Reliability Assessment of MEMS Flow Sensors Considering Pollutant Deposition

ABSTRACT Micro‐Electro‐Mechanical System (MEMS) flow sensors have seen significant advancements in recent years, owing to their advantages of miniaturization, low power consumption, and high precision. These sensors are extensively employed in various flow measurement applications. However, the presence of pollutants in the fluid being measured can result in the deposition of contaminants onto the sensor's sensitive components, which may lead to increased measurement inaccuracies and, in certain instances, sensor malfunction or failure. Furthermore, the lack of standardized manufacturing processes for MEMS sensors results in variations in production techniques, posing challenges for reliability assessment. This paper aims to investigate the impact of pollutant deposition on the measurement performance of flow sensors and to establish corresponding reliability models and evaluation methods. A particle deposition model for dust in pipelines is developed to explore the relationships between the amount of pollutant deposition and factors such as atmospheric pressure and temperature. Subsequently, the finite element model of a MEMS flow sensor considering the effects of pollutant deposition is created to obtain simulation data. Finally, the relationship between the thickness of pollutants and sensor measurement errors is studied, and a reliability model for MEMS flow sensors is built based on the degradation process. A case study is conducted on a flow sensor within an automotive intake manifold to validate the feasibility of the proposed method.

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Publication Details

Journal
Quality and Reliability Engineering International
Published
2025-05-19
DOI
https://doi.org/10.1002/qre.3799
Citations
1
Primary Topic
Advanced Sensor Technologies Research
Type
article
Field-Weighted Citation Impact
0.67

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article

Reliability Assessment of MEMS Flow Sensors Considering Pollutant Deposition

Ying Zeng, Yan‐Feng Li, Xin Huang, Jing Li et al.
1 citations
Quality and Reliability Engineering International
Advanced Sensor Technologies Research
0.67
article

Reliability Assessment of MEMS Flow Sensors Considering Pollutant Deposition

Ying Zeng, Yan‐Feng Li, Xin Huang, Jing Li, Yanyu Wei
article en
1 citations

Abstract

ABSTRACT Micro‐Electro‐Mechanical System (MEMS) flow sensors have seen significant advancements in recent years, owing to their advantages of miniaturization, low power consumption, and high precision. These sensors are extensively employed in various flow measurement applications. However, the presence of pollutants in the fluid being measured can result in the deposition of contaminants onto the sensor's sensitive components, which may lead to increased measurement inaccuracies and, in certain instances, sensor malfunction or failure. Furthermore, the lack of standardized manufacturing processes for MEMS sensors results in variations in production techniques, posing challenges for reliability assessment. This paper aims to investigate the impact of pollutant deposition on the measurement performance of flow sensors and to establish corresponding reliability models and evaluation methods. A particle deposition model for dust in pipelines is developed to explore the relationships between the amount of pollutant deposition and factors such as atmospheric pressure and temperature. Subsequently, the finite element model of a MEMS flow sensor considering the effects of pollutant deposition is created to obtain simulation data. Finally, the relationship between the thickness of pollutants and sensor measurement errors is studied, and a reliability model for MEMS flow sensors is built based on the degradation process. A case study is conducted on a flow sensor within an automotive intake manifold to validate the feasibility of the proposed method.

Quality and Reliability Engineering InternationalVol. 41(6)
University of Electronic Science and Technology of China (CN), China University of Petroleum, Beijing (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 32%
Advanced Sensor Technologies Research
0.67
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