We present the wavelet depth-frequency analysis and variable-scale frequency cycle analysis methods to study sedimentary cycles. The spectrum analysis, variable-scale frequency cycle analysis, and wavelet depth-freque...We present the wavelet depth-frequency analysis and variable-scale frequency cycle analysis methods to study sedimentary cycles. The spectrum analysis, variable-scale frequency cycle analysis, and wavelet depth-frequency analysis methods are mainly discussed to distinguish sedimentary cycles of different levels. The spectrum analysis method established the relationship between the spectrum characteristics and the thickness and number of sedimentary cycles. Both the variable-scale frequency cycle analysis and the wavelet depth-frequency analysis are based on the wavelet transform. The variable-scale frequency cycle analysis is used to obtain the relationship between the periodic changes of frequency in different scales and sedimentary cycles, and the wavelet depth-frequency analysis is used to obtain the relationship between migration changes of frequency energy clusters and sedimentary cycles. We designed a soft-ware system to process actual logging data from the Changqing Oilfield to analyze the sedimentary cycles, which verified the effectiveness of the three methods, and good results were obtained.展开更多
Avariable scale-convex-peak method is constructed to identify the frequency of weak harmonic signal. The key of this method is to find a set of optimal identification coefficients to make the transition of dynamic beh...Avariable scale-convex-peak method is constructed to identify the frequency of weak harmonic signal. The key of this method is to find a set of optimal identification coefficients to make the transition of dynamic behavior topologically persistent. By the stochastic Melnikov method, the lower bound of the chaotic threshold continuous function is obtained in the mean-square sense.The intermediate value theorem is applied to detect the optimal identification coefficients. For the designated identification system, there is a valuable co-frequency-convex-peak in bifurcation diagram, which indicates the state transition of chaosperiod-chaos. With the change of the weak signal amplitude and external noise intensity in a certain range, the convex peak phenomenon is still maintained, which leads to the identification of frequency. Furthermore, the proposition of the existence of reversible scaling transformation is introduced to detect the frequency of the harmonic signal in engineering. The feasibility of constructing the hardware and software platforms of the variable scale-convex-peak method is verified by the experimental results of circuit design and the results of early fault diagnosis of actual bearings, respectively.展开更多
基金supported by the National Science&Technology Major Project(No.2008ZX05020) of CNPC
文摘We present the wavelet depth-frequency analysis and variable-scale frequency cycle analysis methods to study sedimentary cycles. The spectrum analysis, variable-scale frequency cycle analysis, and wavelet depth-frequency analysis methods are mainly discussed to distinguish sedimentary cycles of different levels. The spectrum analysis method established the relationship between the spectrum characteristics and the thickness and number of sedimentary cycles. Both the variable-scale frequency cycle analysis and the wavelet depth-frequency analysis are based on the wavelet transform. The variable-scale frequency cycle analysis is used to obtain the relationship between the periodic changes of frequency in different scales and sedimentary cycles, and the wavelet depth-frequency analysis is used to obtain the relationship between migration changes of frequency energy clusters and sedimentary cycles. We designed a soft-ware system to process actual logging data from the Changqing Oilfield to analyze the sedimentary cycles, which verified the effectiveness of the three methods, and good results were obtained.
基金supported by the National Natural Science Foundation of China (Grant Nos. 11872253, 11602151, 11790282)the Natural Science Foundation for Outstanding Young Researcher in Hebei Province of China(Grant No. A2017210177)+2 种基金the Natural Science Foundation in Hebei Province of China (Grant No. A2019421005)the Hundred Excellent Innovative Talents in Hebei Province (Grant No. SLRC2019037)the Basic Research Team Special Support Projects (Grant No. 311008)。
文摘Avariable scale-convex-peak method is constructed to identify the frequency of weak harmonic signal. The key of this method is to find a set of optimal identification coefficients to make the transition of dynamic behavior topologically persistent. By the stochastic Melnikov method, the lower bound of the chaotic threshold continuous function is obtained in the mean-square sense.The intermediate value theorem is applied to detect the optimal identification coefficients. For the designated identification system, there is a valuable co-frequency-convex-peak in bifurcation diagram, which indicates the state transition of chaosperiod-chaos. With the change of the weak signal amplitude and external noise intensity in a certain range, the convex peak phenomenon is still maintained, which leads to the identification of frequency. Furthermore, the proposition of the existence of reversible scaling transformation is introduced to detect the frequency of the harmonic signal in engineering. The feasibility of constructing the hardware and software platforms of the variable scale-convex-peak method is verified by the experimental results of circuit design and the results of early fault diagnosis of actual bearings, respectively.
