Earticle

In this paper, fiber grating technology is used for accurately measure stresses, temperature and displacement. The paper introduces the basic principles of FBG technology and the wavelength demodulation method of FBG sensors, and put fiber grating technology into practical engineering projects. The paper design a optical fiber grating real-time automation monitoring system to distributed measure stress, temperature and displacement in geological disaster body, to provide effective technical supports for geological disaster prevention and mitigation.

In this paper, a practical multi-packet reception technique is proposed for wireless ad hoc networks in which concurrent transmissions generally occur. In practical systems, these transmissions are performed without pre-compensation of time and frequency offsets before transmission due to decentralized nature of ad hoc networks. We first derive an optimal asynchronous joint detection (OAJD) technique for concurrent transmissions by considering time and frequency offsets among the multiple received packets. Furthermore, we propose a suboptimal asynchronous joint detection (SAJD) technique with log-likelihood ratio by utilizing the fact that practical pulse-shaping filters including raised cosine filter fall down beyond the number of symbol times. The proposed SAJD yields better performance than that of the successive interference cancellation (SIC) technique which successively decodes a packet with the strongest signal and cancels a decoded packet from multiple received packets.

Localization of sensor nodes is a fundamental and a key technology in wireless sensor networks, it has been widely studied by many universities and research institutions in recent years and many localization algorithms have been put forward by scholars from diverse aspects. A new localization algorithm, which is based on the LDV-Hop algorithm, is proposed in this paper. Firstly, to reduce the localization error we modify the average one-hop distance between anchor nodes, and the average one-hop distance used for each unknown node's location is also modified through weighting the received average one-hop distance from anchor nodes. Then, to solve the problem of low localization coverage which is the main disadvantage of LDV-Hop localization algorithm, we regard regular node with newly estimated location as anchor node and utilize believable factor threshold to restrain the error accumulation brought by this method.

This paper presents a method that quickly search for sweet spot of array antenna, and keep it for fast speed transmission in millimeter wave. The proposed method is the Modified Genetic Algorithm (MGA) and Fuzzy Logic system. The MGA is used to find the approximate range as a pre-processing function. And the fuzzy logic system is used to find the exact sweet spot. We can transfer and receive a large data in millimeter wave bandwidth. Because antenna signal accounts for a few bits, influence on communication performance is little. MGA operators are used one-point crossover, rank-based selection, bit string mutation, elitism and 16bit split gene. In the fuzzy logic system, Rule base inference is used the max-min inference procedure. Defuzzification is used the center of gravity computation. The efficiency of the proposed method is verified by means of simulations.

Level control valve of water storage tank is installed in the outlet of tank, which control the water level of water storage tank by adjusting the water emissions, which make great significance for the safe operation of the super (super) criticality thermal power unit boiler . Complete the simulation analysis of internal flow field by the method of numerical simulation ,in order to achieve structure improvements of level control valve of water storage tank, that make level control valve of water storage tank better meet the work requirements. Establish flow channel model and mesh models of level control valve of water storage tank in various stages of the open process. Make three dimensional viscous numerical simulation of the internal complex flow field by the computational fluid dynamics software of ANSYS CFX. The error between the simulation values of the flow coefficient and the theoretical values , trial values is less than 5% ,which verifies the correctness of the simulation results . Get pressure contour , velocity streamline diagrams and outlet mass flow of level control valve of water storage tank in various stages of the open process. According to the pressure contours and velocity streamline diagrams, make detailed analysis of the flow field of level control valve of water storage tank. According to the dates of outlet mass flow, fit the flow characteristic curve of level control valve of water storage tank. Provide a theoretical basis for the structural design of level control valve of water storage tank.

This paper addresses the problem of the autonomous vehicle storage and retrieval system (AVS/RS) scheduling optimization. AVS/RS relies on rail guide vehicle (RGV) to provide horizontal movement within a tier and uses lifts to provide vertical movement between tiers. Firstly, the process of RGVs’ compound operation is analyzed, and the corresponding mathematical model is established. Then, an improved artificial fish swarm algorithm (IAFSA) is proposed to solve the model. According to the characteristics of the storage and retrieval operation in the system, an encoding and decoding method is designed, which contains RGV task allocation and elevator selection information. The tabu list and the optimal strategy are introduced into this algorithm, coupled with memory action and communication action to avoid the algorithm to trap in local optimal solution. Meanwhile, the adaptive step and visual are used to increase the late convergence of this algorithm. Finally, simulations based on the concrete living example of AVS/RS in a provincial verification center are given.The results obtained by the proposed algorithm are compared with another two optimization algorithm. Analysis shows that the proposed algorithm has the characteristics of fast convergence and the best solution, so as to improve the practicality and robustness of the algorithm.

