Method and system for predicting degradation trend interval of hydroelectric generating set

A technology for hydroelectric units and deterioration trends, which is applied in general control systems, control/regulation systems, electrical program control, etc., and can solve problems such as inability to analyze risks

Active Publication Date: 2019-07-12
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the present invention provides a method and system for predicting the degradation trend interval of hydropower units, which can obtain the probability distribution of the degradation trend in the future, thereby obtaining m...

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  • Method and system for predicting degradation trend interval of hydroelectric generating set
  • Method and system for predicting degradation trend interval of hydroelectric generating set
  • Method and system for predicting degradation trend interval of hydroelectric generating set

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Embodiment

[0235] Step 1. Analyze the time series data of the status monitoring data of the hydropower unit, analyze the working water head-vibration relationship diagram, power-vibration relationship diagram, power-working water head-vibration relationship diagram, such as Figure 3-5 As shown, determine the standard health status of the unit.

[0236] Step 2. Establish a hydroelectric unit health model by using the training data of the unit state under the no-fault health state (a total of 853 pieces of data from July 24, 2008 to January 20, 2009). With the power P and water head H of the hydroelectric unit operating state as the input, and the vibration V of the hydroelectric unit as the output, the health state model of the hydroelectric unit is established through MATLAB surface fitting V(t)=f[P(t),H(t)] , the fitting result is as Image 6 As shown, the fitting accuracy error is controlled within 4.5%.

[0237] Step 3. Using the unit state training data in the fault state (May 12,...

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Abstract

The invention discloses a method and system for predicting a degradation trend interval of a hydroelectric generating set. The method comprises the following steps: based on the historical state monitoring data of the hydroelectric generating set, establishing a set health model by using power and waterhead and set vibration data in fault-free healthy state in a previous period, obtaining a set degradation trend model by using the power and waterhead data in a faulty state in a later period, and finally establishing a fuzzy interval prediction model of the degradation trend of the hydroelectric generating set. Further, structural division is performed on the model, and model parameter optimization is performed by using the coverage of a fuzzy model interval prediction result and a comprehensive index of an interval width. By adoption of the method and system disclosed by the invention, the identification precision of the fuzzy interval prediction model of the degradation trend of the hydroelectric generating set is improved, more accurate identification parameters can be obtained, and the prediction process is simplified.

Description

technical field [0001] The invention belongs to the technical field of hydroelectric unit performance monitoring, and more specifically, relates to a method and system for predicting a degradation trend interval of a hydroelectric unit. Background technique [0002] With the increase of the cumulative running time, the equipment of the hydroelectric unit begins to fatigue and degrades continuously. Due to the lack of fault samples, the current hydroelectric unit mainly adopts a static alarm threshold. The early warning capability of the potential failure of the unit is far from enough to fully reflect the operating status of the unit and cannot meet the needs of the site. How to effectively judge the real operating state of the unit, better predict the deterioration trend of the unit, so as to timely carry out abnormal state warnings, improve the level of operation and maintenance of hydropower units, and reduce the shutdown loss caused by failures. important research direc...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 李超顺邹雯刘颉许颜贺
Owner HUAZHONG UNIV OF SCI & TECH
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