Mathematical modeling analysis and verification of vibration isolation parts of washing machine

2020 ◽  
Vol 64 (1-4) ◽  
pp. 993-1000
Author(s):  
Jinhui Jiang ◽  
Yidan Qu
Keyword(s):  
Vibration Isolation ◽  
Optimization Method ◽  
Suspension System ◽  
Optimal Parameters ◽  
Multi Objective Optimization ◽  
Washing Machine ◽  
Lagrangian Equation ◽  
Washing Machines ◽  
Modeling Analysis ◽  
Element Simulation

Washing machines are used very frequently in everyday life. There have been many related studies on the vibration and noise of washing machines. The suspension system is an important vibration isolation component of the washing machine. Based on the Lagrangian equation, the dynamic model of the suspension system was established. The reliability of the model was verified by finite element simulation and experimental methods. Finally, this paper used a multi-objective optimization method to obtain optimal parameters of the washing machine and further to reduce the vibration level of washing machines.

The Simulation and Optimization Design of Adams-Based Engine Suspension System

2014 ◽  
Vol 686 ◽  
pp. 529-534
Author(s):  
Jian Xin Xie ◽  
Xiao Le Wang ◽  
Chao Liu
Keyword(s):  
Initial Data ◽  
Optimization Design ◽  
Vibration Isolation ◽  
Design Method ◽  
Suspension System ◽  
Multi Objective Optimization ◽  
Intrinsic Frequency ◽  
Simulation And Optimization ◽  
Engine Vibration ◽  
Simulation Results

In this study, the engine suspension system was optimized for making the vibration between engine and car body minimized, and also the optimization was simulated using software Adams. The purpose of this study was to research the vibration isolation of the engine mounting system and implement multi-objective optimization for the intrinsic frequency. In this paper, the optimization was implemented in two ways: (1) the intrinsic frequency was optimized by reasonably allocating it: (2) the intrinsic frequency was optimized using energy decoupling. The optimized intrinsic frequencies were simulated using software Adams and then the simulation results were compared. The simulation results showed that the optimized energy distribution was almost up to 90% and the decoupling degree was greatly improved by comparing the initial data, proving the optimized data played a greater effect on engine vibration isolation and further verifying the feasibility of optimization design method.

scholarly journals Design and Analysis of Flexible Hinge Used for Unfolding Spacecraft Solar Panels

2019 ◽  
Author(s):  
Jing Zhang ◽  
Kai Yan ◽  
Ziming Kou
Keyword(s):  
Rotation Angle ◽  
Optimization Method ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Solar Panels ◽  
Flexible Hinge ◽  
Large Rotation ◽  
Radial Stiffness ◽  
Element Simulation ◽  
Relationship Of

Two stiffness models for a flexible hinge with large rotation angle are established based on the pseudo-rigid body method and the series or parallel relationship of flexible units. Finite element simulation of the flexible hinge is conducted in ANSYS to verify the two stiffness models of the flexible hinge. A multi-objective optimization method is used to optimize the design parameters of the hinge. The stiffness models of the flexible hinge are used to establish the optimized objective function of an optimization model to improve the rotation angle of the hinge under a certain radial stiffness. After optimization, the rotation angle can reach 70 deg when the rotational and radial stiffnesses are 1.29 N·mm/rad and 1.37 N/mm.

Multi-objective optimization of a hybrid electromagnetic suspension system for ride comfort, road holding and regenerated power

2016 ◽  
Vol 23 (5) ◽  
pp. 782-793 ◽  
Author(s):  
Mansour Ataei ◽  
Ehsan Asadi ◽  
Avesta Goodarzi ◽  
Amir Khajepour ◽  
Mir Behrad Khamesee
Keyword(s):  
Pareto Front ◽  
Ride Comfort ◽  
Optimization Method ◽  
Suspension System ◽  
Multi Objective Optimization ◽  
Damping Force ◽  
Nsga Ii ◽  
Electromagnetic Suspension ◽  
Multi Objective ◽  
Electromagnetic Component

This paper reports work on the optimization and performance evaluation of a hybrid electromagnetic suspension system equipped with a hybrid electromagnetic damper. The hybrid damper is configured to operate with hydraulic and electromagnetic components. The hydraulic component produces a large fail-safe baseline damping force, while the electromagnetic component adds energy regeneration and adaptability to the suspension. For analyzing the system, the electromagnetic component was modeled and integrated into a 2DOF quarter-car model. Three criteria were considered for evaluating the performance of the suspension system: ride comfort, road holding and regenerated power. Using the genetic algorithm multi-objective optimization (NSGA-II), the suspension design was optimized to improve the performance of the vehicle with respect to the selected criteria. The multi-objective optimization method provided a set of solutions called Pareto front in which all solutions are equally good and the selection of each one depends on conditions and needs. Among the given solutions in the Pareto front, a small number of cases, with different design purposes, were selected. The performances of the selected designs were compared with two reference systems: a conventional and a nonoptimized hybrid suspension system. The results show that the ride comfort and road holding qualities of the optimized hybrid system are improved, and the regenerated power is considerably increased.

The Multi-Objective Optimization Design of Vehicle Suspension System Based on ADAMS

2012 ◽  
Vol 472-475 ◽  
pp. 1932-1936
Author(s):  
Zhi Jian Gou
Keyword(s):  
Dynamic Load ◽  
Optimization Design ◽  
Optimization Method ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Multi Objective Optimization ◽  
System Parameters ◽  
Multi Objective ◽  
Full Vehicle ◽  
Vehicle Suspension System

In order to improve the riding and handling of the vehicle，the full-vehicle dynamical model of a certain vehicle is established by means of the software Adams/Car．The design of multi-objective optimization was used for Suspension system parameters on the base of the dynamical model．The optimized results show that riding of the vehicle is retained and dynamic load of wheel is improved obviously．It can be concluded that the optimization method is feasible for the optimization design of suspension system parameters．the investigation also supply the basis of theory for design considering the matching of the suspension system parameters.

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.

Fault Diagnosis Method of Mine Motor Based on Support Vector Machine

2019 ◽  
Vol 13 ◽  
Author(s):  
Yan Zhang ◽  
Ren Sheng
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Optimization Method ◽  
Support Vector ◽  
Optimal Parameters ◽  
Instantaneous Power ◽  
Practical Usefulness ◽  
Sample Data ◽  
Diagnosis Method ◽  
Fault Characteristic

Background: In order to improve the efficiency of fault treatment of mining motor, the method of model construction is used to construct the type of kernel function based on the principle of vector machine classification and the optimization method of parameters. Methodology: One-to-many algorithm is used to establish two kinds of support vector machine models for fault diagnosis of motor rotor of crusher. One of them is to obtain the optimal parameters C and g based on the input samples of the instantaneous power fault characteristic data of some motor rotors which have not been processed by rough sets. Patents on machine learning have also shows their practical usefulness in the selction of the feature for fault detection. Results: The results show that the instantaneous power fault feature extracted from the rotor of the crusher motor is obtained by the cross validation method of grid search k-weights (where k is 3) and the final data of the applied Gauss radial basis penalty parameter C and the nuclear parameter g are obtained. Conclusion: The model established by the optimal parameters is used to classify and diagnose the sample of instantaneous power fault characteristic measurement of motor rotor. Therefore, the classification accuracy of the sample data processed by rough set is higher.

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 A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

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