Generator fault diagnosis and prediction method

A technology of fault diagnosis and prediction method, applied in the field of fault diagnosis, can solve immature problems, achieve the effect of reducing failure rate, improving economic reliability and increasing maintenance ability

Pending Publication Date: 2021-10-08
国网山东省电力公司嘉祥县供电公司 +2
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] At present, the technology for accurate fault diagnosis and prediction of generators is still immature, and research on related technologies is needed

Method used

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  • Generator fault diagnosis and prediction method

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Embodiment Construction

[0021] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0023] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

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Abstract

The invention provides a generator fault diagnosis and prediction method, which comprises the following steps of: acquiring historical data of normal operation of a generator, constructing a generator database, and determining temperature change related detection characteristics of key components of the generator by adopting a Pearson correlation coefficient; collecting state data information of real-time operation of the generator, and extracting real-time operation temperature change data of key components of the generator; constructing a CNN-LSTM-based temperature prediction model by using temperature change related detection features; training real-time operation temperature change data through a CNN-LSTM-based temperature prediction model, predicting the temperature of a key part of the generator, obtaining the difference between an obtained temperature prediction value and a temperature value collected in real time, obtaining a temperature residual error, comparing the obtained temperature residual error with a preset temperature residual error threshold value, prforming fault diagnosis of the generator, and carrying out temperature rise early warning by combining the change of the temperature residual error so as to realize fault prediction.

Description

technical field [0001] The disclosure belongs to the technical field of fault diagnosis, and in particular relates to a generator fault diagnosis and prediction method. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] In recent years, with the continuous expansion of the grid scale and the continuous increase of power system operating equipment, the complexity of system operation has also increased, and the safe and stable operation of the power system has become more and more important. Therefore, the state monitoring technology and fault diagnosis technology in the power system operation process have attracted more and more attention from the power grid. The fault diagnosis and prediction of the key components of the generator is directly related to the safety and reliability of power production. [0004] According to the knowledge of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/34
CPCG01R31/34
Inventor 丁升朱国栋姚忠凯穆帅史作雨庞秀丽田彦孜郭冻郏国伟刘远哲
Owner 国网山东省电力公司嘉祥县供电公司
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