
Journals >Laser & Optoelectronics Progress
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030102 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030103 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030104 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030001 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030002 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030003 (2018)
ing at the status of an increasing spread of illegal drugs which brings severe threats to public security in recent years, it is pointed that technologies of analysis and detection on illicit materials play a vital role in on-site screening and evidence extraction of illegal drugs related events. The application of surface enhanced Raman spectroscopy (SERS) detection in several typical illegal drugs, such as opiates, cocaines, amphetamines, ketamines, and so on, are summarized. Challenges for in-field and real time detection of illegal drugs are analyzed. The SERS is expected to be one of the most popular detection technologies due to its excellent performances, such as sensitivity, accuracy, simple operation, etc. The future development trend of the technology is predicted to be constructing high quality substrate with good robustness, exploring new surfactants and stabilizers, developing a new portable Raman spectrometer with a high signal-noise ratio, and developing intelligent recognition algorithm with good generalization.
.- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030004 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030005 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030006 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030007 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030008 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030009 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030010 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031201 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031202 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031203 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031204 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031401 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031402 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031403 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031404 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031405 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 032301 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 032302 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 032303 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030601 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030602 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030603 (2018)
ing at the application of optical transmitter signal distortion analysis, we adopt a coherent detection system with slowly varying phase, analyze the preprocessing of the distorted optical signal by means of cluster analysis, and estimate the distortion coefficients accurately to achieve a better constellation restoration effect. In this system, we adjust the length of the local oscillator fiber link to be equal to the fiber length of the signal link, so that the phase difference between the local oscillator and the signal light can be approximately constant over a long time window. It means that we can do intelligent analysis and preprocessing of the constellation for the long time window data by means of cluster analysis. Then, we obtain the distortion coefficients and cluster centroids based on cluster analysis of signal constellation, and use the location information of cluster centroids to equalization process and carrier phase recovery. This scheme solves signal recovery problems in the presence of signal distortion and phase noise, enabling accurate signal distortion evaluation. In this system, we simulate and experiment three kinds of distorted signals (I-Q gain imbalance, I-Q phase error, and I-Q amplitude uneven distribution) by using cluster analysis and blind-phase-search (BPS) algorithm. The results show that in the experimental system we can accurately estimate the transmitter signal distortion mentioned by using cluster analysis.
.- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030604 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030605 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 030606 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031101 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031102 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031103 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031104 (2018)
ing at the interference of the surface burrs, oil, and other attachments on the corner detection in the visual measurement, we propose a method of sub-pixel location based on curvature and gray. Firstly, we use a morphological and bilateral filtering method to eliminate burrs, oil, and other attachments in the region of interest. Secondly, we detect the candidate corners according to the curvature characteristics, pre-screen the false-corners by the multi-scale invariance of the curvature angle at the corner, and use the gray information in the circular window to further eliminate false-corners to achieve the corner of the rough positioning. Finally, we screen the edge point of the original image according to the connection between the coarse positioning corner and the regional end points, and fit the filtered edge points by using least squares fitting to achieve precise positioning of the corner point. The experimental results show that the method can effectively overcome the interference of the surface attachment of the workpiece surface. The repeatability of corner location reaches 0.01 mm, and the accuracy of corner location algorithm reaches 0.004 mm, and the comprehensive measurement accuracy based on corner points is 0.06 mm.
.- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031501 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031601 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031602 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 033101 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 032201 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031001 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031002 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031003 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031004 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031005 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031006 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031007 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031008 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031009 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031010 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031011 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031012 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 031013 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 031301 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 032801 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 033001 (2018)
- Publication Date: Apr. 12, 2018
- Vol. 55, Issue 3, 033002 (2018)
- Publication Date: Apr. 11, 2018
- Vol. 55, Issue 3, 033004 (2018)