Optimization Of Inversion Algorithm For Detecting Unexploded Ordnance By Transient Electromagnetic Method

Unexploded ordnance has brought many security risks to the development of today’s society and economy.Transient electromagnetic method has many advantages such as strong anti-interference ability and has been widely used in the detection and clearance of unexploded ordnance.After obtaining the transient electromagnetic response data of unexploded ordnance,it is very important to adopt appropriate data processing methods to improve the detection efficiency of unexploded ordnance.In this thesis,the position parameters and characteristic responses of unexploded ordnance are Inverted by differential evolution algorithm based on the magnetic dipole model.By analyzing the inversion process of the algorithm to find out the factors affecting the computational efficiency of the inversion algorithm,corresponding measures are taken to optimize the inversion algorithm to improve the computational speed,and the accuracy and stability of the optimization algorithm are verified by measured experiments.The specific research work and innovation results are as follows:Firstly,the data preprocessing of inversion algorithm is optimized to improve the computational efficiency.Optimization of inversion algorithm taking the inversion of transient electromagnetic response data of 82 mm unexploded ordnance as an example,the portable transient electromagnetic system made by the Electromagnetic Sensing Technology Laboratory of Jilin University is used to obtain the target response.In the optimization of the data preprocessing,the response data are averaged before inversion calculation,and the accuracy of inversion results is guaranteed by improving the signal-to-noise ratio of the signal,at the same time,the calculation times are reduced and the efficiency of inversion calculation is improved.Secondly,the parameters of differential evolution algorithm are optimized to improve the computational efficiency.Each parameter of differential evolution algorithm is set to different values from small to large to observe the impact on inversion results and inversion speed,so as to determine the optimal differential evolution algorithm parameters and improve the computational efficiency again.When analyzing the influence of noise on the inversion results of the optimized algorithm,by setting the simulated response data of different background noise,the optimized algorithm is used to invert the position parameters and characteristic response,and the influence of background noise is analyzed.Thirdly,the stability and accuracy of the inversion results of the optimized algorithm are verified by experiment.Nine kinds of target bodies were selected as the test targets in the experiment,and the response data of different target bodies were obtained by using the portable transient electromagnetic detection system.The optimized differential evolution algorithm is used to invert the position parameters of the target,and the position inversion process is analyzed,the results show that the stability of the inversion algorithm is good.The conventional differential evolution algorithm and the optimized differential evolution algorithm are used to invert the position parameters and characteristic responses of the target respectively,the results show that the position parameters and characteristic responses obtained by the two algorithms are basically the same,and the positioning errors are all within 6cm,the calculation time of the optimized differential evolution algorithm is about 1.7% of the conventional differential evolution algorithm,which greatly improves the calculation efficiency.