Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems

Wang, Gang; Wang, Junke; Tiamiyu, Nurayn; Wang, Zufen; Song, Li

doi:10.3390/su151612113

Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems

Journal Article · Tue Aug 08 00:00:00 EDT 2023 · Sustainability (Basel)

DOI:https://doi.org/10.3390/su151612113· OSTI ID:1993935

^[1]; Wang, Junke ^[2]; Tiamiyu, Nurayn ^[3]; Wang, Zufen ^[4]; Song, Li ^[3]

University of Miami, Coral Gables, FL (United States); University of Miami
University of Oklahoma, Norman, OK (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
University of Oklahoma, Norman, OK (United States)
University of Miami, Coral Gables, FL (United States); Tennessee State University, Nashville, TN (United States)

An energy model that correlates fan airflow, head, speed, and system power input is essential to detect device faults and optimize control strategies in fan systems. Since the application of variable-frequency drives (VFDs) makes the motor-efficiency data published by manufacturers inapplicable for VFD–motor–fan systems, the fan efficiency and drive (belt–motor–VFD) efficiency must be identified for each individual system to obtain accurate energy models. The objectives of this paper are to identify an energy model of existing VFD–motor–fan systems using available experimental data and demonstrate its applications in loose belt fault detection and virtual airflow meter development for optimal control. First, an approach is developed to identify the fan head, fan efficiency, and drive-efficiency curves using available fan head, speed, and system power input as well as temporarily measured airflow rate without measuring shaft power. Then, the energy model is identified for an existing VFD–motor–fan system. Finally, the identified model is applied to detect the slipped belt faults and develop the virtual airflow meter. The experiment results reveal that the developed approach can effectively obtain the energy model of VFD–motor–fan systems and the model can be applied to effectively detect slipped belt faults and accurately calculate the fan airflow rate.

View Accepted Manuscript (DOE)

Research Organization:: University of Miami, Coral Gables, FL (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: EE0008683

OSTI ID:: 1993935

Journal Information:: Sustainability (Basel), Journal Name: Sustainability (Basel) Journal Issue: 16 Vol. 15; ISSN 2071-1050

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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Drive systems
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Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems

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