A Study on Identifying the Sources of Dominant Frequency Components of Electric Motor Noise

1989 ◽  
Vol 33 (1) ◽  
pp. 11 ◽  
Author(s):  
Chen Xinzhao ◽  
Li Dengxiao ◽  
Chen Jian ◽  
Liu Zhengshi
Keyword(s):  
Electric Motor ◽  
Dominant Frequency ◽  
Motor Noise ◽  
Frequency Components

scholarly journals HHT based analysis on seismic response recordings for a base-isolated building

2019 ◽  
Vol 277 ◽  
pp. 02021
Author(s):  
Fei Wang ◽  
Xiandong Kang ◽  
Ting Yan ◽  
Ying Liu
Keyword(s):  
Seismic Response ◽  
Dominant Frequency ◽  
Data Series ◽  
Structural Systems ◽  
Original Signal ◽  
Intrinsic Mode Functions ◽  
Hilbert Huang Transform ◽  
Mode Decomposition ◽  
Frequency Components ◽  
Emd Method

Hilbert-Huang transform (HHT) is proposed to process the seismic response recordings in an 8-story frame-shear wall base-isolated building. Empirical Mode Decomposition (EMD) method is first applied to identify the time variant characteristics and the data series can be decomposed into several components. Hilbert transform is well-behaved in identifying the frequency components. The first 5 intrinsic mode functions (IMFs) are decomposed with their different frequencies. The analytical function is reconstructed and compared with the original signal. They are extremely consistent in amplitude and phase. Based on the IMFs obtained, frequencies of the original signal are inferred at 5 Hz and 1.6 Hz. The higher frequency is regarded as the vibration excited by surface waves. 1.6 Hz is suggested as the dominant frequency of the building. Analysis indicates that HHT is accurate in extracting the dynamic characteristics of structural systems.

scholarly journals Development of an on-site system for measuring the low-frequency noise and complainant’s responses

2018 ◽  
Vol 37 (2) ◽  
pp. 373-384
Author(s):  
Hiroshi Sato ◽  
Jongkwan Ryu ◽  
Kenji Kurakata
Keyword(s):  
Time Trends ◽  
Sound Pressure ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Pressure Level ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Measurement Results ◽  
Frequency Components ◽  
The Relationship

An on-site system for measuring low-frequency noise and complainant's responses to the low-frequency noise was developed to confirm whether the complainant suffer from the environmental noise with low-frequency components. The system suggests several methods to find the dominant frequency and major sound pressure level spectrum of the noise causing annoyance. This method can also yield a quantified relationship (correlation coefficient and percentage of response to the noise) between physical noise properties and the complainant’s responses. The advantage of this system is that it can easily find the relationship between the complainant’s response to the acoustic event of the houses and the physical characteristics of the low-frequency noise, such as the time trends and frequency characteristics. This paper describes the developed system and provides an example of the measurement results.

Analysis of Acoustic Signal in the MICRO Discharges Using Continuous Wavelet Transform

2006 ◽  
Vol 9 (2) ◽  
Author(s):  
Toshiyuki Nakamiya ◽  
Daiki Sasahara ◽  
Kenji Ebihara ◽  
Tomoaki Ikegami ◽  
Ryoichi Tsuda
Keyword(s):  
Wavelet Transform ◽  
Energy Distribution ◽  
Power Supply ◽  
Acoustic Signal ◽  
Continuous Wavelet Transform ◽  
Dominant Frequency ◽  
Continuous Wavelet ◽  
Electrode Current ◽  
Current Voltage ◽  
Frequency Components

AbstractTo examine the tracking phenomenon that was one of the main causes of fire breaking, fundamental experiments were carried out. To one of the electrodes AC high voltage was applied. The following samples: the mesh plate, the flat ribbon cable and the ignition plug were prepared as the electrode. Current, voltage waveforms of micro discharge and the sound signal detected by the condenser microphone were stored in the Hi-coder memory. In this paper, Continuous Wavelet Transform (CWT) was applied to determine the acoustic sound of the micro discharge and to study its dominant frequency components. Additionally, the energy distribution of acoustic signal was examined by CWT, when the frequency of power supply increased from 10 kHz to 30 kHz.

scholarly journals Experimental research on the sound recognition of the electric vehicle motor

2020 ◽  
Vol 309 ◽  
pp. 03033
Author(s):  
Dongmei Hu ◽  
Peiyun Xu ◽  
Cheng Cao ◽  
Xiaojun Yan ◽  
Zhihong Hu ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Frequency Converter ◽  
Sound Recognition ◽  
Bench Test ◽  
Switching Frequency ◽  
Frequency Noise ◽  
Motor Noise ◽  
Noise Characteristics ◽  
Order Tracking ◽  
Frequency Components

By synthetically applying order tracking method and acoustic holography method, the noise source of the electric vehicle motor was discerned in the bench test. According to profiling of the test data, the motor noise order tracking diagrams and sound holography contour maps were employed to draw the noise map of the electric vehicle motor. It was revealed that the low and medium frequency components of the motor’s noise are mainly related to the rotational passing frequency of the bearing rolling element and cage, as well as the doubling frequencies of the rotational frequencies of the rotor. The medium and high frequency components of motor’s noise are mainly related to motor’s loads and speeds. In the 1000-2500 r/min speed stage of the motor with load, the main order of motor’s noise is the 72nd order and in the speed stage of 3000-5000 r/min, motor’s noise is mainly the 15th, 18th and 26th orders. When the motor speed increases from 5000r/min to 8000r/min, the main order of motor’s noise is the fourth order. When the motor was accelerated in no-load operation, its noise characteristics are different from those of the motor with load. When the motor run at no load and low speed, the 16th and 72nd order are the main order of motor noise, while at high speed, the 2nd order of motor noise and the orders of motor switching frequency noise caused by frequency converter are the main order of motor noise. The above conclusions will give the assistance to further research on the acoustic characteristic of the electric vehicle motor.

Study on the Mechanism for Line Spectrum Reduction in Nonlinear Vibration Isolation System

2007 ◽  
Author(s):  
Jing-Jing Wang ◽  
Shi-Jian Zhu ◽  
Shu-Yong Liu
Keyword(s):  
Nonlinear Vibration ◽  
Vibration Isolation ◽  
Harmonic Balance Method ◽  
Chaotic Signal ◽  
Dominant Frequency ◽  
Line Spectrum ◽  
Isolation System ◽  
Vibration Isolation System ◽  
Chaotic Response ◽  
Frequency Components

The chaotic response and mechanism for line spectrum reduction in nonlinear vibration isolation system are studied. The harmonic balance method is applied to uncover the interaction between different harmonics. It is clear that the considerable energy transfers from the fundamental harmonic to the others by the nonlinear interactions, and thus the energy at the dominant frequency is reduced greatly. When the nonlinear vibration isolation system is in a chaotic state, the response is characteristic of the broadband spectrum, and thus the energy is distributed to all the frequency components. Chaotic attractor is different from the point, limit cycle and so on, and the fractal dimension can be applied to describe its characteristic. Furthermore, the chaotic signal is distinguished from the random one by the saturation of the correlation dimension. The former approaches to saturation with the increasing embedding dimension, but the latter does not. The phase space reconstruction based on wavelet transform can achieve the study of both the geometry and frequency characteristics of the chaos, so that provides a new way to study chaotic response.

Sign in / Sign up

Export Citation Format

Share Document