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An improved sdt method applied in the field of NC machine tool monitoring

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

Active Publication Date: 2021-10-15
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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  • An improved sdt method applied in the field of NC machine tool monitoring
  • An improved sdt method applied in the field of NC machine tool monitoring
  • An improved sdt method applied in the field of NC machine tool monitoring

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Embodiment Construction

[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 improved SDT method applied in the field of monitoring of numerical control machine tools, comprising: segmenting the original data of the internal state of the numerical control system and performing standard SDT compression; adopting a multi-model optimization method to perform function fitting on the compressed data; According to the fitting error, the points that have a great impact on the compression accuracy are saved; according to the fluctuation state of the adjacent interval, the tolerance of the next interval to be compressed is dynamically adjusted. The method can dynamically adjust the tolerance according to the fluctuation state of the data; use the multi-model optimization method to fit the function; and save the points that have a great influence on the compression accuracy according to the fitting error. In this way, part of the redundant machine tool processing state process information is deleted, and less machine tool state data is stored while ensuring that effective information is not lost as much as possible, which has a better compression effect.

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 Patents(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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