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.
Authors
- Ying Zeng (ORCID: https://orcid.org/0000-0003-4162-6387)
- Yan‐Feng Li (ORCID: https://orcid.org/0000-0002-9121-1465)
- Xin Huang (ORCID: https://orcid.org/0000-0002-6610-6401)
- Jing Li (ORCID: https://orcid.org/0009-0003-4443-9904)
- Yanyu Wei
Institutions
- University of Electronic Science and Technology of China (CN)
- China University of Petroleum, Beijing (CN)
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
Funders
- National Natural Science Foundation of China