Study On Feature Extraction Of Vibration Signal Of Continuous Milling Machine Based On Energy Masking Signal Method

In practical engineering applications,the obtained signal is generally non-stationary signal,and it's very important to analysis and process non-stationary signal.In dealing with these data sequences,the traditional time-frequency analysis methods used in the past are fundamentally Fourier transforms,so there are some limitations in dealing with non-stationary signals.Empirical Mode Decomposition(EMD)is a new,adaptive time-frequency analysis method proposed by NASA's Chinese scientist Norden E.Huang et in 1998 when analyzing nonstationary,non-linear signals.The EMD is a modern signal processing methods which has made a great improvement of the traditional ones,and it doesn't require any prior knowledge,only according to the characteristics of the signal itself to decompose any complex nonstationary signal into a number of intrinsic modal components(IMFs)and a remainder,each IMF obtains an instantaneous frequency of the original signal.Compared with the traditional signal processing methods,the EMD method has been widely used in many fields such as graphics processing,signal processing,vibration testing and mechanical fault diagnosis,and has achieved good results.In this paper,an energy-based masking signal method is proposed based on the study of EMD algorithm,and the mode mixing phenomenon has also been improved.According to the energy conservation law,when there is no false modal component in the IMF,the sum of the energies of all the components is equal to the energy of the original signal.However,when there is a false modal component,is not conserved,the original signal's energy is lower than the sum of the energies of the components,and the energy of the sum of any two components is also less than the sum of their energies,thus determining where the energy goes.As a result,the influence of energy leakage on the frequency of the masking signal is solved,which makes up the deficiency of the masking signal method and improved the applies of the EMD algorithm to nonstationary signal processing in the actual engineering.Continuous shearer is a large underground excavation equipment,its main working frequency is low frequency.In this paper,the study object is the vibration signal collected from the mining machine cutting arm at the working condition.By calculating the modal kinetic energy in different point of the cutting arm to optimize the position of the sensor.The vibration signal of the cutting arm in the working process is obtained.The original signal contains much noise,and the noise is removed by the EMD method.And then through the improved masking signal method to analyze the signal after noise reduction.In the result,the mode mixing phenomenon of the EMD has been successfully eliminated.Indicating that the energy-masking signal method can also solve the mode mixing phenomenon in practical engineering applications.