Dr. Wangquan Ye Profile

Dr. Wangquan Ye

at Ocean Univ. of China

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Publications (2)

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Proceedings Article | 28 February 2021 Paper

Design and sea trial of the ocean sensors integrated interface platform

Kai Cheng, Shoujie Li, Huijun He, Wangquan Ye, Shuang Xu

Proceedings Volume 11781, 117811Q (2021) https://doi.org/10.1117/12.2590041

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According to the comprehensive test requirements of commercial and self-developed marine sensors carried on the Smart Float, an ocean sensor integrated interface platform is developed, which is composed of underwater connection unit and shore-based control center. The underwater connection unit contains the main controller, serial port server, Ethernet switch, and remote transmission equipment, etc. and it communicates with the shore-based control center through a twisted-pair or armored cable. The underwater connection unit is designed to implement the functions of power management, sensor electric current monitoring, environment temperature monitoring, and data self-storage, while the shore-based control center is designed for remote control, curve drawing, and data storage. The offshore test results indicate that our design provides an efficient and stable platform to simulate the Smart Float, ROV and HOV interfaces, and carry out the integrated connection test for the marine sensors. It demonstrates the outstanding ability for the comparison of self-developed sensors and commercial sensors, as well as the scientific application of carbon storage and oxygen capacity

Proceedings Article | 18 December 2019 Paper

Automatic outlier detection based on PLS-MMD model

Qian Chen, Wenyong Xie, Wangquan Ye, Xuejiao Duan, Ying Li

Proceedings Volume 11337, 113371E (2019) https://doi.org/10.1117/12.2548173

KEYWORDS: Mahalanobis distance, Raman spectroscopy, Calibration, Quantitative analysis

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As a chemical detection technology for analysis of in-situ, real time and multiple materials, Laser Raman Spectroscopy is competent to take quantitative research for ingredients in ocean environment, and achieve long-term in-situ supervision of acid radical ionic concentration in seawater. Due to the inevitable interference in the actual detection environment, the spectral data often contains some outliers, the existence of which has a significant impact on the performance of the quantitative analysis model. In order to remove the outliers accurately in the in-situ detection and online analysis, the MMD algorithm was combined with the PLS quantitative analysis model (PLS-MMD model) to detect and remove the outliers in the calibration set. It was demonstrated that the PLS-MMD method can effectively eliminate the abnormal spectra in the calibration data. After removing outliers the accuracy of the measured seawater sample concentration was improved with the relative error decreasing from 1.468% to 1.160%. Correspondingly, the prediction stability of in-situ seawater is also improved.

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