This paper intends to design a high-efficient grid connected three-phase three-level T-type photovoltaic inverter system which is operated with conjunction with grid. Different from the two-level topology mainly used previous, switch elements are increased by 6 pieces, it has the advantages such as the efficiency of the inverter, less stress in the switching elements, and less harmonic component in the output current. This paper will suggest the boost convert always supplying constant DC voltage for a three-phase three-level T-type photovoltaic inverter, and also presents the stability and excellence of the 3 level boost converter through experiments. Also, it offers the stable and high-efficient MPPT algorism and through solar irradiation change experiment and MPPT efficiency assessment, the excellence and efficacy of three-level T-type inverter was verified from experiments.

In this paper, a novel approach of intelligent vehicle to interact and cooperate with other human driving vehicles is proposed at the freeway entrance ramp scenario. The system consists of a Safety Alert Module and Vehicle Control Module. The Safety Alert System module includes intention estimation and conflict judgment. A two dimension Hidden Markov Model (2DHMM) is used to estimate social vehicle’s driving intention in the intention estimation module. Then the conflict judgment module predicts the potential conflicts between the intelligent vehicle and social vehicle. Moreover, the hybrid state system (HSS) is introduced to control the intelligent vehicle while considering its decision making, states and dynamics. Co-simulation using PreScan and Simulink is conducted. The experiment results show that the intelligent vehicle performs well with a commendable social behavior in the freeway entrance ramp.

Based on the analysis of the defect of traditional model, this paper proposes a new control chart pattern recognition model, which includes Wavelet Analysis (WA), Principal Component Analysis (PCA), Particle Swarm Optimization (PSO) and Support Vector Machine (SVM). WA is good to eliminate noise control chart anomaly pattern recognition of the adverse effect. PCA eliminates the redundant information of data between SVM and reduces the input dimension and computational complexity. PSO algorithm optimizes the parameters of SVM and the establishment of the optimal control chart anomaly pattern classifier can solve the problem optimal parameters of SVM. The simulation results show that the model is feasible, the results are reliable. This algorithm improves the control chart abnormal state average recognition accuracy and be used in the machining process real-time monitoring.

In this paper, we propose the analytical approach for burst transmission (BT) adaptive decode-and-forward (ADF) relaying schemes consisting of burst transmission over quasi-static Rayleigh fading channels. At first, we focus on the error-event at relay nodes for symbol burst transmission, whereas previous researches considered one data symbol transmission so that they showed the best performance bounds. By considering symbol burst for ADF relay systems, we derive an exact outage probability expression which can be the performance of practical systems. Furthermore, the average outage probability is derived in approximated closed-form upper bound for an arbitrary link SNR. The derived analytical approach is verified based on the number of relays and burst symbols. Its accuracy is confirmed by comparison with simulation results.

The fuzzy immune PD controller is designed in view of the nonlinear and model uncertainty characteristics of the two-wheeled and self-balancing robot, and the simulation study is carried out. The simulation results show that the designed control system has the advantages of small overshoot amount, short adjustment time and strong anti-jamming capability compared with the conventional fuzzy PD controller. It is suitable for the balance of the robot control system whose mathematical model is difficult to determine and when the parameter changes.

