Pumped storage unit vibration trend prediction method

Abstract

The invention discloses a pumped storage unit vibration trend prediction method, which comprises the following steps of: firstly obtaining historical and real-time data of a unit online when it is innon-stationary vibration; transmitting data to a user terminal; performing time domain analyzing on vibration signals by utilizing experiential wavelet decomposition; extracting comprehensive characteristics of energy entropy and singular value; performing correlation analysis with unit operation working condition after performing discretization processing on signal characteristic data set according to a certain rule; performing frequent item mining by utilizing Apriori algorithm; analyzing time-space correlation of data characteristics and unit faults; dividing a unit safe operation area through correlation analyzing results; finally constructing a time series model, and predicting development trend in the future limited time through time series trend prediction method, so that the unit operate state trend is predicted and evaluated, and technical support is provided for implementing unit state overhaul. According to the pumped storage unit vibration trend prediction method, the trendcan be accurately predicted, evaluation index is comprehensive and it is convenient to evaluate.

Description

technical field [0001] The invention relates to a vibration trend prediction method of a pumped storage unit. Background technique [0002] The pump turbine unit of the pumped storage power station has complex working conditions, frequent start and stop, many vibration parts and wide distribution, and many influencing factors (including hydraulic factors, mechanical factors and electromagnetic factors). The trend prediction method widely used at present is to obtain the historical data trend chart of the vibration state of the unit through the online monitoring system, subjectively analyze the possible operating state of the unit in the future, or use the least square method to achieve regression fitting on the characteristic parameters, but the vibration signal is generally non-linear. Linear and non-stationary, so traditional mathematical statistics methods are difficult to achieve accurate trend prediction of its state. Due to the improper selection of the weight of the ...

AI Technical Summary

Problems solved by technology

The trend prediction method widely used at present is to obtain the historical data trend chart of the vibration state of the unit through the online monitoring system, subjectively analyze the possible operating state of the unit in the future, or use the least square method to achieve regression fitting on the characteristic parameters, but the vibration signal is generally non-linear. Linear and non-stationary, so traditional mathematical statistics methods are difficult to achieve accurate trend prediction of its state

Due to the improper selection of the weight of the AHP, it often cannot meet the requirements of the consistency of the judgment matrix, and cannot obtain the evaluation index reflecting the overall state of the pumped storage unit

Therefore, the existing vibration trend prediction methods for pumped storage units have the problems of inaccurate trend prediction and incomplete evaluation indicators.

Images