基于模数混合FPGA的高频逆变器的研究与设计

通过对高频逆变器前端DC-DC的升压PWM调制和后端DC-AC的SPWM调制的研究,提出了利用FPGA结合DDS技术来实现逆变器的控制电路集成化,并采用模数混合信号F P G A集成了闭环控制的反馈控制电路,从而简化设计,提高系统的稳定和可靠性。本设计中,重点在于外围功率电路部分前端升压的高频变压器的设计以及输出端L C滤波电感与电容的选取,需要综合考虑频率特性、功率因数来选取合适的材料和数值。

城市监控报警联网系统案例解析

分析了平安城市建设中两个典型的视频监控联网系统,即模拟接入方式的模数混合型和数字接入方式的全数字型,对比分析了两者的优缺点。在此基础上。提出了融合两者优势的模拟数字混合型模式。

Gaussian mixture models for clustering and classifying traffic flow in real-time for traffic operation and management

Based on Gaussian mixture models（GMM）, speed, flow and occupancy are used together in the cluster analysis of traffic flow data. Compared with other clustering and sorting techniques, as a structural model, the GMM is suitable for various kinds of traffic flow parameters. Gap statistics and domain knowledge of traffic flow are used to determine a proper number of clusters. The expectation-maximization （E-M） algorithm is used to estimate parameters of the GMM model. The clustered traffic flow pattems are then analyzed statistically and utilized for designing maximum likelihood classifiers for grouping real-time traffic flow data when new observations become available. Clustering analysis and pattern recognition can also be used to cluster and classify dynamic traffic flow patterns for freeway on-ramp and off-ramp weaving sections as well as for other facilities or things involving the concept of level of service, such as airports, parking lots, intersections, interrupted-flow pedestrian facilities, etc.

采用FPGA-AFS600可调式新型逆变器设计

模数混合型FPGA-AFS600作为主控芯片实现高频逆变器的设计,硬件上AFS600内部的模拟模块、软件上Libero IDE的模拟系统软核更是为电压反馈的闭环控制提供了极大的支持;外围强电部分须注意综合考虑频率特性,其升压高频变压器的设计、输出端LC滤波电感、电容的选取都是重点; SPWM中的"H"全桥逆变电路的悬浮电压也是一个需要重视的环节。

Site selection of emergency material warehouse under fuzzy environment

The objective of this work was to determine the location of emergency material warehouses. For the site selection problem of emergency material warehouses, the triangular fuzzy numbers are respectively demand of the demand node, the distance between the warehouse and demand node and the cost of the warehouse, a bi-objective programming model was established with minimum total cost of the system and minimum distance between the selected emergency material warehouses and the demand node. Using the theories of fuzzy numbers, the fuzzy programming model was transformed into a determinate bi-objective mixed integer programming model and a heuristic algorithm for this model was designed. Then, the algorithm was proven to be feasible and effective through a numerical example. Analysis results show that the location of emergency material warehouse depends heavily on the values of degree a and weight wl. Accurate information of a certain emergency activity should be collected before making the decision.

Characterization on the hydrodynamics of a covering-plate Rushton impeller

A modified Rushton impeller with two circular covering-plates mounted on the upper and lower sides of the blades was designed.There are gaps between the plates and the blades.The turbulent hydrodynamics was analyzed by the computational fluid dynamics(CFD) method.Firstly,the reliability of the numerical model and simulation method was verified by comparing with the experimental results from literature.Subsequently,the power consumption,flow pattern,mean velocity and mixing time of the covering-plate Rushton impeller(RT-C) were studied and compared with the standard Rushton impeller(RT) operated under the same conditions.Results show that the power consumption can be decreased about 18%.Compared with the almost unchanged flow field in the lower stirred tank,the mean velocity was increased at the upper half of the stirred tank.And in the impeller region,the mean axial and radial velocities were increased,the mean tangential velocity was decreased.In addition,the average mixing time of RT-C was shortened about 4.14% than the counterpart of RT.The conclusions obtained here indicated that RT-C has a more effective mixing performance and it can be used as an alternative of RT in the process industries.

Optimization of Wind-Marine Hybrid Power System Configuration Based on Genetic Algorithm

Multi-energy power systems can use energy generated from various sources to improve power generation reliability.This paper presents a cost-power generation model of a wind-tide-wave energy hybrid power system for use on a remote island,where the configuration is optimized using a genetic algorithm.A mixed integer programming model is used and a novel object function,including cost and power generation,is proposed to solve the boundary problem caused by existence of two goals.Using this model,the final optimized result is found to have a good fit with local resources.

Application of hybrid robust three-axis attitude control approach to overactuated spacecraft——A quaternion based model

A novel hybrid robust three-axis attitude control approach, namely HRTAC, is considered along with the well-known developments in the area of space systems, since there is a consensus among the related experts that the new insights may be taken into account as decision points to outperform the available materials. It is to note that the traditional control approaches may generally be upgraded, as long as a number of modifications are made with respect to state-of-the-art, in order to propose high-precision outcomes. Regarding the investigated issues, the robust sliding mode finite-time control approach is first designed to handle three-axis angular rates in the inner control loop, which consists of the pulse width pulse frequency modulations in line with the control allocation scheme and the system dynamics. The main subject to employ these modulations that is realizing in association with the control allocation scheme is to be able to handle a class of overactuated systems, in particular. The proportional derivative based linear quadratic regulator approach is then designed to handle three-axis rotational angles in the outer control loop, which consists of the system kinematics that is correspondingly concentrated to deal with the quaternion based model. The utilization of the linear and its nonlinear terms, simultaneously, are taken into real consideration as the research motivation, while the performance results are of the significance as the improved version in comparison with the recent investigated outcomes. Subsequently, there is a stability analysis to verify and guarantee the closed loop system performance in coping with the whole of nominal referenced commands. At the end, the effectiveness of the approach considered here is highlighted in line with a number of potential recent benchmarks.

