Application of Self-tuning Models to Air Handling Units for Fault Detection

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.     

Fault Detection Techniques for Feeder Automation

Fault detection of the distribution systems is one of the key techniques for feeder automation. At all times, it is still very difficult for the exact detection of single phase to ground fault. First of all, the distinguishing rules of the faulted phase are presented when ground fault occurs in distribution systems. This paper analyzes the fault detection technique for single phase to ground in system with floating neutral point. Based on faulted phase's current, a method realizing ground fault protection is proposed and the algorithm model of action criterion is given out. The simulation results show that the method will be with very good selectivity to ground fault, and it can be used preferably in feeder automation. The detection method for short circuit fault is also introduced simply.     

A Novel Method Based on Support Vector Machine for Defect Identification

The traditional fault detection suffers from complicated process, low accurate ratio and off-line implement. The improved methods of defect recognition by artificial neural networks (ANN) can lead to the problems of overfit and bad generalization because of finite samples. With a view of data mining and technique parameters directly, the new approach using support vector machine classification algorithm after removing redundant parameters by rough set theory and eliminating noise of data to identify the defects is discussed. The results of a experiment show that unlike conventional and ANN recognition methods the new technique performs better than conventional evaluation ones with advantages of high efficiency, lower cost, easy implement on-line, excellent generalization and so on. The approach provides a novel technique means for nondestructive defect identification of various products.     

Application of Serial Ports Simulation in a Non-communication Fault Detection Device of Distribution Networks

This paper summarizes two kinds of fault detection techniques for distribution automation, that is with and without communication in fault detection, and then analyzes their merits and shortcomings. Moreover, according to the development tendency of distribution automation techniques, this paper presents an approach, through which the noncommunication FTU devices can detect transient fault voltage of distribution systems effectually. To detect transient fault voltage without standby batteries, the PIC Single Chip microcomputer with low power consumption and DSP chip with powerful data processing capabilities are adopted to form a dual CPU system. To realize the communication between the two CPUs, the general I/O port,s of the DSP chip are firstly used to simulate the UART communication of the serial ports and communicate with the PIC Single Chip microcomputer. The novel FTU devices based on this approach are tested in static and dynamic simulation experiments, the results are satisfied.     

Designing and Realization of Leak Current Fault Flatroof for Lauch Vihicle Controlling System

A visualized analysis system of leak current fault transmission graph is developed. Its functions, program structure and programming principle are described.The system is composed of fault diagnosing module and man machine exchanging module, which make the generation and analysis of leak current fault transmission graph for lauch vehicle controlling system simple and visualized. The system could automatically recognize the picture of transmission and analyze both qualitatively and quantitatively only by drawing it on the monitor by the mouse. Finally an example is given, where a satisfying result is acquired via drawing inputting method which is totally new and expanding-complementing the fault tree alglorithm.     

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 Fault Tolerance Technology in HC 1 Handhold Computer

A type of handhold computer that has been researched successfully is introduced as the application case and practical usage effect about fault tolerance technology in the machine. At the meantime, it can be as a usage for reference while the same type of machine brings in fault tolerance technology in order to increase its reliability. So, it has greater availability and extended character.     

深锥浓密机底流浓度预测与外部结构参数优化

针对困扰支持向量机(SVM)模型参数选择问题,结合遗传算法(GA),建立了深锥浓密机底流放砂浓度的GA-SVM预测模型,研究了不同结构参数状态下底流浓度的变化规律,进行了深锥浓密机的外部结构参数优化选择。以司家营铁矿为例,在最优底流放砂浓度为72%的条件下,经外部结构参数优化后的深锥浓密机锥高10 m、锥角为30°,系统稳定可靠、底流连续均匀,动力荷载较同类矿山降低约15%,压耙停机故障降低80%。     

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.     

Design of networking condition monitoring andfault diagnosis for wind turbine transmission system

In order to solve the incipient fault diagnose problem of the transmission system, a networking condition monitoring and failure diagnosis system based on B/S and C/S hybrid architecture for wind turbine transmission system is designed in the paper. Firstly, the paper analyzes the demands of condition monitoring and fault diagnosis system for wind turbine transmission system, and designs its overall framework and function modules. Then, combining with the data acquisition equipment, by the .NET and SQL Server platform, the paper designs condition monitoring and failure diagnosis system for wind turbine transmission system, which includes the functions of networking data acquisition, remote condition monitoring, signal analysis, fault diagnosis and database as well. The system has been successfully applied to a condition monitoring and fault diagnosis of wind turbine transmission system.     

