Quality Control Of Aeronautical Information Raw Data Based On Quality Management

With the development of civil aviation of China,additions and expansions of airports,the increase and change of airway have increased,resulting in the amount of aeronautical information increasing that needs to be modified.Aeronautical information data is an important material for civil aviation.At present,the review of domestic aeronautical information data is mainly based on manual review that is reported layer by layer,and there is no effective theoretical method for implementation in terms of review efficiency.Quality control is the core of quality management and an important means to ensure the effectiveness of aeronautical information.Quality control runs through the entire production process of aeronautical information data products.Facing the increasing demand for aeronautical information data quality,the traditional manual control of data quality has been unable to adapt to the current situation.Therefore,it is important to use modern and advanced quality management methods to control the quality of aeronautical information data.This dissertation conducts in-depth research on the determination of quality control objectives,the comparison and selection of quality control methods,the development of the automatic review system for data in the flight area,the determination of neural networks and the process adjustment strategy,forming a complete set of quality control for aeronautical information raw data means.The main innovative research work of this dissertation is:(1)For the determination of quality control objectives,start with the use needs of users,analyze the types of users,and combine the requirements of the Civil Aviation Administration of China on the quality of aeronautical information data,use the method of questionnaires to collect the quality needs of users,and conduct factor analysis.Data analysis,construction of indicators to obtain quality control goals.(2)Establish the production process of aeronautical information raw data products based on the similar process quality control theory of statistical control theory,use the principle of process similarity combined with coding grouping technology to encode the aeronautical information raw data,and perform quality control in the form of group data.Improve the efficiency of quality control.(3)Design an automatic quality check system based on coded data,use Python as the system development environment,code as the data quality requirement,use Pandas in the Python library for data processing,and use the Python GUI application Tkinter to design the human-computer interaction interface.Improve the efficiency of data review.(4)It is proposed to use the audit results of the data audit system as input,and use statistical control theory to establish statistical quality control chart models and production process adjustment strategies applicable to this article.The Elman neural network is used to automatically recognize the control chart pattern to improve the recognition accuracy and efficiency.