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Sensors 2015, 15(4), 9136-9155;

Genetic Algorithm (GA)-Based Inclinometer Layout Optimization

The Faculty of Mechanical & Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
School of Computer Science and Engineering, The University of New South Wales, 2052 Sydney, Australia
Institute of Microelectronics, Tsinghua University, 100084 Beijing, China
Guangxi Experiment Center of Information Science, No.1 Jinji Road, Guilin 541004, China
Authors to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 31 August 2014 / Accepted: 10 April 2015 / Published: 17 April 2015
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [897 KB, uploaded 22 April 2015]   |  


This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors. View Full-Text
Keywords: airflow inclinometer; sensitivity study; GA; thermal layout airflow inclinometer; sensitivity study; GA; thermal layout

Figure 1a

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liang, W.; Zhang, P.; Chen, X.; Cai, M.; Yang, D. Genetic Algorithm (GA)-Based Inclinometer Layout Optimization. Sensors 2015, 15, 9136-9155.

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