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Background: The vibration control loop is the key technology adopt to improve the control performance of the vibration table, which is set outside of the hydraulic vibration table servo control loop. However, the huge number of signal processing work prompts high demands on the calculation ability of the vibration controller. One kind of multi-CPU embedded vibration controller constructed by Digital Signal Processor (DSP) is proposed considering the working principle of the hydraulic vibration table and the Power Spectrum Density (PSD) reproduction process. The embedded controller consists of an acquisition unit, a calculation unit, and a monitoring unit distributes vibration control tasks to the different processing unit to realize distributed algorithm calculations. Every processing unit uses dual-port memory to accomplish data interaction between each other. The development of the embedded controller provides a benchmark engineering case for the design of the hydraulic vibration table vibration controller. Objective: This article focuses on the development of the multi-CPU embedded vibration controller and the distributed calculations. Meanwhile, the power spectrum density experiment is carried out to verify the performance of the hydraulic vibration embedded controller. Methods: 1) The structure of the hydraulic vibration table control system is given, that is, two closed-loop controls. The bandwidth of the system is further broadened by the vibration control of the outer loop. Besides, the accuracy of vibration control is also improved. Then, the development needs of the vibration controller are put forward according to the detailed process of the power spectrum density replication. 2) An arithmetic processing unit is formed by using TI C2000 series DSP to calculate a large number of signal processing and a signal acquisition unit at high speed. In order to improve signal processing efficiency, the signal acquisition unit is used to perform preprocessing calculations (data acquisition and filtering) and vibration control calculations in a distributed manner. 3) Processing speed is further improved by taking full advantage of DSP software sources include lots of library functions and optimized assembly library functions. 4) The friendly operation of the controller and the safety monitoring of the experiment process are realized by the industrial computer served as the human-computer interaction unit. 5) Multi-CPU data sharing is achieved through using dual-port RAM to realize. Results: Through experiments, the developed embedded controller is fully estimated. The experiment shows that the developed hydraulic vibration table can realize real-time vibration control. Concerning the acceleration power spectrum density reproduction experiment, 256 acceleration response samples are calculated, and the update time is 4ms. The tracking accuracy of the timedomain waveform is controlled within 0.3%. Conclusion: The use of the developed embedded controller with signal conditioning equipment can achieve real-time control of the hydraulic vibration table, but the performance of the embedded controller can be promoted in advance, and the performance improvement of the hydraulic vibration table embedded controller can be studied from the following aspects: 1) The Fourier calculation is executed by the acquisition unit to share the calculation workload of the calculation unit; 2) The computing unit uses a signal processor chip with better performance, although this will bring development difficulties; 3) The monitoring computer can use an embedded controller with superior performance instead of an industrial computer to reduce the size, improve the performance; 4) The DSP real-time operating system should be used, and the task scheduling of vibration control experiments should be optimized.

The disturbance of the AC system has become one of the main causes of commutation failure in the high voltage direct current (HVDC) transmission system. Here, the time–frequency transformation method is used to analyse the AC-bus voltage disturbance from the perspective of the harmonic content of the AC power network. The time–frequency transformation for AC-bus voltage disturbance is difficult due to its characteristics of time variability and time fixity. With comparative analysis of various transformation methods, the method of combining the wavelet packet transform with the short-time Fourier transform can meet the requirement of time–frequency analysis of the AC voltage disturbance very well, and this method was used to analyse the fault recording data of Fengjing Convert Station when commutation failure occurred in recent years. The result shows that the AC-bus voltage mainly contained third and fifth harmonics, and there was a certain amount of even harmonics, and the low-order harmonics would be more in the case of a remote fault. In addition, there were more harmonics in the voltage when faults occurred in the 500 kV system, while there were more low-order harmonics when faults occurred in the other voltage class systems.

The DC transfer switch is a key switching device that converts the DC operating current in the HVDC transmission system from one operating return line to another. In a multi-terminal DC transmission system, the selection of metallic return transfer breaker and the earth return transfer breaker is closely related to the system topology. This paper analyzes the multi-terminal HVDC transmission system and refines its topology characteristics. A calculation method for determining the configuration mode, parameter selection and operation sequence of the transfer breakers is proposed. This simulation verification is carried out in combination with a three-terminal HVDC project.

