Telemeasuring data storage method based on data pair

Abstract

The invention provides a telemeasuring data storage method based on a data pair. The telemeasuring data storage method comprises steps of (1) cutting continuous telemeasuring data in an equal time interval slicing method to form N groups of independent data point groups, (2) dividing N slices into two sequences of V part and T part and then compressing the N slices, compressing and storing the V part of each slice of the N slices according to a principle, and compressing and storing the T part of each slice of the N slices. A group of independent data point group forms a slice. A data level slicing storage technology and frame structure compression algorithm are employed in the telemeasuring data storage method; frame structure feature compression is achieved on the basis of data partitioning and aggregation; the telemeasuring data storage method is advantaged by fast retrieval speed, prevention of data compression loss and low internal memory cost; and performance output can be improved and storage demands can be lowered.

Description

technical field [0001] The invention belongs to the field of aerospace technology, in particular to a method for storing telemetry data based on data pairs. Background technique [0002] In aerospace and other fields, it is often necessary to store the state data of rockets, aircraft, spacecraft, equipment and other equipment in working state for monitoring and analyzing the operation of the target. Such data containing the operating status of the target device is generally called telemetry data. The telemetry parameter refers to a certain measurement or sampling point in the device, and the telemetry data refers to the sampling result of the telemetry parameter. Telemetry data generally consists of continuous data, including data sampling time T and measurement results V. If the target continues to function, telemetry data is continuously generated from the measurement location. When a device is running for a long time, its sample data volume may reach billions. [0003...

AI Technical Summary

Problems solved by technology

[0004] 1. Most of the existing telemetry data storage systems use relational databases for storage, and the performance may decrease with the data scale due to the dependencies and data integrity requirements of relational databases

[0005] 2. Use additional memory resources to index data keys, and the system hardware requirements are relatively high

[0006] 3. In order to achieve the purpose of fast retrieval and data compression, many existing telemetry data storage systems delete telemetry data with repeated values ​​to achieve data compression. This method cannot accurately restore the original data and cannot meet some special data analysis requirements; The system completely stores the data in the database, thus occupying a large amount of storage devices and reducing the efficiency of data retrieval

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