In this paper we have considered the problem of outdoor mobile robot navigation using dead reckoning (DR) system and single GPS receiver. DR is a very simple and practical positioning technique. It is used in various positioning and navigation applications, especially for the mobile robot. DR can provide short term precise navigation information. But its errors will generally accumulate as the mobile robot continues to travel, and the calculated position of the mobile robot will become less and less accurate. For outdoor navigation application, GPS exhibit lots of advantages. It can provide real time and relatively accurate position data in spite of bad weather or other negative factors. But the big errors of civilian used single GPS receiver prevent it from applying to navigation for mobile robot alone. Differential GPS (DGPS) can be used to achieve an error of less than one meter but the costs are prohibitive in terms of commercializing it into the mass market. In this study, a cheap single GPS receiver cooperated with a DR system was used for the navigation system of a outdoors mobile robot in which a new GPS/DR data fusion method was utilized. This proposed fusion algorithm was based on the characteristics of the chosen single GPS receiver. The presented fusion algorithm does not bring much calculation burden and can provide accurate and robust navigation information for the mobile robot by adaptively switching between GPS/DR and DR when GPS lost the satellite signals. Simulation and experiment were performed to validate the effectiveness of the proposed fusion method and the good results showed its potential for outdoors mobile robot navigation.

The Radio Frequency Identification (RFID) system is a newemerging technology used to identify a tag attached to an object. To make RFID systems practical, the cost of RFIDtags is very important. Further, an interrogator should be able to identify thenumber of tags in the reading range in a short time. The most important technical issue in radio frequency identification (RFID) is to correctly and quickly recognize the number of tag IDs in the reader’s communication range. Unlike the probabilistic RFID tag identification schemes, a query tree(QT)-based protocol guarantees the identification of all the tags, where the distribution of tag IDs is assumed to be uniform. In this paper, we proposed an extended M-ary QT protocol, which effectively reduces unnecessary query-response cycles by using a non-sequential m-bit recognition method. The simulation results show that the proposed scheme significantly outperforms M-ary QT schemes in terms of identification time, efficiency and communications overhead.

RFID (Radio Frequency Identification) has played great important role in tracing and tracking the goods in supply chain management (SCM, where control and automation are very important). The application of RFID technology is able to record the moving path of different objects when they carrying the tags and readers. Thus, large number of information and knowledge are generated when the objects moved from one location to another. Such information and knowledge could be used for decision making such as automation and control. Traditional database does not consider the relationship of different elements of the RFID attributes. This paper introduces an algorithm to discover the frequent moving path of the RFID-equipped objects using graphical mining approaches. A set of experiments are carried out to evaluate the algorithm by using real-life data from a warehouse. It is observed that with the increasing of k , more information will be shown in the graph and the moving path could be discovered according to the weight of the edge.

According to the characteristics of cage wind turbines’ dynamic characteristics which change following the wind speed changes, the dynamic mathematical models of cage wind turbines major subsystems have been established, including the aerodynamic subsystem model, drive train subsystem model and generator subsystem model. Then these nonlinear dynamic models with time-varying parameters have been integrated and linearized to obtain the whole linear time-varying parameters dynamic mathematical model. To take the 2MW cage wind turbines wind turbine as example, the proposed model is validated by the study on the dynamic characteristics of cage wind turbines with wind speed variation , and the results show that the proposed model could provide a theoretical support for optimal control of the cage wind turbines.

In order to improve the performance of Support Vector Machine (SVM) classifier for imbalanced data, this paper proposes dynamic cost-sensitive SVM classifier based on chaos particle swarm optimization (CPDC_SVM). Firstly, this paper introduces dynamic cost-sensitive thought to SVM classifier, and gives the method for structuring dynamic cost and cost-sensitive SVM model. Secondly, we propose the evaluation methodology performance for classifier, and adopts decimal base to code the particles. At last, chaos thought is introduced in particle swarm optimization algorithm, and the Algorithm of the dynamic cost-sensitive SVM classifier is given, which improves convergent speed and accuracy of particle swarm optimization, and can optimize dynamic cost-sensitive SVM well, so CPDC_SVM adds effectively the convergence speed and accuracy for the particle swarm optimization algorithm. Experimental results show CPDC_SVM has higher precision than traditional SVM classifier, and dynamic cost and chaos particle swarm optimization can improve the performance for classifier.

For the Buck-fed DC motor system with parameter uncertainties and external disturbances, an adaptive robust controller is proposed based on dynamic surface control and slide mode control method. The derived adaptive robust control guarantees the closed-loop errors system is uniform ultimately bounded, and the parameters update laws are designed based on the uncertainty equivalence principle. The theoretical analysis and simulation results all reveal that the developed adaptive nonlinear robust controller is not sensitive to uncertainties of system, and owns simpler configuration and more accurate tracking performance than that of conventional backstepping control or PID control method.

