Method for detecting output abnormity of mixed-flow hydroelectric generating set

Abstract

The invention relates to a method for detecting output abnormity of a mixed-flow hydroelectric generating set. The method includes the steps that firstly, output data of the hydroelectric generating set are collected when output of the hydroelectric generating set is normal and the upper level and the lower level of a hydroelectric station are different and guide vane openings of a water turbine are different, and the output data serve as standard samples; secondly, based on the Shepard curved surface interpolation method, a standard hydroelectric generating set output model P = f(Hupper, Hlower and D) is established according to the standard samples; thirdly, real-time online data, obtained by detecting the set state in real time, of the guide vane openings, the upper level and the lower level are substituted into the standard hydroelectric generating set output model, the standard set output value p(i) in the current working condition is calculated, the current set output deviation Od(i) is obtained, and an alarm is given when the absolute value of the output deviation Od(i) is larger than a preset output deviation threshold. Standard set output values under different working conditions are established through historical sample data, online state evaluation can be effectively, truly and reliably conducted, and early warning of set output abnormity is achieved. The method can be widely applied to the field of detection of the operating state of the hydroelectric generating set.

Description

technical field [0001] The invention relates to an online detection method for the operation state of a hydroelectric unit, in particular to a method for detecting abnormal output of a mixed-flow hydroelectric unit based on multi-source monitoring data. Background technique [0002] With the increase of the operating life, the equipment of the hydroelectric unit is gradually aging, and the performance and reliability begin to decline. The output of the unit under the same working conditions will decrease, and the power generation efficiency will begin to decrease. Therefore, it is necessary to carry out in-depth research on the operation guarantee theory of hydropower units to effectively judge the true operating status of the units so as to detect abnormalities in time. Timely detection of abnormal unit output can further improve the operation level of hydroelectric units and realize economical operation of hydropower stations. [0003] The main reasons for the decline in ...

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Problems solved by technology

[0004] At present, there are many related studies on the development and integration of hydropower unit condition monitoring systems and fault diagnosis methods. However, due to the lack of fault samples, the research results of fault diagnosis cannot meet the needs of the site.

With the continuous improvement of the status monitoring system of the power station, a large amount of status data during the normal operation of the unit has been obtained, but there are few fault samples of the hydroelectric unit, so the detection accuracy of the existing fault diagnosis method is not high

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