Earticle

An expert system for fault diagnosis of subsea blowout preventer (BOP) has been developed. According to the expert knowledge, common faults could be diagnosed and the system will be enlarged with the increasing knowledge. Fault tree analysis method is used to extract the fault diagnosis information. By this way, the layers of faults and the logical relationship among them can be shown clearly. Production rules are employed to represent the knowledge extracted from layers of fault trees. It’s convenient and easy to understand that the knowledge is connected together through its logic. The developed interfaces are friendly and easy to operate and the users can learn to use the system according to the one by one prompt and query the failure causes easily.

In this study, a generalized space vector pulse width modulation (SVPWM) method is proposed for cascaded H-bridge multilevel inverters. An explicit modulation function expression of the generalized SVPWM method is established for a single-stage cascaded inverter. Various continuous SVPWM and discontinuous PWM methods are obtained easily by changing the zero vector distribution coefficient. The generalized SVPWM method for cascaded multilevel inverters is achieved via the carrier phase shift strategy. A simple digital realization method for the generalized SVPWM is also proposed. By using this method, complex trigonometric function calculations, coordinate transformations, space vector selections, and duration time calculations are avoided. Finally, the simulation model and experimental device of the eight cascaded multilevel inverters are built to test the proposed method. The harmonic characteristics of the different modulation method are also analyzed. Simulation and experimental results demonstrate the feasibility and effectiveness of the method.

In this research, has been done the next usage of ultrasonic and fuzzy logic to determine fruit maturity level. Reflection of ultrasonic with different frequency are used to measure water content and fruit texture in other side fuzzy logic are used to determine the fruit maturity level depend on water content and fruit texture. The research was limited to avocado, mango and papaya. Sample of data obtained by measure 30 fruit of each kind and test it with laboratories to calibrate and also test it with human perception to prove the fact of maturity. The result of this research is device that can transmit ultrasonic signal then read the reflection of it and MatLab application to fuzzy logic processing. Accuracy and precision analyzing give the result that the system have a good accuracy and precision with low condition of error rate. However, analyze give not good condition of precision for the percentage of maturity level. Analyze with statistic calculation give the result that there is a strong and linear correlation between water content and fruit texture with the level of fruit maturity. The research found that the fruit in mature condition is not always having sweet taste and also the opposite.

This paper is based on Orthogonal Frequency Division Multiplexing (OFDM) technology, which is the core technology of the coal mine medium voltage electric bridge set. And to reduce the high peak-to-average power ratio arising from the OFDM signal and to strengthen the timeliness and accuracy of communication, it puts forward a real-valued genetic improvement of Partial Transmit Sequences Algorithm (RVGA-PTS) and the Timing Synchronization Algorithm which is based on SC algorithm. Finally, it completes the preliminary design of hardware system for the medium voltage electric bridge set. The simulation results show that compared with other optimization algorithm, the convergence speed is faster, the timing estimation precision is higher, and the system performance has been improved obviously.

This paper presents a novel sensorless control method of permanent magnet synchronous motors at standstill and low speed based on a low-frequency current signal injection. The approach superimposes a persistent LF current signal into the estimated d-axis to get the rotor position error angle-related signal by detecting the corresponding voltage response and current response. Then the rotor position and motor speed are obtained. Theoretical analysis and simulation results demonstrate that the approach can achieve sensorless control of permanent magnet synchronous motors at zero and low speed, ensure good dynamic and static performances, and achieve effective control when applied to servo system. Finally, a test prototype system which used a digital signal processor and space vector pulse width modulation technology has been developed. Experimental results show that the system has better static, the effectiveness and dynamic performance of the adaptive test signals in a sensorless controlled surface-mounted permanent magnet synchronous machines.

Even though long delay is permitted in Delay Tolerant Networks (DTNs), some applications explicitly demand an upper bound imposed on message delivery delay for the application specific purpose. Despite some researcher have proposed to meet new requirement, their approaches have weakness in the point of implementation since infinite buffer space on a node or the knowledge prior the moment regarding mobility and connectivity are assumed. To remove dependency on buffer and mobility pattern for bounded delay, we propose how to extend the epidemic routing protocol through delay estimation with inter meeting times record. Moreover, utility based forwarding to decide the adequate next hop while preserving an upper bound imposed on message delivery delay is introduced. Finally the simulation results will be given to prove the guarantee of delay bounded under the same simulation scenarios as comparative well-known protocol, RAPID. As the result, the proposed scheme shows the delivery in upper bound with less resource usages.

