动车组故障预测与健康管理(PHM)体系架构研究思考

从我国动车组故障预测与健康管理(PHM)技术现状出发,利用需求、功能、逻辑和物理架构(RFLP)的概念指导PHM架构设计,从不同层级、业务的需求分解,到PHM系统对动车组各业务场景的核心功能,再到各环节逻辑架构,最终形成考虑当前数据传输、信息化现状的物理架构,以便最终工程化实施落地,形成适用于我国动车组的PHM体系架构。

Approximation Property of the Modified Elman Network

A new type of recurrent neural network is discussed, which provides the potential for modelling unknown nonlinear systems. The proposed network is a generalization of the network described by Elman, which has three layers including the input layer, the hidden layer and the output layer. The input layer is composed of two different groups of neurons, the group of external input neurons and the group of the internal context neurons. Since arbitrary connections can be allowed from the hidden layer to the context layer, the modified Elman network has more memory space to represent dynamic systems than the Elman network. In addition, it is proved that the proposed network with appropriate neurons in the context layer can approximate the trajectory of a given dynamical system for any fixed finite length of time. The dynamic backpropagation algorithm is used to estimate the weights of both the feedforward and feedback connections. The methods have been successfully applied to the modelling of nonlinear plants.

A Modelling Scheme for Flexible Robot Manipulators

Aim To propose a modelling method for flexible manipulators. Methods The improved algorithm and structure of the ANN (artificial neural networks) were used. All of the data used in the process of modelling came from experiments based on a very flexible link which was fixed on a FANUC Robot S-Model 300 in our lab.Results and Conclusion The theoretical analysis and experiment results showed that this modelling scheme is more suitable for flexible systems with characteristics of fast changing dynamics, and also it can be more accurate than others and is more convenient for real-time use.

Modelling and stability analysis of emergent behavior of scalable swarm system

In this paper we propose a two-layer emergent model for scalable swarm system. The first layer describes the indi-vidual flocking behavior to the local goal position (the center of minimal circumcircle decided by the neighbors in the positive visual set of individuals) resulting from the individual motion to one or two farthest neighbors in its positive visual set; the second layer describes the emergent aggregating swarm behavior resulting from the individual motion to its local goal position. The scale of the swarm will not be limited because only local individual information is used for modelling in the two-layer topology. We study the stability properties of the swarm emergent behavior based on Lyapunov stability theory. Simulations showed that the swarm system can converge to goal regions while maintaining cohesiveness.

Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.

Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks

An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.

Modeling and Optimization of Bandwidth Supply Performance for Cloud-Assisted Video Systems under Flash Crowd

The large-scale and sudden video content access such as flash crowds results in huge bandwidth demand,which severely influence user quality of experience and quality of service of video systems.In this paper,we firstly discuss the main reason of generation of flash crowds for video streaming services and analyze key factor for balance recovery between supply and demand of upload bandwidth.We construct two models:bandwidth supply capacity model of video systems and bandwidth demand model of users,which measures usage amount of bandwidth of the cloud.Based on the built models,we further employ a community-based cooperative caching strategy of video resources to promote supply capacity of upload bandwidth of video systems.Extensive tests show how the proposed cooperative caching strategy achieves much better performance results in comparison with original solution.

Dynamic modeling of a parafoil system considering flap deflection

In order to better study the dynamic characteristics and the control strategy of parafoil systems,considering the effect of flap deflection as the control mechanism and regarding the parafoil and the payload as a rigid body,a six degrees-of-freedom(DOF)dynamic model of a parafoil system including three DOF for translational motion and three DOF for rotational motion,is established according to the K rchhoff motion equation.Since the flexible winged paafoil system flying at low altitude is more susceptibleto winds,the motion characteristics of the parafoil system Wth and Wthout winds are simulated and analyzed.Furthermore,the ardropm test is used to further verify the model.The comparison results show that the simulation trajectory roughly overlaps with the actual flight track.The horzontnl velocity of the simulation model is in good accordance with the airdrop test,with a deviation less than0.5m/s,while its simulated vertical velocity fuctuates slightly under the infuence of the wind,and shows a similar trend to the ardrop test.It is concludedthat the established model can well describe the characteristics of the parafoil system.

