The Study Of Muon Tomography Based On Micro-Pattern Gas Detector

Natural cosmic ray muon has strong penetrating power and no radiation,which can not cause radiation damage to operator.Currently,using the technology of the cosmic ray muon imaging for non-destructive testing has become a research hotspot.Micro-Pattern gas detectors have some advantages,which are high detection efficiency,high spatial resolution and high count rate,low cost,large sensitive range.They are very suitable to use for muon imaging spectrometers and to be a trend.In this project,the working principle and performance of Micro-Pattern gas detectors were studied,and we developed a muon spectrum based on Micromegas detector in the State Key Laboratory of Particle Detections and Electronics at the University of Science and Technology of China.In the other hand the inspect materials are reconstructed by two different imaging algorithms.Firstly,ANSYS was used to model the geometric and to compute electric field of Micromegas and M-THGEM,respectively.And Garfield++ was used to recall the files of ANSYS to setup the whole electric field and to computed the effective gain,electron transmittance factor,ion feedback rate and induced signal,and others parameters such as electron drift velocity,diffusion coefficient,detector gain signal under the different ratios mixed gas conditions.The performance of the Micromegas detector under different pitches and the readout board were simulated.The simulation results show that the detector performance is optimal when the operating voltage is 600 V and the pitch is 100μm-200μm.Experimentally,A cosmic ray muon imaging system was build based on unique hot-melt-adhesive-crimping-process Micromegas at USTC.The sensitive area of the detector is 150 mm × 150 mm with two-dimensional readout PCB,and each direction strips are 3×128 with a pitch of 0.4mm.the The DAQ uses AGET multi-channel general electronics system.The experimental results show that the detection efficiency is more than 80%,and the spatial resolution of 200μm.A block of tungsten and copper of 30 mm × 30 mm × 40 mm were inspected.Using the PoCA algorithm and the MLSD algorithm were used to analysis 42 hours of data collection to reconstruct image.The results show that both algorithms can distinguish the tungsten block from the copper block with a roughly judge the position and shape.The reconstruction result of the MLSD algorithm is obviously better than that of the PoCA algorithm,due to the short data collection time and the insufficient efficiency of data,the clarity of the reconstructed image is worse than that of the simulation.