As the core equipment of the power grid, the operating state of the transformer will directly affect the stable operation of the power grid. Partial discharge (PD) is the main reason for the insulation failure of large transformers, and it is currently the primary means of assessing the degree of insulation degradation. Partial discharge detection is an important indicator for measuring the reliability of the internal insulation structure of electrical equipment. The purpose of PD test is to verify whether there is a discharge source inside the transformer. As the earliest proposed and most developed method, the pulse current method is widely used in actual detection. This paper reviews the detection principle and application scope of the method, as well as the derived ultrasonic or ultra-high frequency (UHF) joint detection methods. Meanwhile, this paper analyzes the principles, advantages and disadvantages of every detection method. Finally, given the research and application situation of pulse current method detection, this paper looks forward to its future development.

There is a little difference between transformer split cooling system and conventional cooling mode, which refers to radiator mounting position and installation modes. Thanks to the specialty of split cooling system, it is complicated to research parameter formulation and model constructing of simulation model. At present, there have been little research about thermal simulation. And it is difficult to identify the accuracy of simulation. Maybe we are expect to carry out deeper simulation research and trial comparisons. The paper has conducted three-time temperature-rise test in terms of transformed 10 kV oil-filled transformer. There have set up transformer three dimensional flow of split cooling system-solid-thermal simulation model based on simulation trials. We adopt finite volume methods to solve region temperature field of transformer. And we have obtained winding heat spot of different locations in terms of split cooling. Though the analysis of comparisons, we have concluded that the center height of radiator of miniature oil immersed transformer improves 2 meters. And the hot-spot temperature declines to 8K. Horizontal distance between radiator and transformer shrinks 3.5m, while the hot-spot temperature declines 4K. After the comparisons of experimental data, we have acquired the results of theoretical calculation and simulation model. Besides, we have gained important data that relative error is within +5%, which has verified accuracy of simulation model and engineering practicability. The paper has analyzed the cooling efficiency of split cooling mode effectively. It provides technical support for the building of split cooling mode. It provides relative data for the cooling structure optimization of large-scale oil immersed transformer and orientation of hot-spot temperature measurement of optical fiber.

In order to master operation status of the electronic current transformer(ECT), application investigation and defects statistical analysis were conducted on ECT of 110(66)kV~1000kV applied in smart substation of the State Grid Corporation of China(SGCC). The defect location, defect cause and defect type of ECT with different principles are analyzed. The results indicate that the defects of ECT are mainly concentrated in the acquisition unit, the defect rate is closely related to the reliability of electronic components, the technical level, production process and quality control of the manufacturer. In view of the typical defect analysis, the corresponding solution measures are put forward to provide reference for the subsequent research and application of ECT.

In ultra high voltage(UHV) DC system, the transient characteristics for fault current monitoring of current transformers for DC application (DCCTs) and the consistency of response characteristics when different types of DCCTs are used for differential protection have become important factors affecting the safe and stable operation of DC system. In this paper, transient characteristics of all-fiber DCCTs and shunt DCCTs mainly used in DC system were studied, the main parameters of the transient characteristics including delay time and maximum peak instantaneous error were tested, and the key parameters influencing the response consistency of DCCTs were analyzed. The results show that the maximum peak instantaneous errors of all-fiber DCCTs and shunt DCCTs can meet ±5% limit requirement, meeting the demand for protection application in DC system. The delay time is the main factors affecting the maximum peak instantaneous error of DCCT. The longer the delay time is, the greater the maximum peak instantaneous error is, which may even exceed the limit value of ±5%. If necessary, the delay time of DCCTs participating in differential protection can be compensated. The research results provide a theoretical basis for preventing the malfunction of protection device caused by the inconsistent response characteristics of DCCTs in DC system.

In the new economic era led by big data, enterprises face many consumers with various product requirements. It is important for enterprises to timely meet these personalized product needs to improve their market competitiveness. In this paper, to show how to satisfy users' personalized product customization needs through the Internet and big data technologies, a ceramic product online interactive design system based on bigdata cloud service platform is implemented by adopting Web3D technology and storing a mass of various 3d digital models of ceramic products designed beforehand in the cloud server for designing users' personalized ceramic products. The procedure of online designing a ceramic product using this system includes choosing ceramic product 3d model in cloud server and calling the cloud decoration pattern resources or independent online design decorative pattern. In order to protect the intellectual property rights of users' design works, the platform provides privacy protection mechanism for users' personal information and works' information by setting three kinds of design works' sharing modes: free sharing, non-sharing and paid sharing. With the growth of 3d model data of ceramic products, the platform can also provide online 3d displaying services of ceramic product. The real application of this system demonstrate it can efficiently satisfy users' personalized product customization needs without disclose users' privacy information.

