Multi-surface Permanent Magnet Synchronous Motor Temperature Estimation based on Automate Machine Learning Approach

Yutthanawa, Anurak; Wanthong, Sobree; Inthakheeree, Kamolthip; San-Um, Wimol

doi:10.1109/icbir57571.2023.10147678

2023 8th International Conference on Business and Industrial Research (ICBIR) 2023

DOI: 10.1109/icbir57571.2023.10147678

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Multi-surface Permanent Magnet Synchronous Motor Temperature Estimation based on Automate Machine Learning Approach

Anurak Yutthanawa,

Sobree Wanthong,

Kamolthip Inthakheeree

et al.

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Cited by 2 publications

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How Automated Machine Learning Can Improve Business

Rosário,

Boechat

2024

Applied Sciences

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Automated Machine Learning (AutoML) is revolutionizing how businesses utilize data, but there seems to be a lack of clarity and a holistic view regarding all its advantages, especially concerning the benefits of AutoML for companies. In order to deeply understand how AutoML can improve businesses, a systematic review examined the bibliometric literature of this field, analyzing 74 academic and scientific documents from the Scopus database. Results showed that AutoML (i) reduces the time and resources needed to develop and deploy machine learning models, (ii) accelerates decision-making and enables quicker responses to market changes, (iii) empowers businesses to build accurate predictive models using sophisticated algorithms, (iv) optimizing model performance for reliable insights and better outcomes, and (v) enhances accessibility by reducing technical barriers and democratizing innovation. As businesses grow, AutoML scales to handle larger datasets and more complex problems without extensive manual intervention. In sum, AutoML enhances efficiency, accuracy, and scalability, becoming a crucial driver of business innovation and success.

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How Automated Machine Learning Can Improve Business

Rosário,

Boechat

2024

Applied Sciences

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Simulation Modeling and Temperature Over-Advance Perception of Mine Hoist System Based on Digital Twin Technology

Liang,

Wu,

Ruan

2023

Machines

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The temperature prediction of hoist motor is one of the effective ways to ensure the safe production of mine hoist. Digital twin technology is a technology that combines the physical system of the real world with the digital model of the virtual world. Through digital twin technology, the physical system in the real world can be monitored and simulated in a virtual environment, and the state information of these systems can be monitored in real time. Recurrent neural network is a kind of neural network suitable for processing sequence data, which can automatically extract and learn the feature information in sequential data. To achieve online monitoring and over-advance perception of the temperature of the mine hoist motor, a temperature prediction and advance sensing method based on digital twins and recurrent neural network is proposed. To begin with, a high-fidelity digital twin monitoring system for mine hoists is constructed, enabling the acquisition of real-time temperature data. These temperature data are then fed into a neural network for feature extraction and precise prediction of the motor’s state. Subsequently, based on the temperature prediction module in the digital twin hoist monitoring system, a user interface (UI) is developed, and a fully functional digital twin temperature monitoring system is built and experimentally validated. The experimental results demonstrate that the digital twin system effectively monitors the real-time temperature state of the motor during the operation of the mine hoist. Furthermore, the integration of digital twin and recurrent neural network enables the accurate prediction and proactive detection of temperature variations in the motor of the mine hoist. This innovative approach introduces a novel perspective for implementing predictive maintenance in the mining industry, enhancing the safety and reliability of mine hoists. Additionally, it offers valuable technical support in improving maintenance efficiency and reducing associated costs.

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Multi-surface Permanent Magnet Synchronous Motor Temperature Estimation based on Automate Machine Learning Approach

Cited by 2 publications

References 6 publications

How Automated Machine Learning Can Improve Business

How Automated Machine Learning Can Improve Business

Simulation Modeling and Temperature Over-Advance Perception of Mine Hoist System Based on Digital Twin Technology

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