MODEL AND PERFORMANCE ANALYSIS OF FMT SYSTEM AND ORTHOGONAL FILTERBANKS

An orthogonal multi-carrier modulation-Filtered Multi-Tone (FMT) modulation, is evaluated in this paper. The objective of this paper is to model the FMT system with polyphase fil- terbank network, design its synthesis/analysis orthogonal filterbanks and analyze their performance. Oversampled and critically sampled cases of FMT system are discussed in detail. Perfect Reconstruc- tion (PR) properties of M parallel orthogonal subchannels in the case of critically sampled is derived from filterbank polyphase decomposition. Diverse types of prototype filters which include Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) are designed and analyzed. Performance analysis of orthogonal filterbanks which are implemented by these prototype filters are proposed and compared respectively. Simulation results of FMT orthogonal filterbanks are presented. In the end, the application prospect of FMT is discussed.

Soft Sensor Model Derived from Wiener Model Structure: Modeling and Identification

The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimation accuracy of soft sensor models. Wiener model effectively describes dynamic and static characteristics of a system with the structure of dynamic and static submodels in cascade. We propose a soft sensor model derived from Wiener model structure, which is an extension of Wiener model. Dynamic and static relationships between secondary and primary variables are built respectively to describe the dynamic and static characteristics of system. The feasibility of this model is verified. Then the expression of discrete model is derived for soft sensor system. Conjugate gradient algorithm is applied to identify the dynamic and static model parameters alternately. Corresponding update method for soft sensor system is also given. Case studies confirm the effectiveness of the proposed model, alternate identification algorithm, and update method.

Reliability modeling of hydraulic system of drum shearer machine

The hydraulic system plays an important role in supplying power and its transition to other working parts of a coal shearer machine. In this paper, the reliability of the hydraulic system of a drum shearer was analyzed. A case study was done in the Tabas Coal Mine in Iran for failure data collection. The results of the statistical analysis show that the time between failures （TBF） data of this system followed the 3-parameters Weibull distribution. There is about a 54% chance that the hydraulic system of the drum shearer will not fail for the first 50 h of operation. The developed model shows that the reliability of the hydraulic system reduces to a zero value after approximately 1 650 hours of operation. The failure rate of this system decreases when time increases. Therefore, corrective maintenance （run-to-t^ailure） was selected as the best maintenance strategy for it.

Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance

The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously developed tools,including the norm-bounding technique for relaxing the disturbance-related constraint handling,the dynamic output feedback law,the notion of quadratic boundedness for specifying the closed-loop stability,and the ellipsoidal state estimation error bound for guaranteeing the recursive feasibility,are merged in the control design.Some previous approaches are shown to be the special cases.An example of continuous stirred tank reactor(CSTR) is given to show the effectiveness of the proposed approaches.

Multi-objective modeling and optimization for scheduling of cracking furnace systems

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

Dynamic Resonant Frequency Bands of Suspension System of Vehicles with Varying Speeds Based on Time⁃Frequency Spectrum

The dynamic responses of suspension system of a vehicle travelling at varying speeds are generally nonstationary random processes,and the non-stationary random analysis has become an important and complex problem in vehicle ride dynamics in the past few years.This paper proposes a new concept,called dynamic frequency domain(DFD),based on the fact that the human body holds different sensitivities to vibrations at different frequencies,and applies this concept to the dynamic assessment on non-stationary vehicles.The study mainly includes two parts,the first is the input numerical calculation of the front and the rear wheels,and the second is the dynamical response analysis of suspension system subjected to non-stationary random excitations.Precise time integration method is used to obtain the vertical acceleration of suspension barycenter and the pitching angular acceleration,both root mean square(RMS)values of which are illustrated in different accelerating cases.The results show that RMS values of non-stationary random excitations are functions of time and increase as the speed increases at the same time.The DFD of vertical acceleration is finally analyzed using time-frequency analysis technique,and the conclusion is obviously that the DFD has a trend to the low frequency region,which would be significant reference for active suspension design under complex driving conditions.