In order to solve the problems of occasional occurrence algorithm of negative R waves and misdetection and false detection of irregular R waves, compensates for the misdetection and false detection of R waves is introduced to detect QRS waves using quadratic biorthogonal B-spline wavelet transform, the correspondence relationship between signal singular points and zero-crossing points is analyzed by Mallat algorithm from the perspectives of modulus maxima of signals on different scales and Lipschitz exponent, QRS waves are obtained. Finally, this paper employed Matlab to extract the QRS characteristic waveforms of ECG signals from MIT-BIH arrhythmia database. The results show that the detection accuracy rate for QRS waves is up to 99.89% with higher robustness for several common interferences with ECG signals.

A study on an animal shaped robot that has an animal-assisted therapy effect on early treatment for children with developmental disorders and has no dangerous elements of infection or allergy, like a real animal, has been started since the late 90s. A cat is selected as the object animal of the robot for early treatment of children with developmental disorders, according to the result of their preference research. For making the cat robot more efficient on the therapeutic value, personification must be applied. Personification which reflects the image of an animal or a man on the shape of a robot, makes a man accept a robot as more familiar, and makes it easier to convey a character of a robot to a man through the outward appearance or movements. Therefore, the personification method of a cat robot is researched through prior theses and literatures. Through the results of the study, basic emotions of the cat robot were selected 4 emotions: surprise, anger, sorrow, and happiness. To the design of the cat robot, standards are established and applied to personification, such as outward appearance, facial expressions, emotional expressions and movements.

Development and utilization of wind energy has become an important part of world sustainable energy development strategy. A control method realizing maximum power point tracking of wind turbine through adjusting the load characteristics was proposed in this article. The power management system based on DC/DC convertors was designed. The maximum power point tracker (MPPT) extracts maximum power from the wind turbine from cut-in to rated wind velocity by sensing only dc link power. The MPPT step and search algorithm in addition to the DC/DC are simulated using MATLAB-SIMULINK software. The results show that the DC/DC convertors topology can realize the maximum power point tracking control of the wind turbine.

In this paper, performance assessment methods of multivariable control system subject to piecewise constant time varying disturbance dynamics has been studied. The problem appeared on most industrial controllers are linear time invariant (LTI) while the process are often time varying. Take a series of disturbance dynamics that can be modelled by piecewise linear disturbance models, namely piecewise linear time varying (LTV) disturbance dynamics. The problem is formulated as searching for a multi-input multi-output (MIMO) benchmark control. In the paper, a method, which is based on output variance limit, is proposed to assess the performance of MIMO control system. A weighted performance index is constructed through dividing time varying disturbance in to three types of constant disturbance. The upper and lower limits of the output variance would be determined by a special principle, and then Integral of time-weighted absolute value of the error (ITAE) would be used to optimize the parameters of controller and give the feasible controller model. The results show that the method is simple and available in practical application.

Recently, significant growth in the applications of the wireless sensor networks (WSNs) operating in unlicensed spectrum bands has been made. In the meantime, existing unlicensed bands are becoming congested and overcrowded. On the other hand, Cognitive Radio (CR) technology has been proposed as the key technology for future wireless communication that exploits dynamic spectrum access strategies. Since this offers more flexible way to utilize the wireless spectrum than traditional radio technology based on a fixed spectrum access policy, it is thought that the key feature of cognitive radio, i.e., dynamic spectrum access can be applied in WSNs to access the underutilized spectrum bands to transmit their readings in an opportunistic manner to the next hops and finally to the sink. In cognitive radio sensor networks (CRSNs), obtaining the information about spectrum holes on channel, negotiating among primary users and secondary users for spectrum allocation, synchronizing transmission parameters are the important functions of CR medium access control protocols. In this paper, we mainly focus on investigating the major issues to be considered with the existing communication protocols and algorithms devised while realizing the cognitive capability into wireless sensor networks. We also discuss the main challenges on the basis of dynamic spectrum management and extra energy expenditure to apply the cognitive capability into wireless sensor networks.

