using the channel of communication is proposed. The conjoint protection devices exchanging fault signal with direction information and the fault can be cleared instantly. These information can hel Pto isolate the fault zone and restructure the network rapidly. The recover is used for instantaneous faults. The optical MODEM disjoins the SCADA communication and Boolean signals functions using coding technology. So the fault flags can be exchanged rapidly peer-to-peer and special optical cables are not needed. Frames between optical MODEM are sent automatically. This scheme presented is successful through physical simulation experiment and has operated for about two years in a real distribution network. 相似文献
12.
A novel method for power transmission line monitoring and fault diagnosis is proposed based on non linear frequency response analysis. The power line carrier signal has been used for on line monitoring of power transmission line. As the non linear frequency response function describes the system inherent characterization, different frequency response patterns corresponding to different operation states of transmission line can be established. Based on the analysis of transmission line characteristics of fault modes, various fault features can be extracted, thereby achieve online monitoring and fault diagnosis on transmission line. Simulation experiments show the effectiveness of the proposed method. 相似文献
13.
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. 相似文献
14.
Petri网逆网在主轴故障诊断中的应用 总被引：2，自引：0，他引：2
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。 相似文献
15.
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. 相似文献
16.
A new fault diagnosis model is proposed based on Multi-Class Least Square Support Vector Machine optimized hierarchically by Genetic Algorithm(GA). Original vibration signals are decomposed into several stationary IMFs. Then the instantaneous amplitude energy of the IMFs with fault modulation characteristics is computed and regarded as the input characteristic measure of the Poly-kernel Multi-Class LS-SVM for fault classification. EMD decomposition adaptively isolates the fault modulation signals from original signals. The differences among instantaneous amplitude energy vectors reflect the separability of different fault types. Adopting GA to optimize punish parameter and Poly-kernel parameters hierarchically can not only enhance fault prediction accuracy of Multi-Class LS-SVM with Poly-kernel, but also improve adaptive diagnosis capacity of LS-SVM. The GA-based hierarchical optimization is also applicable to Multi-Class LS-SVM with Lin-kernel, RBF-kernel or Sigmoid-kernel. The deep groove ball bearings fault diagnosis experiment shows the effectivity of this new model. 相似文献
17.
Considering traditional current protection cannot satisfy the micro-grid, a system protection solution for the micro-grid is proposed. In this solution, the failure message with direction information can be exchanged among the adjacent protection units, so the fault coverage can be determined and the fault can be quickly cleared. By analyzing the movement of the protection in three kinds of fault conditions in the micro-grid that contains three branches and two micro-power based on inverter, the method has been proved that the fault can be quickly cleared and the protection has the same protection strategies for both islanded and grid-connected operation. 相似文献
18.
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. 相似文献
19.
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. 相似文献