Real-time monitoring of cleanroom laboratories using low cost sensors

被引:0
|
作者
Han, Yeongcheol [1 ]
Jung, Hyej In [1 ]
Moon, Jangil [1 ]
Baek, Jongmin [1 ]
Han, Changhee [1 ]
Hur, Soon Do [1 ]
机构
[1] Korea Polar Res Inst, Incheon 21990, South Korea
关键词
Arduino; cleanroom; fine dust; air filter; particle counter;
D O I
10.14770/jgsk.2019.55.1.141
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
An air filtration system (AFS) is necessary for laboratories that analyze trace components in natural or artificial samples liable to be contaminated by airborne particulates. In general, an AFS employs multi-stage air filters with a HEPA (high efficiency particulate air) or an ULPA (ultra-low penetration air) filter as the final filter to supply particle-free air to a laboratory. However, using these filters does not guarantee the desired cleanliness of air, and routine assessment of the particle levels in laboratory air is required especially given the potential increase in atmospheric fine particles in Korea. In this context, we have developed a real-time particle monitor (PaMo) using a low cost sensor module and a web based data logger. A temperature and humidity sensor was also included in the PaMo. Two PaMo units have been installed in two cleanroom laboratories for ice core research at the Korea Polar Research Institute. The number of particles larger than 0.3 mu m, temperature and relative humidity were monitored from 29th March to 24th June 2018. This real-time monitoring proved that, although the particle concentrations in the room air increased with that in the outdoor air, the AFSs were able to achieve and maintain the cleanliness required for each laboratory. The PaMo will be able to identify particle sources other than the outdoor air, provide a guideline for when to replace filters and notify unexpected AFS failure. We suggest that the PaMo is an easy and effective alternative to expensive particle counters for laboratories that operate AFS.
引用
收藏
页码:141 / 148
页数:8
相关论文
共 50 条
  • [41] Real-time Haze Monitoring Based on Social Sensors
    Zhu, Dandan
    Wang, Chenchen
    Chen, Dong
    Ye, Zhihui
    Lian, Yuanfeng
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELING AND SIMULATION (AMMS 2017), 2017, 153 : 402 - 405
  • [42] Real-Time Water Quality Monitoring with Chemical Sensors
    Yaroshenko, Irina
    Kirsanov, Dmitry
    Marjanovic, Monika
    Lieberzeit, Peter A.
    Korostynska, Olga
    Mason, Alex
    Frau, Ilaria
    Legin, Andrey
    SENSORS, 2020, 20 (12) : 1 - 22
  • [43] Smart sensors for real-time monitoring of patients on dialysis
    Fokko P. Wieringa
    Jeroen P. Kooman
    Nature Reviews Nephrology, 2020, 16 : 554 - 555
  • [44] Real-Time Remediation Performance Monitoring with ORP Sensors
    Blotevogel, Jens
    Askarani, Kayvan Karimi
    Hanson, Andrea
    Gallo, Sam
    Carling, Brian
    Mowder, Carol
    Spain, Jim
    Hartten, Andrew
    Sale, Tom
    GROUND WATER MONITORING AND REMEDIATION, 2021, 41 (03): : 27 - 28
  • [45] Advances in electrochemical sensors for real-time glucose monitoring
    Harun-Or-Rashid, Md.
    Aktar, Most. Nazmin
    Preda, Veronica
    Nasiri, Noushin
    SENSORS & DIAGNOSTICS, 2024, 3 (06): : 893 - 913
  • [46] Acoustic sensors for monitoring neuronal adhesion in real-time
    Khraiche, ML
    Zhou, A
    Muthuswamy, J
    PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH, 2003, 25 : 2186 - 2188
  • [47] Smart sensors for real-time monitoring of patients on dialysis
    Wieringa, Fokko P.
    Kooman, Jeroen P.
    NATURE REVIEWS NEPHROLOGY, 2020, 16 (10) : 554 - 555
  • [48] Laboratories and a real-time computing
    Årzén, KE
    Blomdell, A
    Wittenmark, B
    IEEE CONTROL SYSTEMS MAGAZINE, 2005, 25 (01): : 30 - 34
  • [49] Towards Adaptive, Real-time Monitoring of Food Quality using Smart Sensors
    Henrichs, Elia
    Krupitzer, Christian
    2022 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING AND SELF-ORGANIZING SYSTEMS COMPANION (ACSOS-C 2022), 2022, : 70 - 71
  • [50] Real-time monitoring of local scour by using fiber Bragg grating sensors
    Lin, YB
    Chen, JC
    Chang, KC
    Chern, JC
    Lai, JS
    SMART MATERIALS AND STRUCTURES, 2005, 14 (04) : 664 - 670