利用微机求取测线交点桩号和井桩号

本文介绍了在微机上利用野外测量成果计算测线交点桩号和井桩号的原理和方法,并编制了相应微机程序。本程序灵活,方便,实用性强,具有下列特点:(1)计算结果既能以表格形式输出,又能以测线底图形式输出;(2)数据库能方便地增删和修改,并能简捷地输出新成果。应用结果表明,这种方法消除了人为误差和随比例尺引入的误差,避免了繁琐的人工劳动,极大地提高了精度和效率。

阿尔及利亚两期施工物探测量方法分析

阿尔及利亚一期地震采集项目采用的是我国SY/T 9171-2003《石油物探测量规范》进行测量施工,二期地震采集项目采用的是阿尔及利亚国家石油公司索纳塔克的测量技术标准进行测量施工。本文通过对这两期物探测量方法的对比、分析,总结出了两种不同技术标准对物探生产的影响,并对我国新实行的SY/T 9171-2011《陆上石油物探测量规范》提出了一些建议。

408UL地震仪排列绕道参数快速设置方法研究

法国SERCEL公司生产的408UL数字遥测地震仪,采集道数多、排列布设灵活、生产效率高。但是,在山地、水网等复杂地表施工时,系统绕道设置费时且极易出错。针对这一问题,尝试利用OFFICE的EXCEL电子表格软件直接生成绕道设置文件,不但能大大提高绕道设置效率,缩短排列生成时间,而且还能为进一步发挥408UL地震仪仪器的优势提供技术上的支持。

Traffic light detection and recognition in intersections based on intelligent vehicle

To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.

Feasibility investigation on deep ocean compact autonomous Raman spectrometer developed for in-situ detection of acid radical ions

A newly developed Deep Ocean Compact Autonomous Raman Spectrometer （DOCARS） system is introduced and used for in-situ detection of acid radical ions in this paper. To evaluate the feasibility and capability of DOCARS for quantitative analysis of the acid radical ions in the deep ocean, extensive investigations have been carried out both in laboratory and sea trials during the development phase. In the laboratory investigations, Raman spectra of the prepared samples （acid radical ions solutions） were obtained, and analyzed using the method of internal standard normalization in data processing. The Raman signal of acid radical ions was normalized by that of water molecules. The calibration curve showed that the normalized Raman signal intensity of SO4^2-, NO3^-, and HCO^-3 increases linearly as the concentration rises with correlation coefficient R^2 of 0.99, 0.99, and 0.98 respectively. The linear function obtained from the calibration curve was then used for the analysis of the spectra ,data acquired in the sea trial under a simulating chemical field in the deep-sea environment. It was found that the detected concentration of NO3 according to the linear function can reflect the concentration changes of NO~ after the sample was released, and the detection accuracy of the DOCARS system for SO^2-_4 is 8%. All the results showed that the DOCARS system has great potential in quantitative detection of acid radical ions under the deep-sea environment, while the sensitivity of the DOCARS system is expected to be improved.

Monitoring damage evolution of steel strand using acoustic emission technique and rate process theory

Utilizing the acoustic emission(AE) technique, an experimental investigation into the damage evolution for steel strand under axial tension was described. The damage evolution model for steel stand relating the damage evolution to acoustic emission parameters was proposed by incorporating the AE rate process theory. The AE monitoring results indicate that damages occur in both elastic and plastic phases of steel strand. In elastic phase, AE signals are mainly sent out from the micro damage due to the surface friction among the wires of steel strand, while in plastic phase, AE signals emitted from the plastic deformation of wires. In addition, the AE cumulative parameters curves closely resemble the loading curve. The AE cumulative parameters curves can well describe the damage evolution process including the damage occurrence and damage development for steel strands. It is concluded that the AE technique is an effective and useful nondestructive technique for evaluating the damage characteristics of steel strand.

