Variable-step-length dynamic compression method for real-time monitored data in mine environment

Abstract

The invention relates to a variable-step-length dynamic compression method for real-time monitored data in a mine environment, belonging to a time sequence data compression method. The method is a variable-step-length data compression method, which is designed for the real-time performance, the timeliness, the multi-source performance and the massive performance of monitored data of a mine hydrological sensor; sample characteristics of monitored data of the mine environment are analyzed, so that an real-time early warning level dividing point of the mine environment is calculated; the event early warning level of the mine environment is comprehensively calculated; compression step lengths of real-time and historical monitored data are respectively calculated; and a compression algorithm of the historical and real-time monitored data is designed. By means of the variable-step-length dynamic compression method for the real-time monitored data in the mine environment disclosed by the invention, a monitored data sample of the mine environment can be dynamically adjusted; the event early warning level of the mine environment is calculated; a monitored data compression function having the variable compression step length can be realized; by means of the method, the change tendency of the monitored data can be reflected as much as possible; while motored time sequence data characteristics are reserved, the data storage space and the time can be simplified; and the monitored data inquiry and display efficiency can be increased.

Description

technical field [0001] The invention relates to a time series data compression method with variable step size, in particular to a dynamic compression method for real-time monitoring data of mine environment with variable step size. Background technique [0002] The mine environment monitoring system based on the Internet of Things deploys a variety of mine environment monitoring sensors under the mine. Through Internet communication technology, the real-time monitoring time series data can be transmitted to the network database on the remote server, and the mine environment monitoring time series data can be collected and sent to the network database. Users provide mine environment real-time monitoring data services. However, the mine environment monitoring system is faced with the need for real-time and comprehensive monitoring of various parameters of the mine environment, so as to be able to dynamically, real-time, and comprehensively respond to the research needs of the ...

AI Technical Summary

Problems solved by technology

Although the dimensions of the compressed data can be expanded arbitrarily without limitation, this method uses fixed components to perform linear combination of M time-based functions to achieve time-series data fitting and compression. The fixed components prevent data compression from changing according to the time-series data. Lossy compression of different degrees is difficult to apply to the dynamic compression of real-time monitoring time-series data such as mine environmental monitoring data, and it is impossible to dynamically obtain the compression step (variable) according to the warning level of mine environmental monitoring. It is difficult to ensure the change trend of time-series data Realize dynamic compression of data without changing

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