Support Quality Analysis And Prediction System Of Hydraulic Support Based On Cloud Platform

Coal occupies the dominant position in China’s energy consumption structure,the situation will not change until emerging alternative energy technologies are developed.The key point of high quality development of coal industry lies in intelligent construction of coal mine,it is of great significance to improve the level of coal mine safety production and guarantee the stable supply of coal.Hydraulic support is the key equipment of fully mechanized mining,its main function is to complete the timely support of working face roof and coal wall,and prevent the occurrence of roof and wall collapse,provide safety guarantee for downhole workers and fully mechanized mining equipment,the failure of hydraulic support will directly affect the safety production and mining efficiency of working face.Therefore,the establishment of digital fully mechanized mining face of support quality analysis and prediction system of hydraulic support,real-time monitoring and analysis of the data generated by the work of hydraulic support,can enable the coal mine enterprises to grasp the working conditions of hydraulic support and ensure the safety of underground personnel and equipment.Aiming at the demand of coal mine enterprises for unified and effective management and analysis of massive data generated during the working cycle of hydraulic support in fully mechanized mining face,with Visual Studio 2019 as the software development environment,SQL Server 2014 as the database,Ali cloud ECS cloud server as the intelligent cloud platform carrier of fully mechanized mining face,the support quality analysis and prediction system of hydraulic support is constructed.Comprehensive use of big data,deep learning and other technologies to analyze and research the massive data of hydraulic supports,mining potential value in data,realize the effective use of massive monitoring data,guide the safe production of working faces,and speed up the intelligent and informatization construction of coal mining enterprises.Sort out the working resistance and moving stroke data generated by the hydraulic support of the fully mechanized coal mining face,design an appropriate data upload strategy and database table structure,use Java Script language,Ajax technology,ECharts technology to build data management module,real-time data monitoring and historical data query functions are realized,provide support for data analysis and prediction work.Through in-depth research on motion process of hydraulic support and the characteristic parameters of working resistance,develop the calculation of initial support pressure,end-ofloop resistance,time-weighted working resistance,analysis of safety valve working status and diagnosis of leakage of support column function,construct hydraulic support quality analysis module,so that the coal mine staff accurately and quickly understand the support of hydraulic support in fully mechanized mining face,to achieve accurate directional support maintenance.Build a bidirectional long short-term memory network model,take the historical data of hydraulic support working resistance as the data source,bring it into the model for training,optimize the model structure parameters,and realize the support working resistance prediction function through the system call model,so as to realize advance forecast and warning of abnormal support state of the hydraulic support.The support quality analysis and prediction system of hydraulic support based on cloud platform realizes the functions of real-time data monitoring,historical data query,support quality analysis,support working resistance prediction,system management and other functions,it is conducive to the working condition analysis and directional maintenance of the hydraulic support of the fully mechanized mining face,guarantees the efficient mining and safe production of coal in the fully mechanized mining face,and provides technical support for coal mining enterprises from extensive development to high-quality development.After practical application,the system runs stably with reliable results.