A risk-based methodology for the optimal placement of hazardous gas detectors

Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.

Ocean Mixing with Lead-Dependent Subgrid Scale Brine Rejection Parameterization in a Climate Model

Sea ice thickness is highly spatially variable and can cause uneven ocean heat and salt flux on subgrid scales in climate models.Previous studies have demonstrated improvements in ocean mixing simulation using parameterization schemes that distribute brine rejection directly in the upper ocean mixed layer.In this study,idealized ocean model experiments were conducted to examine modeled ocean mixing errors as a function of the lead fraction in a climate model grid.When the lead is resolved by the grid,the added salt at the sea surface will sink to the base of the mixed layer and then spread horizontally.When averaged at a climate-model grid size,this vertical distribution of added salt is lead-fraction dependent.When the lead is unresolved,the model errors were systematic leading to greater surface salinity and deeper mixed-layer depth(MLD).An empirical function was developed to revise the added-salt-related parameter n from being fixed to lead-fraction dependent.Application of this new scheme in a climate model showed significant improvement in modeled wintertime salinity and MLD as compared to series of CTD data sets in 1997/1998 and 2006/2007.The results showed the most evident improvement in modeled MLD in the Arctic Basin,similar to that using a fixed n=5,as recommended by the previous Arctic regional model study,in which the parameter n obtained is close to 5 due to the small lead fraction in the Arctic Basin in winter.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network(RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term schedul-ing of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants.

The Alternative Mathematical Models of the World

The biggest insufficiency of the present mathematics is that it consists, in fact, of the eclectic mixture of two different models. In the first model, the world is taken as infinity and what is chosen as an element here is the unit. Everything is measured by the multiples of the unit. According to the second model, this world is in unity and its mathematical manifestation is the unit. The world is between zero and one. Everything here is measured by fraction The simplified variants of the mathematical model of the world paves the way for the comparative analysis of its alternative philosophical interpretations.

Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles

An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.

Design of Multi-attribute Knowledge Base Based on Hybrid Knowledge Representation

Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application; integrate the heterogeneous knowledge, such as model, symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.

A Novel Scheduling Strategy for Crude Oil Blending

For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.

Modeling and optimization methods of integrated production planning for steel plate mill with flexible customization

With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.

Mathematical model of absorption and hybrid heat pump

Recovering waste heat from industrial processes is bene ficial in order to reduce the primary energy demands and heat pumps can be used to this purpose.Absorption heat pumps are energy-saving and environment-friendly because use working fluids that do not cause ozone depletion and can reduce the global warming emissions.The hybrid heat pump processes combine the conventional vapor-compression and the absorption heat pump cycles.Studies about the simulations and modeling of hybrid heat pumps are few in literature.In this research a mathematical model for single effect absorption and hybrid heat pump is carried out with Chem Cad? 6.0.1.LiBr–H_2O is used as working fluid while electrolytic NRTL and electrolytes latent heat are used as thermodynamic model due to the better results.Binary parameters of activity coef ficients are regressed from experimental vapor pressure data while default constants are used for the solubility expressions.A design of heat pumps is developed and a new modeling of generator is analyzed.The coef ficient of performance of absorption heat pump and hybrid heat pump is equal to 0.7 and 0.83 respectively.For absorption heat pump a sensitivity analysis is carried out to evaluate the effect of temperature and pressure generator,the concentration of Li–Br solution on coef ficient of performance,cooling capacity and working fluid temperature.For hybrid heat pump,the different coef ficients of performance,the primary energy ratio,the generator heat,and the compressor power are analyzed for different values of compressor proportion.Results show that comparing the two systems the hybrid pump allows to save more primary energy,costs and carbon dioxide emissions with respect to absorption heat pump with the increasing of compressor proportion parameter.Future researches should focus on the construction of this heat pumps integrated in chemical processes as a biogas plant or trigeneration systems.

Behavior of Reinforced Concrete Columns under Combined Axial Load and Bending in Accordance with a Nonlinear Numerical Model

A nonlinear numerical model was developed to analyze reinforced concrete columns under combined axial load and bending up to failure. Results of reinforced concrete columns under eccentric compression tested to failure are presented and compared to results from a numerical nonlinear model. The tests involved 10 columns with cross-section of 250 mm × 120 mm, geometrical reinforcement ratio of 1.57% and concrete with compression strength around 40 MPa, with 3,000 mm in length. The main variable was the load eccentricity in the direction of the smaller dimension of cross-section. Experimental results of ultimate load and of the evolution of transverse displacements and concrete strains are compared with the numerical results. The estimated results obtained by the numerical model are close to the experimental ones, being suitable for use in verification of elements under combined axial load and bending.

Modeling of U-shaped Ba0.5Sr0.5Co0.8Fe0.2O3-δhollow-fiber membrane for oxygen permeation

A mathematic model is developed for the perovskite-type mixed ionic-electronic conducting(MIEC) membrane,which makes it possible to simulate the process of oxygen separation in the U-shaped Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_3-δhollow-fiber membrane. The model correlates the oxygen permeation flux to the measurable variables. The trends of calculated results for purge operation coincide well with the experimental data, therefore the model is considerable for flux prediction under vacuum operation. Higher oxygen separation efficiency can be achieved with vacuum operation than purge operation. Parameter study with vacuum operation reveals that oxygen permeation flux increases with higher vacuum levels, and vacuum pressure of around 1.013 × 10~3 Pa is the optimal.Also, vacuum operation on the lumen side is much more efficient to achieve higher oxygen permeation flux compared with compression mode on the shell side.

A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems

To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.