The method of selective assembly for the RV reducer based on genetic algorithm

2017 ◽  
Vol 232 (6) ◽  
pp. 921-929 ◽  
Author(s):  
Xuyang Chu ◽  
Huihuang Xu ◽  
Xiaomin Wu ◽  
Jiping Tao ◽  
Guifang Shao
Keyword(s):  
Genetic Algorithm ◽  
Complex Structure ◽  
Selective Assembly ◽  
Matching Algorithm ◽  
Assembly Method ◽  
Assembly Accuracy ◽  
Manufacturing Errors ◽  
Rv Reducer ◽  
Assembly Precision ◽  
Very High

As a precision gear reducer, the RV reducer has a low-transmission backlash (very high assembly accuracy). Therefore, the selective assembly method is the only assembly method which can guarantee the assembly precision of the RV reducer. However, the RV reducer has a complex structure; it consists of a high number of parts whose machining tolerance cannot be very low. Furthermore, there are numerous parts, the tolerances of which influence the RV reducer transmission backlash. Therefore, it is difficult to achieve high assembly accuracy by using the traditional selective assembly method. In this paper, a method of selective assembly is proposed to make the backlash of the RV reducer meet the requirements through the analysis of the characteristics of the RV reducer structure, the processing and assembly process of the parts, and the influence of manufacturing errors on the backlash. Then, a mathematical model was established for the RV reducer assembly issue. And a matching algorithm based on a genetic algorithm was developed. Finally, the algorithm was applied to the selective assembly of the RV reducer for verifying the feasibility and validity of the proposed matching method.

scholarly journals A new spatial angle assembly method of the ICF target

2017 ◽  
Vol 5 ◽  
Author(s):  
Wenrong Wu ◽  
Lie Bi ◽  
Kai Du ◽  
Juan Zhang ◽  
Honggang Yang ◽  
...  
Keyword(s):  
Inertial Confinement Fusion ◽  
Feedback System ◽  
Inertial Confinement ◽  
Assembly Method ◽  
Assembly Accuracy ◽  
Angle Measuring ◽  
Real Time Image ◽  
Confinement Fusion ◽  
Time Image ◽  
Assembly Precision

The designs of inertial confinement fusion (ICF) targets, which field on ShenGuang III, are becoming more complex and more stringent in terms of assembly precision. A key specification of these targets is the spatial angle alignment accuracy. To meet these needs, we present a new spatial angle assembly method, using target part’s 3D model-based dual orthogonal camera vision, which is better suited for the flexible automation of target assembly processes. The two-hands structure micromanipulate system and dual orthogonal structure visual feedback system were investigated by considering the kinematics, spatial angle measuring, and motion control in an integrated way. In this paper, we discuss the measurement accuracy of spatial angle assembly method, which compared the real-time image acquisition with the redrawing 2D projection. The result shows that the assembly method proposed is very effective and meets the requirements of angle assembly accuracy, which is less than $1^{\circ }$. Also, this work is expected to contribute greatly to the advancement of other target microassembly equipments.

scholarly journals Optimization of Selective Assembly for Shafts and Holes Based on Relative Entropy and Dynamic Programming

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1211
Author(s):  
Mingyi Xing ◽  
Qiushuang Zhang ◽  
Xin Jin ◽  
Zhijing Zhang
Keyword(s):  
Dynamic Programming ◽  
High Precision ◽  
Relative Entropy ◽  
Optimization Method ◽  
Geometric Error ◽  
Selective Assembly ◽  
Assembly Method ◽  
Assembly Accuracy ◽  
Mating Surface

Selective assembly is the method of obtaining high precision assemblies from relatively low precision components. For precision instruments, the geometric error on mating surface is an important factor affecting assembly accuracy. Different from the traditional selective assembly method, this paper proposes an optimization method of selective assembly for shafts and holes based on relative entropy and dynamic programming. In this method, relative entropy is applied to evaluate the clearance uniformity between shafts and holes, and dynamic programming is used to optimize selective assembly of batches of shafts and holes. In this paper, the case studied has 8 shafts and 20 holes, which need to be assembled into 8 products. The results show that optimal combinations are selected, which provide new insights into selective assembly optimization and lay the foundation for selective assembly of multi-batch precision parts.

