Sensors distribution optimization for impact localization using NSGA-II

Sensor Review ◽  
2015 ◽  
Vol 35 (4) ◽  
pp. 409-418 ◽  
Author(s):  
Peng Li ◽  
Yuhua Wang ◽  
Jingru Hu ◽  
Jianmin Zhou
Keyword(s):  
Principal Component ◽  
Optimization Method ◽  
Objective Functions ◽  
Nsga Ii ◽  
Element Analysis ◽  
Content Type ◽  
Time Frequency ◽  
Real World Problem ◽  
Conflicting Objectives ◽  
Impact Localization

Purpose – The purpose of this study which resulted in this work is to propose an optimization method of sensors distribution for structural impact localization. Design/methodology/approach – This paper presents a multi-objective optimization study of a novel sensors distribution technique, where two optimization objective functions are considered: sensors number and sensors location optimization performance index. In addition, the finite element analysis, the time-frequency transform and the principal component analysis are combined to quantize the above objective functions. The non-dominated sorting genetic algorithm II (NSGA-II) is used to acquire Pareto solutions. Findings – The effectiveness of this method is validated through a prototype laboratory called the piezoelectric intelligent structure where promising results are obtained. Originality/value – An optimization method of this novel sensors distribution technique is built and produced a set of efficiency solutions for the real-world problem of impact localization where two conflicting objectives are involved.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

scholarly journals Hydraulic Optimization of Double Chamber Surge Tank Using NSGA-II

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 455 ◽  
Author(s):  
Resham Dhakal ◽  
Jianxu Zhou ◽  
Sunit Palikhe ◽  
Khem Prasad Bhattarai
Keyword(s):  
Water Level ◽  
Optimization Method ◽  
Water Levels ◽  
Transient Processes ◽  
Objective Functions ◽  
Surge Tank ◽  
Nsga Ii ◽  
Reservoir Water ◽  
High Head ◽  
Double Chamber

A surge tank effectively reduces water hammer but experiences water level oscillations during transient processes. A double chamber surge tank is used in high head plants with appreciable variations in reservoir water levels to limit the maximum amplitudes of oscillation by increasing the volume of the surge tank near the extremes of oscillation. Thus, the volume of the chambers and the design of an orifice are the most important factors for controlling the water level oscillations in a double chamber surge tank. Further, maximum/minimum water level in the surge tank and damping of surge waves have conflicting behaviors. Hence, a robust optimization method is required to find the optimum volume of chambers and the diameter of the orifice of the double chamber surge tank. In this paper, the maximum upsurge, the maximum downsurge, and the damping of surge waves are considered as the objective functions for optimization. The worst condition of upsurge and downsurge is determined through 1-D numerical simulation of the hydropower system by using method of characteristics (MOC). Moreover, the sensitivity of dimensions of a double chamber surge tank is studied to find their impact on objective functions; finally, the optimum dimensions of the double chamber surge tank are found using non-dominated sorting genetic algorithm II (NSGA-II) to control the water level oscillations in the surge tank under transient processes. The volume of the optimized double chamber surge tank is only 44.53% of the total volume of the simple surge tank, and it serves as an effective limiter of maximum amplitudes of oscillations. This study substantiates how an optimized double chamber surge tank can be used in high head plants with appreciable variations in reservoir water levels.

A framework for tolerance design considering systematic and random uncertainties due to operating conditions

2019 ◽  
Vol 39 (5) ◽  
pp. 854-871
Author(s):  
S. Khodaygan
Keyword(s):  
Operating Conditions ◽  
Tolerance Allocation ◽  
Manufacturing Cost ◽  
Tolerance Design ◽  
Element Analysis ◽  
Content Type ◽  
Multi Objective ◽  
Mechanical Assemblies ◽  
Conflicting Objectives ◽  
Random Uncertainties

