An assembly deviation calculation method based on surface deviation modeling for circumferential grinding plane

2020 ◽  
pp. 095440542097819
Author(s):  
Lihong Qiao ◽  
Peilin Shao ◽  
Hanqing Zhao ◽  
Zhicheng Huang
Keyword(s):  
Calculation Method ◽  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Contact Method ◽  
Deviation Function ◽  
Two Factors ◽  
Part Surface ◽  
Surface Deviation ◽  
Assembly Behavior ◽  
Assembly Deviation

Performance of mechanical product is highly influenced by assembly deviation. Due to manufacturing errors, the real part surface is machined with morphology deviations, which would cause mating surface deviating from ideal position in assembly behavior, consequently leading to assembly deviation. Meanwhile, the random variation of relative position and orientation between two non-ideal parts also affects the assembly deviation. To efficiently obtain the maximum assembly deviation considering the comprehensive influence of two factors above for circumferential grinding plane, an assembly deviation calculation method based on surface deviation modeling is proposed in this paper. In this method, morphology deviations models of part surfaces are firstly established from the deviation function. The randomness of two factors are represented by a multivariate group with randomness containing deviation function coefficients and three deflected parameters. Then based on surface deviation modeling method, differential evolution algorithm is applied to search the maximum assembly deviation, which involves the construction of fitness function by implementing optimized progressive contact method and iterative operations of mutation, crossover and selection. Finally, the effectiveness of this method is illustrated by an assembly in the end.

Wheel-Rail Multi-Point Contact Method for Railway Turnouts

2011 ◽  
Vol 97-98 ◽  
pp. 378-381
Author(s):  
Zhi Wei Chen ◽  
Linan Li ◽  
Shi Gang Sun ◽  
Jun Long Zhou
Keyword(s):  
Calculation Method ◽  
Normal Force ◽  
Contact Point ◽  
Point Contact ◽  
Contact Model ◽  
Contact Method ◽  
Elastic Contact ◽  
Simulation Calculation ◽  
Acute Change

A calculation method of wheel-rail multi-point contact based on the elastic contact model is introduced. Moreover, the simulation calculation of vehicles passing through branch lines of No.18 turnouts is carried out. The result showed that the acute change of wheel-rail normal force caused by the transfers of wheel-rail contact point between two rails can be avoid by wheel-rail multi-point contact method, and the transfers of wheel-rail normal force between two rails is smoother. The validity of wheel-rail multi-point contact method is verified.

Research on Calculation Method of Alternative Fuel Quantity for Natural Gas Bus

2014 ◽  
Vol 687-691 ◽  
pp. 415-418
Author(s):  
Xiao Li ◽  
Li Liu ◽  
Zhong Xiang Li
Keyword(s):  
Energy Efficiency ◽  
Natural Gas ◽  
Calculation Method ◽  
Calorific Value ◽  
Alternative Fuel ◽  
Correction Coefficient ◽  
Actual Situation ◽  
Two Factors ◽  
Natural Gas Vehicle ◽  
Selection Of

There is no more in-depth research in the amount of alternative between natural gas and tradition fuel. The paper consider two factors about gas calorific value and vehicle level and put forward the fuel calorific value correction coefficient and vehicle energy efficiency correction coefficient. On this basis, the coefficient table and calculation method was established. The paper proved that because of the influence of the factors, equivalent ratio in the range of 1.13~1.67. The method can indicate the gas replacement more scientific and real, because of consider of the actual situation of application of the enterprise.The research can guide the selection of natural gas vehicle reasonable and scientific.

Cost Optimization Problem of Hybrid Flow-Shop Based on Differential Evolution Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 1692-1700
Author(s):  
Zhong Hua Han ◽  
Xiang Bin Meng ◽  
Bin Ma ◽  
Chang Tao Wang
Keyword(s):  
Differential Evolution ◽  
Production Cost ◽  
Job Scheduling ◽  
Flow Shop ◽  
Fitness Function ◽  
Cost Optimization ◽  
Differential Evolution Algorithm ◽  
Hybrid Flow Shop ◽  
Processing Cost ◽  
Evolution Algorithm

A differential evolution algorithm based job scheduling method is presented, whose optimization target is production cost. The cost optimization model of hybrid flow-shop is thereby constructed through considering production cost as a factor in scheduling problem of hybrid flow-shop. In the implementation process of the method, DE is used to take global optimization and find which machine the jobs should be assigned on at each stage, which is also called the process route of the job; then the local assignment rules are used to determine the job’s starting time and processing sequence at each stage. With converting time-based scheduling results to fitness function which is comprehensively considering the processing cost, waiting costs, and the products storage costs, the processing cost is taken as the optimization objective. The numerical results show the effectiveness of the algorithm after comparing between multi-group programs.

