| The ATLAS detector is a large particle detector located on the LHC of the European Nuclear Center Large Hadron Collider.In 2012,the ATLAS/CMS device on the LHC discovered the Higgs boson,introducing the basic science of particle physics into a new stage of development,and made a great contribution to the progress of basic physical science.In order to further discover new particles beyond the standard model,the LHC collider will be upgraded twice,and its collision energy and particle brightness will be greatly increased.After the upgrade of LHC,ATLAS detectors will face many problems.For this reason,the ATLAS cooperation team decided to carry out Phase I and Phase II upgrades of existing ATLAS detectors in 2018 and 2022 respectively.The main task of the Phase I upgrade is to develop a new detector system for the Muon spectrometer end cover,NSW,to solve the problems encountered by the SW detector system for Muon particle measurement.NSW PhaseI is mainly composed of three parts:track detector Micromegas,trigger detector sTGC and electronic readout system,and calorimeter CAL trigger electronics upgrade.Among them,the University of Science and Technology of China is mainly responsible for the research,production,and installation of the front-end electronics FEB of the sTGC detector of the NSW System.In the end,the NSW upgrade requires 153 6 blocks to be divided into two different types of FEB.Each block uses about 6-15 ASICs of various types,and finally provides about 322,000 read channels.FEB will undergo design and development,commissioning and testing,beam testing,upper chamber testing,and production and installation.Each link will generate a large amount of test data that will have a significant impact on the ultimate physical analysis of ATLAS experiments.Therefore,special management is required.For FEB design and development,debugging and testing,production and installation process will produce a large variety of data,difficult to manage issues,this paper first conducted a detailed investigation and analysis of the management requirements of FEB related data,put forward to build FEB data management A systematic way to solve this problem.Combining the results of previous needs analysis,we finally decided to develop the FEB data management system based on the Django model.Then we designed the conceptual model of the FEB data management system and the table structure of the underlying database hierarchically,and completed the FEB data management system on this basis.Development.Currently,this FEB data management system has been successfully applied to the storage and management of actual FEB-related data.The main innovations in this thesis are the following:(1)Based on the Django model,an electronic FEB-related data management system for ATLAS NSW Phase 1 sTGC detector front-ends was built,successfully solving the difficult problem of managing a large number of data in the entire ATLAS NSW Phase 1 upgrade process.The management system meets the different requirements put forward in various stages of FEB development,commissioning and testing,and test installation,and provides powerful scalability that can solve future demands.(2)In the face of a large number of data that need to be managed,two input methods,"single entry" and "batch entry," are provided,enabling users to select different methods for entry under different working conditions,successfully reducing the number of identical formats.The amount of work that the data is recorded at the same time is arduous.At the same time,the "single entry" mode retains the simplicity and convenience of entering a small amount of data. |
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