Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

Application of MPSO technique to find optimal location and parameter setting of TCSC

A new mothod was presented to find the optimal location and parameter setting of Thyristor Controlled Series Compensator (TCSC) to maxmize the transfer capability.Firstly the sensitivity of the transfer capability with respect was described to the line's reactance was described to find the more sensitive lines for installing TCSC,however,the line which has the most sesitivity value is always not the best line for installing TCSC.For solving this problem,the more sensitive m lines were selected as the alternative line group of installing TCSC,and then modified particle swarm optimization (MPSO) was used to find out the optimal location and the optimal parameter settings of TCSC.Particle swarm optimization (PSO) algorithm can results premature convergence.For solving this problem,population entropy and cellular automata were introduced to it.Simulation results of IEEE 30-bus system proved the effectiveness of the method and its application values.

Sensor Configuration and Test for Fault Diagnoses of Subway Braking System Based on Signed Digraph Method

Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph （SDG） method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure （BCP） sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.

Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning

Accurate multi-source fusion is based on the reliability, quantity, and fusion mode of the sources. The problem of selecting the optimal set for participating in the fusion process is nondeterministic-polynomial-time-hard and is neither sub-modular nor super-modular. Furthermore, in the case of the Kalman filter(KF) fusion algorithm, accurate statistical characteristics of noise are difficult to obtain, and this leads to an unsatisfactory fusion result. To settle the referred cases, a distributed and adaptive weighted fusion algorithm based on KF has been proposed in this paper. In this method, on the basis of the pseudo prior probability of the estimated state of each source, the reliability of the sources is evaluated and the optimal set is selected on a certain threshold. Experiments were performed on multi-source pedestrian dead reckoning for verifying the proposed algorithm. The results obtained from these experiments indicate that the optimal set can be selected accurately with minimal computation, and the fusion error is reduced by 16.6% as compared to the corresponding value resulting from the algorithm without improvements.The proposed adaptive source reliability and fusion weight evaluation is effective against the varied-noise multi-source fusion system, and the fusion error caused by inaccurate statistical characteristics of the noise is reduced by the adaptive weight evaluation.The proposed algorithm exhibits good robustness, adaptability,and value on applications.

一类最优调频序列的线性复杂度(英文)

For the anti-jamming purpose,frequency hopping sequences are required to have a large linear span. In this paper,we firstly give the linear span of a class of optimal frequency hopping sequences. The results show that the linear span is very small compared with their periods. To improve the linear span,we transform these optimal frequency hopping sequences into new optimal frequency hopping sequences with large linear span by using a general type of permutation polynomials over a finite field. Furthermore,we give the exact values of the linear span of the transformed optimal frequency hopping sequences.

Optimization and Mechanical Accuracy Reliability of a New Type of Forging Manipulator

Researches on forging manipulator have enormous influence on the development of the forging industry and national economy.Clamp device and lifting mechanism are the core parts of forging manipulator,and have been studied for longer time.However,the optimization and mechanical accuracy reliability of them are less analyzed.Based on General Function（G_F）set and parallel mechanism theory,proper configuration of 10t forging manipulator is selected firstly.A new type of forging manipulator driven by cylinders is proposed.After solved mechanical analysis of manipulator＇s core mechanisms,expressions of force of cylinders are carried out.In order to achieve smaller force afforded by cylinders and better mechanical characteristics,some particular sizes of core mechanisms are optimized intuitively through the combined use of the genetic algorithms（GA）and GUI interface in MATLAB.Comparing with the original mechanisms,optimized clamp saves at least 8 percent efforts and optimized lifting mechanism 20 percent under maximum working condition.Finally,considering the existed manufacture error of components,mechanical accuracy reliability of optimized clamp,lifting mechanism and whole manipulator are demonstrated respectively based on fuzzy reliability theory.Obtained results show that the accuracy reliability of optimized clamp is bigger than 0.991 and that of optimized lifting mechanism is 0.995.To the whole manipulator under maximum working condition,that value exceeds 0.986 4,which means that optimized manipulator has high motion accuracy and is reliable.A new intuitive method is created to optimize forging manipulator sizes efficiently and more practical theory is utilized to analyze mechanical accuracy reliability of forging manipulator precisely.

Fuzzy linear model for production optimization of mining systems with multiple entities

Planning and production optimization within multiple mines or several work sites （entities） mining systems by using fuzzy linear programming （LP） was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Continuity of Solution Mappings for Parametric Set Optimization Problems under Partial Order Relations

This paper mainly investigates the semicontinuity of solution mappings for set optimization problems under a partial order set relation instead of upper and lower set less order relations. To this end, we propose two types of monotonicity definition for the set-valued mapping introduced by two nonlinear scalarization functions which are presented by these partial order relations. Then, we give some sufficient conditions for the semicontinuity and closedness of solution mappings for parametric set optimization problems. The results presented in this paper are new and extend the main results given by some authors in the literature.

Satellite constellation design with genetic algorithms based on system performance

Satellite constellation design for space optical systems is essentially a multiple-objective optimization problem. In this work, to tackle this challenge, we first categorize the performance metrics of the space optical system by taking into account the system tasks（i.e., target detection and tracking）. We then propose a new non-dominated sorting genetic algorithm（NSGA） to maximize the system surveillance performance. Pareto optimal sets are employed to deal with the conflicts due to the presence of multiple cost functions. Simulation results verify the validity and the improved performance of the proposed technique over benchmark methods.

