With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the uns...With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the unstable operating conditions brought by flexible operation.A vibration measuring method for the shrouded blades of a steam turbine based on eddy current sensors with high frequency response is proposed,meeting the requirements of non-contact heath monitoring.The eddy current sensors produce the signals which are related to the area changing of every blade’s shroud resulting from the rotation of stator.Then an improved blade tip timing(BTT)technique is proposed to detect the vibrations of shrouded blades by measuring the arrival time of each area changing signal.A structure of eddy current sensors is developed in steam turbines and an amplitude modulation/demodulation circuit is designed to improve the response bandwidth up to 250 kHz.Vibration tests for the last stage blades of a steam turbine were carried out and the results validate the efficiency of the improved BTT technique and the high frequency response of the eddy current sensors presented.展开更多
A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The pa...A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.展开更多
基金National Natural Science Foundation of China(No.51775377)National Key Research and Development Plan(No.2017YFF0204800)+2 种基金Natural Science Foundation of TianJin City(No.17JCQNJC01100)Young Elite Scientists Sponsorship Program by Cast of China(No.2016QNRC001)Open Project of Key Laboratory of Underwater Information and Control(No.6142218081811)
文摘With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the unstable operating conditions brought by flexible operation.A vibration measuring method for the shrouded blades of a steam turbine based on eddy current sensors with high frequency response is proposed,meeting the requirements of non-contact heath monitoring.The eddy current sensors produce the signals which are related to the area changing of every blade’s shroud resulting from the rotation of stator.Then an improved blade tip timing(BTT)technique is proposed to detect the vibrations of shrouded blades by measuring the arrival time of each area changing signal.A structure of eddy current sensors is developed in steam turbines and an amplitude modulation/demodulation circuit is designed to improve the response bandwidth up to 250 kHz.Vibration tests for the last stage blades of a steam turbine were carried out and the results validate the efficiency of the improved BTT technique and the high frequency response of the eddy current sensors presented.
文摘A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.
