Research And Application Of Fault Information Recognition Method For Ship Propulsion Shafting

As an important part of the ship’s power plant,the ship’s propulsion shafting functions as a "link" for the ship’s propulsion torque and thrust transmission.Its operating status directly affects the stability of the entire ship’s operation.However,the ship’s propulsion shafting system has a poor working environment,and the propulsion shafting failure caused by severe vibrations sometimes occurs.Therefore,the research on the fault diagnosis method of ship propulsion shafting is carried out,the monitoring and fault diagnosis of its working state are carried out,and the targeted measures are taken in time to avoid the occurrence of malignant accidents,which has certain engineering application value.However,the ship’s propulsion shafting fault vibration signal is easily overwhelmed by strong background noise and difficult to extract.For this problem,the following research is done:Firstly,based on the relevant basic theory and method research,the common fault types,fault mechanism and fault vibration characteristics of the ship propulsion shafting are introduced,and the corresponding relationship between different fault types and different vibration signal characteristic parameters is established for the subsequent ship propulsion.The study of shafting fault diagnosis methods provides a theoretical basis.Secondly,based on the principle of vibration signal analysis method,two feature extraction methods are introduced in detail: empirical mode decomposition and collective empirical mode decomposition.Based on this,innovative two-vessel propulsion shafting is proposed.Periodic fault information identification method(abbreviation: EAF,EEAF): First,the EMD/EEMD decomposition of the vibration test signal is obtained,and a series of natural mode components(IMF)are obtained.Then,according to the nature of the autocorrelation function,the existence cycle is selected.The IMF component of the component is used to exclude environmental interference;the fast Fourier transform is performed on the corresponding decomposition layer,and the spectral analysis identifies the extracted feature quantity.At the same time,the effectiveness of the proposed method is verified by using analog signals.The results show that the feature extraction accuracy of both methods is 97%.Finally,the applicability,convenience and accuracy of the four methods of EAF,EEAF,FFT and time domain statistical methods in feature extraction are compared using measured data.Finally,the design of the fault ship actual ship test plan is based on the actual ship test data.The EEAF method is used to analyze the tail bearing vibration and the hull tail structure vertical,longitudinal and lateral vibration test signals,extract the fault information feature quantity and summarize the feature quantity.The law of change guides the problem of abnormal wear and heat of the tail bearing during the test;at the same time,the possibility of predicting abnormal wear failure of the bearing by the frequency and amplitude of the number of blades or the harmonic vibration of the master cylinder is obtained,which is the failure of the ship propulsion shafting.The forecast provides strong technical support.