Research On Diagnosis And Early Warning System Of Important Rotating Equipment Status And Performance In Nuclear Power Plant

The prime objective of nuclear power plant operations is to operate safely.Rotating equipment,including main pumps and steam turbines,is a vital part of the safe operation of nuclear power plants.The majority of rotating equipment failures are gradually generated.Therefore,the use of diagnostic early warning system for real-time monitoring of the status and performance of rotating equipment to diagnose the future of possible failures early warning for the safe and stable operation of nuclear power plant has an important role and guidance.Turbine is the most important rotating equipment of nuclear power plant.In this paper,the nuclear power plant steam turbine as the research object,focusing on equipment failure warning and diagnosis research.According to the historical operation data of steam turbines,predict the future trend of equipment status and performance,and combine forecast information with fault diagnosis technology to establish the status and performance diagnosis and early warning system of important rotating equipment of nuclear power station.Through the equipment status of real-time monitoring and diagnosis,equipment failure early warning to improve the operation of rotating equipment safety.First of all,this paper studies the working mechanism of steam turbine and establishes the mechanical model of steam turbine bearing-rotor system.And the failure mechanism of the most common mechanical faults in steam turbines is studied.Combined with the design parameters of steam turbines in a nuclear power plant in China,a bearing-rotor system model with corresponding mechanical faults is established,and the correctness of the established model is verified.By adjusting the parameters of the fault model to get the turbine operating data under various operating conditions.Secondly,research on the warning state and performance of rotating machinery in nuclear power station.It is divided into two parts altogether: Firstly,the extraction of the characteristic parameters of vibration data obtained from the three aspects of time domain,frequency domaiand time-frequency domain is carried out to obtain the characteristic parameters including amplitude,vibration peak and root mean square value,Axis trajectory,amplitude-frequency characteristics,phase-frequency characteristics,wavelet packet decomposition energy,including a variety of characteristic parameters.Secondly,through the thorough research on fault collection,symptom collection,confidence rule base,rule variable and diagnosis rule base,the state pre-warning diagnosis confidence rule is completed.Use the confidence rule base to diagnose and evaluate the status and performance of rotating machinery.Finally,the early warning system of rotating machinery is studied,and the prediction of the development trend of the characteristic parameters of steam turbines with unbalanced failure and misalignment in time domain,frequency domain and time-frequency domain are respectively predicted by using gray prediction.The results of the prediction and equipment failure are analyzed.The results show that the state-of-the-art diagnosis and warning system for the status of rotating equipment and performance of the nuclear power plant researched in this paper can monitor and diagnose the status of the equipment in real time and predict more accurately the developing trend of equipment operating status.And to achieve the purpose of early warning of equipment failure.