Development of a Low-Cost IOT Device Focused on Protection and Monitoring Compressors in Refrigeration and Air-Conditioning Applications

Nelson Sierra^1, and Felipe Gonzalez²

¹Department of Electrical and Electronics Engineering, National University of Colombia Bogota DC, Colombia

²Department of Mechanics and Mechatronics Engineering, National University of Colombia Bogota DC, Colombia

Cite this paper:
Nelson Sierra and Felipe Gonzalez. Development of a Low-Cost IOT Device Focused on Protection and Monitoring Compressors in Refrigeration and Air-Conditioning Applications. Journal of Embedded Systems. 2023; 6(1):1-8. doi: 10.12691/jes-6-1-1

Abstract

This project addresses the problem of correctly diagnosing compressors for air conditioning and refrigeration systems. The aim is to use readily available instrumentation from the global market to create a low-cost, accessible, and easy-to-assemble diagnostic solution for all types of users. In this work, we propose the use of an Espressif ESP32 controller, compatible with Arduino language, connected to Microsoft Azure. Additionally, we introduce algorithms based on trends that provide both basic and advanced users with real-time knowledge of relevant variables and detected failures in the refrigeration process. This enables users to anticipate and prevent failures through an enhanced condition-based maintenance scheme. The proposed solution aims to reduce incorrect diagnoses, minimize system downtime, and enhance troubleshooting capabilities, spare parts control, and product preservation. Furthermore, to expand the reach of this solution, the device can be utilized as an input for system data to generate valuable information for a recurrent neural network. This network can diagnose not only compressors but also the entire system, considering two significant variables: coefficient of performance and mass flow.

Keywords:
Data acquisition industrial internet of things IIOT refrigeration air conditioning compressors condition based maintenance diagnostics measurement Azure arduino esp32 artificial intelligence recurrent neural network

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	T. Birmpili, “Montreal protocol at 30: The governance structure, the evolution, and the kigali amendment,” Comptes Rendus Geoscience, vol. 350, no. 7, pp. 425-431, 2018.
[2]	U. N. E. Programme, “The kigali amendment to the montreal protocol: Hfc phase-down,” United Nations Environment Programme, Nairobi, Kenya, Tech. Rep., 2016. [Online]. Available: https://wedocs.unep.org/bitstream/handle/20.500.11822/25495/Kigali Amend eng.pdf.
[3]	A. Koons-Stapf, “Condition based maintenance: Theory, methodology, application,” 01 2015, pp. 1-35.
[4]	D. L. Pinzón Niño, “Panorama de aplicación de internet de las cosas (iot),” 2016.
[5]	A. A. Kader, “Increasing food availability by reducing postharvest losses of fresh produce,” in V International Postharvest Symposium 682, 2004, pp. 2169-2176.
[6]	T. Stuart, Waste: Uncovering the global food scandal. WW Norton & Company, 2009.
[7]	R. S. Rolle, “Improving postharvest management and marketing in the asia-pacific region: issues and challenges,” Postharvest management of fruit and vegetables in the Asia-Pacific region, vol. 1, no. 1, pp. 23–31, 2006.
[8]	J. Gustavsson, C. Cederberg, U. Sonesson, R. Van Otterdijk, and A. Meybeck, “Global food losses and food waste,” 2011.
[9]	Nelson Sierra, “Symbionte UN,” GitHub repository, 2022. [Online]. Available: {https://github.com/nasierras/Symbionte UN}
[10]	H. Air-Conditioning and R. Institute, “2020 standard for performance rating of positive displacement refrigerant compressors,” in AHRI Standard 540, march 2020, pp. 6-23.
[11]	J. Chaudhary and A. Mishra, “Detection of gas leakage and automatic alert system using arduino,” SSRN Electronic Journal, 01 2019.
[12]	“Mechanical vibration — measurement and evaluation of machine vibration — part 8: Reciprocating compressor systems,” International Organization for Standardization, Geneva, CH, Standard, Mar. 2018.
[13]	M. Corporation, “Arduino sdk cloud azure development for arduino,” https://github.com/Azure/azure-sdk-for-c-arduino, 2013.
[14]	S. Nan, “Thingesp cloud client library,” Sep 2021. [Online]. Available: https://github.com/SiddheshNan/ThingESP-Arduino-Library.
[15]	N. Tudoroiu, M. Zaheeruddin, E.-R. Tudoroiu, and V. Jeflea, “Fault detection and diagnosis (fdd) in heating ventilation air conditioning systems (hvac) using an interactive multiple model augmented unscented kalman filter (immaukf),” 2008 Conference on Human System Interactions, pp. 334–339, 2008.
[16]	National Electrical Manufacturers Association (NEMA), “Nema standards publication mg 1-2020: Motors and generators,” NEMA, Rosslyn, VA, Technical Report MG 1, 2020. [Online]. Available: https://www.nema.org/Standards/Pages/Motors-and-Generators.aspx.
[17]	J. Smith and M. Johnson, “Effects of voltage and current unbalance on the performance and efficiency of three-phase induction motors,” IEEE Transactions on Industry Applications, vol. 51, no. 2, pp. 987–996, 2015.
[18]	Z. Soltani, K. K. Sorensen, J. Leth, and J. D. Bendtsen, “Fault detection and diagnosis in refrigeration systems using machine learning algorithms,” International Journal of Refrigeration, vol. 144, pp. 34-45, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0140700722002997.
[19]	Y. Ust, “Performance analysis and optimization of irreversible air refrigeration cycles based on ecological coefficient of performance criterion,” Applied Thermal Engineering, vol. 29, no. 1, pp. 47-55, 2009.
[20]	H. Air-Conditioning and R. Institute, “2012 standard for performance rating of positive displacement carbon dioxide refrigerant compressors and compressor units,” in AHRI Standard 571, march 2012, pp. 6-23.
[21]	Y. Cengel and M. Boles, Thermodynamics: An Engineering Approach, ser. Cengel series in engineering thermal-fluid sciences. McGraw-Hill, 2011.
[22]	E. Winandy, C. Saavedra, and J. Lebrun, “Experimental analysis and simplified modelling of a hermetic scroll refrigeration compressor,” Applied thermal engineering, vol. 22, no. 2, pp. 107-120, 2002.
[23]	D. Adelekan, O. Ohunakin, and B. Paul, “Artificial intelligence models for refrigeration, air conditioning and heat pump systems,” Energy Reports, vol. 8, pp. 8451–8466, 2022.