张永存

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:力学与航空航天学院

学科:工程力学. 计算力学. 航空航天力学与工程

办公地点:系楼504

联系方式:yczhang@dlut.edu.cn

电子邮箱:yczhang@dlut.edu.cn

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A new sensitivity improving approach for mass sensors through integrated optimization of both cantilever surface profile and cross-section

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论文类型:期刊论文

发表时间:2015-01-01

发表刊物:SENSORS AND ACTUATORS B-CHEMICAL

收录刊物:SCIE、EI、Scopus

卷号:206

页面范围:343-350

ISSN号:0925-4005

关键字:Mass sensor; Trapezoidal grooved cantilever; Sensitivity improvement; Integrated optimization

摘要:Sensitivity is of great importance for piezoelectric resonance mass sensors in the fields of material and particle analyzing. Different from the custom used methods such as geometric dimension reduction and configuration modification, a new sensitivity improving method was proposed by simultaneously modifying both the surface profile and the cross-section type of the cantilever to optimize its stiffness and mass distribution. Knowing the effects of the structural parameters on the resonance frequency, a novel piezoelectric resonant mass sensor was designed and fabricated by introducing the grooved trapezoidal cantilever with variable cross-section as the key elastic element. Through the cantilever vibration analysis by the finite element method, the sensitivity analyzing model for the grooved trapezoidal cantilever mass sensor was established, with which, the influence of the groove and profile parameters on the sensitivity improvement was systematically analyzed. The experimental and simulated sensitivities of the proposed sensor are 33.7 x 10(3) Hz/g and 38.0 x 10(3) Hz/g respectively, which are nearly 387.8% greater than that of the custom rectangular cantilever sensor of 9.8 x 10(3) Hz/g. More importantly, the proposed sensor also possesses the character of high sensitivity for distributed mass detection, which is 2.92 times that of the rectangular cantilever sensor. Finally, the feasibility and effectiveness of the newly proposed sensitivity improving method was validated. (C) 2014 Elsevier B.V. All rights reserved.