Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (07): 88-92.doi: 10.13475/j.fzxb.20190502205

• Textile Engineering • Previous Articles     Next Articles

Active noise control for tufted carpet equipment based on filtered least mean square algorithm

CHEN Shaoyong, XU Yang(), SHENG Xiaowei, ZHANG Ziyu   

  1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
  • Received:2019-05-13 Revised:2020-01-19 Online:2020-07-15 Published:2020-07-23
  • Contact: XU Yang E-mail:xuyang@dhu.edu.cn

Abstract:

In order to reduce tufted carpet equipment's low frequency noise, this paper introduces the filtered least mean square algorithm (FXLMS) for textile machinery noise control. The active noise control system model was established to complete the sensor-actuator arrangement taking the British COBBLE 1/8-pitch tufted carpet loom as the research object. The dual-microphone offline channel identification method was used to estimate the primary and secondary channel transfer functions. For the secondary acoustic feedback phenomenon caused by the elected feed-forward control system, the parametric array speaker was used to reduce the influence on stability of the noise reduction experiment as secondary acoustic source. The noise reduction simulation and experiment of the tufted carpet loom verified the feasibility and effectiveness of the proposed method. The experimental results show that the active noise control method used in tufted carpet loom has better effect on low-frequency noise control than medium and high frequency noise control, and the noise cancellation at the main frequency point reaches 9.8 dB.

Key words: tufted carpet loom, noise control, filtered least mean square algorithm, low-frequency noise

CLC Number: 

  • TS103.2

Fig.1

Drive mechanism of British COBBLE 1/8-pitch tufted carpet loom"

Fig.2

Workspace of tufted carpet loom"

Fig.3

Map of feed forward active noise control system"

Fig.4

Spectrogram of tufted carpet loom noise signal"

Fig.5

Dual-microphone method for secondary path modeling"

Fig.6

Diagram of adaptive active feed forward control system"

Fig.7

Active noise control flow chart"

Fig.8

Psd map of noise signal before and after simulation when N is 128"

Tab.1

Sound pressure before and after noise reduction at main frequency points"

主要频率点/Hz 声压/Pa
降噪前 降噪后
36.10 0.035 40 0.031 26
124.77 0.043 38 0.014 03
282.30 0.030 56 0.015 49
550.70 0.030 63 0.010 31
810.00 0.003 01 0.003 09

Fig.9

Sound pressure spectrum before active noise reduction"

Fig.10

Sound pressure spectrum after active noise reduction"

[1] 李铁, 严胜刚, 刘道旭. 基于DSP的直升机舱室内的有源噪声控制系统[J]. 测控技术, 2009,28(6):54-57.
LI Tie, YAN Shenggang, LIU Daoxu. Active noise control system in helicopter cabin based on DSP[J]. Measurement & Control Technology, 2009,28(6):54-57.
[2] 鲍雪山. 舰艇自噪声自适应有源抵消技术研究[D]. 哈尔滨:哈尔滨工程大学, 2007: 3-26.
BAO Xueshan. Research on adaptive active noise cancellation technology of warship[D]. Harbin: Harbin Engineering University, 2007: 3-26.
[3] 杨益民. 特种车辆有源噪声控制系统的研究与设计[D]. 杭州:浙江大学, 2014: 3-21.
YANG Yimin. Research and design of active noise control system for special vehicles[D]. Hangzhou: Zhejiang University, 2014: 3-21.
[4] 白松, 徐新喜, 刘孝辉, 等. 车内噪声控制技术及其在卫生技术车辆中的应用[J]. 军事医学, 2012,36(2):99-102,106.
BAI Song, XU Xinxi, LIU Xiaohui, et al. In-vehicle noise control technology and its application in sanitary technology vehicles[J]. Military Medicine, 2012,36(2):99-102,106.
[5] 张帅. 一种大耳罩有源降噪耳机的设计与实现[D]. 成都:电子科技大学, 2018: 1-30.
ZHANG Shuai. Design and implementation of active noise reduction earphone with large earmuff[D]. Chengdu: University of Electronic Science and Technology of China, 2018: 1-30.
[6] MORGAN D R. History, applications, and subsequent development of the FXLMS algorithm[J]. IEEE Signal Processing Magazine, 2013,30(3):172-176.
[7] 徐洋, 李昂昂, 盛晓伟, 等. 基于近场声全息的纺织装备高速运动机构噪声源识别[J]. 纺织学报, 2019,40(4):129-134.
XU Yang, LI Ang'ang, SHENG Xiaowei, et al. Noise source identification of high-end textile equipment based on near-field acoustic holography method[J]. Journal of Textile Research, 2019,40(4):129-134.
[8] 陈智. 基于FxLMS算法的前馈式自适应有源噪声控制系统建模与仿真[J]. 自动化与仪器仪表, 2018(5):10-13.
CHEN Zhi. Modeling and simulation of feedforward adaptive active noise control system based on FxLMS Algorithm[J]. Automation & Instrumentation, 2018(5):10-13.
[9] 杨浩, 吴亚锋, 王春云, 等. AANC次级通道建模方法[J]. 噪声与振动控制, 2011,31(3):33-36.
YANG Hao, WU Yafeng, WANG Chunyun, et al. AANC secondary channel modeling method[J]. Noise and Vibration Control, 2011,31(3):33-36.
[10] 陈克安. 有源噪声控制[M]. 2版. 北京: 国防工业出版社, 2014: 118-119.
CHEN Ke'an. Active noise control[M]. 2nd ed. Beijing: National Defense Industry Press, 2014: 118-119.
[11] 叶超, 吴鸣, 杨军. 利用参量阵扬声器进行有源噪声控制的研究[J]. 电声技术, 2011,35(3):61-63.
YE Chao, WU Ming, YANG Jun. Research on active noise control using parametric array loudspeakers[J]. Audio Engineering, 2011,35(3):61-63.
[1] LI Huiqin, ZHANG Nan, WEN Xiaodan, GONG Jixian, ZHAO Xiaoming, WANG Zhishuai. Progress of noise reduction product based on fiber materials [J]. Journal of Textile Research, 2020, 41(03): 175-181.
[2] XU Yang, LI Ang'ang, SHENG Xiaowei, SUN Zhijun. Noise source identification of high-speed motion mechanism of textile equipment based on near-field acoustic holography method [J]. Journal of Textile Research, 2019, 40(04): 129-134.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!