Health monitoring sensor placement optimization based on initial sensor layout using improved partheno-genetic algorithm

2020 ◽  
pp. 136943322094719
Author(s):  
Xianrong Qin ◽  
Pengming Zhan ◽  
Chuanqiang Yu ◽  
Qing Zhang ◽  
Yuantao Sun
Keyword(s):  
Genetic Algorithm ◽  
Health Monitoring ◽  
Large Scale ◽  
Complex Structure ◽  
Sensor Placement ◽  
Placement Problem ◽  
Optimal Sensor Placement ◽  
Placement Optimization ◽  
Sensor Placement Optimization ◽  
Sensor Locations

Optimal sensor placement is an important component of a reliability structural health monitoring system for a large-scale complex structure. However, the current research mainly focuses on optimizing sensor placement problem for structures without any initial sensor layout. In some cases, the experienced engineers will first determine the key position of whole structure must place sensors, that is, initial sensor layout. Moreover, current genetic algorithm or partheno-genetic algorithm will change the position of the initial sensor locations in the iterative process, so it is unadaptable for optimal sensor placement problem based on initial sensor layout. In this article, an optimal sensor placement method based on initial sensor layout using improved partheno-genetic algorithm is proposed. First, some improved genetic operations of partheno-genetic algorithm for sensor placement optimization with initial sensor layout are presented, such as segmented swap, reverse and insert operator to avoid the change of initial sensor locations. Then, the objective function for optimal sensor placement problem is presented based on modal assurance criterion, modal energy criterion, and sensor placement cost. At last, the effectiveness and reliability of the proposed method are validated by a numerical example of a quayside container crane. Furthermore, the sensor placement result with the proposed method is better than that with effective independence method without initial sensor layout and the traditional partheno-genetic algorithm.

scholarly journals Control of the lighting system using a genetic algorithm

2012 ◽  
Vol 16 (suppl. 1) ◽  
pp. 237-250 ◽  
Author(s):  
Velimir Congradac ◽  
Bosko Milosavljevic ◽  
Jovan Velickovic ◽  
Bogdan Prebiracevic
Keyword(s):  
Genetic Algorithm ◽  
Social Life ◽  
Electricity Consumption ◽  
Energetic Efficiency ◽  
Lighting System ◽  
Total Consumption ◽  
The Social ◽  
Series Of Experiments ◽  
The Mathematical Model ◽  
Very High

The manufacturing, distribution and use of electricity are of fundamental importance for the social life and they have the biggest influence on the environment associated with any human activity. The energy needed for building lighting makes up 20-40% of the total consumption. This paper displays the development of the mathematical model and genetic algorithm for the control of dimmable lighting on problems of regulating the level of internal lighting and increase of energetic efficiency using daylight. A series of experiments using the optimization algorithm on the realized model confirmed very high savings in electricity consumption.

scholarly journals Problems of mineral raw material losses of quality and quantity management in developing of large-scale complex-structure deposits.

2018 ◽  
Vol 56 ◽  
pp. 04003
Author(s):  
Sergei Tkach
Keyword(s):  
Large Scale ◽  
Raw Materials ◽  
Complex Structure ◽  
Raw Material ◽  
Qualitative And Quantitative ◽  
Mineral Raw Material ◽  
Regulatory Documents ◽  
Geological Conditions ◽  
High Degree ◽  
Very High

The article deals with the problems of mineral raw material losses of quality and quantity management in developing of large-scale complex-structure and composition deposits of solid minerals. It is shown that a very high degree of mining and geological conditions variability in time and space for the development of mining units is typical for such deposits. This significantly complicates the qualitative and quantitative operating losses setting and accounting of mineral raw materials during its extraction in the framework of existing general and industry regulatory documents. Conceptual principles for face-by-face operational setting of losses and impoverishment of minerals for the conditions of bulk mining of complex-structure deposits with the formation of gross mining flow with economically feasible and specified level of quality (the content of commercial and harmful components) are stated. These principles generally do not contradict effective instructions main provisions and are made to minimize the total operating losses during the processing of several mine sections (faces).

