Research on the noise source identification and operating noise prediction of the industrial sewing machine
Zhang Zhiyong1, Liu Xin1, Huang Caixia3, Tan Tao2
1. Key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle, Hunan Province，Changsha 410114, China
2. College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
3. College of Mechanical Engineering, Hunan International Economics University, Changsha 410205, China
Abstract：In order to effectively control the operating noise of the industrial sewing machine, the noise source identification and operating noise prediction are very necessary. Firstly, an experiment for acquiring the signals of vibration and noise of the sewing machine is implemented based on the method of separated operation, and the vibration signals are processed by low pass filtering and anti-trend processing. Then the main noise sources are identified by the power spectral density of operating noise under separated operation, they are the mechanism of piercing cloth and pick-up thread and the rotary shuttle mechanism. Finally, the vibration accel-erations and the noise pressures nearby the main noise sources are treated as the independent variables and de-pendent variable, respectively, with which the operating noise predictive model is 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 Y direction of the mechanism of piercing cloth and pick-up thread, followed by the vibration accelerations of the rotating shuttle mechanism in Z direction.
张志勇1,2，刘鑫1，黄彩霞3，谭涛2. 工业平缝机的噪声源识别与运行噪声预测研究[J]. 振动与冲击, 2016, 35(20): 220-225.
Zhang Zhiyong1, Liu Xin1, Huang Caixia3, Tan Tao2. Research on the noise source identification and operating noise prediction of the industrial sewing machine. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(20): 220-225.
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