This paper proposes a novel hierarchical multi-agent architecture for the automatic fault detection and restoration of smart grids based on traditional power transmission systems that are composed of a lot of electric substations (ESs). Each agent is associated with an ES to control the ES. If a fault occurs in the input lines of an ES, the agent corresponding to the ES can automatically detect the fault and choose a solution from other agents. The ES of the chosen agent can supply power to the faulty ES by closing a corresponding electric switch and then the fault is restored. Furthermore, a coordination protocol is proposed to allow the fault restoration. Moreover, the agents are formally modeled by timed automata and the coordination protocol is verified by the model checker UPPAAL. Finally, the contribution of this paper is applied to a real-world system.

The prediction of wind farm output power is considered as an effective way to increase the wind power capacity and improve the safety and economy of power system. It is one of the hot research topics on wind power. The wind farm output power is related to many factors such as wind speed, temperature, etc., which is difficult to be described by some mathematical expression. In this paper, Back Propagation (BP) neural network algorithm is respectively combined with genetic algorithm (GA) and particle swarm optimization (PSO) to establish the combination prediction model of the short-term wind farm output power based on meteorological data collected by Wireless Sensor Network (WSN). The meteorological data is used to determine the input variables of the BP neural network. Meanwhile, the GA and the PSO is respectively used to adjust the value of BP's connection weight and threshold dynamically. Then the trained GA-BP and PSO-BP neural network are used to predict the wind power by combination method. The experiment results show that our method has better prediction capability compared with that using BP neural network, GA-BP neural network and PSO-BP neural network alone.

After analysis the importance of continuous attributes in the C5.0 algorithm processing, and consider the shortcomings of discretization method of C5 algorithm, this paper proposes a new method based on Rough set theory- information entropy- discernible matrix discretization (RSIEDM). The method uses rough, information entropy and Discernible matrix that can be more reasonable and more accurately to continuously attribute discretization, and making created decision tree have better accuracy. In the application of optimization of lightning disaster statistics and evaluation result of lightning disaster, the algorithm which has obtained a better effect.

A conventional B-ternary logic for an asynchronous design has many drawbacks, most notably its incomplete truth table of the basic logic gates. This paper presents a new asynchronous ternary logics based on a new data-encoding scheme. The main aim of this research is to provide the flawless truth table for varying logic gates. The asynchronous circuit employing these logics uses two-rail logic for two data bits. It can reduce the number of wire by half comparing to the dual-rail or 1-of-4 data encoding. Furthermore, the proposed encoding scheme reduces switching by 25% to compare with the conventional B-ternary one.

It is the common issue for all of countries that lots of safety risk accidents happen in large scale engineering projects. To save cost, generally, no enough resource is booked, or not very qualified resource is selected, which is one of the import safety risk factors in large scale engineering projects. But less scientific strategies are available to balance between safety risk values and safety risk investment. In the large scale engineer safety risk management filed, currently most of methods are qualitative, so it is a hot and difficult topic that constructs a quantitative model for practical problems, especially based on optimal control theory. In this paper, we will take both advantages of maximum principle and dynamic programming to solve the large scale engineering project safety risk issues caused by resource numbers and resource quality. Firstly, by maximum principle, establishes safety risk model considering resource numbers, and give iterative steps of the gradient descent method for numerical solution; Secondly, by dynamic programming, establishes safety risk economic model which takes into account the quality of resource; In the end, both the models are validated in one practical equipment case by combining the advantages of each algorithms .

In allusion to the importance of insects’ movement forms detection, this paper puts forward an linear insects’ movement forms detection method using Micro-Doppler radar. This paper have a point model classification on linear insects’ body and get the vibration characteristics of each model point in different movement forms through experiments. It combines with Doppler echo equations of point model vibration, and builds the linear insects’ Doppler echo model. This paper detect different movement forms of tenebrio molitor in larva period with real-time Doppler radar data acquisition system, compare the movement echo time-frequency diagram of different movement forms obtained by STFT with the simulation. It aims to verify the rationality of building the linear model of the insects using model points and the feasibility of applying the Micro-Doppler to the real-time detection of insect movement forms.