Control System Modeling for Automotive Brake Test-Bench Based on Improved PID Algorithm

2012 ◽  
Vol 542-543 ◽  
pp. 1007-1010
Author(s):  
Jia Xi Du ◽  
Hong Shen ◽  
Yuexia Feng
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Pid Control ◽  
Test Bench ◽  
Control Function ◽  
Fitness Function ◽  
System Modeling ◽  
Loop Model ◽  
Deviation Function ◽  
Automotive Brake

Based on PID controller, the closed-loop model of instantaneous torque for automotive brake test-bench was established, and then the instantaneous torque and the deviation function were calculated, furthermore, the genetic algorithm was adopted in order to get a global optimal solution and to optimize the parameters of the PID control system. So that the deviation function can be reduced or improved. By comparing the effect of control function, the causes for error volatility of the PID control system were derived, and the fitness function of genetic algorithm was determined reasonably. This algorithm can improve the reliability and accuracy of the control model effectively, and provide an effective method for testing the merits and integrated performance of automotive brake design.

scholarly journals Parameter Tuning of Brushless DC Motor for Improving Control Effect with Worm Algorithm

2021 ◽  
Vol 23 (3) ◽  
pp. 229-235
Author(s):  
Jianhua Qin ◽  
Wenrong Wang ◽  
Xiao Liu
Keyword(s):  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Parameter Tuning ◽  
Absolute Error ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Control Effect ◽  
Two Phase ◽  
Brushless Dc ◽  
Control Precision

Aiming at the problem of low control precision and small applicable scope caused by adjusting control parameters in Ziegler-Nichols (ZN) method, a parameter tuning method based on Worm algorithm (WOA) is proposed for Brushless DC motor. Firstly, the model of speed control is established by proportional integral method for Brushless DC motor with two - phase conduction and three - phase full bridge drive. Then the fitness function of the controller is constructed by the Integral Absolute Error (IAE). Finally, the early optimization process, the later movement rule and the peak extraction rule are determined for WOA, and the controller parameter tuning process is designed. Simulation results under constant and sinusoidal conditions show the effectiveness of the proposed method. WOA was compared with ZN, genetic algorithm (GA), differential evolution algorithm (DE) and particle swarm optimization algorithm (PSO) in the experiment. The experimental results show that the control effect (CE) of WOA under uniform speed has been improved by 2.56% on average, and has been improved by 16.93% on average under sinusoidal speed. Compared with previous methods, this method can be used for parameter adjustment of complex control with higher control precision.

scholarly journals A Nonlinear Adaptive Observer-Based Differential Evolution Algorithm to Multiparameter Fault Diagnosis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiaoliu Yang ◽  
Zetao Li ◽  
Qingfang Zhang ◽  
Qinmu Wu ◽  
Linli Yang
Keyword(s):  
Differential Evolution ◽  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Adaptive Observer ◽  
Identification System ◽  
Water Tank ◽  
Suggested Approach ◽  
Differential Evolutionary Algorithm ◽  
On Line ◽  
Evolution Algorithm

In this paper, a novel adaptive diagnosis scheme is proposed for multiparametric faults of nonlinear systems by using the model and intelligent optimization-based approaches. The key idea of the proposed method is to analyze the correlation of the output signals between the real system and the fault identification system instead of residual. A new adaptive scheme is built based on an adaptive observer and differential evolution algorithm. Meanwhile, the conditions of detectability and identifiability of faults are analyzed. The isolation and estimation of the multiparametric fault are formulated as the solution of an optimization problem that is solved by using a differential evolutionary algorithm (DE). The fitness function of DE is constructed by the correlation coefficient equations in which the faulty components are contained. The application on a coupled three water tank model attests the feasibility and validity of the suggested approach. Simulation and experimental results show that the developed method is applicable to diagnose either single or multiparameter faults on-line.

Cloud e-mail security: An accurate e-mail spam classification based on enhanced binary differential evolution (BDE) algorithm

2021 ◽  
pp. 1-13
Author(s):  
Nadir O. Hamed ◽  
Ahmed H. Samak ◽  
Mostafa A. Ahmad
Keyword(s):  
Differential Evolution ◽  
Correlation Coefficient ◽  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Feature Space ◽  
Support Vector ◽  
Svm Classifier ◽  
Binary Differential Evolution ◽  
E Mail ◽  
Email Spam

