Method and device for diagnosing equipment status

A technology of equipment status and diagnostic methods, applied in the direction of measuring devices, machine/structural component testing, instruments, etc., can solve problems such as difficulty in ensuring the accuracy of status judgment results, and reduce the possibility of misjudgment and judgment credibility High, accurate results

Active Publication Date: 2019-08-30
ZHEJIANG SUPCON TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

With the diversification of monitored states and parameters and the complexity of the production process of the industry or other non-uniform objective conditions, the traditional fixed value monitoring technology is increasingly unable to adapt to this change, and it is difficult to guarantee the accuracy of the state judgment results. Accuracy
[0003] In order to solve this problem, under the existing technical conditions, experienced personnel are used to cooperate with the monitoring system to realize manual intervention and pre-judgment to make effective judgments. Due to differences in personal experience and various thinking inertias, this machine Combined manual methods have certain limitations

Method used

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  • Method and device for diagnosing equipment status
  • Method and device for diagnosing equipment status
  • Method and device for diagnosing equipment status

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Embodiment 1

[0048] see figure 1 It is a schematic flowchart of a method for diagnosing equipment status provided by Embodiment 1 of the present invention, the method includes the following steps:

[0049] S11. Process the acquired historical samples to obtain typical sample fault classifications and their characteristic values, wherein the historical samples are equipment historical fault sample data;

[0050]Specifically, after obtaining the historical sample data in the historical sample database, statistical methods are used to initially classify and organize the sample data, and the K-nearest neighbor algorithm is usually used for induction to obtain typical sample fault classifications. The number of classifications is determined by The combination of manual judgment and historical data collation will gradually increase. For example, if the historical fault sample data of a steam turbine is obtained, the fault classification of typical samples can be divided into sudden unbalance of...

Embodiment 2

[0061] Referring to embodiment one of the present invention and figure 1 The specific process of steps S11 to S16 described in , and see figure 2 , the step S12 performs a similarity judgment on the tested sample according to the typical sample fault classification and its characteristic value to obtain a preliminary fault classification of the tested sample, which specifically includes the following steps:

[0062] S121. Determine a judgment condition for each fault classification according to the typical sample fault classification and its characteristic value;

[0063] S122. According to the judgment condition, perform parameter correlation analysis on the tested sample, and judge to obtain a preliminary fault classification of the tested sample.

[0064] Specifically, after the fault classification of typical samples is obtained, clear judgment conditions are summarized for different classification situations, and then parameter correlation analysis and classification ar...

Embodiment 3

[0079] Corresponding to the equipment diagnosis method disclosed in the first and second embodiments of the present invention, the third embodiment of the present invention also provides an equipment diagnosis device, see Figure 4 , the device consists of:

[0080] The processing module 1 is used to process the acquired historical samples to obtain typical sample fault classifications and their characteristic values, wherein the historical samples are equipment historical fault sample data;

[0081] The first judging module 2 is used to judge the similarity of the tested sample according to the typical sample fault classification and its characteristic value to obtain a preliminary fault classification of the tested sample;

[0082] The classification module 3 is used to obtain the sample feature value corresponding to the preliminary classification of the fault, perform weighted calculation on the sample feature value to obtain a similarity parameter, and determine the fault...

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Abstract

The invention discloses a method and device for diagnosing equipment status. The method includes: processing the acquired historical samples to obtain typical sample fault classifications and their characteristic values; performing similarity judgment on the tested samples to obtain preliminary fault classifications; Obtaining the sample feature value corresponding to the preliminary classification of the fault, performing weighted calculation to obtain a similarity parameter, and determining the fault classification of the tested sample; when the fault classification is a single type, determining the fault classification as the The fault diagnosis classification of the tested sample; if it is not a single type, create an accurate model, input the preliminary fault classification into the accurate model for judgment, and obtain the fault diagnosis classification of the tested sample. The invention achieves the purpose of improving the accuracy and precision of equipment state diagnosis.

Description

technical field [0001] The invention relates to the technical field of equipment production monitoring, in particular to a method and device for intelligent diagnosis of equipment status based on machine learning. Background technique [0002] In the field of industrial production, the traditional equipment status monitoring scheme is judged by fixed threshold monitoring or simple multi-threshold monitoring, but this scheme can generally solve a class of status detection problems. With the diversification of monitored states and parameters and the complexity of the production process of the industry or other non-uniform objective conditions, the traditional fixed value monitoring technology is increasingly unable to adapt to this change, and it is difficult to guarantee the accuracy of the state judgment results. Accuracy. [0003] In order to solve this problem, under the existing technical conditions, experienced personnel are used to cooperate with the monitoring system ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M99/00G06K9/62
CPCG01M99/00G06F18/22G06F18/241
Inventor 姚杰孔伟阳阮志坚马楠桦
Owner ZHEJIANG SUPCON TECH
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