Optimization of Styrene Reactor Using Tabu Search and Genetic Algorithm Methods

2012 ◽  
Vol 9 (1) ◽  
Author(s):  
Shahrokh Shahhosseini ◽  
Samaneh Vakili
Keyword(s):  
Genetic Algorithm ◽  
Tabu Search ◽  
Homogeneous Model ◽  
Ethyl Benzene ◽  
Catalytic Dehydrogenation ◽  
Algorithm Optimization ◽  
Decision Variables ◽  
Adiabatic Reactor ◽  
Very High ◽  
Styrene Conversion

This paper deals with multi-objective optimization of styrene reactor using Tabu search (TS) and genetic algorithm (GA) methods. Styrene is produced commercially by catalytic dehydrogenation of ethyl benzene. As styrene is an important monomer, the capacity of the plant is usually very high, as a result the investment cost is also very high, and even a small enhancement in the plant operation can generate major income. The adiabatic reactor using the pseudo homogeneous model was considered in this study for maximizing the styrene conversion and selectivity. A computer program was written to simulate an adiabatic reactor in order to evaluate the possibility of optimizing the process in simulation environment. The simulation results were compared with the experimental data. This comparison indicated that the value of overall mean squarer of errors for conversion of the compounds was 7.09E-05 and overall means relative error of them was 2.18 percent. In order to optimize the performance of the reactors, conversion of styrene was adopted as the objective function. Six decision variables, namely, ethyl benzene feed temperature at the entrance of each bed, pressure, the ratio of steam to ethyl benzene and initial ethyl benzene flow rate were used for the optimization. The results of GA optimization showed final conversion of styrene increased from an initial value of 0.710 to 0.75 after 100 generation of population. Applying Tabu algorithm optimization, the value rose from 0.725 to 0.813 after generation of 100 neighborhoods. The results revealed that the CPU time needed to optimize the reactor for TS was shorter than that of GA method. In addition, using the same iteration numbers for both methods, the optimum value of styrene conversion was greater when TS method was applied.

Research of Gantry Machining Center Assembly Deviation Sensitivity Based on Multi-Body System

2014 ◽  
Vol 494-495 ◽  
pp. 365-372
Author(s):  
Guo Ping An ◽  
Zhuang Zhuang Liu ◽  
Zhi Feng Liu ◽  
Yong Sheng Zhao ◽  
Li Gang Cai
Keyword(s):  
Complex Structure ◽  
Cnc Machine Tools ◽  
Body System ◽  
Heavy Duty ◽  
Cnc Machine ◽  
Machining Center ◽  
Assembly Method ◽  
Special Points ◽  
Multi Body ◽  
Assembly Deviation

Heavy duty machine tool has some special points, such as large size, complex structure, long cycle at Installation and commissioning, high requirements assembly processes and so on. Therefore, this paper established a mathematical model to transform the origin parts of the gantry machining center into assembly special form and creates a software as a plug-in for Solidworks based on it, proposes an easy but very practical assembly method based on Multi-body system under virtual environment. This method can calculate assembly deviation caused by manufacturing tolerance very quickly, and bring the sensitivity information clearly. Assembly deviation sensitivity and assembly method proposed in this paper can provide a way for the virtual assembly of heavy-duty CNC machine tools, Thus provide an important theoretical basis to improve the performance of the machine

A Multistage Approach to the Selective Assembly of Components Without Dimensional Distribution Assumptions

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Abolfazl Rezaei Aderiani ◽  
Kristina Wärmefjord ◽  
Rikard Söderberg
Keyword(s):  
Genetic Algorithm ◽  
Past Research ◽  
Selective Assembly ◽  
Quality Product ◽  
Dimensional Distribution ◽  
Surplus Parts

Selective assembly is a means of obtaining higher quality product assemblies by using relatively low-quality components. Components are selected and classified according to their dimensions and then assembled. Past research has often focused on components that have normal dimensional distributions to try to find assemblies with minimal variation and surplus parts. This paper presents a multistage approach to selective assembly for all distributions of components and with no surplus, thus offering less variation compared to similar approaches. The problem is divided into different stages and a genetic algorithm (GA) is used to find the best combination of groups of parts in each stage. This approach is applied to two available cases from the literature. The results show improvement of up to 20% in variation compared to past approaches.

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