Advanced Materials Research Vols. 846-847

Abstract: This paper studies about two parts :one is about principle and construction of the equivalent capacitive output impedance of inverter, the other is that through comparing different compensation strategy of the application of simulation experiment, and verify the effect of C-Inverter.1) In this paper we study the droop control characteristics of three types of inverters with inductive, resistive and capacitive equivalent output impedance respectively, and use the virtual impedance to get C-Inverter in wind power.2) This paper sets up SVC and STATCOM models and improved the converter which changes to capacitive inverter in DIgSLIENT, which are connected to wind power system, verifying the validity of SVC and STATCOM models and the effect of C-Inverter.

Abstract: Active frequency drift islanding detection method is one of most widely used in the distributed generator islanding detection. Now domestic researches of islanding detection have not been done deep researched about the reason why islanding detection method will become invalid. Therefore, the paper analyses the performances of the frequency drift islanding method from load phase frequency characteristic and algorithm phase frequency characteristic, which are the major factors affecting the effectiveness of islanding detection method. At last, this paper proved the analysis results with MATLAB.

Abstract: For the purpose of life prediction of smart meters, an analysis on the method of sampling inspection for smart meter with mathematical statistics is presented in this paper. Firstly, this paper introduces the sampling approaches for smart meters for inspection. Secondly, the mathematical model of sample size is established and the effect of sampling parameter on the accuracy of evaluation is discussed. Finally, on the basic of the mathematical model, the smart meters in Hei Longjiang province of China is token as an example and the sampling size is achieved.

Abstract: Nowadays, smart meters are widely used in power grid, which plays an important role in building the smart power grid and its stability is the key to stable operation of the grid. However, the reliability prediction of the smart meters is difficult to be performed due to its huge number and it cannot be tested one by one. In order to study the prediction method, according to the working principle of smart meters, this paper presents a simulation smart meter model based on Matlab/Simulink software. And related experiments are performed to measure the power consumption under different loads, through comparing the measured power consumption between the simulation model and power analyzer, the correctness of the presented model is verified.

Abstract: A new technology named Direct Digital Synthesizer, DDS technology, was applied on a FPGA chip to design a signal generator which can produce periodic waveforms, and its frequency, phase and amplitude were all adjustable. Since the DDS technology has the function of frequency and phase adjustment, no additional circuits are needed in design. The theoretical model was built and the programs for each module were well developed. Using Modelsim software, three signal waveforms were simulated corresponding to sine, triangle, and square signals. The theoretical and simulation results show that the combination of DDS technology and FPGA can generate arbitrary waveforms in theory, while the hardware system fabricated has strong capability of anti-jamming.

Abstract: If plants absorb too little water and the cells in plant leaves is not full, there might exist atrophy characteristic distortion of the cell concentration of leaf and leaf morphological characteristic. Traditional algorithm carries out deformation measurement for withered leaf based on cell concentration characteristics and leaf morphological characteristics. Once the character distorted, characteristic parameters of leaf cell sap will be inaccurate reducing the measurement accuracy for withered leaf deformation. Therefore, we propose a computer vision-based plant leaves wilt deformation measurement method. The experimental results show that this algorithm significantly improves the accuracy of the measurement.

Abstract: Conventional communication control methods cannot solve the Doppler frequency shift problem in high-speed moving network communication of EMU. The shift phenomenon in signal propagation, the high error rate and the low transmission efficiency make it's unable to ensure the stability of the high-speed communication network. Therefore, the paper designs the control model accordance with fuzzy estimation and data communication error correction for stability control of EMU network communications. Experimental results show that under the method delay and bandwidth changes of EMU communication is relatively stable, which means that the method can achieve high efficiency, high precision control for EMU network communication, and with a high application value.

Abstract: Wireless network control system is characterized by high uncertain delay time, thus the state of the system can not be fully observed. The fault characteristic is interfered by time delay so to be unstable, leading inaccurate fault detection. Traditional fault detection method of wireless network control system is usually based on the characteristics of the stability of the network status data. If the network has time delay fluctuations, it is unable to obtain accurate fault detection results. This paper presents a stochastic delay fault detection method. It builds a state space model of the system, analyzes the delay vector between the sensor end of the system and the controller end, depending on the delay residual signal of the system and the corresponding evaluation function to obtain the system failure detection result. The final simulation result shows that this method has high accuracy in the detection of Stability and randomness of the wireless network fault detection. Thus it is an effective wireless network control system fault detection method.

Abstract: Wireless network control system has high failure rate, and is difficult to be diagnosed. Wireless network transmission signal effectively reflect the failure categories. In order to effectively detect the wireless network control system fault, this paper presents a fault detection method of correlation dimensional nonlinear timing characteristics for wireless network transmission signal, which mainly improves the traditional correlation dimension extraction algorithm. The method processes and analyzes the collected transmission signal of four types wireless network control system in fault condition, and then extract fault feature through an improved correlation dimension algorithm. It improves the calculation accuracy of the correlation dimension with a standard deviation 15% -30% than that of the traditional algorithm, and it significantly enhances the clustering distribution characteristics, reflecting its superiority in fault detection. Fault detection results show that the improved feature extraction method for correlation dimension can effectively detect failure in wireless network control system, whose accuracy is improved by 21.4%, and has great practical value.

Abstract: Sensor technology is one of the most rapid development technologies in the world, we cant leave without it. The bioremediation of waste acidic water in mining industry are the hot topic in the world. It is our focus of this paper to measure the pressure in the reactor to obtain the growth status of sulfate reducing bacteria (SRB) using pressure sensor.