Research On Acoustic Simulation And Wavelet Packet Denoising For Predicting Internal Leakage Condition In Steam Traps

With the active promotion of China’s "carbon peaking and carbon neutrality" goals and green high-quality development policies,energy-saving and efficiency improvements in the industrial field have become one of the necessary means to achieve sustainable development.As the dividing point between steam systems and condensate systems,the leakage detection of steam traps is of great significance for energy conservation.In order to meet the demand for predictive maintenance of steam trap valves from a domestic manufacturer,an in-depth investigation was conducted on acoustic numerical simulation,noise reduction algorithms for leakage signals,and acoustic leak detection.The following indepth research was carried out.(1)This study focuses on the PN40DN15 inverted bucket steam trap and employs the theory of fluid-structure-acoustic coupling to conduct numerical simulations of the leak flow field and acoustic characteristics within the valve.By establishing an accurate and reliable model for calculating internal leakage,the study explores the flow field distribution characteristics during the internal leakage process,revealing that the velocity during the steam leakage process can reach 525.691m/s,leading to strong dipole and quadrupole noise.Furthermore,the study investigates the acoustic characteristics of the steam leakage jet process,demonstrating that the energy of the leakage noise is mainly distributed in the low-frequency band and is positively correlated with the leakage volume.The study also finds that the leakage aperture has a significant impact on both the leakage volume and acoustic intensity,while the pressure before the valve has a relatively small impact.As such,the leakage aperture and pressure before the valve are the key parameters affecting the leakage volume and acoustic intensity.(2)Based on the principle of sound emission detection for internal valve leakage,this study selects appropriate sensors,signal controllers,and signal processors to design low-noise preamplifiers and low-ripple power supply modules,enabling the acquisition of weak sound signals.(3)By selecting the optimal wavelet basis function and decomposition level based on the definitions of energy,kurtosis,and entropy,this study utilizes the signal-to-noise ratio and root-mean-square error as evaluation indicators to optimize the parameters of the improved threshold function and improve the wavelet packet denoising algorithm.Through the study of simulated sound emission signals,the research demonstrates that the algorithm effectively suppresses high-frequency noise while highlighting useful information,facilitating subsequent noise reduction of measured signals.(4)Based on Lighthill’s acoustic theory and Ma Dayou’s law of sound power,this study establishes a relationship between the sound emission signal of internal valve leakage and the key parameters affecting the leakage volume,enabling the conduct of sound emission tests for internal valve leakage.By performing waveform and spectral analysis on the measured sound emission signals under different operating conditions,the results show that as the leakage aperture increases,the signal energy gradually increases and the energy is mainly distributed in the low-frequency band,with the frequency with the largest amplitude being 14 k Hz.Subsequently,the study uses the improved wavelet packet denoising algorithm to process the sound emission signals,extracts the characteristic parameter AErms,and fits the internal leakage model of the steam trap,achieving accurate prediction of the internal leakage status through sound emission signals.This research demonstrates that the acoustic characteristics of internal valve leakage can serve as a basis for determining the leakage status.By improving the wavelet packet denoising algorithm for sound emission signals and establishing a reliable model for predicting internal valve leakage status based on Lighthill’s acoustic theory and Ma Dayou’s law of sound power,the study achieves accurate prediction of the internal leakage status of the valve.