Supervision data generation device and supervision data generation method

A data generation and data technology, applied in the direction of length measuring device, reasoning method, database update, etc., can solve the problems of controlling interference, finding control rules, and difficult to achieve control accuracy, so as to achieve the effect of realizing control and high-precision control

Pending Publication Date: 2019-12-17
HITACHI LTD
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AI Technical Summary

Problems solved by technology

When the control rules become unrealistic, if the control rules are not tested and improved, it is difficult to achieve a certain degree of control accuracy
[0014] However, once the shape control operates, the operator's manual operation interferes with the control, so the operator does not perform manual operation.
Therefore, it is difficult to find new control rules

Method used

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  • Supervision data generation device and supervision data generation method
  • Supervision data generation device and supervision data generation method
  • Supervision data generation device and supervision data generation method

Examples

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Example Embodiment

[0039] First, the basic concept included in the present embodiment will be described.

[0040] In equipment control, actual phenomena that cannot be modeled, operator skills based on past experience, etc. are included in the past operation performance data of equipment. Therefore, it is effective for optimal equipment control to collect past operation performance data of equipment, extract control rules offline, and use the extracted control rules as supervisory data for learning. A control rule is information that associates shape outputs (state quantities) with operations (operation quantities). Here, an implementation procedure for applying the results of machine learning performed by AI offline using supervised data generated based on previously accumulated past facility operation performance data to an actual machine will be described below.

[0041] (1) Collect the actual operation performance data of the equipment.

[0042] (2) Supervision data used in machine learnin...

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Abstract

The invention provides a supervision data generation device and a supervision data generation method, which can realize high-precision control from an early stage by starting control of equipment based on artificial intelligence. An operation result evaluation value (Tv), which is an evaluation value of a result corresponding to an operation performed during a predetermined extraction time width (tband) from a predetermined start time (t1), is calculated on the basis of the device operation performance data. Whether new supervision data (Tnew) can be generated is determined using the operationresult evaluation value (Tv). When it is determined that the supervision data (T) can be generated, supervision data (T) including a supervision data input unit (Tin) calculated on the basis of the plate shape state quantity S (t) at the start time (t1) and a supervision data output unit (Tout) calculated on the basis of the operation machine state quantity O (t) during a predetermined extractiontime width tband from the start time (t1) is extracted. The extracted supervision data (T) is stored in a neural network learning supervision data database (DB2).

Description

technical field [0001] The present invention relates to a technique for generating supervisory data used for machine learning of artificial intelligence such as a neural network for real-time feedback control. Background technique [0002] In various devices, in order to obtain desired control results, device control is implemented based on various control theories. [0003] A rolling mill is mentioned as an example of equipment. In the control of rolling mills, for example, fuzzy control and neuro-fuzzy control are applied as control theories aimed at controlling the shape control of the fluctuating state of the plate. Fuzzy control is applied to shape control using coolant. Neuro-fuzzy control applied to shape control of Sendzimir rolling mill. [0004] Patent Document 1 discloses shape control using neuro-fuzzy control. Patent Document 1 discloses a technique of obtaining the similarity ratio between the difference between the actual shape pattern detected by the shap...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06F16/23
CPCG06N3/08G06N3/044B21B37/00B21B38/02B21C51/00B21B37/46G05B13/0285G06N5/04G06N3/043G06N3/042
Inventor 高田敬规服部哲田内佑树
Owner HITACHI LTD
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