Experimental Research of the Cleaning Device of Ginkgo

2013 ◽  
Vol 373-375 ◽  
pp. 2061-2067
Author(s):  
Li Hua Zhang ◽  
Shu Lei Qiao ◽  
Xing Yang ◽  
Jun Wang
Keyword(s):  
Mathematical Model ◽  
Wind Speed ◽  
Loss Rate ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Surface Method ◽  
Cleaning Equipment ◽  
Cleaning Device ◽  
Cleaning Machine ◽  
Feeding Speed

This paper studied the suspension characteristics of ginkgo, and designed a cleaning machine of ginkgo as well. At the same time, the effects of feeding speed, the wind speed and the angle of wind outlet on the performance of the equipment were analyzed, and a mathematical model was established. By taking multi-objective optimization method and response surface method, this paper obtained the conclusion that the best combination conditions of cleaning equipment of ginkgo: the feeding speed was 270.86kg/h, the wind speed was 9.25m/s, and the angle of wind outlet was 17°. Then the cleaning equipment reached the best performance: the loss rate was 1.20%, while the cleaning rate was 95.21%.

scholarly journals Multi-Objective Optimization of Process Parameters of Longitudinal Axial Threshing Cylinder for Frozen Corn Using RSM and NSGA-II

2020 ◽  
Vol 10 (5) ◽  
pp. 1646 ◽  
Author(s):  
Jun Fu ◽  
Haikuo Yuan ◽  
Depeng Zhang ◽  
Zhi Chen ◽  
Luquan Ren
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Loss Rate ◽  
Optimization Method ◽  
Operational Performance ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Nsga Ii ◽  
Multi Objective ◽  
Damage Rate

Corn was frozen at harvest time in high-latitude areas, when corn kernel is wetter and more easily broken. When frozen corn was threshed and separated by the longitudinal axial threshing cylinder of a combine harvester, it caused a significantly high kernel damage rate and loss rate. The process parameters of threshing cylinder were optimized using RSM (response surface method) and NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). The drum speed (Ds), feed rate (Fr) and concave clearance (Cc) were determined as the optimized process parameters. The loss rate (Lr) and damage rate (Dr) were indicators of operational performance. The RSM was used to establish a mathematical model between process parameters and indicators. With an elite strategy, NSGA-II was used for multi-objective optimization to obtain the optimal operational performance of the threshing cylinder. Overall, when the drum speed was selected as 384.1 rpm, the feed rate as 8.6 kg/s and the concave clearance as 40.5 mm, according to the requirement of corn harvest, the best operational performance of the longitudinal axial threshing cylinder on frozen corn was obtained. The Lr was 1.98% and the Dr was 3.49%. This result indicated that the applicability of the optimal process parameters and the optimization method of combining NSGA-II and RSM was effective for determining the optimal process parameters. This will provide an optimization method for synchronously reducing the loss rate and damage rate of grain harvesters.

Gear-tolerance optimization based on a response surface method

2018 ◽  
Vol 42 (3) ◽  
pp. 309-322
Author(s):  
Rui Xu ◽  
Kang Huang ◽  
Jun Guo ◽  
Lei Yang ◽  
Mingming Qiu ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Response Surface ◽  
Response Surface Method ◽  
Tolerance Analysis ◽  
Optimization Method ◽  
Small Displacement ◽  
Tooth Contact Analysis ◽  
Tolerance Optimization ◽  
Surface Method ◽  
Low Efficiency

To address the low efficiency of gear-tolerance analysis and optimization, a gear-tolerance optimization method based on a response surface method (RSM) and optimization algorithm is presented. A gear-tolerance mathematical model, including profile deviation, pitch deviation, and geometric deviation, was developed by combining traditional profile modeling with a small displacement torsor (SDT) method. Based on this mathematical model, a tooth-contact analysis method, which takes a variety of deviations into account, and a program to compute transmission error were developed. Using the RSM and a genetic algorithm, a gear-tolerance optimization model was created to consider a variety of gear tolerances as design variables and process cost as an optimization objective. An example of gear-tolerance optimization was analyzed, and the result indicates that the method presented in this paper may help improve the efficiency of gear-tolerance optimization and is practicable for precision gear design.

Optimization Design of Finger Seal Performances Based on Game Theory

2010 ◽  
Vol 156-157 ◽  
pp. 1275-1280
Author(s):  
Yan Chao Zhang ◽  
Guo Ding Chen
Keyword(s):  
Mathematical Model ◽  
Game Theory ◽  
Nash Equilibrium ◽  
Optimization Design ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Equilibrium Method ◽  
Wear Ratio ◽  
Payoff Functions

To reach the expecting goal of lower leakage ratio and longer operation life(lower wear ratio) for finger seal, great efforts have been made continuously to obtain good structure of finger seal with advanced optimization design technology. A cooperation Nash equilibrium mathematical model of multi-objective optimization for finger seal is presented in current work based on Nash equilibrium of game theory. In this solution, the reciprocal of leakage ratio and the wear ratio value for finger seal are thought as the payoff functions and the game is solved by genetic algorithm. The numerical simulation in the paper shows that the finger seal with better performances can be achieved by using Nash equilibrium method. This means Nash equilibrium method can be used as a new multi-objective optimization method for finger seal performances optimization.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Analysis of Performance of the Wind-Driven Pulverizing Aerator Based on Average Wind Speeds in the Conditions of Góreckie Lake

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2796
Author(s):  
Andrzej Osuch ◽  
Ewa Osuch ◽  
Stanisław Podsiadłowski ◽  
Piotr Rybacki
Keyword(s):  
Mathematical Model ◽  
Wind Speed ◽  
Water Pump ◽  
Average Wind Speed ◽  
Flow Rates ◽  
Wind Speeds ◽  
Average Wind ◽  
Flow Through ◽  
Analysis Of Performance ◽  
Research Period

In the introduction to this paper, the characteristics of Góreckie lake and the construction and operation of the wind-driven pulverizing aerator are presented. The purpose of this manuscript is to determine the efficiency of the pulverizing aerator unit in the windy conditions of Góreckie Lake. The efficiency of the pulverization aerator depends on the wind conditions at the lake. It was necessary to conduct thorough research to determine the efficiency of water flow through the pulverization segment (water pump). It was necessary to determine the rotational speed of the paddle wheel, which depended on the average wind speed. Throughout the research period, measurements of hourly average wind speed were carried out. It was possible to determine the efficiency of the machine by developing a dedicated mathematical model. The latest method was used in the research, consisting of determining the theoretical volumetric flow rates of water in the pulverizing aerator unit, based on average hourly wind speeds. Pulverization efficiency under the conditions of Góreckie Lake was determined based on 6600 average wind speeds for spring, summer and autumn, 2018. Based on the model, the theoretical efficiency of the machine was calculated, which, under the conditions of Góreckie Lake, amounted to 75,000 m3 per year.

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