Diagnosis method and system for inter-turn short circuit of double water internally cooled generator rotor based on resistance method

By employing a rotor-turn short-circuit diagnosis method based on resistance method and artificial intelligence algorithm, the problem of online detection in existing technologies is solved, enabling the diagnosis of generator faults. This method achieves accuracy and stability in the diagnosis system for dual water-cooled turbines, and demonstrates the effectiveness of the generator diagnosis system. The effectiveness of the diagnosis system for dual water-cooled turbines is demonstrated, and safety risks are reduced.

CN115792609BActive Publication Date: 2026-03-24HUAQIAO UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-12-06
Publication Date
2026-03-24

AI Technical Summary

Technical Problem

Traditional online diagnostic systems for rotor turn-to-turn short circuits in dual water-cooled generators cannot accurately diagnose faults, and their installation and deployment pose safety hazards, thus failing to achieve efficient fault diagnosis.

Method used

A resistance-based method combined with artificial intelligence algorithms is adopted to predict rotor resistance by training a model. The deviation value is calculated by using the fitted value and real-time value of rotor resistance, thereby realizing online diagnosis of rotor inter-turn short circuits. This includes sample collection, screening, model training and real-time data processing.

Benefits of technology

It enables online diagnosis of rotor turn-to-turn short circuits with low deployment threshold, improves the accuracy of diagnosis and the stability of the system, and reduces safety risks.

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Abstract

The application discloses a method and system for diagnosing a turn-to-turn short circuit of a double-water internally-cooled generator rotor based on an intelligent resistance method.The method comprises the following steps: collecting rotor voltage, rotor current, rotor total water inlet flow rate, rotor total water inlet temperature and rotor total water outlet temperature sample parameters, and calculating a rotor resistance value; taking the rotor total water inlet flow rate, the rotor total water inlet temperature and the rotor total water outlet temperature as input quantities, taking the rotor resistance as an output quantity, submitting the sample to a machine learning model training, and obtaining a trained model; obtaining real-time values of the rotor voltage, the rotor current, the rotor total water inlet flow rate, the rotor total water inlet temperature and the rotor total water outlet temperature, and calculating a real-time value of the rotor resistance value; taking the real-time values of the rotor total water inlet flow rate, the rotor total water inlet temperature and the rotor total water outlet temperature as input quantities, inputting the trained model, and obtaining a rotor resistance fitting value through prediction; calculating a deviation value between the real-time value and the fitting value of the rotor resistance, determining whether the rotor has a turn-to-turn short circuit according to the deviation value, and marking a turn-to-turn short circuit severity.The method has low implementation difficulty, and the diagnosis result is accurate and reliable.
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Citation Information

Patent Citations

  • Early online detection method for turn-to-turn short circuit of generator rotor winding

    CN109188185A

  • Phase modifier rotor winding turn-to-turn short circuit fault diagnosis method and device

    CN112327208A