We present the thermal expansion coefficient （TEC） measurement technology of compensating for the effect of variations in the refractive index based on a Nd： YA G laser feedback system, the beam frequency is shifte...We present the thermal expansion coefficient （TEC） measurement technology of compensating for the effect of variations in the refractive index based on a Nd： YA G laser feedback system, the beam frequency is shifted by a pair of aeousto-optic modulators and then the heterodyne phase measurement technique is used. The sample measured is placed in a muffle furnace with two coaxial holes opened on the opposite furnace walls. The measurement beams hit perpendicularly and coaxially on each surface of the sample. The reference beams hit on the reference mirror and the high-refiectivity mirror, respectively. By the heterodyne configuration and computing, the influences of the vibration, distortion of the sample supporter and the effect of variations in the refractive index are measured and largely minimized. For validation, the TECs of aluminum samples are determined in the temperature range of 29-748K, confirming not only the precision within 5 × 10-7 K-1 and the accuracy within 0.4% from 298K to 448K but also the high sensitivity non-contact measurement of the lower reflectivity surface induced by the sample oxidization from 448 K to 748 K.展开更多
In this paper, we present a method based on self-mixing interferometry combing extreme learning machine for real-time human blood pressure measurement. A signal processing method based on wavelet transform is applied ...In this paper, we present a method based on self-mixing interferometry combing extreme learning machine for real-time human blood pressure measurement. A signal processing method based on wavelet transform is applied to extract reversion point in the self-mixing interference signal, thus the pulse wave profile is successfully reconstructed. Considering the blood pressure values are intrinsically related to characteristic parameters of the pulse wave, 80 samples from the MIMIC-II database are used to train the extreme learning machine blood pressure model. In the experiment, 15 measured samples of pulse wave signal are used as the prediction sets. The results show that the errors of systolic and diastolic blood pressure are both within 5 mm Hg compared with that by the Coriolis method.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No F050306
文摘We present the thermal expansion coefficient （TEC） measurement technology of compensating for the effect of variations in the refractive index based on a Nd： YA G laser feedback system, the beam frequency is shifted by a pair of aeousto-optic modulators and then the heterodyne phase measurement technique is used. The sample measured is placed in a muffle furnace with two coaxial holes opened on the opposite furnace walls. The measurement beams hit perpendicularly and coaxially on each surface of the sample. The reference beams hit on the reference mirror and the high-refiectivity mirror, respectively. By the heterodyne configuration and computing, the influences of the vibration, distortion of the sample supporter and the effect of variations in the refractive index are measured and largely minimized. For validation, the TECs of aluminum samples are determined in the temperature range of 29-748K, confirming not only the precision within 5 × 10-7 K-1 and the accuracy within 0.4% from 298K to 448K but also the high sensitivity non-contact measurement of the lower reflectivity surface induced by the sample oxidization from 448 K to 748 K.
基金supported by the National Natural Science Foundation of China (No.61675174)the Natural Science Foundation of Fujian Province (No.2020J01705)。
文摘In this paper, we present a method based on self-mixing interferometry combing extreme learning machine for real-time human blood pressure measurement. A signal processing method based on wavelet transform is applied to extract reversion point in the self-mixing interference signal, thus the pulse wave profile is successfully reconstructed. Considering the blood pressure values are intrinsically related to characteristic parameters of the pulse wave, 80 samples from the MIMIC-II database are used to train the extreme learning machine blood pressure model. In the experiment, 15 measured samples of pulse wave signal are used as the prediction sets. The results show that the errors of systolic and diastolic blood pressure are both within 5 mm Hg compared with that by the Coriolis method.
