Power station equipment fault monitoring model generation method, system and device

A technology for equipment failure and model generation, which is applied in the direction of measuring devices, measuring electricity, and measuring electrical variables, etc., can solve the problems of inability to obtain monitoring effects and difficulty in learning statistical characteristics, so as to solve fault monitoring problems, reduce modeling complexity, The effect of reducing training time

Pending Publication Date: 2021-10-29
DATANG ENVIRONMENT IND GRP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At the same time, since the power station is a typical multi-mode system, the parameters under different working conditions have different statistical characteristics, and it is difficult for a single PCA monitoring model to learn such statistical characteristics, so it cannot obtain better monitoring results

Method used

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  • Power station equipment fault monitoring model generation method, system and device
  • Power station equipment fault monitoring model generation method, system and device
  • Power station equipment fault monitoring model generation method, system and device

Examples

Experimental program
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Embodiment 1

[0078] The embodiment of the present invention provides a device for generating a fault monitoring model of power station equipment, such as Figure 4 As shown, it includes: a memory 40, a processor 42, and a computer program stored on the memory 40 and executable on the process 42, the computer program being executed by the processor 42 and implemented as in the method embodiment the steps described.

Embodiment 2

[0080] An embodiment of the present invention provides a computer-readable storage medium, where a program for implementing information transmission is stored thereon, and when the program is executed by the processor 42, the steps described in the method embodiments are implemented.

[0081] The computer-readable storage medium described in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk or optical disk, and the like.

[0082] It should be noted that the embodiment of the storage medium in this specification and the embodiment of the blockchain-based service provision method in this specification are based on the same inventive concept, so the specific implementation of this embodiment can refer to the aforementioned corresponding power station equipment failure The implementation of the monitoring model generation method will not be repeated here.

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Abstract

The invention discloses a power station equipment fault monitoring model generation method, system and device, and the method comprises the steps: presetting the maximum capacity of an initial training sample set, and carrying out the standardization processing of a large amount of historical normal data stored in a database based on the maximum capacity, and obtaining a training sample set containing training data; determining an optimal cluster number by calculating and comparing Calinski-Harabasz score values under training data under different clusters, taking the determined optimal cluster number as a cluster number of a K-means algorithm, and performing algorithm training on the training data to determine a clustering center set of the data; and taking the determined clustering center set as an initial clustering center of an FCM algorithm, performing algorithm training on training data to determine a cluster membership degree of the data, establishing an FCM model, classifying the training data according to the maximum membership degree, establishing corresponding PCA models according to different categories, and completing a training process.

Description

technical field [0001] The invention relates to the technical field of power station monitoring, in particular to a method, system and device for generating a fault monitoring model of power station equipment. Background technique [0002] In the prior art, fault detection (Fault Detection) is to use when a fault occurs in the system, to find and confirm it in time, and to give a corresponding display or alarm. Early detection of failures can provide important warnings of impending problems, allowing appropriate action to be taken to avoid serious incidents. PCA (Principle Component Analysis) fault monitoring method belongs to the fault monitoring method in the field of statistical learning. It has the characteristics of high efficiency, convenient calculation and does not depend on fault variables, and has been widely used in recent years. [0003] Fault monitoring of power station equipment is an important link in the safe and economic operation of power stations. Contin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G01R31/00G06Q50/06G06F30/27
CPCG01R31/00G06F30/27G06Q50/06G06F18/23213G06F18/214
Inventor 孟磊王彦文袁照威谷小兵司风琪白玉勇李文龙乔宗良曹书涛王力光杨大洲李广林
Owner DATANG ENVIRONMENT IND GRP
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