This study presents the comparison among three control systems: Cigre Benchmark model, ABB model, and SIMENS model based on PSCAD. Firstly, the control systems which refer to Cigre Benchmark control model, ABB control model, and SIMENS control model are introduced, respectively. Analysis and comparison are done on these control systems about their design theories, control logic, and functional models, and the advantages and disadvantages of each control system are concluded. Secondly, simulations in both normal and fault conditions are done in order to verify the conclusions. On the one hand, the steady-state response characteristics of these three high-voltage direct current (HVDC) models are obtained and compared by setting different voltage of the receiving terminal AC bus. On the other hand, the transient response characteristics of these three HVDC models under different operating conditions are obtained, such as symmetrical and asymmetrical short-circuit fault, line switching on or off etc. The research results will provide experiences and references for the future optimisation of the HVDC control system.

With the construction of the global energy internet, the broad demand for the development of HVDC transmission methods will inevitably bring about more problems of DC magnetic bias. Therefore, it is necessary to further upgrade to standards, which is of great significance in promoting the construction of the global energy Internet. For this reason, The performance parameters and structural parameters of the resistive and capacitive DC magnetic bias suppression devices that are currently used in many applications are analyzed, and the principles for selection are summarized.

This article designs a power supply status monitoring system in order to verify the reliability of the active electronic current transformer's power supply switching and monitor its power supply status. It is proposed that analyzing the merged unit IEC61850-9-2LE message to obtain primary current and analyzing the merger unit TCP/IP protocol to get the laser power and photo-voltaic cell output voltage. While using a high-power optical splitter to monitor the laser power output directly, thus enabling the active electronic current transformer power supply status monitoring according to its working principle. Through this monitoring system, a certain type of active electronic current transformer is energized state monitoring test verification; the monitoring data can display the current energy status in real time, and gives several common power supply failure alarms. Experiments show that the monitoring system can verify the reliability of power supply switching and realize the alarm of power supply status so as to improve the quality testing capability of active electronic current transformer.

This research employs sensor techniques (i.e., radio-frequency identification system) in developing a smart assistant for home furniture shopping. The implemented assistant provides friendly accessed interface that allows consumers to easily locate the product, confirm the detail information of it, and moreover, provide real-time recommendation(s) in accordance with interests of consumers. Unlike conventional online stores, the system offers the retailer extra spaces for varieties of merchandize, eliminated duplicated products display, etc. In addition, the assistant can avoid an unnecessary crashing of huge shopping carts in a crowded situation. This research discusses a new shopping pattern implemented by a smart assistant with the integration of consumer, retailer, and warehouse sides. In addition, an application is provided on smart phones in conjunction with the system to improve the competiveness in the market and increase the loyalty of their consumers. The experiment results demonstrate that collected data from end users (e.g., consumer, warehouse, and retailer itself) may provide essential information to revise business models.

The focusness detection methods for digital refocusing both in spatial and frequency domain are presented.The spatial method reduces the data used in image reconstruction according to the selected evaluation area.And the frequency domain method embeds the evaluation functions in image reconstruction.The experimental results show that the improved methods are faster than the conventional.

Transformers are essential devices of the power system. The accurate computation of the highest temperature (HST) of a transformer's windings is very significant, as for the HST is a fundamental parameter in controlling the load operation mode and influencing the life time of the insulation. Based on the analysis of the heat transfer processes and the thermal characteristics inside transformers, there is taken into consideration the influence of factors like the sunshine, external wind speed etc. on the oil-immersed transformers. Experimental data and the neural network are used for modeling and protesting of the HST, and furthermore, investigations are conducted on the optimization of the structure and algorithms of neutral network are conducted. Comparison is made between the measured values and calculated values by using the recommended algorithm of IEC60076 and by using the neural network algorithm proposed by the authors; comparison that shows that the value computed with the neural network algorithm approximates better the measured value than the value computed with the algorithm proposed by IEC60076.

