Advanced Materials Research Vols. 433-440

Abstract: Because of nonparametric detectors’ ability of ensuring constant false alarm rate (CFAR) for a wide class of input noise distributions and engineering implementation simply, much efforts have been directed towards the study of nonparametric methods of signal detection. This paper deals with a comparative analysis of nonparametric detectors-GS, MW, Savage detector under K-distributed clutter in homogeneous and nonhomogeneous background caused by multiple targets and clutter edge. Some results of detection probability versus signal-to-clutter ratio (SCR) are presented in curves for different detector parameter values in homogeneous and multiple targets background. And the ability to control the false alarm probability for the three nonparametric detectors is presented in table. The simulation results show that S detector performs robustly in homogeneous background and clutter edge background, and can tolerate more interfering targets through increasing the number of reference cells and pulse sweeps. Therefore as a compromise solution, S detector with moderate parameters can be used in actual radar system.

Abstract: This paper presents a building detection approach based on HSV color space. The method is based on the gray level histogram features, which can separate the housing construction units from complex background. A building damage detection algorithm based on regional statistical information is also proposed in this paper, and a set of performance parameters of feature vector is studied to identify the extent of the housing collapse. The experiments on Haiti post-earthquake images from Google Earth and Yushu post-earthquake images from Internet are discussed in the paper. The experimental results show that proposed approach is effective and feasible.

Abstract: A new faults classification method based on on-line independent support vector machine (OISVM) is proposed for fault diagnosis in nonlinear processes. Fault diagnosis can be taken as a pattern recognition problem. As most processes are intrinsically nonlinear, support vector machines (SVMs) are one of the most popular and promising classification algorithms. The fatal drawbacks of standard SVM is the computing overhead grows with the number of training samples, where as training samples from real industrial processes are increasing with time grows. An incremental fault diagnosis approach based on OISVM is proposed in this work. Some related problem such as variable selection and parameter setting are also discussed in this work. Simulation results on the Tennessee Eastman process (TEP) demonstrate the effectiveness of the proposed method.

Abstract: With the fast development of electronic industry,the techniques of testing electronical system have varied from traditional functional test to structured test accordingly.The principel of functional test is presented in this paper and the representative techniques of structured test, as in-circuit test(ICT),boundary-scan test(BST),build-in self-test(BIST) and scan-path test,are explored subsequently.Finally,the developmenting trends in the future are looked forward to.

Abstract: Detecting and characterizing the community structure of complex network is fundamental. We compare the classical optimization indexes of modularity and modularity density, which are quality indexes for a partition of a network into communities. Based on this, we propose a quantitative function for community partition, named communitarity or C value. We demonstrate that the quantitative is superior to modularity Q and modularity density D. Both theoretical and numerical results show that optimizing the new index not only can resolve small modules, but also can correctly identify the number of communities.

Abstract: This paper introduces the research and development of the temperature measurement system using wireless network based on ZigBee protocol. The system consists of network coordinator and a number of nodes. The structural and functional design for the nodes highlights the characteristics of industrial applications, and is of a certain reference value on research and development of industrial wireless sensor systems.

Abstract: Bone image segmentation is the important technology for computer aided bone diagnosis system and the foundation for three-dimensional visualization of the human skeleton. Agent searching edge detection algorithm for bone images is proposed. Based on neighbor region correlation and regional harmonic mean feature vector correlation, different species of agent accomplish searching bone edge and experimental results are satisfactory. Experimental results comparison about the proposed algorithm, Prewitt, Sobel, Log and Canny is illustrated that demonstrates the proposed algorithm has advantages in some respects.

Abstract: In this work, the application of time delay estimation in ultrasonic wind speed measurement system is discussed. The algorithm of time delay estimation based on least mean square (LMS) adaptive noise cancellation of generalized correlation with fixed ultrasonic is presented. The algorithm uses LMS daptive filter to eliminate the noise interference efficiently and does not need to know prior-knowledge of signal and noise. Then, it uses generalized correlation to estimate the time delay. Computer simulation and practical test results show that the algorithm can effectively eliminate noise. The wind speed estimation accuracy is very high; so the algorithm can be used for monitoring the low-level wind field at airport regional.

Abstract: In power systems there are many non-linear loads, the resulting harmonics on the power quality can cause great impact to the power system. Thus it is important to monitor and analyze harmonics generated by these equipments in order to get a better power quality. In this paper, we firstly analysis the theoretical foundation of the harmonic measurement. Secondly, by use of the experimental data received from oscilloscope, we calculate and analyze the harmonic currents by using the tool of FFT in MATLAB. The method is of universal applicability, particularly compared with the expensive power analyzing equipments, which may be a good alternative.

Abstract: Carrying out the fault diagnosis of water-steam chemistry process in power plant has an important significance to ensuring high qualified rates of water and steam quality as well as maintaining safe operation of units. This paper proposed a fault diagnosis method based on improved credibility theory which is used to construct fuzzy diagnosis rules and data mining technique used to determine symptom weights and rule limens of reliability rules, and also improved the setting method of rule confidence. The adoption of data mining technique and new setting method of rule confidence can solve the problem that credibility reasoning results are influenced by person’s subjective factors, and make the reasoning process more scientific. Example results prove that this diagnosis model has a high accuracy, which indicates the significant practical value of the model.