Abstract

The failure analysis and diagnosis of hydraulic-turbine generator unit (HGU) is important to protect the safety and stability of the electric system. But failure analysis and diagnosis for HGU is lacking of fault data, and most of the failure analysis and diagnosis methods are proposed without considering the characteristic of HGU. In this paper, a vibration dynamic modeling method for HGU is proposed by using the finite element method, and further the vibration data in different states are getting through numerical simulation. Then, the failure feature is extracted based on the nonlinear output frequency response functions (NOFRFs). Finally, a diagnosis system with Support Vector Machine (SVM) is proposed and employed for diagnosis of the HGU. The experimental results indicate that the feature which extracted from NOFRFs has a strong effect, and demonstrates that the proposed method is feasible and helpful for fault diagnosis in HGU.

Highlights

  • The hydraulic-turbine generator unit (HGU) is part of the key equipment in hydropower station

  • The results indicate that the features which extracted from nonlinear output frequency response functions (NOFRFs) are much more useful than other diagnosis methods

  • The traditional failure analysis and diagnosis methods ignore the characteristic of HGU which makes the failure analysis and diagnosis less effective

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Summary

Introduction

The hydraulic-turbine generator unit (HGU) is part of the key equipment in hydropower station. Recent research has proposed many modeling methods for fault diagnosis [8,9,10,11,12]. A NOVEL FAILURE ANALYSIS AND DIAGNOSIS METHOD FOR HYDRAULIC-TURBINE GENERATOR UNIT. This method simplifies the nonlinear frequency domain model, and makes people have an intuitive feeling. In order to overcome the lacking of failure data, a finite element model of a hydroelectric generator unit is proposed, and further the vibration data in different states are acquired based on the model. In. Section 4, the proposed method is employed in a HGU which is simplified from a real hydroelectric generator unit, and the proposed is compare to others fault diagnosis methods.

Dynamic model of HGU
Rubbing state
Misalignment state
Numerical simulation
Feature extraction based on NOFRFs
SVM diagnosis system
Verification experiment of the proposed method
Experiment of anti-noise ability of the proposed method
Comparison experiment
Conclusion
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