Novel method for fault line selection in arc suppression coils system using transient energy

In order to overcome low sensitivity of the protection based on transient components when the faulty voltage passes zero, regarding arc suppression coill branch as a healthy feeder line, using the relation of its transient energy and all feeders of transient energy amounting to zero, this paper presents an improved fault line selection method in arc suppression coils system using transient energy. This method has no requirements of detection fault close angle and pre setting, has a good anti interference ability and adaptability to various faults occurred in the systems with arc suppression coils. Large amount of digital simulation results show that the proposed method is effective and reliable.     

THE NEW PHASE SELECTION SCHEMES ON USE OE FAULT COMPONENT

In accordance with the characteristic of digital relay and fault locatoin four methods of phase selection on fault component are presented in this paper.These methods are simple in principle, reliable in action, and immune from load flow,system oscillation.Hardly affected by fault location, source impedance and fault resistance, they can select fault phase reliably for any power system and fault type.As phase selection schemes, they can be used for perfect digital relay.     

Assembly fault rate analysis using grey relation and least squares support vector machines

To get the relationship between assembly fault rate and its attributes, least squares support vector machine (LSSVM)is introduced to quantitatively study assembly fault rate. Aiming at the drawbacks of assembly reliability evaluation method(AREM), the attributes of assembly-fault-rate-affecting 5M1E(Man, Machine, Material, Method, Measurement and Environment) factors obtained by AREM are improved, hence the LSSVM model with all attributes is established. To reduce the time of calculating the assembly fault rate and provide the priority for assembly reliability improvement, grey relation analysis is applied to extracting the main attributes, at the same time genetic algorithm(GA)is used for parameter optimization in LSSVM. The assembly fault rate analysis results show that the method using grey relation analysis and least square support vector machine is simpler and more accurate compared with other methods such as LSSVM model using all attributes and BP neural network using main attributes.     

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。     

Key technology of detecting hot heavy rail steel surface faults based on machine vision

Aiming at the low efficiency and precision of hot rail steel surface faults detecting at present,a suit of surface defect detection system of hot heavy rail based on the machine vision is put forward. Multi-CCD cameras are used to collect pictures. According to the geometric characteristics of the heavy rail and its defect characteristics of high-frequency region,six angle shot is used for heavy rail,and then various image processing technology are adopted in workstation. The system adopts improved Hough transform to get surface faults and Kohonen network to make a classification for the characteristics of low SVM training algorithm. The above key machine vision technology for detection of hot heavy rail surface defects greatly improves the speed and accuracy of testing and the detecting correct rate arrives over 85%.     

励磁功率单元主回路快速故障诊断策略

分析总结了发电机组励磁系统功率单元的故障类型和常见故障,通过Matlab仿真功率单元主回路故障类型,重点研究基于故障频谱分析的定量故障特征提取和故障分类,提出了一种快速针对功率单元主回路的故障诊断真值表法,最后通过实验平台验证故障类别,结果表明：该方法能够正确有效地诊断出功率单元主回路具体的故障晶闸管,为励磁系统功率单元故障诊断提供依据。     

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.     

A Study on Vibration Isolation for the Machine on Flexible Foundations

The problem of vibration isolation for the multi supporting machine installed on flexible foundations was studied by power flow and four end parameters methods.The general model of machine,isolator and flexible foundations was founded,and the transmission characteristic of the vibration system is analyzed.The expressions of power flow of the system with wave propagation effect being concerned was also presented.Finally,the effect of foundation flexibility and wave propagation on isolation was analyzed in detail.     

THE NEW METHOD-QL SYSTEM FOR MEASURING DYNAMIC ACCURACY OF THE DRIVETRAIN

The paper introduces a new method-QL system suggested for the first time by the author for measuring dynamic accuracy of gear cutting machine drivetrain. The system has many uses. It suits not only the measurement of mid-size machine tool but also the measurement of very slow speed, large ratio, large-size machine drivetrain     

采动影响下逆断层特征参数对断层活化的作用规律

笔者分析了采动影响下断层滑移的主要影响因素,以数值模拟为研究手段,利用FLAC 3D建立了逆断层简化模型,分析了不同断层倾角、不同落差及采掘工作面与断层不同距离的断层带附近煤岩体弹性能、断层面正应力与剪应力、断层滑移量的变化规律,从而揭示了采动影响下逆断层特征参数对断层活化的基本作用规律。研究结果表明：上盘或下盘开采,断层带附近煤岩体弹性能集中程度随工作面与断层距离的增大而降低,随断层倾角及落差的增加而增大,但下盘开采对断层带的能量集中程度较上盘高。下盘开采时剪应力较上盘显著增加,但正应力变化较小,易于断层活化。上盘或下盘开采,随工作面与断层距离的增加,断层滑移量减小。上盘开采,随断层倾角增大,断层滑移量增加;随断层落差增大,断层滑移量减小。下盘开采,随断层倾角增大,断层滑移量减小;随断层落差的增大,断层滑移量增加。