On Dynamic Compression Method Of Monitoring Data For Network Transmission Of Complicated Engineering Systems

The monitoring data generated in the operation cycle of a complicated engineering system can be directly used to reflect the overall state characteristics of the system and provide data support for online analysis,fault diagnosis and deep mining.However,in the process of system operation,the scale of monitoring data is large and the network environment is complex,which will seriously affect the overall transmission efficiency and data timeliness of the system.Some existing solutions such as improving the system network bandwidth,improving the transport layer protocol,and data caching have not solved the transmission efficiency problem caused by massive monitoring data in essence,and the complexity and cost are high.The compression algorithm is adopted to reduce the information redundancy of the data to be transmitted provides a new solution to the transmission efficiency problem.However,the compression algorithm will take additional data processing time,which is closely related to the data compression ratio.Therefor,on the basis of adjusting the lossless data compression ratio,a dynamic data compression method aiming at optimizing the overall transmission efficiency of the system has important theoretical and practical significance.The complex engineering system is taken as the application object,and the original data is compressed to reduce the amount of data transmitted by the system,so as to reduce the time of data transmission.Based on an in-depth analysis of the impact of compression algorithm on the overall transmission time of the system,and combined with the impact of transmission rate on transmission optimization in an unstable network environment,a transmission optimizAation method based on the prediction of transmission rate and dynamic regulation of compression ratio was proposed to improve the overall transmission efficiency of the system.The main work is as follows:(1)Based on the analysis of the current data transmission problems faced by the system,the advantages of the compression algorithm in solving the problem of mass monitoring data transmission are pointed out,and combined with the data transmission environment in the system's operating cycle,the overall scheme for optimizing the monitoring data transmission efficiency of the complicated engineering system is given.(2)LZW(Lempel-Ziv-Welch)compression algorithm is selected as the method to reduce the redundancy of data information to be transmitted in combination with the data size,characteristics and structure of the application object.At the same time,under the premise of ensuring the efficiency and accuracy of data transmission,in order to avoid adding too much data processing time to the sender and receiver,the in-depth analysis of the time-consuming composition of the system data transmission after the introduction of the compression algorithm is proposed.A transmission time-consuming optimization method based on dynamic compression ratio is further improved to improve system data transmission efficiency.(3)For the transmission rate under the network environment change on the influence of the current transmission optimization strategy,combined with the Long Short-Term Memory neural network to predict and analyze system data transmission rate,based on this,propose a dynamic adjustment of the compression ratio based on the predicted data transmission rate.The transmission time-consuming optimization method reduces the impact of data transmission rate changes on system transmission time-consuming optimization.Finally,the transmission time optimization method proposed is applied to the transmission process of monitoring data in complex engineering systems.The experimental results show that compared with the traditional transmission time optimization method based on data compression,the overall transmission time of monitoring data in the system can be effectively reduced with the method of the transmission time optimization.