The vibration signal contains a wealth of sensitive information which reflects the running status of the equipment. It is one of the most important steps for precise diagnosis to decompose the signal and extracts the ...The vibration signal contains a wealth of sensitive information which reflects the running status of the equipment. It is one of the most important steps for precise diagnosis to decompose the signal and extracts the effective information properly. The traditional classical adaptive signal decomposition method, such as EMD, exists the problems of mode mixing, low decomposition accuracy etc. Aiming at those problems, EAED（extreme average envelope decomposition） method is presented based on EMD. EAED method has three advantages. Firstly, it is completed through midpoint envelopment method rather than using maximum and minimum envelopment respectively as used in EMD. Therefore, the average variability of the signal can be described accurately. Secondly, in order to reduce the envelope errors during the signal decomposition, replacing two envelopes with one envelope strategy is presented. Thirdly, the similar triangle principle is utilized to calculate the time of extreme average points accurately. Thus, the influence of sampling frequency on the calculation results can be significantly reduced. Experimental results show that EAED could separate out single frequency components from a complex signal gradually. EAED could not only isolate three kinds of typical bearing fault characteristic of vibration frequency components but also has fewer decomposition layers. EAED replaces quadratic enveloping to an envelope which ensuring to isolate the fault characteristic frequency under the condition of less decomposition layers. Therefore, the precision of signal decomposition is improved.展开更多
A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated...A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated by factor 2 and modulated by (- 1)n, and then is interpolated by a linear phase FIR all-pass filter, finally the modulated complex envelope of bandpass signal can be produced.展开更多
In order to search for the seismic wave characteristics of low frequency signals in the Alxa Left Banner region,Inner Mongolia,the low frequency signals of seismic wave data are extracted from the earthquakes of MS5. ...In order to search for the seismic wave characteristics of low frequency signals in the Alxa Left Banner region,Inner Mongolia,the low frequency signals of seismic wave data are extracted from the earthquakes of MS5. 8 in 2015 and MS5. 0 in 2016 in this area. The results show that:① Before the MS5. 8 earthquake,the seismic stations located near the epicenter in Wuhai,Dongshengmiao,and Shizuishan recorded seismic waves that showed the phenomenon of spectrum shift from high to low frequency.② The low frequency signals recorded by different stations have obvious difference.③ According to the data recorded by the station closest to the epicenter,low-frequency signals were recorded about120 hours before the earthquake and had obvious anomalies. This may reflect slow slip before the earthquake.展开更多
In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils...In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar(GPR)and obtained different types of soil with frequencies of 500 MHz,250 MHz,and 100 MHz antennas.The soil profile data were obtained for 500 MHz,250 MHz,and 100 MHz antennas,and the dielectric properties of each type of soil were analyzed.In the image processing procedure,wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information.Secondly,the reconstructed signal is taken as an envelope to enhance the stratification information.The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification.Finally,the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon.The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah,horizon and the absolute accuracy of the stratification is within 5 cm.The effect on the soil stratification below the tillage horizon is not apparent,and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm.The overwhelming majority of the overall calculation errors are kept to within 15%.Based on the three central frequency antennas,the soil horizon detection rate reaches 93.3%,which can achieve accurate stratification of soil profiles within 1 m.The experimental and image processing methods used are practical and feasible;however,the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties.Overall,this study can quickly and accurately determine the information of each soil stratification,ultimately providing technical support for acquiring soil configuration information and developing smart agriculture.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51175316,51575331)
文摘The vibration signal contains a wealth of sensitive information which reflects the running status of the equipment. It is one of the most important steps for precise diagnosis to decompose the signal and extracts the effective information properly. The traditional classical adaptive signal decomposition method, such as EMD, exists the problems of mode mixing, low decomposition accuracy etc. Aiming at those problems, EAED（extreme average envelope decomposition） method is presented based on EMD. EAED method has three advantages. Firstly, it is completed through midpoint envelopment method rather than using maximum and minimum envelopment respectively as used in EMD. Therefore, the average variability of the signal can be described accurately. Secondly, in order to reduce the envelope errors during the signal decomposition, replacing two envelopes with one envelope strategy is presented. Thirdly, the similar triangle principle is utilized to calculate the time of extreme average points accurately. Thus, the influence of sampling frequency on the calculation results can be significantly reduced. Experimental results show that EAED could separate out single frequency components from a complex signal gradually. EAED could not only isolate three kinds of typical bearing fault characteristic of vibration frequency components but also has fewer decomposition layers. EAED replaces quadratic enveloping to an envelope which ensuring to isolate the fault characteristic frequency under the condition of less decomposition layers. Therefore, the precision of signal decomposition is improved.
文摘A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated by factor 2 and modulated by (- 1)n, and then is interpolated by a linear phase FIR all-pass filter, finally the modulated complex envelope of bandpass signal can be produced.
基金the Major Scientific andTechnical Project of Department of Science and Technology,Inner Mongolia in 2016(Strong Earthquake Track in the Short Stage and Integration Innovation of Stereoscopic Observation Technology in Space and Ground)
文摘In order to search for the seismic wave characteristics of low frequency signals in the Alxa Left Banner region,Inner Mongolia,the low frequency signals of seismic wave data are extracted from the earthquakes of MS5. 8 in 2015 and MS5. 0 in 2016 in this area. The results show that:① Before the MS5. 8 earthquake,the seismic stations located near the epicenter in Wuhai,Dongshengmiao,and Shizuishan recorded seismic waves that showed the phenomenon of spectrum shift from high to low frequency.② The low frequency signals recorded by different stations have obvious difference.③ According to the data recorded by the station closest to the epicenter,low-frequency signals were recorded about120 hours before the earthquake and had obvious anomalies. This may reflect slow slip before the earthquake.
基金Under the auspices of the National Key R&D Program of China(No.2021YFD1500100)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28100000)。
文摘In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar(GPR)and obtained different types of soil with frequencies of 500 MHz,250 MHz,and 100 MHz antennas.The soil profile data were obtained for 500 MHz,250 MHz,and 100 MHz antennas,and the dielectric properties of each type of soil were analyzed.In the image processing procedure,wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information.Secondly,the reconstructed signal is taken as an envelope to enhance the stratification information.The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification.Finally,the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon.The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah,horizon and the absolute accuracy of the stratification is within 5 cm.The effect on the soil stratification below the tillage horizon is not apparent,and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm.The overwhelming majority of the overall calculation errors are kept to within 15%.Based on the three central frequency antennas,the soil horizon detection rate reaches 93.3%,which can achieve accurate stratification of soil profiles within 1 m.The experimental and image processing methods used are practical and feasible;however,the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties.Overall,this study can quickly and accurately determine the information of each soil stratification,ultimately providing technical support for acquiring soil configuration information and developing smart agriculture.
