Location Optimization of Wireless Sensor Network in Intelligent Workshop Based on the Three-Dimensional Adaptive Fruit Fly Optimization Algorithm

Shaobo Li,Chenglong Zhang,Jinglei Qu

doi:10.3991/ijoe.v14i11.9544

Abstract

The production process of modern manufacturing industry is complex and changeable, manufacturing resources have extensive dynamic characteristics. For effectively managing and controlling manufacturing resources, realizing real-time location data collection of intelligent workshop, a manufacturing resource location sensing architecture based on the wireless sensor network is proposed. For en-suring real-time accuracy of manufacturing resource location data in the intelligent workshop, a three-dimensional adaptive fruit fly optimization algorithm is de-signed to estimate the location coordinates, the new algorithm introduced the adaptive inertial weight coefficient, retained the advantage of strong local search ability of fruit fly optimization algorithm, improved the ability of global optimiza-tion, effectively solved the problem of three-dimensional location in intelligent workshop. The simulation results show that, the algorithm in this paper is applied to the location calculation of triangulation, which has smaller location error and shorter operation time, it improves the accuracy of the location data and meets the real-time location requirements of manufacturing resources such as intelligent workshop staff, materials, logistics vehicles etc. facilitate resource sensing and scheduling management, thereby improving management standards and product quality.

Highlights

As a new type of manufacturing mode, Internet of manufacturing things is a technology contains highly integrated and mixed together with electronic information technology, intelligent sensing technology and advanced manufacturing technology
In order to overcome the disadvantages of fly optimization algorithm (FOA) which is easy to fall into local optimum, combined with the strong global optimization ability of particle swarm optimization (PSO), aiming at the need of 3D location of manufacturing resources in intelligent workshop
Because the FOA is mainly used in the two-dimensional location optimization of wireless sensor network (WSN) nodes and has limited reference value, this article compares the 3D adaptive fruit fly optimization algorithm (3D-AFOA) with the three-dimensional fruit fly optimization algorithm (3D-FOA)to evaluate the superiority of the design algorithm

Summary

Introduction

As a new type of manufacturing mode, Internet of manufacturing things is a technology contains highly integrated and mixed together with electronic information technology, intelligent sensing technology and advanced manufacturing technology. The manufacturing resources such as raw material, equipment, tooling mold, site and operator have extensive dynamic characteristics, for effectively management and control manufacturing resources, to ensure the safety of the enterprises, improve the production efficiency, promote the intelligent development of the manufacturing industry, real-time and effective production data location collection becomes very necessary. The simulation results show that the design algorithm has strong local optimization ability and high efficiency of operation, can effectively find the minimum estimated coordinates of location error, efficiently locate 3D nodes and is conducive to achieving high precision location in the workshop to promote the realization of intelligent manufacturing

Location sensing architecture for intelligent workshop

The 3D-AFOA

Algorithm analysis

Conclusion