Optimization Design of CMUT Sensors with Broadband and High Sensitivity Characteristics Based on the Genetic Algorithm

In this study, we propose a method for optimizing the design of CMUT sensors using genetic algorithms. Existing CMUT sensors face frequency response and sensitivity limitations, necessitating optimization to enhance their sensing performance. Traditional optimization methods are often intricate and...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-05, Vol.24 (10), p.3155
Main Authors: Zhang, Sai, Lu, Wentao, Wang, Ailing, He, Huizi, Wang, Renxin, Zhang, Wendong
Format: Article
Language:English
Subjects:
Algorithms
Arrays
Bandwidths
Behavior
Broadband transmission
Business metrics
CMUT
Design optimization
Design techniques
Efficiency
Electrodes
finite element simulation
genetic algorithm
Genetic algorithms
Medical imaging
MEMS devices
Methods
Microelectromechanical systems
Sensors
Silicon wafers
Ultrasonic imaging
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Summary:In this study, we propose a method for optimizing the design of CMUT sensors using genetic algorithms. Existing CMUT sensors face frequency response and sensitivity limitations, necessitating optimization to enhance their sensing performance. Traditional optimization methods are often intricate and time-consuming and may fail to yield the optimal solution. Genetic algorithms, which simulate the biological evolution process, offer advantages in global optimization and efficiency, making them widely utilized in the optimization design of Microelectromechanical Systems (MEMS) devices. Based on the theoretical framework and finite element model of CMUT sensors, we propose a CMUT array element optimization design method based on genetic algorithms. The optimization and validation results demonstrate that we have successfully designed a broadband CMUT array element consisting of four microelements with a 1-2 MHz frequency range. Compared with a randomly arranged array element, the optimized array shows a 63.9% increase in bandwidth and a 7.5% increase in average sensitivity within the passband. Moreover, the sensitivity variance within the passband is reduced by 50.2%. Our proposed method effectively optimizes the design of high sensitivity CMUT sensors with the desired bandwidth, thereby offering significant reference value for the optimization design of CMUT sensors.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24103155