The Application of Sensitivity Analysis on Comprehensive Transportation Evaluation

Comprehensive transportation evaluation objects using multi-objective decision method is a process of choosing the best one from a few objects through calculating, analyzing, and comparing the index system. The result may be different because of the difference of the index weight and index value. Therefore, sensitivity analysis should be one of the necessary parts of the decision-making. It is desired to give the index with higher sensitivity and its varying scope to control the index strictly during the execution process. This paper derives transfer index weight, which changes the rank evaluation order of the projects. Meanwhile, a simple, effective and practical method based on sensitivity district and sensitivity matrix is proposed for the sensitivity analysis of decision-making. As an example, the index sensitivity in decision-making of some provinces comprehensive transportation objects, and their influence on the final decision are discussed.

Electronic Nose with an Air Sensor Matrix for Detecting Beef Freshness

China is one of the largest meat producing countries in the wodd. With the growing concern for food safety more attention has been paid to meat quality. The application of conventional test methods for meat quality is limited by many factors, and subjectiveness, such as longer time to prepare samples and to test. A sensor matrix was constructed with several separate air sensors, and tests were conducted to detect the freshness of the beef. The results show that the air sensors TGS2610, TGS2600, TGS2611, TGS2620 and TGS2602 made by Tianjin Figaro Electronic Co, Ltd could be used to determine the degree of freshness but TGS2442 is not suitable. This study provides a foundation for designing and making an economical and practical detector for beef freshness.

Parameters Sensitivity Characteristics of Highly Integrated Valve-Controlled Cylinder Force Control System

Nowadays, a highly integrated valve?controlled cylinder(HIVC) is applied to drive the joints of legged robots. Although the adoption of HIVC has resulted in high?performance robot control, the hydraulic force system still has problems, such as strong nonlinearity, and time?varying parameters. This makes HIVC force control very diffcult and complex. How to improve the control performance of the HIVC force control system and find the influence rule of the system parameters on the control performance is very significant. Firstly, the mathematical model of HIVC force control system is established. Then the mathematical expression for parameter sensitivity matrix is obtained by applying matrix sensitivity analysis(PSM). Then, aimed at the sinusoidal response under(three factors and three levels) working conditions, the simulation and the experiment are conducted. While the error between the simulation and experiment can’t be avoided. Therefore, combined with the range analysis, the error in the two performance indexes of sinusoidal response under the whole working condition is analyzed. Besides, the sensitivity variation pattern for each system parameter under the whole working condition is figured out. Then the two sensitivity indexes for the three system parameters, which are supply pressure, proportional gain and initial displacement of piston, are proved experimentally. The proposed method significantly reveals the sensitivity characteristics of HIVC force control system, which can make the contribution to improve the control performance.

Soft Sensing Modelling Based on Optimal Selection of Secondary Variables and Its Application

The composition of the distillation column is a very important quality value in refineries, unfortunately, few hardware sensors are available on-line to measure the distillation compositions. In this paper, a novel method using sensitivity matrix analysis and kernel ridge regression （KRR） to implement on-line soft sensing of distillation compositions is proposed. In this approach, the sensitivity matrix analysis is presented to select the most suitable secondary variables to be used as the soft sensor＇s input. The KRR is used to build the composition soft sensor. Application to a simulated distillation column demonstrates the effectiveness of the method.

Development of an Intelligent Voltage Control System for Jeju Island Power System in Korea

As the voltage has local characteristics in a power system, system voltage control has depended on human experts in distribution substation local reactive power control station so far in Korea. Since coordinative automatic control has been possible due to the recent advances in computers and communication networks, the hierarchical voltage control system, consisting of primary, secondary, and tertiary control, has been applied in several European countries. Recently the Korea power system has been operated more closely to stability limits because of rapid growth in load-demand as seen in Europe. For this reasons, Korea electric power corporation recognized the need of the voltage control system and developed the voltage control system. This paper presents an intelligent voltage control system for domestic power system using numerical algorithm based on the sensitivity matrix and the expert system. Dynamic characteristics of the developed system are investigated using EMTDC （electromagnetic transient DC analysis program） and RTDS （real time digital simulator）. Several case studies showed the promising performance.

Microstructure and Mechanical Performance of Cu-SnO_2-rGO based Composites Prepared by Plasma Activated Sintering

A novel chemical technique combined with unique plasma activated sintering（PAS） was utilized to prepare consolidated copper matrix composites（CMCs） by adding Cu-SnO2-rGO layered micro powders as reinforced fillers into Cu matrix. The repeating Cu-SnO2-rGO structure was composed of inner dispersed reduced graphene oxide（r GO）, SnO2 as intermedia and outer Cu coating. SnO2 was introduced to the surface of rGO sheets in order to prevent the graphene aggregation with SnO2 serving as spacer and to provide enough active sites for subsequent Cu deposition. This process can guarantee rGO sheets to suffi ciently disperse and Cu nanoparticles to tightly and uniformly anchor on each layer of rGO by means of the SnO2 active sites as well as strictly control the reduction speed of Cu^2＋. The complete cover of Cu nanoparticles on rGO sheets thoroughly avoids direct contact among rGO layers. Hence, the repeating structure can simultaneously solve the wettability problem between rGO and Cu matrix as well as improve the bonding strength between rGO and Cu matrix at the well-bonded Cu-SnO2-rGO interface. The isolated rGO can effectively hinder the glide of dislocation at Cu-rGO interface and support the applied loads. Finally, the compressive strength of CMCs was enhanced when the strengthening effi ciency reached up to 41.

Applications of different criteria in structural damage identification based on natural frequency and static displacement

This paper presents a damage identification method that consists of a fusion sensitivity matrix that contains information on dynamic and static responses. Based on natural frequency and static displacement, the study defines and considers damage criteria such as 1D and 2D single and fusion load cases. To overcome the lack of sufficient information on damage identification in large-scale structures, the authors consider multiple responses to and objective descriptions of uncertainties and various criteria.According to the finite element model and the structural responses described and measured, the fusion methods and damage criteria treat uncertainty as non-probability intervals. As long as we know the bounds of uncertain parameters, the intervals of the elemental stiffness parameters in undamaged and damaged models can be obtained by interval technology. Two numerical examples—a damage-criteria numerical example and a 5-span with 25-bar truss structure in a space solar power station—are proposed. Both examples indicate the veracity of the interval method.

Minimizing assembly variation in selective assembly for auto-body parts based on IGAOT

Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping process.Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components.Therefore,the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox(IGAOT)in MATLAB.Design/methodology/approach–The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation.Afterwards,the IGAOT is proposed to generate optimal selective groups,which consists of advantages of genetic algorithm for optimization toolbox(GAOT)and simulated annealing.Findings–The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups.These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.Originality/value–The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly.The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.