Wavelet and improved Hilbert–Huang transform method are used to study the spectrum distribution and energy of turbine pressure pulsation

Abstract In order to reveal the relationship between steam turbine operating state and energy characteristics, the energy characteristics and frequency band distribution of steam turbine tail pipe pressure pulsation acquisition are studied. Wavelet analysis is used to remove the noise of steam turbine pressure pulsation signal, the noiseless signal is transformed by short‐time Fourier transform, and the energy histogram and energy proportion diagram of each frequency band are given. The traditional image continuation method is improved, the cubic Hermite interpolation method is used to replace the traditional cubic spline interpolation method, and then the traditional Hilbert–Huang transform (HHT) method is improved, which overcomes the endpoint effect problems, and reduces the overshoot and undershoot phenomenon in curve fitting to a certain extent. Using wavelet transform, empirical mode decomposition and improved HHT to study the distribution diagram, energy proportion diagram, and frequency band energy of pressure pulsation signal with frequency and time. The results show that with the increase of internal cavitation, the energy ratio in low‐frequency band decreases, the signal energy in high‐frequency band increases, the spectrum widens, and tends to the state of continuous spectrum.

Abstract licence: CC BY-NC

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.