A method for extracting and predicting equipment performance degradation trend

Abstract

The invention relates to a method for extracting and predicting the degradation trend of equipment performance. Real-time online data to obtain the current performance degradation time series of hydropower units; (2) use ITD to decompose the performance degradation time series of hydropower units into the sum of several stationary PRC time series and a trend component; (3) for all the obtained components Identify the complexity characteristics of the time series, and reconstruct the components to obtain the performance degradation trend according to the preset complexity characteristic threshold; (4) evaluate, judge and predict the performance of the hydroelectric unit equipment according to the obtained performance degradation trend, and use Detect equipment abnormalities in time. The invention can be widely used in the field of predicting the performance degradation trend of hydroelectric unit equipment.

Description

technical field [0001] The invention relates to a method for extracting and predicting the degradation trend of equipment performance, in particular to a method for extracting and predicting the degradation trend of equipment performance based on inverse distance weighting and ITD (Intrinsic Time Scale Decomposition). Background technique [0002] With the increase of accumulative running time, the performance of each equipment of the hydroelectric unit degrades continuously. How to effectively determine the true state of the unit and better predict the degradation trend of the unit, so as to detect the abnormality of the unit in time and arrange maintenance reasonably, is an important issue for the transformation of hydropower units from planned maintenance to condition-based maintenance. [0003] At present, the fault diagnosis technology of hydroelectric units cannot meet the needs of the field, the main reason is the complexity of hydroelectric unit faults and the lack o...

AI Technical Summary

Problems solved by technology

[0004] Vibration is the main failure factor that affects the normal operation of hydroelectric units and endangers the life of the unit. Excessive vibration will cause dynamic and static friction of the unit, accelerate the wear of parts, cause fatigue damage to parts, reduce the economy of the unit, and even cause damage to the unit in severe cases. serious accident

However, at present, most methods such as neural networks are used to directly predict the vibration time series of hydroelectric units. This method completely ignores the influence of unit operating conditions on vibration, and there are large errors and impracticalities.

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