基于PLC技术的矿井提升机电控系统可靠性优化

电控系统作为提升机运行的关键基础,确保其运行的有效高质意义重大。以此为着手点,针对基于PLC技术的矿井提升机电控系统可靠性优化开展探究。在分析优化方案的基础上,对系统的安装和调试做出针对性分析,希望能为其他矿井相似工程的开展提供借鉴与参考。

煤矿主竖井提升及装载系统优化设计

针对任楼煤矿主竖井提升及装载系统效率提升的问题,结合现代PLC控制理论,根据对提升系统电控程序进行S形加减速优化及装载系统电控优化,实现了主竖井及装载系统的效率提升。该改进通过现场分析计算来优化运行流程,从修改控制程序及参数出发,在不增加任何设备和投资的情况下,利用科学技术使提升发挥了最大效率,经试验系统运行检测准确,处理方法合理,使主井自动化提升系统效率最大化,运行更安全可靠。

船用柴油-天然气双燃料发动机活塞熔顶分析与改进

在船用柴油-天然气双燃料发动机的开发过程中,铸铝活塞顶面出现了熔顶现象。经过燃烧分析,发现该问题的主要原因在于柴油喷射控制策略导致的爆震裕度不足,以及对试验边界条件的变化过于敏感,造成了缸内温度和活塞顶面温度的异常升高,最终引起活塞的熔顶。通过优化电控标定、改进活塞内冷油道设计以及进行活塞顶面陶瓷化处理,提升了爆震裕度,活塞顶面温度明显降低,问题得到了有效解决。

VIBRATION CONTROL OF A SPACE TRUSS STRUCTURE WITH A PIEZOELECTRIC ACTIVE MEMBER

Active vibration control is an effective way of increasing robustness of the design to meet the stringent accuracy requirements for space structures. This paper presents the results of active damping realized by a piezoelectric active member to control the vibration of a four-bay four-longern aluminum truss structure with cantilever boundary. The active member, which utilizes a piezoelectric actuating unit and an integrated load cell, is designed for vibration control of the space truss structures. Active damping control is realized using direct velocity feedback around the active member. The placement of the active member as one of the most important factor of affecting the control system performance, is also investigated by modal dissipation energy ratio as indicator. The active damping effectiveness is evaluated by comparing the closed-loop response with the open loop response.

多制程工艺共线生产在“熄灯工厂”中的应用

随着自动化在生产现场中的占比逐步提升,“熄灯工厂”的概念已不断被制造业提及。产品加工制造对生产线的要求越来越高,传统生产输送线已不能满足现今产品的日益推陈出新。完全摒弃原有生产线,架设新型生产线成本高,投资大,回收时间长。而采用沿用现有设备,在原生产线的基础上进行改造升级,以适应新产品的加工要求。

The control and optimization of macro/micro-structure of ion conductive membranes for energy conversion and storage

Ion conductive membranes(ICMs)are frequently used as separators for energy conversion and storage technologies of fuel cells,flow battery,and hydrogen pump,because of their good ion-selective conduction and low electronic conductivity.Firstly,this feature article reviews the recent studies on the development of new nonfluorinated ICMs with low cost and their macro/micro-structure control.In general,these new nonfluorinated ICMs have lower conductivity than commercial perfluorinated ones,due to their poor ion transport channels.Increasing ion exchange capacity(IEC)would create more continuous hydrophilic channels,thus enhancing the conductivity.However,high IEC also expands the overall hydrophilic domains,weakens the interaction between polymer chains,enhances the mobility of polymer chains,and eventually induces larger swelling.The micro-scale expansion and macro-scale swelling of the ICMs with high IEC could be controlled by limiting the mobility of polymer chains.Based on this strategy,some ef ficient techniques have been developed,including covalent crosslinking,semi-interpenatrating polymer network,and blending.Secondly,this review introduces the optimization of macro/microstructure of both perfluorinated and nonfluorinated ICMs to improve the performance.Macro-scale multilayer composite is an ef ficient way to enhance the mechanical strength and the dimensional stability of the ICMs,and could also decrease the content of per fluorosulfonic acid resin in the membrane,thereby reducing the cost of the perfluorinated ICMs.Long side chain,multiple functionalization,small molecule inducing micro-phase separation,electrospun nano fiber,and organic–inorganic hybrid could construct more ef ficient ion transport channels,improving the ion conductivity of ICMs.

Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)

Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.

Sensing Time Optimization in Energy-Harvesting Cognitive Radio with Interference Rate Control

In this paper,an energy-harvesting cognitive radio(CR) is considered,which allows the transmitter of the secondary user(SU) to harvest the primary signal energy from the transmitter of the primary user(PU) when the presence of the PU is detected.Then the harvested energy is converted into the electrical power to supply the transmission of the SU at the detected absence of the PU.By adopting the periodic spectrum sensing,the average total transmission rate of the SU is maximized through optimizing the sensing time,subject to the constraints of the probabilities of false alarm and detection,the harvested energy and the interference rate control.The simulation results show that there deed exists an optimal sensing time that maximizes the transmission rate,and the maximum transmission rate of the energy-harvesting CR can better approach to that of the traditional CR with the increasing of the detection probability.