AN ADAPTIVE MOVING TARGET TRACKING ALGORITHM FOR SMART ANTENNA SYSTEMS

In wireless communication environment, the time-varying channel and angular spreads caused by multipath fading and the mobility of Mobile Stations (MS) degrade the performance of the conventional Direction-Of-Arrival (DOA) tracking algorithms. On the other hand, although the DOA estimation methods based on the Maximum Likelihood (ML) principle have higher resolution than the beamforming and the subspace based methods, prohibitively heavy computation limits their practical applications. This letter first proposes a new suboptimal DOA estimation algorithm that combines the advantages of the lower complexity of subspace algorithm and the high accuracy of ML based algo- rithms, and then proposes a Kalman filtering based tracking algorithm to model the dynamic property of directional changes for mobile terminals in such a way that the association between the estimates made at different time points is maintained. At each stage during tracking process, the current suboptimal estimates of DOA are treated as measurements, predicted and updated via a Kalman state equation, hence adaptive tracking of moving MS can be carried out without the need to perform unduly heavy computations. Computer simulation results show that this proposed algorithm has better per- formance of DOA estimation and tracking of MS than the conventional ML or subspace based algo- rithms in terms of accuracy and robustness.

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

Instantaneous frequency estimation of multi-component Chirp signals in noisy environments

A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate the 1F of a multi-component Chirp signal accurately. Wigner distribution maxima （WDM） are usually utilized for this estimation. But in practice, estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal 1F estimation named Wigner Viterbi fit （WVF）, based on Wigner-Ville distribution （WVD） and the Viterbi algorithm. First, we transform the WVD of the Chirp signal into digital image, and apply the Viterbi algorithm to separate the components and estimate their IF. At last, we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments, and better suppression of interference and the edge effect. Compared with WDM, WVF can reduce the mean square error （MSE） by 50% when the signal to noise ration （SNR） is in the range of-15dB to -11dB. WVF is an effective and promising 1F estimation method.

JOINT SPACE-FREQUENCY MULTIUSER SYMBOL DETECTOR FOR MC-CDMA SYSTEM WITH UNIFORM LINEAR ARRAY

The MultiCarrier Code Division Multiple Access (MC-CDMA) scheme is promising for relieving capacity limit problems of Direct Sequence (DS-) CDMA systems due to serious InterChip Interference (ICI) and MultiUser Interference (MUI) in high-data-rate wireless communication systems. In this paper, the Uniform Linear Array (ULA) is applied to the base station of macrocellular MC-CDMA systems in a frequency-selective fading channel environment. A joint space-frequency multiuser symbol sequence detector is developed for all active users within one macrocell without space-frequency channel estimation. Simultaneously, Directions-Of-Arrivals (DOAs) of all active users can also be estimated. By dividing the ULA into two identical overlapping subarrays, a specific auxiliary matrix is constructed, which includes both symbol sequence and DOA information of all active users. Then, based on the subspace method, performing the eigen decomposition on such auxiliary matrix, the closed-form solution of symbol sequences and DOAs for all active users can be obtained. In comparison with schemes based on channel estimation, our algorithm need not explicitly estimate the space-frequency channel for each active user,so it has lower computation complexity. Extensive computer simulations demonstrate the overall performance of this novel scheme.

Seasonal Effect on Atmospheric Refractivity in Diverse Terrains

Air masses in the atmosphere have contrasting temperature, humidity and moisture, which influence radio signals traversing the atmosphere. The influence of the atmosphere on refractivity is strongly determined by its temporal and spatial variability. This paper uses meteorological measurements to investigate the impact of meteorological structures on diverse environments evident in Nigeria. The study hypothesises that refractivity measures could serve as indicators of diurnal radio wave degradation traversing the atmosphere.

AN EFFICIENT APPROXIMATE MAXIMUM LIKELIHOOD SIGNAL DETECTION FOR MIMO SYSTEMS

This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search points in each transmit antenna signal constellation instead of all hy-perplane. Both of the selection and search complexity can be reduced significantly. The method per-forms the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.

Mixing matrix estimation of underdetermined blind source separation based on the linear aggregation characteristic of observation signals

Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.