The evolution of technology has brought new challenges and opportunities for the different dimensions of feature space. The higher dimension of the feature space is one of the most critical issues in e-mail classification problems due to accuracy considerations. The problem of finding the subset features that significantly influence the performance of e-mail spam classification has become one of the important challenges. This paper proposes to overcome such a problem, an intelligent approach to Binary Differential Evolution Support Vector Machine (BDE-SVM). The proposed approach enhances the Binary Differential Evolution (BDE) algorithm based on the correlation coefficient as a fitness function to select the significant subset feature evaluated by an SVM classifier. To our best of knowledge, the correlation coefficient as the fitness function has not been used in the differential evolution algorithm before. The selected subset feature is used to assess the most features that contribute to the reliability of the email spam classification. The finding of the enhanced BDE is to present a powerful accuracy. The tests were conducted using “Spambase” and “SpamAssassin.” Identified benchmark datasets are to assess the feasibility of the proposed solution. The result with full-feature accuracy was 93.55 percent compared to the proposed BDE-SVM approach, which is 93.99 percent. Empirical findings also show that our method is capable of effectively increasing the number of features required to enhance the reliability of the email spam classification.

A generic integrated approach of assembly tolerance analysis based on skin model shapes

2020 ◽  
pp. 095440542095886
Author(s):  
Yang Yi ◽  
Xiaojun Liu ◽  
Tingyu Liu ◽  
Zhonghua Ni
Keyword(s):  
Tolerance Analysis ◽  
Integrated Approach ◽  
Design Stage ◽  
Variation Theory ◽  
Contact Method ◽  
Skin Model ◽  
Manufacturing Defects ◽  
Assembly Tolerance ◽  
Contact Points ◽  
Assembly Deviation

Nowadays, assembly tolerance analysis has become a challenging problem to predict the accuracy of a final assembly and examine whether specified tolerances satisfy assembly functional requirements (AFRs) for ensuring product assembly performance. Skin model shapes can be addressed to represent part geometric tolerances with manufacturing defects, thereby providing high fidelity surfaces that can replace nominal or ideal surfaces and significantly improve the accuracy and reliability of assembly tolerance analysis. However, their application in easy-to-use assembly simulation is limited by the level of detail required for manufacturing defect simulation and the complicated calculation process for integrating these defects into the tolerance analysis. Therefore, to overcome these issues in predicting assembly deviations in the early design stage, we propose a generic integrated approach of assembly tolerance analysis based on skin model shapes. First, two methods are introduced for modelling and generating skin model shapes according to different mate types of assembly key features. Second, a calculation method of assembly deviation propagation is developed by the integration of skin model shapes and stream-of-variation theory with accuracy and efficiency guarantees. Besides, a slightly modified relative contact positioning method is presented, based on different surface and progressive contact method, to obtain deterministic contact points and contact positioning errors between key mating joint surfaces. And then, the deviation values of AFRs are calculated, considering the inevitable manufacturing and assembly process errors. Finally, a typical mechanical assembly on assembly tolerance analysis is used as a case study to demonstrate the effectiveness of the proposed approach.

scholarly journals Computer-Aided Design for Identifying Anticancer Targets in Genome-Scale Metabolic Models of Colon Cancer

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1115
Author(s):  
Chao-Ting Cheng ◽  
Tsun-Yu Wang ◽  
Pei-Rong Chen ◽  
Wu-Hsiung Wu ◽  
Jin-Mei Lai ◽  
...  
Keyword(s):  
Side Effects ◽  
Computer Aided Design ◽  
Fitness Function ◽  
Cholesterol Biosynthesis ◽  
Differential Evolution Algorithm ◽  
Fuzzy Optimization ◽  
Drug Efficacy ◽  
Pentose Phosphate ◽  
Normal Cells ◽  
Development Costs

The efficient discovery of anticancer targets with minimal side effects is a major challenge in drug discovery and development. Early prediction of side effects is key for reducing development costs, increasing drug efficacy, and increasing drug safety. This study developed a fuzzy optimization framework for Identifying AntiCancer Targets (IACT) using constraint-based models. Four objectives were established to evaluate the mortality of treated cancer cells and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Fuzzy set theory was applied to evaluate potential side effects and investigate the magnitude of metabolic deviations in perturbed cells compared with their normal counterparts. The framework was applied to identify not only gene regulator targets but also metabolite- and reaction-centric targets. A nested hybrid differential evolution algorithm with a hierarchical fitness function was applied to solve multilevel IACT problems. The results show that the combination of a carbon metabolism target and any one-target gene that participates in the sphingolipid, glycerophospholipid, nucleotide, cholesterol biosynthesis, or pentose phosphate pathways is more effective for treatment than one-target inhibition is. A clinical antimetabolite drug 5-fluorouracil (5-FU) has been used to inhibit synthesis of deoxythymidine-5′-triphosphate for treatment of colorectal cancer. The computational results reveal that a two-target combination of 5-FU and a folate supplement can improve cell viability, reduce metabolic deviation, and reduce side effects of normal cells.

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