SDT improvement method applied to field of numerical control machine tool monitoring

A technology in the field of numerical control machine tools, applied in general control systems, program control, computer control, etc., can solve the problems of excessive memory consumption and occupying large storage units, and achieve the effect of reducing data compression errors and accurate fitting results

Active Publication Date: 2019-01-04
SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD
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Problems solved by technology

[0004] Aiming at the problem of occupying a large number of storage units and excessive memory consumption caused by the real-time collection of internal state data of the numerical control system, in order to make the massive process data easy to store and call back, the present invention provides an improved SDT method applied in the field of numerical control machine tool monitoring

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  • SDT improvement method applied to field of numerical control machine tool monitoring
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  • SDT improvement method applied to field of numerical control machine tool monitoring

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[0037] The method of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0038] In the SDT improved compression algorithm, ΔE represents the tolerance in the SDT algorithm, and the range is ΔE min ≤ΔE≤ΔE max ; T represents the time interval of the compression interval; δ max Indicates the compressed maximum fitting error. Among them, ΔE min is the minimum value of the tolerance, ΔE max is the maximum tolerance.

[0039] The indicators to measure the quality of a process data compression algorithm include compression ratio CR (Compression Ratio) and compression error CE (Compression Error). Where n is the number of original data points, m is the number of compressed data points, and satisfies m≤n. the y i is the actual data point value, is the data point value recovered after decompression by compressed data. CE describes how close the data recovered after decompression is to the actual data after compressio...

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Abstract

The invention relates to an SDT improvement method applied to the field of numerical control machine tool monitoring. The SDT improvement method comprises the following steps: segmenting the internalstate original data of the numerical control system and performing standard SDT compression; performing function fitting of the compressed data by using the multi-model optimization method; saving thepoints having high influence on the compression precision according to the fitting error; and dynamically adjusting the tolerance of the next interval to be compressed according to the fluctuation state of the adjacent intervals. According to the method, the tolerance can be dynamically adjusted according to the fluctuation state of the data; function fitting is performed by using the multi-modeloptimization method; and the points having high influence on the compression precision are saved according to the fitting error. Therefore, the partially redundant machining state process informationof the machine tool can be deleted, and less machine tool state data can be stored without losing the effective information as far as possible so that the compression effect is better.

Description

technical field [0001] The invention relates to the field of monitoring of numerically controlled machine tools, in particular to an improved SDT method applied to the field of monitoring of numerically controlled machine tools. Background technique [0002] In the CNC machine tool monitoring platform, usually multiple pieces of industrial process data can be collected per second, and there are many types of data collected, such as shaft speed, power, load, current and sensor data, etc., the data volume of multiple machine tools in a day is large It reaches the GB level, which brings a great burden to the storage of the database. Therefore, it is necessary to compress these data to improve storage efficiency and save storage space. [0003] At present, there are generally three types of compression methods for industrial process data: piecewise linear interpolation methods, vector quantization methods, and signal transformation methods. Among them, the piecewise linear inte...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/408
CPCG05B19/408G05B2219/35356
Inventor 胡毅李力毕筱雪刘劲松张曦阳吴迪
Owner SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD
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