梅山铁矿多级机站通风系统机站局阻研究

通过对多级机站通风系统局阻的研究 ,找到了机站局阻的范围 ,并在新机站的设计过程中加以应用 ,降低了机站投资 ,减小了机站局阻 。

矿井多级机站可控式通风系统的研究与实践

本文对矿井多级机站可控式通风系统研究工作作总结,并列举了工业应用情况,说明多级机站可控式通风技术是一种节能、易于风量调节等特点的新技术。

梅山多级机站通风系统压力分布研究

根据梅山铁矿多级机站通风系统的测定结果 ,对二期系统的优化方案进行了网络解算 ,分析了整个通风系统的压力分布情况 。

Cellular manufacturing layout on adding/removing machines

In order to rapidly respond to the complex and mutational market, a new facility layout plan based on cellular manufacturing is proposed, which gives consideration to high efficiency and flexibility. The plan designs two phases of integrated cell layout, i.e., cell construction and cell system layout, on the condition of adding/removing machines. First, in view of the costs of logics and machine-relocation, the cell construction based on the alternative processing routes and intra-cell layout are integrated as a whole, which achieves cell formation, process planning and the intra-cell layout in a single step. Secondly, an approach of a continuous optimized multi-line layout for solving the cell system layout problem is proposed, which eliminates the coupling relationship from the machine-relocation and realizes an integrated design of the two phases of the cell layout. An application based on real factory data is optimally solved by the Matlab 7.0 software to validate and verify the models.

Seismic random noise suppression using an adaptive nonlocal means algorithm

Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods （e.g., f-x deconvolution）, which is important for subsequent seismic processing and interpretation.

CMOS Mixers for 2.4GHz WLAN Transceivers

A down-conversion mixer and an up-conversion mixer for 2.4GHz WLAN transceivers are presented.The down-conversion mixer uses a class-AB input stage to get high linearity and to realize input impedance matching and single-ended to differential conversion.The mixers are implemented in 0.18μm CMOS process.The measured results are given to show their performance.

Integrated Low-Power CMOS VCO and Its Divide-by-2 Dividers

An integrated low power CMOS VCO and its divide by 2 dividers for WLAN transceivers are presented.The VCO is based on on chip symmetrical spiral inductor and differential diode and the divide by 2 dividers are based on the ILFD technique.Due to differential LC tanks and ILFD techniques,power consumption is low.The circuit is implemented in a 0 18μm CMOS process.Measurements show the proposed circuit could produce 3 6/1 8GHz dual band LO signals with a wide tuning range and low phase noise.1 8GHz LO signals are quadrature.It consumes 5mA at V DD =1 5V.The size of die area is only 1 0mm×1 0mm.

Generation of scale-free knowledge network with local world mechanism

In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribution of the knowledge network is given, which is verified by Matlab simulations. When the new added node＇s local world size is very small, the degree distribution of the knowledge network approximately has the property of scale-free. When the new added node＇s local world size is not very small, the degree distribution transforms from pure power-law to the power-law with an exponential tailing. And the scale-free index increases as the number of new added edges decreases and the tunable parameters increase. Finally, comparisons of some knowledge indices in knowledge networks generated by the local world mechanism and the global mechanism are given. In the long run, compared with the global mechanism, the local world mechanism leads the average knowledge levels to slower growth and brings homogenous phenomena.

A Low Noise,High Linearity CMOS Receiver for 802.11b WLAN Applications

A 2.4GHz monolithic CMOS receiver with direct-conversion architecture is presented. This quadrature receiver is designed for 802.11b wireless LAN applications at the maximum data rate of 11Mbps as a low-cost solution. Five key blocks,i, e., a low noise amplifier （LNA）, a down-conversion mixer, a variable gain amplifier, a low pass filter, and a DC- offset cancellation circuit,are designed based on system design and low noise high linearity considerations. The necessary auxiliary circuits are also included. Fabricated in SMIC 0.18μm 1p6m RF CMOS process, the receiver＇s performance is measured as：4. 1 dB noise figure, - 7.5dBm input third order intercept point （IIP3） for LNA ＆ mixer at high gain setting, - 14dBm IIP3 for the whole receiver,53dBc @30MHz offset of adjacent channel power rejection,and less than 5mV out- put DC-offset. The receiver consumes 44mA under a 1.8V power supply with I,Q two paths.

Computer Network Control System in Automatic Automobile Detection

An automobile test controlling and managing system with computer network is introduced. The architecture of the local network, hardware structure, software structure, design of the test process, and error tolerating redundant design in work position substituting are presented. At last, the pivotal questions solved are discussed. With an advanced structure, this system is multi functional and flexible. Furthermore, advanced computer technology is adopted to improve its technical degree.

天河煤矿A303采区火灾密闭启封实践

在低瓦斯矿井火灾采区回风巷内进行密闭启封工作时,采取水管洒水降尘灭火、局机供风、风帘导风、风门增阻均压等措施,可提高密闭启封作业的安全可靠性,此措施经验可供参考并推广使用。

OPTIMIZATION FOR COMBAT CONFIGURATION OF AIR DEFENSE WEAPON SYSTEMS

At evaluating the combat effectiveness of the defense system, target′s probability to penetrate the defended area is a primary care taking index. In this paper, stochastic model to compete the probability that target penetrates the defended area along any flight path is established by the state analysis and statistical equilibrium analysis of stochastic service system theory. The simulated annealing algorithm is an enlightening random search method based on Monte Carlo recursion, and it can find global optimal solution by simulating annealing process. Combining stochastic model to compete the probability and simulated annealing algorithm, this paper establishes the method to solve problem quantitatively about combat configuration optimization of weapon systems. The calculated result shows that the perfect configuration for fire cells of the weapon is fast found by using this method, and this quantificational method for combat configuration is faster and more scientific than previous one based on principle via map fire field.

