A Fault Diagnosis Method of Steam Turbine Rotor Based on LSTM

Abstract

The invention discloses a steam turbine rotor fault diagnosis method based on LSTM, which belongs to the technical field of mechanical fault diagnosis. Firstly, multi-measuring point acquisition sensors are deployed to collect vibration signals of various typical steam turbine rotor faults as training sets and verification sets. Secondly, the vibration signal of the steam turbine rotor is extracted from the DCS system of the power plant as a test set. Then, the training set, test set and verification set are divided and stacked to realize the fusion and data enhancement of multi-point signal data. Then build a neural network based on LSTM, use the training set and verification set to complete the training of the network, and finally combine the actual diagnosis task to maintain the diagnosis model, and finally realize the turbine rotor fault diagnosis on the test set.

Description

Technical field[0001]This is a mechanical fault diagnosis technology, and it is specifically involved in an LSTM-based steam turbine rotor fault diagnosis method.Background technique[0002]Turbo generator is a key device for electricity production. It has the complicated structure, poor working conditions (high temperature, high pressure, high speed), continuous operation requirements, and failure. In the unit operation, the rotor acts as an important part, and once the failure cannot be investigated in time, it will cause non-planning downtime due to the amount of vibration, which will cause damage to the unit damage and personnel casualties. Therefore, the fault diagnosis method and experimental study of turbine generator set rotors, which is of great significance for ensuring safe operation of steam turbine generator sets, reducing significant economic losses and avoiding disastrous accidents.[0003]Steam turbine rotor faults include composite faults such as rotor cracks, imbalance...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to detect and identify steam turbine rotor faults and ensure the safe operation of steam turbine generator sets. A LSTM-based steam turbine rotor fault diagnosis method is provided to solve the need for steam turbine rotor diagnosis in traditional methods with the help of experience and extremely high signals. Handling skills lead to low diagnostic efficiency, poor diagnostic accuracy, and are not conducive to industrial promotion and other issues

Images