bldc

Brushless DC (BLDC) motors depend on accurate rotor position detection via Hall sensors for optimal performance. Faults, such as sensor displacement, can disrupt commutation and lead to efficiency losses. This study utilizes deep learning to detect Hall sensor faults, focusing on a meticulously prepared dataset designed for this purpose. The dataset study consists of phase current measurements under various Hall sensor displacement conditions, categorized as No Delay, 0.0001 Delay, 0.005 Delay, and 0.01 Delay.

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 This dataset is in support of my research paper '9-DoF Personal Robot Servant'.  

Preprint :

On this robot servant, my first work was done in the year 2011.

Image Source:  https://www.dreamstime.com/robot-tray-d-rendering-mini-holding-serving-i...

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1574 Views

This dataset is in support of my following Research papers  

Preprint  (Make sure you have read Caution) :

  • Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I* 

  https://doi.org/10.36227/techrxiv.19758517.v1

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2102 Views

This dataset is in support of my Research paper 'Design of 6-DoF Combat Quadcopter'.

Preprint:   

The system is basic, on existing designs.It is very simple for any graduate,degree holder.

 

Related Claim : Novel ß Non-Linear Theory

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1217 Views

 This dataset is in support of my research paper 'Comparative Control Loop Stability & Eigen Analysis of Transfer Functions in 7.5 Hp BLDC Sensorless SMO'.

Preprint :

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6966 Views