Modelling the upwelling off the east Hainan Island coast in summer 2010

A synoptic-scale upwelling event that developed off the east coast of the Hainan Island（EHIU） in the summer of 2010 is defi ned well via processing the Moderate Resolution Imaging Spectroradiometer（MODIS） sea surface temperature（SST） data. The Regional Ocean Modeling System（ROMS） with high spatial resolution has been used to investigate this upwelling event. By comparing the ROMS results against tide station data, Argo fl oat profi les and MODIS SST, it is confi rmed that the ROMS reproduces the EHIU well. The cooler-water core（CWC） distinguished by waters（27） 27.5℃ in the EHIU, which occurred in the east Qiongzhou Strait mouth area and was bounded by a high temperature gradient, was the focus of this paper. Vertical structure of the CWC suggests that interaction between the westward fl ow and the bathymetry slope played a signifi cant role in the formation of CWC. Numerical experiments indicated that the westward fl ow in the Qiongzhou Strait was the result of tidal rectifi cation over variable topography（Shi et al., 2002）, thus tides played a critical role on the development of the CWC. The negative wind stress curl that dominated the east Qiongzhou Strait mouth area suppressed the intensity of the CWC by 0.2–0.4℃. Further, nonlinear interaction between tidal currents and wind stress enhanced vertical mixing greatly, which would benefi t the development of the CWC.

Modeling Relative Humidity Effects on Power Electronic Performance

Variations in the behavior of power supplies caused electrical behavior dependence with environmental conditions. by environmental conditions require accurate characterization of the This paper introduces models to help predict relative humidity （Rtt） and other environmental factors influence on sensitive circuitry in power electronic systems. The resistivity and permittivity of an insulator have been modeled using different water contents i.e. RH, such model also included the mechanical properties of the design. An application example of a high power density, high voltage DC-DC converter is used to verify the results.

Modelling and Vibration of Gear Drive Systems Influenced by Real Face Width

Gear drives are one of the most common parts in many rotating machinery. If the gear drive runs under lower torque load, nonlinear effects like gear mesh interruption can occur and vibration is accompanied by impact motions of the gears, This paper presents an original method of the mathematical modelling of gear drive nonlinear vibrations by using the modal synthesis method with degrees of freedom number reduction. The model respects nonlinearities caused by gear mesh interruption, parametric gearing excitation caused by time-varying meshing stiffness and nonlinear contact forces acting between journals of the rolling-element bearings and the outer housing. The nonlinear model is then used for investigation of gear drive vibration, especially for constant gear mesh determination. The theoretical method is applied for investigating of test gear drive nonlinear vibration.

A Quarter Century of Work to Revolutionize Architecture, Engineering and Construction Enterprise Information Systems

More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.

Performance modeling of the adaptive optics system on the 2.16 m telescope

The adaptive optics system on the 2.16 m telescope is modeled and simulated using an ends-to-ends Monte Carlo method in this paper.Under the optimized parameters,the Strehl ratio can be increased from about 0.02 to more than 0.2 in the J,H and K bands with a classical adaptive optics system.Based on the simulation results,the practical system design is also considered and discussed.

Analysis and prediction of loudspeaker large-signal symptoms

Nonlinear lumped-parameter force factor Bl(x), stiffness Kms(x) and inductance Le(x) of electrodynamic loudspeakers change frequency responses and generate some nonlinear effects for large stimulus: harmonic and intermodulation distortion, DC component in diaphragm displacement, instability of vibration and jumping effects. By modeling the nonlinear system under large-signal conditions, relationship between the nonlinear parameters and large-signal behavior can be revealed and help to provide guidance to diagnose loudspeakers. Agreement between the measured and predicted responses of a real loudspeaker validates the modeling and enables new methods for loudspeaker diagnosis.