摘要
为了有效控制工业平缝机的运行噪声,有必要开展噪声源识别和运行噪声预测研究。首先基于分部运行法进行平缝机振动与噪声信号的测试实验,并对采集的振动信号进行低通滤波和去趋势项处理;然后根据分部运行下的噪声功率谱密度,确定出主要的噪声源是刺布挑线机构和旋梭机构;最后分别以主要噪声源附近的振动加速度信号和运行噪声声压为自变量和因变量,基于核偏最小二乘回归方法建立运行噪声的预测模型,开展了运行噪声对振动加速度的敏感性分析。噪声预测模型的精度分析表明,振动加速度与噪声声压之间的非线性关系能被准确建模,运行噪声预测模型具有非常高的精度。敏感性分析进一步确定,平缝机运行噪声对刺布挑线机构Y方向的振动最敏感,其次是旋梭机构Z方向的振动。
In order to effectively control the operating noise of industrial sewing machines, the noise source identification and operating noise prediction are very necessary. An experiment for acquiring the signals of vibration and noise of sewing machines was implemented based on the method of separated operation. The vibration signals were processed by low pass filtering and anti-trend processing. The main noise sources were identified by the power spectral density of operating noise under separated operation, which are the part of piercing cloth and pick-up thread and the rotary shuttle part. The vibration accelerations and the noise pressures nearby the main noise sources were treated as the independent variables and the dependent variable, respectively, with which an operating noise predictive model was established based on the kernel partial least squares method. The accuracy analysis of the predictive model shows that the nonlinear relationship between the vibration accelerations and noise sound pressure can be accurately modeled and the model has a very high accuracy. The sensitivity analysis further determines that the operating noise is the most sensitive to the vibration accelerations in the Y direction of the part of piercing cloth and pick-up thread, followed by the vibration accelerations of the rotating shuttle part in the Z direction.
出处
《振动与冲击》
EI
CSCD
北大核心
2016年第20期220-225,共6页
Journal of Vibration and Shock
基金
湖南省自然科学基金(2015JJ2002)
湖南省教育厅资助科研项目(15B008)
国家自然科学基金(51305047)
关键词
噪声源识别
噪声预测
分部运行
核偏最小二乘
敏感性分析
工业平缝机
noise source identification
noise prediction
separated operation
kernel partial least squares
sensitivity analysis
industrial sewing machine