A novel nature-inspired swarm intelligence (SI) optimization is proposed called dolphin swarm optimization algorithm (DSOA), which is based on mimicking the mechanism of dolphins in detecting, chasing after, and preying on swarms of sardines to perform optimization. In order to test the performance, the DSOA is evaluated against the corresponding results of three existing well-known SI optimization algorithms, namely, particle swarm optimization (PSO), bat algorithm (BA), and artificial bee colony (ABC), in the terms of the ability to find the global optimum of a range of the popular benchmark functions. The experimental results show that the proposed optimization seems superior to the other three algorithms, and the proposed algorithm has the performance of fast convergence rate, and high local optimal avoidance.

By analyzing the current computer network security situation and the existing intrusion detection system, this paper introduces the data mining technology into the intrusion detection system and structures behavior model and invasion information database of intrusion detection system based on data mining. This model improves the efficiency of intrusion detection.

So far the group purchase websites are at the stage of quick growth and it becomes important to research the ways for steady development in the near future. Depending on customers’ satisfaction is the most important factor for group purchase websites. As referred to customers’ expectation in this paper is calculated the maximum under some conditions. Then the paper transforms the problem of matching to the problem of product positioning. Moreover, in the following example adopts the ‘Integer Goal Programming’ of WINQSB software to attain optimization scheme of research about group purchase website.

Traditional method of Web Service search is based on the UDDI registry. UDDI is very popular in the domain of Web Service publishing, but it's not very suitable for Web Service discovering as it is based on keyword match. In this paper we propose a model to discover Web service based on semantic and search engine, and design its architecture. At the same time, we put forward the algorithm of splitting words and the algorithm of query expansion, develop a Web Service search prototype, give a case study, and discuss the recall, the precision and the efficiency of the prototype.

After the study of the connotation, the architecture, the core ideology and the characteristics of E-SCM, the paper discusses how to achieve E-SCM, referring to the principles, the holistic scheme and steps of the implementation of E-SCM. Finally, the paper draws lessons from the investigation of the current situation and the content of the implementation of the E-SCM of the Wal-Mart.

Cluster supply chain is the network of supply chains based on localization and integration in industrial cluster. It is often that multiple supply chains in the same cluster are interactive and collaborate with each other. This paper considers the dual-pipeline replenishment across two supply chains including two echelons (supplier-retailer). The third party logistics provider (TPL) is introduced into the cluster supply chain network to coordinate the replenishment. Adopting the theory of Automatic Pipeline, Inventory and Order Based Production Control System (APIOBPCS) and system dynamics, this paper proposes a VMI&TPL-APIOBPCS model to simulate the process of dualpipeline replenishment and dispatching when the TPL implements Vendor Managed Inventory (VMI) to coordinate the two supply chains. The simulation results show that the model can effectively decrease the total inventory of two supply chains, make the production rate smoother and reduce the Bullwhip effect.

Applying control theory and simulation technique, a simply hybrid system with manufacturing /remanufacturing model is built. We study an infinite horizon, continuous time, Order-Up-To (OUT) policy. We specifically highlight the effect of remanufacturing lead-time and the return rate on the bullwhip produced by the ordering policy. We first address the stability of this system. We find that the remanufacturing lead-time and return rate have no effect on system stability. We then investigate the bullwhip. Our results clearly show that a larger return rate leads to less bullwhip. So, returns can be used to absorb demand fluctuations to some extent. However a longer remanufacturing lead-time has less impact at reducing bullwhip. Furthermore, within our specified system, we conclude that with returns, bullwhip is always less than without returns. Our results are completely analytic and exact. They are verified with simulation.

This paper presents a reliable transport technology of tubular distribution Mobile Wireless Sensor Network (MWSN). The combination of GPRS and distance measurement location algorithm is presented to precisely locate sensor nodes. Connection handoff is put forward to support the reliable transport technology. Cluster Node Selection Algorithm and Connection Handoff Node Selection Algorithm are proposed to dynamically arrange the nodes in MWSN. The method is transparent to the sensor node so can be used to many fields.

In this paper, we propose a novel face image super-resolution using the method of projection onto convex sets (POCS) and residue compensation. First, the initial reconstructed high-resolution image, which is similar to the original high-resolution image, is built under the POCS algorithm. Second, the residue compensation is estimated. The higher frequency information is reconstructed by learning two corresponding sets of high- and low- resolution training residue images. The optimal super-resolution face image, which has more image content, is hallucinated by compensating the residue to the initial reconstructed high-resolution image. Experiments demonstrate that our approach does render high quality super- resolution faces.

