Diesel powered vehicles, in compliance with the more strict exhaust emission standards such as Euro V, is likely to require a diesel particulate filter （DPF）. A DPF used on a vehicle will affect the acoustic emissio...Diesel powered vehicles, in compliance with the more strict exhaust emission standards such as Euro V, is likely to require a diesel particulate filter （DPF）. A DPF used on a vehicle will affect the acoustic emission of the diesel engine, so it is important to investigate the sound propagation rule in DPF and further to propose the optimum DPF design. However, due to the geometrical complexity of the DPF, the traditional analysis method, such as analytical method, can not assess the acoustic performance of DPF accurately in medium and high frequency band. In this paper, a combined approach of finite element analysis and viscosity correction is proposed to predict acoustic performance of DPF. A simplified model of the full DPF is established and is used to analyze the sound propagation characteristic of the DPF. The distribution of the sound pressure and velocity, the transmission matrix of the DPF are obtained using the finite element method. In addition, the method of the viscosity correction is used in the transmission matrix of the DPF to evaluate the acoustic performance of DPF. Based on the FEM computation and the viscosity correction, the transmission losses under the rated load and idle condition of a diesel engine are calculated. The calculation results show that DPF can effectively attenuate exhaust noise, and sound attenuation increase with the rise of the frequency. Sound attenuation is better under rated condition than idle condition of diesel engine, particularly in frequency above 1 000 Hz.展开更多
Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust l...Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications.展开更多
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2009AA045103 )Tianjin Provincial Natural Science Foundation of China (Grant No. 05YFJMJC10700)
文摘Diesel powered vehicles, in compliance with the more strict exhaust emission standards such as Euro V, is likely to require a diesel particulate filter （DPF）. A DPF used on a vehicle will affect the acoustic emission of the diesel engine, so it is important to investigate the sound propagation rule in DPF and further to propose the optimum DPF design. However, due to the geometrical complexity of the DPF, the traditional analysis method, such as analytical method, can not assess the acoustic performance of DPF accurately in medium and high frequency band. In this paper, a combined approach of finite element analysis and viscosity correction is proposed to predict acoustic performance of DPF. A simplified model of the full DPF is established and is used to analyze the sound propagation characteristic of the DPF. The distribution of the sound pressure and velocity, the transmission matrix of the DPF are obtained using the finite element method. In addition, the method of the viscosity correction is used in the transmission matrix of the DPF to evaluate the acoustic performance of DPF. Based on the FEM computation and the viscosity correction, the transmission losses under the rated load and idle condition of a diesel engine are calculated. The calculation results show that DPF can effectively attenuate exhaust noise, and sound attenuation increase with the rise of the frequency. Sound attenuation is better under rated condition than idle condition of diesel engine, particularly in frequency above 1 000 Hz.
基金the financial support provided by the National Key Research and Development Program for Young Scientists(No.2021YFC2900400)Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(CPSF)(No.GZB20230914)+2 种基金National Natural Science Foundation of China(No.52304123)China Postdoctoral Science Foundation(No.2023M730412)Chongqing Outstanding Youth Science Foundation Program(No.CSTB2023NSCQ-JQX0027).
文摘Monitoring sensors in complex engineering environments often record abnormal data,leading to significant positioning errors.To reduce the influence of abnormal arrival times,we introduce an innovative,outlier-robust localization method that integrates kernel density estimation(KDE)with damping linear correction to enhance the precision of microseismic/acoustic emission(MS/AE)source positioning.Our approach systematically addresses abnormal arrival times through a three-step process:initial location by 4-arrival combinations,elimination of outliers based on three-dimensional KDE,and refinement using a linear correction with an adaptive damping factor.We validate our method through lead-breaking experiments,demonstrating over a 23%improvement in positioning accuracy with a maximum error of 9.12 mm(relative error of 15.80%)—outperforming 4 existing methods.Simulations under various system errors,outlier scales,and ratios substantiate our method’s superior performance.Field blasting experiments also confirm the practical applicability,with an average positioning error of 11.71 m(relative error of 7.59%),compared to 23.56,66.09,16.95,and 28.52 m for other methods.This research is significant as it enhances the robustness of MS/AE source localization when confronted with data anomalies.It also provides a practical solution for real-world engineering and safety monitoring applications.