Cognitive Radio is continually studied by many engineers and researchers. However, it doesn’t still get an optimal standard proposal and technical skill. In this paper, we deal with just partial face in that field and suggest the proposed device but it doesn’t state specific and physical things. This can be some problem in this scheme. However, if we use this proposed method properly, Secondary terminal (ST)’s power is flexible in the future communication of Cognitive Radio. Also, this is a good solution of power dealing with next communication of other fields.

Sliding window (SW) technique is one of common paradigms employed for object detection. However, the computational cost of this approach is so expensive because the detection window is scanned at all possible positions and scales. To overcome this problem, we propose a compact feature together with fast recursive coarse-to-fine object localization strategy. To build a compact feature, we project the Histograms of Oriented Gradient (HOG) features to linear subspace by Principal Component Analysis (PCA). We call this feature as PCA-HOG feature. The exploitation of the PCA-HOG feature not only helps the classifiers run faster but also still maintains the accuracy. In order to further speeding up the localization, we propose a recursive coarse-to-fine refinement to scan image. We scan image in both scale space and multi-resolution space from coarsest to finest resolutions. Only the best obtained hypothesis from the coarser resolution could be passed to finer resolution. Each resolution has its own linear Support Vector Machine (SVM) classifier and PCA-HOG features. Evaluation with INRIA dataset shows that our method achieves a significant speed-up compared to standard sliding window and original HOG feature, while even get higher detection accuracy.

Clouds focus on flexibility and on-demand provisioning of virtualized resources, which allow users to scale up and down the usage of resources according to their needs. These characteristics give rise to more challenges for resource allocation in cloud system. The optimization of virtual machines (VMs) allocation and the minimization of time and infrastructure cost are still needed to be improved. Meanwhile, failure-aware VMs rescheduling and allocation is another key point to be considered. This paper focuses on the resource failures and presents efficient VMs scheduling mechanisms and policies which try to keep the trade off between system performance and QoS.

Wireless sensor networks (WSNs) have emerged as one of the most promising technology to provide a wide variety of industrial applications. However, it is still failing to respond in a timely fashion service. In contrast to existing studies, we propose a more practical standard known as Data Distribution Service (DDS), as a middleware standard for interoperable Data Centric Publish-Subscribe (DCPS) architecture with real-time data distribution capabilities, and a candidate for standards based realizations of equally data centric WSN environments. Especially, this paper aims to evaluate on customized design features for real-time WSNs of an applicable and supportive architecture of DDS-based middleware. In the meantime, to integrate the underlying heterogeneous WSN and DDS, a supportive wireless protocol design is required and, thus, those features could be taken into account in designing the protocol.

The application of industrial robots is an important symbol of a nation's industrial automation level. While domestic universities robot teaching is mostly on pint-sized robot. This paper introduces how combine the pint-sized robot teaching with the industrial robot practical operation. Through the pint-sized robot simulating industrial robot, realizing the manipulator operation, the student further to get more knowledge, learn the method to analyze and solve problems, and get effectively training and all-round development in innovation ability.

This paper proposes a new algorithm to position the area of a truck’s compartment in images for the intelligent sampling control system. The goal is to identify a truck’s compartment and assure that some works are done inside it. For example, while a mechanical arm automatically snatches goods carried by a truck, we must ensure that the goods must be obtained inside the truck’s compartment. Firstly, the compartment image is acquired by the camera overhead. Secondly, the Canny operator is used to extract the edge of the image, because it is sensitive to the image texture features. Thirdly, the Canny edge image is transformed to the Hough transform space. The peak points in the Hough parameter space indicate the straight lines which may be the elements of the compartment. The straight lines which meet the conditions of the actual size of the compartment make up the area of the compartment. Finally, converting the image coordinate to the physical compartment coordinate. The experiment result shows that the algorithm is effective and the coordinate conversion error analysis indicates that the converting algorithm is workable.