Experimental Evaluation of Rogowski Coil Performance for Locating PD in Energized Overhead Covered-Conductor Feeder

An experimental analysis is performed to evaluate Rogowski coil performance for PD （partial discharge） location on overhead CC （covered-conductor） distribution lines. The measuring set-up is arranged in high voltage laboratory. A multi-end measuring method is chosen as a technique to locate PD source point on the line. A power transformer is used to energize one end of the CC line by the AC voltage source. The performance of Rogowski-coil is tested in noisy environment. The tests are carried out conceming different measurement conditions such as off-line and on-line PD measuring systems. The results obtained from the laboratory measurements confirm the capability of the Rogowski-coil in order to measure and locate the high frequency PD source on the CC line in consistent with energizing AC source. Chirp detector is used as a signal-processing tool in order to extract the PD signals and then apply the locator algorithm.

An Experience of On-site PD Testing for Condition Monitoring of an 11 kV PILC Cable Insulation System

A cable circuit of a substation in the United Kingdom showed high level of PD activities during a survey using hand hold PD testing equipment. The authors were invited to carry out on-site PD testing experiment to further diagnose and locate the potential problem of the cable system. This paper presents the experience of the present authors carrying out the cable test. Following a brief introduction to the experiment equipments and physical connections, the paper analyses the data collected from the testing, including PD pulse shape analysis, frequency spectrum analysis and phase resolved PD pattern analysis. Associated with PD propagation direction identification, PD source diagnosis and localisation was made. Four different types of sensors, which were adapted during the testing, are shown to have different frequency bandwidths and performed differently. Aider comparing the parameters of the sensor and the PD signals detected by individual sensor, optimal PD monitoring bandwidth for cable system is suggested.

Analysis and prediction of loudspeaker large-signal symptoms

Nonlinear lumped-parameter force factor Bl(x), stiffness Kms(x) and inductance Le(x) of electrodynamic loudspeakers change frequency responses and generate some nonlinear effects for large stimulus: harmonic and intermodulation distortion, DC component in diaphragm displacement, instability of vibration and jumping effects. By modeling the nonlinear system under large-signal conditions, relationship between the nonlinear parameters and large-signal behavior can be revealed and help to provide guidance to diagnose loudspeakers. Agreement between the measured and predicted responses of a real loudspeaker validates the modeling and enables new methods for loudspeaker diagnosis.

A new image processing method for discriminating internal layers from radio echo sounding data of ice sheets via a combined robust principal component analysis and total variation approach

Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely used for improving the signal to noise ratio(SNR)and discriminating internal layers by radio echo sounding data of ice sheets.This method is not efficient when we use edge detection operators to obtain accurate information of the layers,especially the ice-bed interface.This paper presents a new image processing method via a combined robust principal component analysis-total variation(RPCA-TV)approach for discriminating internal layers of ice sheets by radio echo sounding data.The RPCA-based method is adopted to project the high-dimensional observations to low-dimensional subspace structure to accelerate the operation of the TV-based method,which is used to discriminate the internal layers.The efficiency of the presented method has been tested on simulation data and the dataset of the Institute of Electronics,Chinese Academy of Sciences,collected during CHINARE 28.The results show that the new method is more efficient than the previous method in discriminating internal layers of ice sheets by radio echo sounding data.

On-line chatter detection using servo motor current signal in turning

Chatter often poses limiting factors on the achievable productivity and is very harmful to machining processes. In order to avoid effectively the harm of cutting chatter,a method of cutting state monitoring based on feed motor current signal is proposed for chatter identification before it has been fully developed. A new data analysis technique,the empirical mode decomposition(EMD),is used to decompose motor current signal into many intrinsic mode functions(IMF) . Some IMF's energy and kurtosis regularly change during the development of the chatter. These IMFs can reflect subtle mutations in current signal. Therefore,the energy index and kurtosis index are used for chatter detection based on those IMFs. Acceleration signal of tool as reference is used to compare with the results from current signal. A support vector machine(SVM) is designed for pattern classification based on the feature vector constituted by energy index and kurtosis index. The intelligent chatter detection system composed of the feature extraction and the SVM has an accuracy rate of above 95% for the identification of cutting state after being trained by experimental data. The results show that it is feasible to monitor and predict the emergence of chatter behavior in machining by using motor current signal.