Optimal Configuration for Distributed Generations in Micro-grid System Considering Diesel as the Main Control Source

This paper proposes an optimal configuration of the distributed hybrid renewable generations based on the stand-alone micro-grid system, considering the diesel as the main control source. Due to the natural sources and load of user changes randomly and the non-tinearity of the power output by renewable generations, an intelligent optimization method based on the improvement of the genetic algorithm and the control strategy are discussed. The instance analysis is compared with the optimization result of the hybrid system based on HOMER （hybrid optimization of multiple energy resources） and GA （genetic algorithm） method on Matlab software. The simulation result of the optimal configuration showed the new hybrid renewable system and would improve the power supply situation which decreased the cost of energy greatly compared with the conventional form of power supply system which was operated only by diesel. The conclusion of the comparing result between HOMER and GA method shows the advantages of the strategy for the diesel as main control sources.

Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm

Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algorithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance.

Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP.For damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was proposed.The performance of the suggested controller was tested using a 16-machine 5-area network.The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions.The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP.Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.

Optimization control strategy for single-phase permanent magnet generator based on voltage ripple

A method of feedforward compensation for electromotive force(EMF) in the single-phase permanent magnet linear generation system and a research in the performance of the single-phase PMLG system are presented.A general mathematical model for the single-phase permanet magnet linear generator(PMLG) system is established and the current loop,voltage loop and the feedforward control are studied based on it for the control system.Then this paper analyses the transfer function of the power system,optimizes current loop and voltage loop parameters by engineering algorithm,and calculates the optimal control parameters.An EMF feedforward compensation method is developed to optimize the control system which improves dynamic performance of the power system but does not affect the steady-state performance.The result of this research verifies the correctness and rationality of the design for the control system.

Genetic-fuzzy HEV control strategy based on driving cycle recognition

A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.

Research on Intelligent Positioning Bed of Body Gamma Knife Based on Sensor

This paper introduces a design to improve the radiotherapy accuracy of gamma knife. In this design, sensor is used to collect respiratory parameters and tumor displacement (caused by human respiration) model is established through optimization modeling. At the same time, data are transferred to single chip microcomputer (SCM) system by pressure sensor and then stepping motor is controlled by SCM. Finally, the intelligent positioning bed is under the control of stepping motor. As a result, the intelligent positioning bed can move reverse to respiratory law. The experimental results showed that this method can reduce the influence of respiration on tumor displacement, improving the accuracy of intelligent positioning bed with simple circuit and low cost at the same time.

Evaluation of an Agent Based Monitoring and Brokerage System for Neighbourhood Electricity Usage Optimization

The current paper presents the evaluation results of a monitoring system, developed within NOBEL （Neighbourhood Oriented Brokerage Electricity） project. NOBEL is an EU funded project of the 7th Framework Programme that developed a pilot monitoring and energy brokerage system, within a local electricity network, aiming to the optimization of energy usage by reducing consumption and maximizing RES （renewable energy sources） usage on neighbourhood level. A holistic evaluation methodology was followed encompassing all aspects, focusing on the enhancement of energy efficiency due to NOBEL system. In specific, indicators related to energy and monetary impacts were analysed and finally assessed. The system was tested through pilot trials in Alginet, a village in Spain. NOBEL managed to achieve total energy savings of 12%, contributing also to respective emissions reduction and to economic benefits for brokerage platform participants. Analytic results and conclusions are presented in the current manuscript that will assess the project＇s system overall performance.

Optimal design of coordination control strategy for distributed generation system

This paper presents a novel design procedure for optimizing the power distribution strategy in distributed generation system. A coordinating controller, responsible to distribute the total load power request among multiple DG units, is suggested based on the conception of hierarchical control structure in the dynamic system. The optimal control problem was formulated as a nonlinear optimization problem subject to set of constraints. The resulting problem was solved using the Kuhn-Tucker method. Computer simulation results demonstrate that the proposed method can provide better efficiency in terms of reducing total costs compared to existing methods. In addition, the proposed optimal load distribution strategy can be easily implemented in real-time thanks to the simplicity of closed-form solutions.

A Parameter Determination Method of Distribution Voltage Regulators Considering Tap Change and Voltage Profile

This paper proposes a parameter determination method of distribution voltage regulators load ratio control transformers （LRT） and step voltage regulators （SVR） considering the tap change and voltage profile. The method takes two procedures in order to simplify the optimization problem and to reduce calculation time. One is to simultaneously determine the control parameters of LRT and SVR minimizing voltage violations and voltage variations. The algorithm is based on particle swarm optimization （PSO）, which is one of non-linear optimization methods by using a concept of swarm intelligence. Another is to determine the dead-band width of LRT and SVR on the basis of bi-evaluation of tap change and voltage margin. The concept of a Pareto optimal solution is used for the decision of the best dead-band width. As the results of numerical simulations using distribution network model, the validity of the proposed method has been affirmed.