Optimal sensor placement for deployable antenna module health monitoring in SSPS using genetic algorithm

Abstract The concept of space solar power satellite (SSPS) is an advanced system for collecting solar energy in space and transmitting it wirelessly to earth. However, due to the long service life, in-orbit damage may occur in the structural system of SSPS. Therefore, sensor placement layouts for structural health monitoring should be firstly considered in this concept. In this paper, based on genetic algorithm, an optimal sensor placement method for deployable antenna module health monitoring in SSPS is proposed. According to the characteristics of the deployable antenna module, the designs of sensor placement are listed. Furthermore, based on effective independence method and effective interval index, a combined fitness function is defined to maximize linear independence in targeted modes while simultaneously avoiding redundant information at nearby positions. In addition, by considering the reliability of sensors located at deployable mechanisms, another fitness function is constituted. Moreover, the solution process of optimal sensor placement by using genetic algorithm is clearly demonstrated. At last, a numerical example about the sensor placement layout in a deployable antenna module of SSPS is presented, which by synthetically considering all the above mentioned performances. All results can illustrate the effectiveness and feasibility of the proposed sensor placement method in SSPS.

[1]  Q. Feng,et al.  Optimizing well placement in a coalbed methane reservoir using the particle swarm optimization algorithm , 2012 .

[2]  Seamus D. Garvey,et al.  Automatic choice of measurement locations for dynamic testing , 1994 .

[3]  Junjie Li,et al.  Virus coevolution partheno-genetic algorithms for optimal sensor placement , 2008, Adv. Eng. Informatics.

[4]  Wei Liu,et al.  Optimal sensor placement for spatial lattice structure based on genetic algorithms , 2008 .

[5]  Abolfazl Toroghi Haghighat,et al.  Energy-aware framework with Markov chain-based parallel simulated annealing algorithm for dynamic management of virtual machines in cloud data centers , 2017, The Journal of Supercomputing.

[6]  Loris Vincenzi,et al.  Influence of model errors in optimal sensor placement , 2017 .

[7]  Gun-Shing Chen,et al.  OPTIMAL PLACEMENT OF ACTIVE/PASSIVE MEMBERS IN TRUSS STRUCTURES USING SIMULATED ANNEALING , 1991 .

[8]  D. Kammer.  Effect of model error on sensor placement for on-orbit modal identification of Large Space Structures , 1991 .

[9]  Bin Ma,et al.  Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm , 2013 .

[10]  Chinchao Liu,et al.  Sensor placement for time-domain modal parameter estimation , 1996 .

[11]  Hongnan Li,et al.  A modified monkey algorithm for optimal sensor placement in structural health monitoring , 2012 .

[12]  Jinqing Jia,et al.  Acceleration sensor placement technique for vibration test in structural health monitoring using microhabitat frog-leaping algorithm , 2018 .

[13]  K. W. Wang,et al.  Damage detection via electrical impedance tomography in glass fiber/epoxy laminates with carbon black filler , 2015 .

[14]  Shunan Wu,et al.  Robust optimal sun-pointing control of a large solar power satellite , 2016 .

[15]  C. Papadimitriou,et al.  The effect of prediction error correlation on optimal sensor placement in structural dynamics , 2012 .

[16]  Shunan Wu,et al.  Parametrical Excitation Model for Rigid–Flexible Coupling System of Solar Power Satellite , 2017 .

[17]  Aditi Chattopadhyay,et al.  Application of System-Identification Techniquest to Health Monitoring of On-Orbit Satellite Boom Structures , 2011 .

[18]  Shunan Wu,et al.  Gravitational orbit–attitude coupling dynamics of a large solar power satellite , 2017 .

[19]  Shiqi Li,et al.  Optimal sensor placement using FRFs-based clustering method , 2016 .

[20]  P. Glaser.  Power from the sun: its future. , 1968, Science.

[21]  Chen Yang,et al.  An interval effective independence method for optimal sensor placement based on non-probabilistic approach , 2017 .

[22]  F. Udwadia.  Methodology for Optimum Sensor Locations for Parameter Identification in Dynamic Systems , 1994 .

[23]  Hong-Nan Li,et al.  Comments on “Clustering of Sensor Locations Using the Effective Independence Method” , 2016 .

[24]  D. Kammer.  Sensor Placement for On-Orbit Modal Identification and Correlation of Large Space Structures , 1990, 1990 American Control Conference.

[25]  Qingshan Yang,et al.  Sensor placement methods for an improved force identification in state space , 2013 .

[26]  Sang Jun Lee,et al.  Damage detection sensitivity characterization of acousto-ultrasound-based structural health monitoring techniques , 2016 .

[27]  Rakesh K. Kapania,et al.  Placement Optimization of Distributed-Sensing Fiber-Optic Sensors Using Genetic Algorithms , 2008 .

[28]  Hashim Abdul Razak,et al.  Optimal sensor placement for time-domain identification using a wavelet-based genetic algorithm , 2016 .

[29]  Ting-Hua Yi,et al.  Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm , 2011 .

[30]  Xiongfei Li,et al.  A High Performance Piezoelectric Sensor for Dynamic Force Monitoring of Landslide , 2017, Sensors.

[31]  Rafael Castro-Triguero,et al.  Clustering of Sensor Locations Using the Effective Independence Method , 2015 .

[32]  Lei Wang,et al.  Inverse system method for dynamic loads identification via noisy measured dynamic responses , 2016 .

[33]  E. J. Friebele,et al.  Optical fiber sensors for spacecraft: applications and challenges , 2004, SPIE Optics + Photonics.

[34]  Ruixing Wang,et al.  Time-Dependent Reliability Modeling and Analysis Method for Mechanics Based on Convex Process , 2015 .

[35]  D. MacManus,et al.  Correction: Aerodynamic interference on a finned slender body , 2016 .

[36]  Dongsheng Li,et al.  The connection between effective independence and modal kinetic energy methods for sensor placement , 2007 .

[37]  Daniel C. Kammer,et al.  Mass-weighting methods for sensor placement using sensor set expansion techniques , 2008 .

[38]  Lei Wang,et al.  Dynamic loads identification in presence of unknown but bounded measurement errors , 2015 .

[39]  Peter Thomson,et al.  Optimal sensor placement for modal identification of structures using genetic algorithms—a case study: the olympic stadium in Cali, Colombia , 2010, Ann. Oper. Res..

[40]  Quan Hu,et al.  Optimal Placement of Sensors and Actuators for Gyroelastic Body Using Genetic Algorithms , 2016 .

[41]  Makola M. Abdullah,et al.  Placement of sensors/actuators on civil structures using genetic algorithms , 2001 .

[42]  Chen Yang,et al.  Applications of different criteria in structural damage identification based on natural frequency and static displacement , 2016 .

[43]  Li Wang,et al.  Thermal design, analysis and comparison on three concepts of space solar power satellite , 2017 .

[44]  Qingshan Yang,et al.  Sensor placement method for dynamic response reconstruction , 2014 .

[45]  Keng C. Yap,et al.  Structural Health Monitoring and Risk Management of a Reusable Launch Vehicle , 2012 .

[46]  Xiaojun Wang,et al.  Structural time‐dependent reliability assessment of the vibration active control system with unknown‐but‐bounded uncertainties , 2017 .

[47]  Clark R. Dohrmann,et al.  A modal test design strategy for model correlation , 1994 .

[48]  Nobuo Takeda,et al.  Damage detection of satellite structures by optical fiber with small diameter , 2000, Smart Structures.