Grid-connected solar micro-inverter is a highly nonlinear and time-varying system, so it is difficult to achieve good control effect using traditional PI controller. In this paper, small signal analysis model of micro-inverter is established, grid-connected current control strategy composed of fuzzy PI controller and grid voltage feed-forward is put forward, and the initial parameters of PI controller is optimized using the genetic algorithm. Simulation results show that the control strategy has the virtues of good robustness, small dynamic deviation, and could reduce the harmonic content of grid-connected current.

Content-Centric Network (CCN) is next generation internet communication technology to provide existing internet communication paradigm as content based communication for efficient use various information in the Internet. Therefore, unlike existing internet communication technology, which focus on host based communication process, all of resource is defined as contents in CCN. Moreover it focus on purpose of communication for using information. CCN communicate with between routers through broadcast flooding method in their network environments. This characteristic of CCN is not considering increasing network traffic about each of CCN routers. Therefore, when the requesters are rapidly increased to particular CCN router, network congestion may be occurred by broadcast traffic. Moreover, this characteristic of CCN has low turnaround time about user request due to reducing performance of network system. To resolve this problem, this paper propose a traffic aware routing protocol for congestion avoidance in CCN. The proposed routing protocol consider rapidly increasing traffic in the situation and establish another routing path to avoid increasing traffic problem in CCN.

A direct torque control method based on fractional order sliding mode variable structure (DTC-FOSMVS) was proposed for the speed control of a permanent magnet synchronous motor (PMSM). The proposed method in which the space vector pulse width modulation (SVPWM) with fixed switch frequency is applied, reduces the torque and flux ripple, and improves the speed control performance. In order to improve the energy efficiency and reduce the demagnetization effect, the DTC-FOSMVS method with dynamic flux reference was designed. The stability of the control method is proved by Lyapunov theory. The performance of the proposed method is verified through experiment which is based on hardware in loop and Simulink/QuaRC real time control software. The experiment results show the robustness and effectiveness of the proposed method.

Elliptic crank is a planet mechanism which is able to generate elliptic curve, with elliptic crank as the driven crank of slider-crank mechanism is equal to the mechanism which has a variable length and a variable speed along the elliptical moving crank, which changed the kinematic characteristics of the slider. This paper studies the motion characteristics of the in-line slider- elliptic crank mechanism. A slider mechanism, which has approximate dwell characteristics at the limit position, is proposed. The analysis and synthesis method of the mechanism was presented. The effect on dwell performance of mechanism parameters was analyzed. The adjusting method of the dwell range was put forward. In the end, the design example was given.

Aiming at the characteristics of the inverter and induction motor system in V/F mode, a full digital control of induction motor frequency control system is designed in this paper. BP neural network is adopted to adjust the parameters of PID controller online, so as to perform closed-loop control of the system. The full digital, distant and intelligent control experimental platform is built based on three communication modes, such as OPC, MPI and PROFIBUS-DP. Practical experiments are debugged based on the system designed. The results show that, the control system has good real-time performance, strong resistance to interference, and higher dynamic and static performances and following performances.

In this paper, we propose link-adaptive cooperative communication in wireless USB networks. To select the optimal relay node, we propose the RNS (Relay Node Selection) algorithm considering channel condition. Also, the proposed protocol can be directly applied with small overhead to the current wireless USB standard system. Furthermore, each device independently performs RNS algorithm by using the proposed protocol.

In the terahertz (THz) science research field, electro-optic (EO) polymer possesses many superior characters compared with mineral crystal. Two kinds of the side group EO polymer, polyphosphazene with plmaol grained by 2, 4-dinitroaniline and polyphenylacrylate containing p-nitro bisazo group, are synthesized and characterized. For higher EO coefficient, the double EO molecules polymer thin films are prepared by mixing a small nonlinear optical (NLO) molecule into the side group EO polymer. The principles of preparation are given and the EO coefficients are tested. The effect on the EO coefficients by different mixing proportion and different poling temperature are analyzed in details. Experiments results show that the double EO molecules polymer has fine stability, higher EO coefficient and can be easily processed. This kind of material has the potential to be widely applied in the emission and detection of THz radiation.

