Shu Wang

A method research on fire source localization using dual-line gas sensor array

Fire source localization is an important direction in the research area of fire detection. For application researches of fire source localization in fire nonage, a method of fire source localization and its algorithm are presented in the paper, via. transforming the task of fire source localization to the orientation detection of gas signal source beneath the certain conditions, in which a mode of dual-line gas sensor array is applied to collect the gas concentration signal in real time when material burning in fire nonage and time delay of the signal obtained from various array elements in the condition of different concentration grads is used to perform the orientation estimation of signal source based on time delay estimation. Furthermore, the simulation of the method is done, and it is indicated that the method has fine veracity and robustness for estimating the orientation of gas signal source and locating the fire source.

An algorithm for carbon monoxide concentration detection based on molecular multi-relaxation model

In this paper, we focus on the relaxation process of acoustic waves in polyatomic gases, and build up a multi-relaxation algorithmic model of a gas mixture of nitrogen, oxygen, water vapor and carbon monoxide. The model is basing on the complicated transfer mechanism of vibrational-translational, vibrational-vibrational degrees of freedom. By computing acoustic velocity and relaxation attenuation, which is depend on the composition of the gas mixture, acoustic frequency, temperature, and pressure, we notice that changes in carbon monoxide concentration have great influence on these acoustic characteristics of the mixture. Thus it proves the feasibility of detecting carbon monoxide by means of molecular acoustic method. Finally, we describe a detailed model to measure proportion of carbon monoxide. This novel approach not only determines the concentration of carbon monoxide, but also reflects other gases proportional fluctuations of the mixture, such as water vapor.

An Algorithm of Feeble Gas Signal Recognition for Bioenergy Detection Using Wireless Sensor Network

For realizing the rules of microorganisms living behavior and detecting the distribution of its bioenergy, the method research of recognizing feeble biology signal using wireless sensor network for signal detection is discussed in the paper. An algorithm of feeble signal recognition for the gas releasing from organisms is presented, which is based on rough set mathematically. In the algorithm computation, the fractal characteristics of signal space are acquired from disorder signal space constructed by feeble gas sampling signals. And then the simulation of algorithm is given in order to show the proposed approach having fine robustness and accuracy for recognizing feeble biology signal applied in the area of biology information.

A novel nonuniform sampling method and processing system to overcome the Nyquist limit and suppress the noise

A method for nonuniform sampling based on amplitude of signals is proposed. It combines sampling rate with amplitude of signals. It make the most of some special samples that it helps to process signal so it is very effective to suppress noise. A sampled threshold should be computed and selected automatically in this algorithm. The mean and maximum amplitudes of signal decide the sampled threshold. It can estimate exactly the frequency of signal hidden beneath the noise when signal-to-noise ratio (SNR) is below -15 dB. The system can detect the signal above 18 MHz at the maximal sampling of 1.5 MHz, achieving 24 times the bandwidth of a classic uniformly digital signal processing (DSP) system that only can detect the signal above 0.75 MHz at the sampling of 1.5 MHz.

CogDFH- a Cognitive-Based differential frequency hopping network

Cognitive radio (CR) is a revolutionary wireless mobile communication technology. Smart users can use the CR technology to sense the surrounding environment, search for available spectrum resources and access spectrum dynamically. Differential frequency hopping (DFH) is known as an effective FH technique for increasing data rate of HF communication system. In this study, the cognitive radio technology was applied in DFH, and a CogDFH network was proposed. This network which is built upon the interference temperature model, IC-colorings and IC-indices of graphs, was applied to the DHF network with easy build, high robustness and low interference. The scenario simulations of both Cognitive-Based DFH Network and traditional DFH were performed. The results indicate that the network performance can be improved by CR.

Performance of nonuniform sampled signal with MUSIC algorithm

The channel outputs are sampled on nonuniform sampling sets, and an analysis of the sensitivity of MUSIC algorithm with nonuniform sampling (NUS) is investigated. It is demonstrated that it may be capable to select the nonuniform sampled received signal of interesting using MUSIC algorithm. NUS in the time domain is equivalent to construct a virtual nonuniform array through a virtual array transformation, which expands the relative phase difference of the received signal at the different sensors just as that of nonuniform linear array (NLA) arising by the antenna placement. Simulations are conducted to verify that using NUS is beneficial to reduce the system complexity as sampling wide frequency signals at low sampling rate, and greatly improve the DOA estimation performance in lower SNR than using typical uniform sampling with MUSIC algorithm.

DOA Estimation of Coherent Signal Using MUSIC Algorithm with Nonuniform Sampling

The channel outputs are sampled on nonuniform sampling sets, and an analysis of the decorrelation based on nonuniform sampling (NUS) is investigated. It is demonstrated that MUSIC algorithm with NUS of various array elements may be capable of selecting the signal of interesting including the coherent group. NUS in the time domain is equivalent to alter the relative distance between sensors and leads to the radiant sources impinging the different arrays between two snapshots just as a virtual array spatial smoothing preprocessing. Simulations are conducted to verify that MUSIC based on nonuniformity of sensor sampling is effective to estimate direction-of-arrival (DOA) of incident signals in the coherent environment. Simultaneously, its beneficial to greatly improve the estimation accuracy and angular resolution as a result of larger array aperture introduced but no angle-measure ambiguity and offer a better performance in lower SNR than weighted spatial smoothing (WSS) with MUSIC algorithm.

Developed Acoustic Multi-relaxation Algorithm for Humidity Measurement in Gas Mixtures

In this paper, we focus on the relaxation process of acoustic waves in polyatomic gases, and build up a multi-relaxation algorithmic model of a gas mixture of nitrogen, oxygen and water vapor. The algorithmic is basing on the complicated transfer mechanism of vibrational-translational, vibrational-vibrational degrees of freedom. By computing acoustic velocity and relaxation attenuation, we notice that changes in water vapor concentration have great influence on the relaxation frequency of the mixture, thus proving the feasibility of detecting humidity by means of relaxation method. Finally, we describe a detailed algorithm to measure proportion of water vapor. This novel approach not only determines the concentration of water vapor, but also reflects the proportional fluctuation of the mixture.

Research on Detection Method of Uncertainty Fire Signal Based on Fire Scenario

For a safe evacuation of people in fire, which is a serious disaster to damage the security of peoples lives and possessions, the fire signal for alarm is accurately detected and recognized in a period of early or extremely early fire time which people wanted in possible. At the same time, the accuracy and validity of fire detection is greatly weakened by reason of increasing uncertainty of fire signal. Therefore a new approach is presented for the detection of uncertainty fire signal based on fire scenario, which its algorithm in the detection of one-dimension fire space is given in order to show the proposed method having fine fault-tolerance, robustness and accuracy. In this method, a certain character of fire space fractal in the detected fire space is obtained firstly by a performance analysis of fire scenario, and then a character of signal space fractal is acquired by using intelligent method based on rough set theory and trend fusion to process the multi-source signal detected from a group of fire detectors, when a logical coincident relationship between the two characters recognized, a real fire alarm is produced lastly

A method improving accuracy of self-localization in wireless sensor networks

Determining the location of nodes with error as low as possible in wireless sensor networks is an essential task for many applications. It can be shown that, in some case, evident location estimation errors would be brought even if the ranging error is low. This work involves a parameter called geometry favorable factor (GFF) to filter these ill case. We propose an improving method choosing the available beacon nodes (nodes with prior known locations) with the best GFF for sensor location estimation. Simulation results show that the improving method lead to a significant improvement in location estimation accuracy compared with normal method that without filtering, while some decrease in population of localizable nodes.