Implementation method for monitoring status of hydraulic turbine set based on HLSNE

Abstract

An implementation method for monitoring the status of a hydraulic turbine set based on HSLNE comprises the following steps of (1) signal detection and acquiring, namely collecting a set of vibration signals which can comprehensively reflect vibration anomalies of different noise sources by utilizing a vibration sensor on the hydraulic turbine set; (2) feature extraction, namely calculating an optional linear projection matrix A by using the HLSNE, and performing feature extraction on the vibration signals according to the linear projection matrix A; (3) status identification, namely identifying whether the status of the vibration signals subjected to feature extraction is normal or abnormal; (4) status analysis, namely adopting a nearest neighbor classifier to judge, classify and analyze a fault source of abnormal vibration signals; (5) result output, namely presenting a diagnosis decision according to results of the status analysis. The beneficial effect of the implementation method is mainly reflected in that a heavy-tailed linear stochastic neighbor embedding analysis method (HLSNE) is applied to the status monitoring of the hydraulic turbine set, so that multi-parameter setting and adjusting are feasible in a gradient optimization process by using a fast descent method in the actual application process, parameters do not need to be adjusted manually, and the efficiency and robustness of the hydraulic turbine set status monitoring process are effectively improved.

Description

technical field [0001] The invention relates to an HLSNE-based method and system for realizing state monitoring of a water turbine unit. Background technique [0002] With the implementation of the "Six Small Projects", the proportion of small hydropower in the power energy structure is gradually increasing. The mutual influence and interaction of the dynamic behaviors among them, the vibration problem of the unit is becoming more and more prominent, and the impact on the safe and stable operation of the power grid is also becoming more and more prominent. The operating health of hydroelectric units is not only related to the safety of hydropower plants, but also directly related to whether hydropower plants can provide reliable power to the grid safely and economically. Therefore, it is of great significance to monitor the operation status of the hydroelectric unit to ensure the safe, reliable and stable operation of the hydroelectric unit and maximize the power generation...

AI Technical Summary

Problems solved by technology

The original data processed in the above fields are often of high dimensionality, which brings problems such as high computational complexity, large storage capacity, and algorithm performance degradation to subsequent operations.

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