Functional games are games that combine play and study together, and this genre is consolidating its position as a new alternative that has the potential to transform the industry. Functional games are an excellent tool for attaining specific goals such as increasing concentration levels and learning abilities by capitalizing on the entertainment nature of games. Moreover, the scope of use for functional games is becoming increasingly diverse, ranging from specialized domains such as medical support, medical learning, military simulation, health, special education, and learning tools for everyday education and well being. To optimize 3D multi-dimensional functional games’ benefits, this paper presents an analysis of the level of 3D feel perceived by users regarding 3D depth level, distance and location. Moreover, to ensure the optimization of the user’s concentration levels and engagement with the games themselves, this paper proposes a system that provides sound effects that incorporate ultrasonic waves’ auxiliary sounds to be integrated with traditional sound effects. When the recommendations of this paper are implemented, it is possible to select the distance and the location that are optimal for viewing in 3D, and it is hypothesized that optimization of user benefits concerning functional games will be enabled through auxiliary sound effects.

In view of the limit of mechanical products adaptive design in aspects of case representation, retrieval and modification, the representation and reuse technique of knowledge are studied. There are different importance of matter-element in different design stage, so a kind of similarity calculation method which based on the extension of weighted matter-element is put forward. The product design not only have functional requirements but also structural requirements, so the solving method about incompatible problems and opposite problems in extenics is introduced, a model of products extension adaptive design which based on case reuse is established.

Frequency controlling technique applied to the coal mine electromechanical equipments results in the absence of reactive power and harmonics pollution, which brings hidden troubles to power net in coal mine. Considering electromechanical equipment's safe and economic operation, this study opened with the mathematical model and parameters design of cascade STATCOM based on LCL filter. Then a low-pass filter time delay link and a PI controller were adopted for ensuring high dynamic response and low-frequency stable accuracy of the inner current loop. Eventually the repetitive control loop based on internal principal was used as outer current loop to realize zero static error tracking of referenced harmonic current, so that both high dynamic response and small steady-state error were obtained. Simulation and the actual device experiments validate the feasibility of the design.

This paper proposes an AE (Auto-Exposure) control method for stereo cameras. Image processing has a problem that it shows different performance depending on brightness values even with the same image processing algorithm. Auto-exposure control solves this problem by maintaining the brightness value of the acquired image. If preprocessing maintains the brightness value of the acquired image in a stereo camera, the performance of the image-processing algorithm becomes more stable. Traditional Auto-exposure control methods change the average brightness value of the image to attain the desired brightness value. However, this method is a disadvantageous in that it responds sensitively to exterior lighting sources and incurs low resource efficiency. The proposed method uses Gaussian sampling, with more sampling in the center region such that the sensitivity to light from exterior areas decreases and the resource efficiency improves. In experiments we confirmed that the performance of the proposed method is improved compared to that of existing methods.

Neural network has strong ability of pattern recognition. In consideration of the problems of the traditional pure BP neural network, such as subjecting to the randomness of initial weights, slow convergence speed, low efficiency, easy to fall into local extreme value, in this paper we proposing an optimal BP network fusing with the genetic algorithm using in bridge health assessment. The optimized BP network algorithm has a good diagnosis effect, and improves the calculation accuracy and speed of the identification of bridge structure damage.

For the issue of being difficult to carry out various experiments of vehicle braking systems, a real-time simulation platform which is an vehicle braking pressure based on xPC Target is proposed. In the design of platform, the method is studied through writing CS-function driver development. Under MATLAB RTW, the problems of hardware simulation in the loop to support I / O device is resolved in xPC Target toolbox. Upon the analysis of the basic principles and structure of the driver, the solution to the key issues such as register operation and base seeking address are studied. And PCI-1710 driver is developed. The verifications about the driver validation of the data acquisition card and closed-loop regulation to the vehicle braking pressure are completed with the platform. The experimental results show that the A / D sampling frequency of acquisition card can be up to 10 kHz, signals can be displayed in real time and the test platform can be long-running. The development process is stable. Pressure waveforms consistent with the waveforms measured by the oscilloscope. The braking pressure can be adjusted by the real-time simulation platform. A new experimental method is provided for research on the vehicle braking performance.