A Fuzzy Sequential Optimization Method for the Antenna Structures with Multiple Objectives

This paper presents a fuzzy sequential optimization method for the antenna structures with multiple objectives (structural displacement, weight, cost, nature frequency characteristic) based on fuzzy sets. This has led to a set of new concepts which are discussed here. The paper establishes a sequential optimization model, in which the cost function is constructed, the membership function of single objective is defined as extended quadratic function, the membership function in decision making is constructed with linearly weighted and power product weighted models and the objectives are classed. In addition, the paper presents two methods, namely the linear extended method and the secondary constrained sequential optimization method, by which effective satisfactory design can be found. A computer program is given, optimization computing of the truss- type and antenna structures are described. It is shown that the method is practical and effective.

Solution set calculation of the Sun-perturbed optimal two-impulse trans-lunar orbits using continuation theory

The solution set of the Sun-perturbed optimal two-impulse trans-lunar orbit is helpful for overall optimization of the lunar exploration mission.A model for computing the two-impulse trans-lunar orbit,which strictly satisfies the boundary constraints,is established.The solution set is computed first with a circular restricted three-body model using a generalized local gradient optimization algorithm and the strategy of design variable initial continuation.By taking the solution set of a circular restricted three-body model as the initial values of the design variables,the Sun-perturbed solution set is calculated based on the dynamic model continuation theory and traversal search methodology.A comparative analysis shows that the fuel cost may be reduced to some extent by considering the Sun’s perturbation and choosing an appropriate transfer window.Moreover,there are several optimal two-impulse trans-lunar methods for supporting a lunar mission to select a scenario with a certain ground measurement and to control the time cost.A fitted linear dependence relationship between the Sun’s befitting phase and the trans-lunar duration could thus provide a reference to select a low-fuel-cost trans-lunar injection window in an engineering project.

A Modified Direct Allocation Algorithm with Application to Redundant Actuators

Control allocation considers the problem of controlling instruction distribution for control systems with multiple and redundant actuators. This paper focuses on the direct allocation method, making the time requirement of the algorithm analogous compared with modified pseudoinverse redistribution methods, linear programming methods solved by simplex method, and sub-gradient optimization method. To reduce off-line computations of constructing the attainable moment set of actuators, a new approach based on the null space of the control effectiveness matrix is proposed, which is superior when the number of actuators is less than 10 compared with traditional method. To decrease on-line computations, an improvement method of searching the facet that is aligned with the desired moment is presented, shortening the search time by checking only the facets that lie around the desired moment. To find such facets, the vertices of the attainable moment set are normalized and saved during off-line computations. Simulation results show that at least 32.22% of off-line computation time would be saved using null space-based construction when the number of actuators is less than 10. In on-line computations, the modified method performs superiorly compared with the three aforementioned methods. Furthermore, it may solve the problem of control allocation efficiently when a remarkable large number of redundant actuators are configured.

Asymptotic uniformity of the quantization error for the Ahlfors-David probability measures

Let μ be an Ahlfors-David probability measure on Rq;therefore,there exist some constants s0> 0 and ε0,C1,C2> 0 such that C1εs0≤μ(B(x,ε))≤C2εs0 for all ε∈(0,ε0) and x ∈ supp(μ).For n≥ 1,let αn be an n-optimal set for μ of order r;furthermore,let {Pa(αn)}a∈αn be an arbitrary Voronoi partition with respect to αn.The n-th quantization error en,r(μ) for μ of order r can be defined as en,rr(μ):=∫ d(x,αn)r dμ(x).We define Ia(αn,μ):=∫Pa(αn) d(x,αn)r dμ(x),a ∈αn,and prove that,the three quantities ■ are of the same order as that of 1/nen,rr(μ).Thus,our result exhibits that,a weak version of Gersho’s conjecture holds true for the Ahlfors-David probability measures on Rq.

Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm

Research has demonstrated a significant overlap between sleep issues and other medical conditions.In this paper,we consider mild difficulty in falling asleep(MDFA).Recognition of MDFA has the potential to assist in the provision of appropriate treatment plans for both sleep issues and related medical conditions.An issue in the diagnosis of MDFA lies in subjectivity.To address this issue,a decision support tool based on dual-modal physiological feature fusion which is able to automatically identify MDFA is proposed in this study.Special attention is given to the problem of how to extract candidate features and fuse dual-modal features.Following the identification of the optimal feature set,this study considers the correlations between each feature and class and evaluates correlations between the inter-modality features.Finally,the recognition accuracy was measured using 10-fold cross validation.The experimental results for our method demonstrate improved performance.The highest recognition rate of MDFA using the optimal feature set can reach 96.22%.Based on the results of current study,the authors will,in projected future research,develop a real-time MDFA recognition system.

On the Stability of the Solution Set Mappings to Parametric Set Optimization Problems

In this paper,under some suitable assumptions without any involving information on the solution set,we give some sufficient conditions for the upper semicontinuity,lower semicontinuity,and closedness of the solution set mapping to a parametric set optimization problem with possible less order relation.