A novel defrosting control strategy with image processing technique and fractal theory

Miao, Hongfei; Yang, Xueqing; Yin, Dazhen; Zheng, Wandong; Zhang, Huan; Zhang, Sirui; Liu, Zijian

doi:10.1016/j.ijrefrig.2022.03.002

Cited by 11 publications

(2 citation statements)

References 43 publications

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“…Compared with the traditional methods, the proposed temperature and humidity image defrosting control strategy effectively avoided delayed defrosting and unnecessary defrosting. Meanwhile, the defrosting energy consumption was reduced by 10.6% and 22.3%, respectively [40].…”

Section: Application Status Of MV Inmentioning

confidence: 99%

Review on the Application of Machine Vision in Defrosting and Decondensation on the Surface of Heat Exchanger

et al. 2022

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Under low outdoor temperature and high humidity, frost easily forms on the Heat Exchanger (Exchanger) surface on the outdoor side. The formation and growth of this frost layer will seriously impact the Exchanger’s heat extraction process and the system’s energy efficiency, triggering malfunction in the compressor. To this end, this work first analyzes the formation and growth mechanism of Exchanger surface frosting and condensation. It then summarizes the current research status of Machine Vision (MV) technology in defrosting and decondensation. Further, it previews the follow-up research direction. The experimental findings show that MV technology can automatically observe frost and dew, guaranteeing a real-time understanding of the frost layer. Directly obtaining the frost and dew information from the image can significantly save human resources and improve efficiency.

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Section: Application Status Of MV Inmentioning

confidence: 99%

Review on the Application of Machine Vision in Defrosting and Decondensation on the Surface of Heat Exchanger

et al. 2022

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“…The T-H-I method's defrost start-stop control information is more accurate and significantly reduces the false defrost phenomenon. Miao et al [259] improved the T-H-I method for the characterization of the frost degree in terms of thickness and structure. According to the experimental results, defrosting was performed at a frost thickness of 0.726 mm and a fractal dimension of 2.839, and the optimal state point was terminated when the fractal dimension was reduced to 2.324.…”

Section: Heat Pump Surface Frosting Phenomenon Monitoringmentioning

confidence: 99%

Computer Vision Technology for Monitoring of Indoor and Outdoor Environments and HVAC Equipment: A Review

Yang

Zhu

et al. 2023

Sensors

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Artificial intelligence technologies such as computer vision (CV), machine learning, Internet of Things (IoT), and robotics have advanced rapidly in recent years. The new technologies provide non-contact measurements in three areas: indoor environmental monitoring, outdoor environ-mental monitoring, and equipment monitoring. This paper summarizes the specific applications of non-contact measurement based on infrared images and visible images in the areas of personnel skin temperature, position posture, the urban physical environment, building construction safety, and equipment operation status. At the same time, the challenges and opportunities associated with the application of CV technology are anticipated.

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Deep learning-based image recognition method for on-demand defrosting control to save energy in commercial energy systems

Chen

Zhu

et al. 2022

Applied Energy

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A novel defrosting control strategy with image processing technique and fractal theory

Cited by 11 publications

References 43 publications

Review on the Application of Machine Vision in Defrosting and Decondensation on the Surface of Heat Exchanger

Review on the Application of Machine Vision in Defrosting and Decondensation on the Surface of Heat Exchanger

Computer Vision Technology for Monitoring of Indoor and Outdoor Environments and HVAC Equipment: A Review

Deep learning-based image recognition method for on-demand defrosting control to save energy in commercial energy systems

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