A new emergency evacuation model based on Multi- Agent framework and Particle Swarm Optimization was presented. This model simulated human's individual behaviors and social behaviors in multi-exit evacuation environment. The Linear Weight Decreasing Particle Swarm Optimization (LWDPSO) was introduced to simulate individual's movement. A hierarchy of behavior rules was described, and a series of individual behaviors and social behaviors during evacuation were defined. A prototype system of emergency evacuation simulation was implemented based on Geographic Information System (GIS) application framework. The result shows that the simulation system well performs some typical evacuation behaviors, the model based on multi- agent and LWDPSO has good efficiency and practicability.

An extendable framework is developed for an ensemble HME model based on the theoretical analysis of information geometry. In a hierarchical set of systems, a lower order system is included in the parameter space of a large one as a subset. Such a parameter space has rich geometrical structures that are responsible for the dynamic behavior of learning. The HME network divides a task into small tasks by the principle of divide and conquer to improve the performance of a single network. By studying the dual manifold architecture for mixtures of neural networks and analyzing the probability of knowledge-increasable model based on information geometry, the paper proposes a new method to achieve the multi-HME model that has knowledge-increasable and structure-extendible ability. The method helps to provide explanation of the transformation mechanism of the human recognition system and understand the theory of the global architecture of neural network.

Research the small sample face recognition approach. A small sample statistics face recognition approach based on virtual sample is presented. In this method, prototype faces and an optic flow and expression ratio image based method are presented to generate more expressive facial expression, which are used to create virtual sample to extend the sample set, the training set is rational extended by generating different expressive expressions for one given facial image. A Local probabilistic approach is used to recognize test samples. Experiment result shows the approach can improve face recognize rate of small sample efficiently.

Research the small sample face recognition approach. A small sample statistics face recognition approach based on virtual sample is presented. In this method, prototype faces are used to create virtual sample to extend the sample set, independent component analysis (ICA) algorithm is used to reduce dimensions and extract features, and then Bayesian expectation maximisation algorithm is adopted to learn the parameters of condition probability function of class features. A Bayes classifier is constructed to recognize test samples. Experience result shows the approach can improve face recognize rate of small sample efficiently.

Super-Resolution (SR) reconstruction is posed as a Bayesian estimation of the location and appearance parameters of a face model. Image registration and image fusion, the two steps for SR reconstruction, are combined into one unified probabilistic framework, in which the prior information about facial appearance and gray from the face model is incorporated into both of the steps. In addition, a particle filter based algorithm is proposed to achieve the estimation, i.e. SR reconstruction. The proposed approach avoids the inherent dilemma of the most traditional methods, in which it demands a high-resolution image to get an accurate and robust estimation of the motion field, while reconstructing a high-resolution image requires the accurate and robust estimation of motion field. Experiments performed on synthesized frontal face sequences show that the proposed approach gains superior performance both in registration and reconstruction.

To achieve workflow retrieving and compliance checking based on behavior, it is necessary to identify the behavioral profiles of workflow models. Since the execution timing and the occurrence probability of tasks are crucial to choose appropriate workflows, it is significant to conduct exact quantitative analysis on the ordering relations by considering the time constraints and occurrence probabilities of tasks in workflow models. In this paper, the quantitative ordering relations are formally defined and an algorithm is proposed to efficiently compute the ordering relations with time and probability constraints based on complete firing sequences. Experiments show that the algorithm works well. Refereed/Peer-reviewed

As cloud computing platforms are widely accepted by more and more enterprises and individuals, the underlying cloud workflow systems accumulate large numbers of business process models. Retrieving and recommending the most similar process models according to the tenant's requirements become extremely important, for it is not only beneficial to promote the reuse of the existing model assets, but also helpful to reduce the error rate of the modeling process. Since the scales of cloud workflow repositories become bigger and bigger, developing efficient and exact query approaches is urgent. To this end, an improved two-stage exact query approach based on graph structure is proposed. In the filtering stage, the composite task index, which consists of the label, join-attribute and split-attribute of a task, is adopted to acquire candidate models, which can greatly reduce the number of process models needed to be tested by a time-consuming verification algorithm. In the verification stage, a novel subgraph isomorphism test based on task code is proposed to refine the candidate model set. Experiments are conducted on 6 synthetic model sets and 2 real model sets. The results demonstrate that the presented approach can significantly improve the query efficiency and reduce the query response time. Refereed/Peer-reviewed