In order to construct the design system of nuclear power valve, the axiomatic design theory is introduced in configuration process of the valve structure design. According to the functional requirement and the complex mechanical structure of the nuclear power valves, the relationship model between design parameters and functional requirements is created by using the“zigzagging”mapping. Then the design matrix can be established and the design order can be planned. After that, the complete mapping table in design process is established through decoupling to quasi-coupling design, and the valve design process according to axiomatic method is constructed. On this basis, a rapid design system is constructed by combining the structural features with the multi-characteristic optimization requirement, in which the configuration process model established by axiomatic method provides valve design in integrated system with reasonable navigation and improves the rationality and the objectivity in design development process.

The paper describes a method to damp out low-frequency oscillations by design and tuning of both power system stabilizer (PSS) and controllable series capacitive reactance compensator (SCRC) controllers in power system. The PSS is generally used to mitigate the low-frequency oscillation by injecting supplementary signal to automatic voltage regulator (AVR) and the SCRC is used to enhance the transfer capacity for the transmission line in power system. Especially, the design of the external controller of the SCRC can provide effective damping for the low-frequency oscillation. In the paper, the effect of the design of both controllers on the system stability is analyzed. Also, the parameter tuning method is introduced and the performances of the proposed method are carried out by time-domain simulation with single-machine connected to infinite bus.

With the development of modern technology, the intelligent household appliances are more and more popular among people. However, now the lamps on the market are mostly ordinary lamps, and they can not meet the requirements of users. Because of that situation, in this paper, an intelligent lamp based on virtual reality and face/book and voice recognition is designed. Firstly, the master control circuit and peripheral functional circuit of the intelligent lamp are designed with the key of ATMEGA2560 micro dips, and the body of the lamp is designed. At the same time, the virtual environment carrying virtual three-dimensional model is developed using Java (based on cell phone) and C＋＋ (based on personal computer). The Open CV algorithms are used to identify images of objects that the intelligent lamp uploads. Users can interact with intelligent lamp between peripheral functional circuit and virtual environment. There are many characteristics of this intelligent lamp, such as, variety of control mode, high intelligent, stable performance, simple operation, high degree of user experience and so on. Users can modify the PC code and add related module at the reserved ports of the lamp to achieve more functions.

This paper presents a single-stage LED converter with high power factor. The proposed converter utilizes a single-stage power circuit that combinesthe boost DC-DC converter topology and theflyback converter topology. The control of the proposed converter operates using critical conduction mode and fixed on-time voltage control techniques. In this way the proposed converter is much simpler than currentconventional LED converters. An operational principle and a design example of the proposed converter are explained, briefly. Also, it is shown through experimental results that the proposed converter built based on the design example has good performance for driving LEDs.

Although localization has been widely studied for Wireless Sensor Networks (WSNs), the complex environments and the large network scale pose severe challenges and make it necessary to develop new reliable localization algorithms. In this paper, we propose a novel Multi-Hop Localization Algorithm for large-scale WSNs in complex environments. This work is based on the consideration that the localization process would encounter several kinds of adverse factors with different nature at the same time (e.g. anisotropic network characteristics, ranging uncertainty, link quality of multihop paths, etc.), which lead to obvious degradation of localization performance. Unlike most of the existing schemes, we transform the localization problem in complex environments into a hybrid constraint satisfaction problem (CSP) which is composed of three different kinds of constraints, i.e. spatial constraint, network situation constraint, and confidence constraint. Set-membership approach and interval analysis method have been utilized to deal with the CSP and determine the positions of sensor nodes. Simulation results show that our scheme is an effective and efficient approach to localization in large-scale WSNs.

To make “Ramp-Strike Risk” evaluation making accurately, this paper introduces a new wave-off risk assessment method based on neural network of carrier-based aircraft. On account of defining “Wave-Off Retain Clearance”, the wave-off operation system with military power and vertical elevator is established as evaluation medium. The “Wave-Off Risk State Area” established by limited wave-off envelope can reduce network training burden, and the quantitative “Ramp-Strike Risk” function with flight state is presented through BP neural network finally. Simulation results show that the risk with flight states can be predicted by using new estimation method, moreover auxiliary rectification and early-warning for landing is provided.