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作 者:余建平[1] 刘武杰 李栋 YU Jian-ping;LIU Wu-jie;LI Dong(School of Petrochemical Engineering,Lanzhou University of Technology;Shandong Dongming Petrochemical Group Co.,Ltd.)
机构地区:[1]兰州理工大学石油化工学院 [2]山东东明石化集团有限公司
出 处:《化工机械》2023年第6期882-890,919,共10页Chemical Engineering & Machinery
基 金:甘肃省重点研发计划(批准号:20YF8GA013)资助的课题。
摘 要:针对被动降噪法不能有效消除调节阀节流过程中产生的低频噪声的问题,提出了将主动降噪技术应用于阀门降噪的方法,通过在阀门噪声源附近增设次级声源的方式,来控制调节阀节流过程中产生的低频噪声。针对阀门噪声的特点,提出了一种将压缩因子粒子群算法和带修正因子的反正切函数变步长法相结合的滤波新算法(AFXLMS-CFPSO算法)。数值仿真结果表明,AFXLMS-CFPSO算法比传统的FXLMS算法、VSS-LMS算法、A-LMS算法收敛速度更快,稳态误差更小、稳定性和抗噪性更好。为了进一步验证AFXLMS-CFPSO算法的可靠性,在通过有限元声学仿真确定了最佳的次级声源位置后,对调节阀噪声降噪效果进行了实验验证,结果表明增设主动降噪设备后调节阀噪声的加权A声压级普遍降低了15~20 dB,再次验证了AFXLMS-CFPSO算法和主动降噪的可行性。Aiming at the problem that passive de-noise method failed to effectively eliminate the low-frequency noise generated in the throttling process of regulating valve,a method of applying active de-noise technology to valve noise reduction was proposed where a secondary sound source near the valve noise source was adopted to control low-frequency noise produced in throttle process of the control valve.Through considering the characteristics of valve noise,a new filtering algorithm(AFXLMS-CFPSO algorithm)which having compression factor particle swarm optimization(PSO)algorithm combined with the variable step size of arctangent function with correction factor was proposed.The numerical simulation results show that,the AFXMFS-CFPSO algorithm outperforms traditional FXLMS algorithm,VSS-LMS algorithm and A-LMS algorithm in convergence speed,steady-state error,stability and anti-noise.In addition,for purpose of further verifying the reliability of AFXLMS-CFPSO algorithm,having the optimal secondary sound source position determined by the finite element acoustic simulation was implemented,including verifying the de-noise effect of the regulator through experiments.The results show that,after adding the active de-noise device,the weighted A sound pressure level of the regulator noise can be generally reduced by 15 dB to 20 dB.This verifies the feasibility of both AFXLMS-CFPSO algorithm and active noise reduction again.
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