This work first investigated the detection of slags,slag pool liquid level,and slag accumulation height in laboratory scale based on acoustic emission(AE)detection,and further tried the feasibility of this method in a...This work first investigated the detection of slags,slag pool liquid level,and slag accumulation height in laboratory scale based on acoustic emission(AE)detection,and further tried the feasibility of this method in an industrial scale coal gasifier.Results show that the energy and variance of acoustic signals can realize the accurate detection of large slag(criterion:E>1.5 E0,S>1.2 S0),and the average relative error is only 0.28%.The acoustic energy in the frequency range of 20–40 k Hz is defined as the characteristic energy,which can realize the accurate detection of slag accumulation height and slag pool liquid level,and the average relative error is only 3.94%.Furthermore,AE detection also realize accurate detection of large slag in an industrial scale gasifier and the acoustic signals at slag screen can be used to realize the early warning of the slag collapse(5 h earlier).展开更多
The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sour...The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sources of inner cracks in rail, AE sources with different types, depths and propagation distances are examined for crack in rail. The finite element method is utilized to model the rail with cracks and the results of experiment demonstrate the effectiveness of this model. Wavelet transform and Rayleigh-Lamb equations are utilized to extract the features of crack AE sources. The results illustrate that the intensity ratio among AE modes can identify the AE source types and the AE sources with different frequencies in rail. There are uniform AE mode features existing in the AE signals from AE sources in rail web, however AE signals from AE sources in rail head and rail base have the complex and unstable AE modes. Different AE source types have the different propagation features in rail. It is helpful to understand the rail cracks and detect the rail cracks based on the AE technique.展开更多
基金the support and encouragement of The National Science Fund for Distinguished Young(21525627)the Science Fund for Creative Research Groups of National Natural Science Foundation of China(61621002)。
文摘This work first investigated the detection of slags,slag pool liquid level,and slag accumulation height in laboratory scale based on acoustic emission(AE)detection,and further tried the feasibility of this method in an industrial scale coal gasifier.Results show that the energy and variance of acoustic signals can realize the accurate detection of large slag(criterion:E>1.5 E0,S>1.2 S0),and the average relative error is only 0.28%.The acoustic energy in the frequency range of 20–40 k Hz is defined as the characteristic energy,which can realize the accurate detection of slag accumulation height and slag pool liquid level,and the average relative error is only 3.94%.Furthermore,AE detection also realize accurate detection of large slag in an industrial scale gasifier and the acoustic signals at slag screen can be used to realize the early warning of the slag collapse(5 h earlier).
基金supported by the China Scholarship Council,the National Natural Science Foundation of China(61171197,61201307,61371045)the Innovation Funds of Harbin Institute of Technology(Grant IDGA18102011)the Promotive Research Fund for Excellent Young and Middle-Aged Scientisits of Shandong Province(BS2010DX001)
文摘The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sources of inner cracks in rail, AE sources with different types, depths and propagation distances are examined for crack in rail. The finite element method is utilized to model the rail with cracks and the results of experiment demonstrate the effectiveness of this model. Wavelet transform and Rayleigh-Lamb equations are utilized to extract the features of crack AE sources. The results illustrate that the intensity ratio among AE modes can identify the AE source types and the AE sources with different frequencies in rail. There are uniform AE mode features existing in the AE signals from AE sources in rail web, however AE signals from AE sources in rail head and rail base have the complex and unstable AE modes. Different AE source types have the different propagation features in rail. It is helpful to understand the rail cracks and detect the rail cracks based on the AE technique.
