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Machinery Assessment Device - A Deep Learning Approach

Shriram KV

Shriram KV

Bengaluru, Karnataka

9 0

In many industries, with the course of time, efficiency of the machines decreases and maintenance has to be done to make it into normal functioning. With our approach, the deep learning techniques shall enable predicting faults before it occurs for that machinery. ...learn more

Project status: Published/In Market

Internet of Things, Artificial Intelligence

Intel Technologies
Intel Python, OpenVINO

Links [1]

Overview / Usage

•In many industries, with the course of time, efficiency of the machines decreases and maintenance has to be done to make it into normal functioning.

•But, many times the maintenance is done only after we notice any fault in the machine due to which the machine lifetime decreases as it is being run in a bad stage for a long time without service being done on it.

•So, we propose a system which can continuously monitor the efficiency of machine only with a gyro sensor.

We also use Deep Learning Techniques to train the movements of the machine. Based on the training, our system can track the motions and predict quickly in case of a deviation being found. Currently we have got the up/down and Pendulum motion captured / trained.

Methodology / Approach

  1. Gyro Sensor

  2. Real time data capture

  3. Deep learning with OpenVino

  4. Diagnose faults.

Technologies Used

  1. OpenVino

  2. Sensors

  3. Data Analytics

  4. Python

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