Purpose The purpose of this paper is to present a novel Kriging meta-model assisted method for multi-objective optimal tolerance design of the mechanical assemblies based on the operating conditions under both systematic and random uncertainties. Design/methodology/approach In the proposed method, the performance, the quality loss and the manufacturing cost issues are formulated as the main criteria in terms of systematic and random uncertainties. To investigate the mechanical assembly under the operating conditions, the behavior of the assembly can be simulated based on the finite element analysis (FEA). The objective functions in terms of uncertainties at the operating conditions can be modeled through the Kriging-based metamodeling based on the obtained results from the FEA simulations. Then, the optimal tolerance allocation procedure is formulated as a multi-objective optimization framework. For solving the multi conflicting objectives optimization problem, the multi-objective particle swarm optimization method is used. Then, a Shannon’s entropy-based TOPSIS is used for selection of the best tolerances from the optimal Pareto solutions. Findings The proposed method can be used for optimal tolerance design of mechanical assemblies in the operating conditions with including both random and systematic uncertainties. To reach an accurate model of the design function at the operating conditions, the Kriging meta-modeling is used. The efficiency of the proposed method by considering a case study is illustrated and the method is verified by comparison to a conventional tolerance allocation method. The obtained results show that using the proposed method can lead to the product with a more robust efficiency in the performance and a higher quality in comparing to the conventional results. Research limitations/implications The proposed method is limited to the dimensional tolerances of components with the normal distribution. Practical implications The proposed method is practically easy to be automated for computer-aided tolerance design in industrial applications. Originality/value In conventional approaches, regardless of systematic and random uncertainties due to operating conditions, tolerances are allocated based on the assembly conditions. As uncertainties can significantly affect the system’s performance at operating conditions, tolerance allocation without including these effects may be inefficient. This paper aims to fill this gap in the literature by considering both systematic and random uncertainties for multi-objective optimal tolerance design of mechanical assemblies under operating conditions.

Improved hybrid Strength Pareto Evolutionary Algorithms for multi-objective optimization

2018 ◽  
Vol 11 (1) ◽  
pp. 20-46 ◽  
Author(s):  
K. Shankar ◽  
Akshay S. Baviskar
Keyword(s):  
Engineering Design ◽  
Nsga Ii ◽  
Design Problems ◽  
Content Type ◽  
Multi Objective ◽  
Decision Variables ◽  
Engineering Design Problems ◽  
Wide Range ◽  
Conflicting Objectives ◽  
Utopia Point

Purpose The purpose of this paper is to design an improved multi-objective algorithm with better spread and convergence than some current algorithms. The proposed application is for engineering design problems. Design/methodology/approach This study proposes two novel approaches which focus on faster convergence to the Pareto front (PF) while adopting the advantages of Strength Pareto Evolutionary Algorithm-2 (SPEA2) for better spread. In first method, decision variables corresponding to the optima of individual objective functions (Utopia Point) are strategically used to guide the search toward PF. In second method, boundary points of the PF are calculated and their decision variables are seeded to the initial population. Findings The proposed methods are tested with a wide range of constrained and unconstrained multi-objective test functions using standard performance metrics. Performance evaluation demonstrates the superiority of proposed algorithms over well-known existing algorithms (such as NSGA-II and SPEA2) and recent ones such as NSLS and E-NSGA-II in most of the benchmark functions. It is also tested on an engineering design problem and compared with a currently used algorithm. Practical implications The algorithms are intended to be used for practical engineering design problems which have many variables and conflicting objectives. A complex example of Welded Beam has been shown at the end of the paper. Social implications The algorithm would be useful for many design problems and social/industrial problems with conflicting objectives. Originality/value This paper presents two novel hybrid algorithms involving SPEA2 based on: local search; and Utopia point directed search principles. This concept has not been investigated before.

Self-adaptive migration NSGA and optimal design of inductors for magneto-fluid hyperthermia

2018 ◽  
Vol 35 (4) ◽  
pp. 1727-1746 ◽  
Author(s):  
Elisabetta Sieni ◽  
Paolo Di Barba ◽  
Fabrizio Dughiero ◽  
Michele Forzan
Keyword(s):  
Genetic Algorithms ◽  
Pareto Front ◽  
Real Life ◽  
Computational Effort ◽  
Nsga Ii ◽  
Element Analysis ◽  
Content Type ◽  
Power Inductors ◽  
The Magnetic Field

Purpose The purpose of this paper is to present a modified version of the non-dominated sorted genetic algorithm with an application in the design optimization of a power inductor for magneto-fluid hyperthermia (MFH). Design/methodology/approach The proposed evolutionary algorithm is a modified version of migration-non-dominated sorting genetic algorithms (M-NSGA) that now includes the self-adaption of migration events- non-dominated sorting genetic algorithms (SA-M-NSGA). Moreover, a criterion based on the evolution of the approximated Pareto front has been activated for the automatic stop of the computation. Numerical experiments have been based on both an analytical benchmark and a real-life case study; the latter, which deals with the design of a class of power inductors for tests of MFH, is characterized by finite element analysis of the magnetic field. Findings The SA-M-NSGA substantially varies the genetic heritage of the population during the optimization process and allows for a faster convergence. Originality/value The proposed SA-M-NSGA is able to find a wider Pareto front with a computational effort comparable to a standard NSGA-II implementation.

scholarly journals Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System

2018 ◽  
Vol 7 (4) ◽  
pp. 529-537
Author(s):  
Noraishikin Binti Zulkarnain ◽  
Hairi Zamzuri ◽  
Sarah ’Atifah Saruchi ◽  
Mohd Marzuki Mustafa ◽  
Siti Salasiah Mokri ◽  
...  
Keyword(s):  
Ride Comfort ◽  
Optimization Method ◽  
Ride Quality ◽  
Objective Functions ◽  
Vehicle Model ◽  
Validation Process ◽  
Nsga Ii ◽  
System A ◽  
Nonlinear Vehicle Model ◽  
Benchmark System

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated.

