Steady-state torque control system with secondary-current feedback for three-phase squirrel-cage induction motors

This paper presents a highly stable steady-state torque control system with a feedback of a secondary current signal. The torque control system is constructed with a feedback of the secondary current (I₂) signal using a quick response magnetic-field sensor constructed with an amorphous core multivibrator bridge, which can solve the secondary resistance change problem for temperature variation in the IM. Moreover, we added a state feedback to the system to improve the response speed for the unit step function of a torque order. The I₂ sensor method has advantages especially at a low-speed range, in which conventional method using an integrator shows control errors.     

Development of cable fault location method using fiber optic distributed temperature sensor

When ground-fault problems occur on a cable line, immediate fault location and restoration are required. Therefore, various new methods to locate the fault point instantaneously have been investigated to replace such conventional methods as the Murray loop method and the pulse radar method [1]. These methods require a long time to locate the fault point. One possible fault location method is to sense the temperature rise following a ground fault using a fiber optic distributed temperature sensor. Application of this method was found feasible through sensing the temperature rise at a ground-fault test using a thermocouple as a temperature sensor with test cables [4]. A power/optical composite cable was prepared experimentally and after verifying its thermal mechanical performance, the temperature rise at an incidence of a fault was determined and the anticipated performance was demonstrated in a ground-fault test. This article describes the outline of the test.     

A social interaction system based on cloud computing for mobile video telephony

As the use of smartphones become popular,people heavily depend on smartphone applications to deal with their social activities.For this reason,traditional message texting between mobile applications does not fulfill the versatile requirements of social networking.Many mobile applications use multimodality to deliver multimedia messages including sticker,voice and photo message,video call,and snap movie to enhance the communicative capability.However,without face-to-face interaction,people may fail to detect the other side’s non-verbal social behavior such as fine-grain facial expressions,body movements,or hand gesture.During social interaction,non-verbal behavior conveys information about the involved individuals and help the speakers express their social emotion in an implicit way.It is so important for real-world face-to-face interaction but is often blocked on the mobile telephony.To cope with this problem,we propose an afective computing model to assist the representation of social emotion and then help the progress of social interaction on the mobile telephony.In this model,for the purpose of real-time afective analysis,we delegate the computing loading to the cloud side service and enhance the system’s scalability and availability.The result of this experiment approves the feasibility of our system design for the applications of social intelligent.Also,the system provides a research framework of the social intelligent system on the mobile telephony.     

基于超声传感技术在污水旋流池测量中的应用

为了能够准确地测量污水旋流池的液面高度,设计了基于超声传感技术的污水旋流池液面测量方法,通过长时间的运行,测量数据完全满足污水旋流池的生产工艺要求。     

智能投币机在城市公交上使用的改进分析

通过鱼骨图的方法对现有智能公交投币机存在识别率偏低的问题进行了分析,提出在智能投币机中采用闭式五角叶轮或增加硬币预处理部分,对现有的智能公交投币机进行改进,使智能公交投币机的硬币辨识率得到提高.     

Evaluation of the coupled multielectrode array sensor as a real-time corrosion monitor

Coupled multielectrode array sensors made of carbon steel and stainless steels were evaluated and compared with electrochemical noise (EN) sensors. Good correlations between sensor signals and solution corrosivity were observed for all multielectrode array sensors. Some correlation between the average pit index and solution corrosivity was observed for the carbon steel EN sensors, but not for the stainless steel EN sensors. The time-average noise resistances from the stainless steel EN sensors correlate well with solution corrosivity. There were, however, large random fluctuations and drifting for all EN signals, which make the EN sensors unreliable as real-time monitors.     

Evolutionary circuit design for fast FPGA-based classification of network application protocols

The evolutionary design can produce fast and efficient implementations of digital circuits. It is shown in this paper how evolved circuits, optimized for the latency and area, can increase the throughput of a manually designed classifier of application protocols. The classifier is intended for high speed networks operating at 100 Gbps. Because a very low latency is the main design constraint, the classifier is constructed as a combinational circuit in a field programmable gate array (FPGA). The classification is performed using the first packet carrying the application payload. The improvements in latency (and area) obtained by Cartesian genetic programming are validated using a professional FPGA design tool. The quality of classification is evaluated by means of real network data. All results are compared with commonly used classifiers based on regular expressions describing application protocols.     

Evaluation of tile–wall bonding integrity based on impact acoustics and support vector machine

It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy.     

An ant direction hybrid differential evolution heuristic for the large-scale passive harmonic filters planning problem

This article presents a heuristic which combines the orthogonal array experiment technique and an ant direction hybrid differential evolution algorithm (ADHDEOA) for planning of a large-scale passive harmonic filters problem. The addressed problem has a multi-bus and under abundant harmonic current sources in the system. In this study, an orthogonal array is first conducted to obtain the initial solution. Next, an ant direction hybrid differential evolution (ADHDE) is applied to search for a near optimum solution. The objective is to minimize the cost of the filter, the total demand distortion of harmonic currents and the total harmonic distortion of voltages at each bus simultaneously. In order to determine a set of weights of each term in the objective function, the simplest and most efficient form of triangular membership functions has been considered. The designed heuristic ADHDEOA is applied to a practical harmonic problem in a steel plant, and three design schemes are compared to demonstrate the performance of the ADHDEOA.