Swarm intelligence for mixed-variable design optimization

Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence ap-proach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.

Evaluation of diagnostic findings and scoring systems in outcome prediction in acute pancreatitis

AIM： To determine factors related to disease severity, mortality and morbidity in acute pancreatitis.METHODS： One hundred and ninety-nine consecutive patients were admitted with the diagnosis of acute pancreatitis （AP） in a 5-year period （1998-2002）. In a prospective design, demographic data, etiology, mean hospital admission time, clinical, radiological, biochemical findings, treatment modalities, mortality and morbidity were recorded. Endocrine insufficiency was investigated with oral glucose tolerance test. The relations between these parameters, scoring systems （Ranson, Imrie and APACHE Ⅱ） and patients＇ outcome were determined by using invariable tests and the receiver operating characteristics curve.RESULTS： One hundred patients were men and 99 were women; the mean age was 55 years. Biliary pancreatitis was the most common form, followed by idiopathic pancreatitis （53% and 26%, respectively）. Sixty-three patients had severe pancreatitis and 136 had mild disease. Respiratory rate 〉 20/min, pulse rate 〉 90min, increased C-reactive protein （CRP）, lactate dehydrogenase （LDH） and aspartate aminotransferase （AST） levels, organ necrosis 〉 30% on computed tornography （CT） and leukocytosis were associated with severe disease. The rate of glucose intolerance, morbidity and mortality were 24.1%, 24.8% and 13.6%, respectively. CRP 〉 142 mg/L, BUN 〉 22 mg/dL, LDH 〉 667 U/L, base excess 〉 -5, CT severity index 〉 3 and APACHE score 〉 8 were related to morbidity and mortality.CONCLUSION： APACHE Ⅱ score, LDH, base excess and CT severity index have prognostic value and CRP is a reliable marker for predicting both mortality and morbidity.

Wave propagation control in periodic track structure through local resonance mechanism

Excessive vibration and noise radiation of the track structure can be caused by the operation of high speed trains.Though the track structure is characterized by obvious periodic properties and band gaps,the bandwidth is narrow and the elastic wave attenuation capability within the band gap is weak.In order to effectively control the vibration and noise of track structure,the local resonance mechanism is introduced to broaden the band gap and realize wave propagation control.The locally resonant units are attached periodically on the rail,forming a new locally resonant phononic crystal structure.Then the tuning of the elastic wave band gaps of track structure is discussed,and the formation mechanism of the band gap is explicated.The research results show that a new wide and adjustable locally resonant band gap is formed after the resonant units are introduced.The phenomenon of coupling and transition can be observed between the new locally resonant band gap and the original band gap of the periodic track structure with the band gap width reaching the maximum at the coupling position.The broader band gap can be applied for vibration and noise reduction in high speed railway track structure.

Robot SLAM with Ad hoc wireless network adapted to search and rescue environments

An innovative multi-robot simultaneous localization and mapping(SLAM)is proposed based on a mobile Ad hoc local wireless sensor network(Ad-WSN).Multiple followed-robots equipped with the wireless link RS232/485module act as mobile nodes,with various on-board sensors,Tp-link wireless local area network cards,and Tp-link wireless routers.The master robot with embedded industrial PC and a complete robot control system autonomously performs the SLAM task by exchanging information with multiple followed-robots by using this self-organizing mobile wireless network.The PC on the remote console can monitor multi-robot SLAM on-site and provide direct motion control of the robots.This mobile Ad-WSN complements an environment devoid of usual GPS signals for the robots performing SLAM task in search and rescue environments.In post-disaster areas,the network is usually absent or variable and the site scene is cluttered with obstacles.To adapt to such harsh situations,the proposed self-organizing mobile Ad-WSN enables robots to complete the SLAM process while improving the performances of object of interest identification and exploration area coverage.The information of localization and mapping can communicate freely among multiple robots and remote PC control center via this mobile Ad-WSN.Therefore,the autonomous master robot runs SLAM algorithms while exchanging information with multiple followed-robots and with the remote PC control center via this local WSN environment.Simulations and experiments validate the improved performances of the exploration area coverage,object marked,and loop closure,which are adapted to search and rescue post-disaster cluttered environments.

Signal classification system using global-local feature extraction algorithm

A continuous wavelet transform(CWT)and globallocal feature(GLF)extraction-based signal classificationalgorithm is proposed to improve the signal classification accuracy.First,the CWT is utilized to generate the timefrequency scalogram.Then,the GLF extraction method is proposed to extract features from the time-frequency scalogram.Finally,a classification method based on the support vector machine(SVM)is proposed to classify the extracted features.Experimental results show that the extended binary phase shift keying(EBPSK)bit error rate(BER)of the proposed classification algorithm is1.3x10_5under the environment of additional white Gaussian noise with the signal-to-noise ratio of-3dB,which is24times lower than that of the SVM-based signal classification method.Meanwhile,the BER using the GLF extraction method is13times lower than the one using the global feature extraction method and24times lower than the one using the local feature extraction method.

Random noise suppression for seismic data using a non-local Bayes algorithm

For random noise suppression of seismic data, we present a non-local Bayes （NL- Bayes） filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.

An Indoor Ubiquitous Computing Environment Based on Location-awareness

To provide the right services or information to the right users, at the right time and in the right place in ubiquitous computing environment, an Indoor Ubiquitous Computing Environment based on Location-Awareness, IUCELA, is presented in this paper. A general architecture of IUCELA is designed to connect multiple sensing devices with locationaware applications. Then the function of location-aware middleware which is the core componnet of the proposed architecture is elaborated. Finally an indoor forum is taken as an example scenario to demonstrate the security, usefulness, flexibiltity and robustness of IUCELA.