| Sensors | |
| Inline Measurement of Particle Concentrations in Multicomponent Suspensions using Ultrasonic Sensor and Least Squares Support Vector Machines | |
| Xiaobin Zhan2  Shulan Jiang1  Yili Yang2  Jian Liang2  Tielin Shi2  Xiwen Li2  | |
| [1] Tribology Research Institute, National Traction Power Laboratory, Southwest Jiaotong University, Chengdu 610031, China; E-Mail:;State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China; E-Mails: | |
| 关键词: ultrasonic sensor; particle concentration; multicomponent suspensions; inline measurement; LS-SVM; | |
| DOI : 10.3390/s150924109 | |
| 来源: mdpi | |
PDF
|
|
【 摘 要 】
This paper proposes an ultrasonic measurement system based on least squares support vector machines (LS-SVM) for inline measurement of particle concentrations in multicomponent suspensions. Firstly, the ultrasonic signals are analyzed and processed, and the optimal feature subset that contributes to the best model performance is selected based on the importance of features. Secondly, the LS-SVM model is tuned, trained and tested with different feature subsets to obtain the optimal model. In addition, a comparison is made between the partial least square (PLS) model and the LS-SVM model. Finally, the optimal LS-SVM model with the optimal feature subset is applied to inline measurement of particle concentrations in the mixing process. The results show that the proposed method is reliable and accurate for inline measuring the particle concentrations in multicomponent suspensions and the measurement accuracy is sufficiently high for industrial application. Furthermore, the proposed method is applicable to the modeling of the nonlinear system dynamically and provides a feasible way to monitor industrial processes.
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO202003190006046ZK.pdf | 1257KB |
PDF