Mobile QR Code QR CODE : Korean Journal of Air-Conditioning and Refrigeration Engineering
Korean Journal of Air-Conditioning and Refrigeration Engineering

Korean Journal of Air-Conditioning and Refrigeration Engineering

ISO Journal TitleKorean J. Air-Cond. Refrig. Eng.
  • Open Access, Monthly
Open Access Monthly
  • ISSN : 1229-6422 (Print)
  • ISSN : 2465-7611 (Online)
Online Submission

Journal Search

  1. Home
  2. Archive
  3. 2022-03 (Vol.34 No.03)
  4. 10.6110/KJACR.2022.34.3.111
XML PDF INFO REF

References

1 
Li H., Yu D., Braun E. J. E., 2011, A Review of Virtual Sensing Technology and Application in Building Systems, HVAC&R Reserach, Vol. 17, pp. 619-645DOI
2 
Cheung H., Braun J. E., 2016, Minimizing Data Collection for Field Calibration of Steady-State Virtual Sensors for HVAC Equipment, International Journal of Refrigeration, Vol. 69, pp. 96-105DOI
3 
Ploennigs J., Ahmed A., Hensel B., Stack P., Menzel K., 2011, Virtual Sensors for Estimation of Energy Consumption and Thermal Comfort in Buildings with Underfloor Heating, Advanced Engineering Informatics, Vol. 25, No. 4, pp. 688-698DOI
4 
Zhao X., Yang M., Li H., 2012, A Virtual Condenser Fouling Sensor for Chillers, Energy and Buildings, Vol. 52, pp. 68-76DOI
5 
Himeur Y., Alsalemi A., Al-Kababji A., Bensaali F., Amira A., 2020, Data Fusion Strategies for Energy Efficiency in Buildings: Overview, Challenges and Novel Orientations, information fusion, Vol. 64, pp. 99-120DOI
6 
Yu D., Li H., Yang M., 2011, A Virtual Supply Airflow Rate Meter for Rooftop Air-Conditioning Units, Building and Environment, Vol. 46, pp. 1292-1302DOI
7 
Hong Y., Yoon S., Kim Y. S., Jang H., 2021, System-level Virtual Sensing Method in Building Energy Systems Using Autoencoder: Under the Limited Sensors and Operational Datasets, Applied Energy, Vol. 301, No. 117458DOI
8 
Yoon S., Choi Y., Koo J., Hong Y., Kim R., Kim J., 2020, Virtual Sensors for Estimating District Heating Energy Consumption under Sensor Absences in a Residential Building, Energies, Vol. 13, No. 6013DOI
9 
Choi Y., Yoon S., 2021, Autoencoder-driven Fault Detection and Diagnosis in Building Automation Systems: Residual-based and Latent Space-based Approaches, Building and Environment, Vol. 203, No. 108066DOI
10 
Zhao Y., Li T., Zhang X., Zhang C., 2019, Artificial Intelligence-based Fault Detection and Diagnosis Methods for Building Energy Systems: Advantages, Challenges and the Future, renewable and sustainable energy review, Vol. 109, pp. 85-101DOI
11 
Choi Y., Yoon S., Kim Y. S., 2021, A Study on System Heat Loss Monitoring Model in a Residential Building District Heating System Under the Limited Sensing Environment, Proceeding of SAREK 2021 Summer Annual Conference,, pp. 43-36Google Search
12 
Somu N., Sriram A., Kowli A., Ramamritham K., 2021, A Hybrid Deep Transfer Learning Strategy for Thermal Comfort Prediction in Buidings, Building and Environment, Vol. 24, No. 108133DOI
13 
Choi Y., Yoon S., 2020, Virtual Sensor-assisted in Situ Sensor Calibration in Operational HVAC Systems, Building and Environment, Vol. 181, No. 107079DOI