Research On The Optimal Arrangement Of Cable-stayed Bridge Sensor Based On Adaptive Dragonfly Algorithm

As the scale of bridge structures increases,the force characteristics become more and more complex.During normal service,environmental erosion,material aging,fatigue effects and complex loads are subject to the adverse effects of environmental erosion,material aging,fatigue effects and complex loads,which will inevitably lead to the accumulation of damage to the bridge,which in turn affects the function of the structure.How to establish a health monitoring system for bridge structures,timely and accurate information on the health status of the structure during operation and safety assessment of its own status has become particularly important.It is imperative to collect and obtain the corresponding information of the structure in real time for bridge health assessment,and the optimal arrangement of sensors is an extremely critical part of the bridge structural health monitoring system,which plays a decisive role in the effectiveness of data collection.Considering the influence of economic and other factors,the optimal arrangement of sensors is to use as few sensors as possible to obtain as much structural information as possible,and the following aspects are studied in this paper for large bridge structures:(1)The health monitoring of bridge structure and the optimal arrangement of sensors are discussed,and the background and significance of the optimal arrangement of sensors are clarified.The current status of sensor optimization arrangement research at home and abroad is analyzed,and the main problems existing in the existing sensor optimization layout research are pointed out: intelligent optimization algorithm selection and improvement problem,optimization criterion determination problem,structural mode selection order problem and sensor arrangement quantity and position problem,and the content to be studied in this paper is clarified.(2)In order to solve the disadvantages of particle swarm and genetic algorithms in sensor optimisation,such as the tendency to fall into local solutions and slow convergence,the Dragonfly algorithm is proposed for optimisation and its principles are investigated in more detail.In order to better improve the performance of the algorithm and dynamically balance its global and local search capabilities,the dragonfly algorithm with linearly decreasing,non-linearly decreasing and adaptive inertia weights is proposed.(3)Use Matlab software to program the dragonfly algorithm and three improved algorithms,as well as particle swarm and genetic algorithms,and use Ackley and Rastrigin functions as numerical test platforms to analyze the performance of the above six algorithms.The experimental results show that the convergence and optimization ability of the dragonfly algorithm are significantly better than the particle swarm algorithm and the genetic algorithm,and the results obtained have higher accuracy and better stability.At the same time,among the three improved algorithms,the dragonfly algorithm with adaptive inertia weights has the best performance.(4)A cable-stayed bridge is used as the engineering background and a finite element model is established.For its structural characteristics,the locations where the optimal arrangement of sensors is required are clarified,followed by the screening of candidate measurement points.The modal extraction of the established cable-stayed bridge model is carried out using the Lanczos method,and the modal theory is used to transform the tower displacement modal into the inclination modal,in preparation for the subsequent analysis and the optimisation of the sensor arrangement.(5)The rate of change of the Fisher information matrix 2 norm is used to screen and determine the modal vector and order that represent all modal information of the entire structure required for the optimal arrangement of the sensor.The number of sensors to be arranged is determined by using the non-diagonal element maximum minimum and average minimum objective functions of the modal confidence matrix MAC,respectively.Then,the adaptive dragonfly algorithm,particle swarm algorithm and genetic algorithm are used to optimize the sensor arrangement,and the sensor layout scheme of the main beam and bridge tower is given,and the arrangement results of the three algorithms are evaluated,which verifies the feasibility and superiority of the adaptive dragonfly algorithm for the optimal arrangement of the sensor.