Analysis of 24Slot wound field salient rotor switched-flux machine based on 2D-FEA

2016 ◽  
Vol 13 (5) ◽  
pp. 381-385 ◽  
Author(s):  
Faisal Khan ◽  
Erwan Sulaiman ◽  
Hassan Ali Soomro ◽  
Fairoz Omar ◽  
Zarafi Ahmad
Keyword(s):  
High Speed ◽  
Design Methodology ◽  
Optimization Method ◽  
Optimized Design ◽  
Flux Linkage ◽  
Element Analysis ◽  
Content Type ◽  
Three Phase ◽  
Rotor Poles ◽  
Dimensional Finite Element

Purpose The paper aims to propose and compare two new structures of a three-phase wound field salient rotor (WFSR) switched-flux motor (SFM) with 24 stator slots and 10 or 14 rotor poles, respectively, for high-speed operation. Design/methodology/approach The paper outlines the motor general construction and design concept of proposed machines. Flux linkage, average torque, rotor mechanical strength and torque–speed characteristics of both machines were analyzed and compared by two-dimensional finite element analysis (2D-FEA). Deterministic optimization method was adopted to enhance the characteristics of 24Slot-10Pole WFSR SFM. Findings The paper provides simulation results and discusses how 24Slot-10Pole WFSR SFM structure is superior to the 24Slot-14Pole in the aspects of flux linkage, average torque and power. It further concludes that the optimized design of 24Slot-10P has achieved 58 and 72 per cent higher average torque and power compared to initial design, as well as high average torque and power compared to 24Slot-14P design. Originality value Optimized structure of the 24Slot-10Pole WFSR SFM with non-overlapping windings has been proposed.

Design and control of electrotechnological systems

2019 ◽  
Vol 39 (1) ◽  
pp. 239-247
Author(s):  
Yuliya Pleshivtseva ◽  
Edgar Rapoport ◽  
Bernard Nacke ◽  
Alexander Nikanorov ◽  
Paolo Di Barba ◽  
...  
Keyword(s):  
Design Methodology ◽  
Quality Criteria ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Content Type ◽  
Electromagnetic Devices ◽  
Design Variables ◽  
And Control ◽  
Standard Genetic Algorithm

Purpose This paper aims to investigate different multi-objective optimization (MOO) approaches for design and control of electromagnetic devices. The main goal of MOO is to find the set of design variables or control parameters which will provide the best possible values of typical conflicting objective functions. Design/methodology/approach In the research studies, standard genetic algorithm (GA), non-dominated sorting GA (NSGA-II), migration NSGA algorithm and alternance method of optimal control theory are discussed and compared. Findings The test practical problems of multi-criteria optimization of induction heating processes with respect to chosen quality criteria confirm the effectiveness of application of considered MOO approaches both for the problems of design and control. Originality/value This paper represents and investigates different MOO approaches for design and control of electrotechnological systems.

Investigation and Parametric Analysis of Steel Perforated Sheet Metal (PSM) for Optimum Forming Process

2015 ◽  
Vol 21 ◽  
pp. 118-123 ◽  
Author(s):  
Kartik D. Kothari ◽  
R.L. Jhala
Keyword(s):  
Sheet Metal ◽  
Principal Component ◽  
Optimization Method ◽  
Displacement Curve ◽  
Forming Process ◽  
Element Analysis ◽  
Punch Velocity ◽  
Perforated Sheet ◽  
Blank Shape ◽  
The Impact

This research paper deals with the finite element analysis of forming process of Steel perforated sheet metal (PSM). Simulations are conducted to scrutinize the impact of material thickness, type of blank, blank shape, shape & pattern of perforation, pitch of perforation etc on stress and load-displacement curve for set of results. Modeling of part files are done on software CATIA V5 which is later imported to FEA software package. Numerical method is used to determine optimum results with reference to process parameters as blank thickness punch velocity and stress distribution during the process on the sheet metal. Weighted Principal Component Analysis a multi response objective optimization method is used to derive best parameters for minimizing the induced stress value.

Sign in / Sign up

Export Citation Format

Share Document