Papers by Keyword: Recurrence Plot (RP)

Abstract: Previous studies have indicated that the chronic effects of exposure to low-frequency noise causes annoyance. However, during the past two decades, most studies have employed questionnaires to characterize the effects of noise on psychosomatic responses. This study investigated cardiovascular activity changes in exposure to low-frequency noise for various noise intensities by using recurrence plot analysis of heart rate variability (HRV) estimation. The authors hypothesized that distinct noise intensities affect cardiovascular activity, which would be reflected in the HRV and recurrence quantification analysis (RQA) parameters. The test intensities of noises were no noise, 70-dBC, 80-dBC, and 90-dBC. Each noise level was sustained for 5 min, and the electrocardiogram (ECG) was recorded simultaneously. The cardiovascular responses were evaluated using RQA of the beat-to-beat (RR) intervals obtained from ECG signals. The results showed that the mean RR interval variability and mean blood pressure did not substantially change relative to the noise levels. However, the length of the longest diagonal line (L_max) of the RQA of the background noise (no noise) condition was significantly lower than the 70-dBC, 80-dBC, and 90-dBC noise levels. The laminarity showed significant changes in the noise levels of various intensities. In conclusion, the RQA-based measures appear to be an effective tool for exposure to low-frequency noise, even in short-term HRV time series.

Abstract: The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

Abstract: Hilbert-Huang transform is developed in recent years dealing with nonlinear, non-stationary signal analysis of the complete local time-frequency method, recurrence plot method is a recursive nonlinear dynamic behavior of time series method of reconstruction. In this paper, Hilbert-Huang Transform empirical mode decomposition (EMD) and the recurrence plot (RP) method, a new voice activity detection algorithm. Firstly, through the speech and noise based on the empirical mode decomposition and multi-scale features of the different intrinsic mode function (IMF) on a time scale filtering and nonlinear dynamic behavior of the recurrence plot method, quantitative Recursive analysis of statistical uncertainty for endpoint detection. Simulation results show that the method has a strong non-steady-state dynamic analysis capabilities, in low SNR environment more accurately than the traditional method to extract the start and end point of the speech signal, robustness.

Abstract: In this paper, a new method of the recurrence analysis pitch detection of nonlinear dynamical characteristics for speech signals is designed，which calculated firstly the pitch by recurrence quantification，and then distinguished accurately voiced/unvoiced by the product of the recurrence degree and the pitch, and modified the fluctuating pitch. The results show that the new method performance is better than the conventional autocorrelation algorithm and cepstrum method，especially in the part that the surd and the sonant are not evident, and get a high robustness in noisy environment.

Abstract: Aero-engine rotor system is the core component of engine. Aim at difficulties of fault diagnosis of engine rotor system, a method to detect the fault feature is proposed, which is based on recurrence plot (RP) and recurrence quantification analysis(RQA) by research of the characteristics and the mechanism of faults. An experiment is used to detect the fault of rotor system by using this new method. The results showed that the RQA is an effective way to extract features from vibration signal and by the use of quantitative features it is possible to identify and classify different types of rotor. Comparing with classical statistical features, the proposed algorithm has better classification rate. The research will be helpful in the further study of fault diagnosis of rotor system.