JZ-8型制动控制系统过滤器优化及重要操作

文章介绍了JZ-8型制动控制系统的主要组成及部件功能,并结合本系统的实际运用经验,对制动控制系统总风过滤器进行了滤油性能优化,以提高制动系统可靠性。最后,文章阐述了制动控制系统的重要操作方法,可供乘务员、检修人员及技术人员进行参考。

BDO装置加氢过滤系统的优化和改进

本文以某2*4.5万/吨BDO项目加氢装置过滤系统为研究对象,研究和总结系统运行中的出现各种问题,通过生产实践进行调整改造创新,进行了生产运行数据的收集对比,为过滤系统的经济长周期运行提供了重要的技术依据。

Adaptive bands filter bank optimized by genetic algorithm for robust speech recognition system

Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open.Owing to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is presented.The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters.The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop.The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank.In ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria.For the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.

Directions of Arrival Optimization Method for Broadband Antenna Array Based on Filter Bank

This paper proposes an estimation method of the directions of arrival(DOA) for the broadband signals received by a uniform planar antenna array including the mutual coupling effect. The process modeling of antenna array receiving dynamic signal is obtained accurately via building the array system electromagnetic space-time model, and the mutual coupling effect is included in the synthesis procedure automatically. The broadband signal is divided into several sub-bands, and the complex weight of these sub-bands frequencies is figured out using the least mean square iteration programming. In the proposed method, the mutual coupling effect is compensated at the different frequencies. The calculation results show that the method is suitable for the uniform linear and uniform circular array pattern integration, and it is commendably satisfied with the requirement of engineering design.

Optimization of Nozzle Design for Pulse Cleaning of Ceramic Filter

The experimental study was carried out to optimize the nozzle shape and dimension for the pulse cleaning of a ceramic filter candle. A bench scale unit of ceramic filter consisting of four commercial filter elements was used to measure the traces of the transient pressure around the nozzle and the overpressure in the filter cavity during the pulse-jet injection of pulse gas. Overpressure in the filter cavity is related to the pulse cleaning force. Nozzle design is concerned to increase the overpressure at the open end of filter element of pulse cleaning inlet, as well as to minimize the consumption of pulse gas. Convergent nozzle induces more secondary flow and generates higher pulse cleaning effect than straight nozzle. Nozzles of different convergent ratio （ratio of outlet to inlet diameter of nozzle） by changing the convergent angle and height were tested. The outlet diameter of convergent nozzle seriously influences the cleaning effect. The optimum convergent ratio increases with the increase of pulse gas pressure The nozzle position （distance of nozzle tip from the open end of filter inlet） is also important to decide the nozzle dimension. Nozzle of large outlet diameter accepts high pressure of pulse gas to provide large overpressure in the filter cavity of top position by applying long distance.

Adaptive template filter method for image processing based on immune genetic algorithm

To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.

A NONMONOTONE LINE SEARCH FILTER METHOD WITH REDUCED HESSIAN UPDATING FOR NONLINEAR OPTIMIZATION

This paper proposes a nonmonotone line search filter method with reduced Hessian updating for solving nonlinear equality constrained optimization.In order to deal with large scale problems,a reduced Hessian matrix is approximated by BFGS updates.The new method assures global convergence without using a merit function.By Lagrangian function in the filter and nonmonotone scheme,the authors prove that the method can overcome Maratos effect without using second order correction step so that the locally superlinear convergence is achieved.The primary numerical experiments are reported to show effectiveness of the proposed algorithm.

Optimal Multimodel Representation by Laguerre Filters Applied to a Communicating Two Tank System

This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.

Adaptive TQWT filter based feature extraction method and its application to detection of repetitive transients

The local defect in rotating machine always gives rise to repetitive transients in the collected vibration signal. However, the transient signature is prone to be contaminated by strong background noises, thus it is a challenging task to detect the weak transients for machine fault diagnosis. In this paper, a novel adaptive tunable Q-factor wavelet transform(TQWT) filter based feature extraction method is proposed to detect repetitive transients. The emerging TQWT possesses distinct advantages over the classical constant-Q wavelet transforms, whose Q-factor can be tuned to match the oscillatory behavior of different signals, but the parameter selection for TQWT heavily relies on prior knowledge. Within our adaptive TQWT filter algorithm, the automatic optimization techniques for three TQWT parameters are implemented to achieve an optimal TQWT basis that matches the transient components. Specifically, the decomposition level is selected according to a center frequency ratio based stopping criterion, and the Q-factor and redundancy are optimized based on the minimum energy-weighted normalized wavelet entropy.Then, the adaptive TQWT decomposition can be achieved in a sparse way and result in subband signals at various wavelet scales.Further, the optimum subband signal which carries transient feature information, is identified using a normalized energy to bandwidth ratio index. Finally, the single branch reconstruction signal from the optimum subband is obtained with transient signatures via inverse TQWT, and the frequency of repetitive transients is detected using Hilbert envelope demodulation. It has been verified via numerical simulation that the proposed adaptive TQWT filter based feature extraction method can adaptively select TQWT parameters and the optimum subband for repetitive transient detection without prior knowledge. The proposed method is also applied to faulty bearing vibration signals and its effectiveness is validated.

Improved Algorithm for Distributed Localization in Wireless Sensor Networks

Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.

A FILTER SECANT METHOD WITH NONMONOTONE LINE SEARCH FOR EQUALITY CONSTRAINED OPTIMIZATION

This paper proposes a filter secant method with nonmonotone line search for non-linearequality constrained optimization.The Hessian of the Lagrangian is approximated using the BFGSsecant update.This new method has more flexibility for the acceptance of the trial step and requires lesscomputational costs compared with the monotone one.The global and local convergence of the proposedmethod are given under some reasonable conditions.Further,two-step Q-superlinear convergence rateis established by introducing second order correction step.The numerical experiments are reported toshow the effectiveness of the proposed algorithm.