K. Aditya Anirudh (adityaanirudhk)

adityaanirudhk

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K. Aditya Anirudh's repositories

Aditya-Robotics-

Python sample codes for robotics algorithms.

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Design-of-Axial-and-Radial-Active-Magnetic-Bearing-for-High-Speed-Epoxy-Granite-Micromilling-Machine

This project addresses issues with current CNC micromilling machine bearings, limiting spindle speed to 20,000 rpm due to friction. Conventional bearings cause thermal complications and tool chatter, disrupting precision machining for tolerances under 5 micrometers. Axial and Radial Magnetic Bearings (AMB) aim to reduce friction.

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Fault-Diagnosis-for-Mobile-Robots

Fault diagnosis for mobile robot using ROS2 and Machine learning.

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Fault-Diagnosis-In-Stator-Windings-Of-A-Three-Phase-Induction-Motor-Using-Machine-Learning-Technique

First of all we have collected data and exported in data sheet.we have collected the data for healthy, unbalance, Faulty(stator winding) motor by doing an experiment and all of the data has been collected by YOKOGOWA power analyser. The collected data is stator current of three phases.For making the anaysis simplier we have converted the all 3 phase data into a single one by doing park's vector method. For ML Algorithms we need to select some of the feature We have done Feature extraction(33 feature) from PVM and PVAC . We have trained and tasted the model choosen classifier by giving 75% data for traning and we have used 25% data for testing out of180 sample. Then choose the best classifier and the best classifier that we get is K-Nearest Neighbour. After selecting the best model we have to tune the parameter of KNN model so that we get best accuracy. After fitting test data into the model we get accuracy of 91.1% and we can see the confusion matrix that shows how well the model classified the different fault (Healthy(0), Unbalance(1), Stator fault(2)) of motor . Out of 15 healthy test data all 15 are predicted in heathy class, out of 15 unbalance data 13 samples are classified in unbalance class and other 2 are misclassified in faulty case, out of 15 stator fault data 13 samples are classified in fault class and other 2 are misclassified in unbalance case.

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MATLAB-Robotics

Robotics Toolbox for MATLAB

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Predictive-Modeling-of-Combined-Cycle-Power-Plant-Energy-Output-using-Linear-Regression

Environmental factors significantly impact power plant energy output, enabling cost-efficient, collaborative production through accurate predictions. This project uses Linear Regression to predict energy output at a Combined Cycle Power Plant, analyzing temperature, pressure, vacuum, and humidity.

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ROBOTICS-PROJECT

Write the code for the line tracing robot in python. Deadline:12/05/2022

Weed-Management-Rover

Designed a simple 3D model of Weed Management Rover in SolidWorks with a 5-DOF UR5 manipulator attached to its body, and spawned and controlled the robot in ROS using appropriated controllers.

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Design-and-Development-of-Damped-Boring-Bar-using-Cellular-Solids

Design and develop a high-damped cellular structure boring bar to enhance machining performance by eliminating vibrations and improving dynamic stability.

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Driver-monitoring-system-for-automobile-using-machine-learning-and-OpenCV

The following project can be used to monitor the driver continuously for fatigue and the case of exhaustion and that of falling asleep. In such a case when the computer finds that the driver is sleeping the computer will trigger an alarm automatically, and the alarm will only stop on killing the process/stopping the car.

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IoT-Automotive-Tuning-Diagnostics-Analytics

Introducing IoT Automotive Tuning, Diagnostics & Analytics, a cutting-edge GitHub repository that revolutionizes the way we interact with our vehicles in the connected world. Imagine the power to disable that pesky Check Engine Light, remotely install firmware updates, receive alerts for overdue maintenance, or even start your car from your alarm c

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pybotics

The Python Toolbox for Robotics

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Steel-Plate-Fault-Diagnosis-Using-Classification-Models

The objective of the project is to classify steel plates fault into 7 different types. The end goal is to train several machine Learning Algorithms for automatic pattern recognition.

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High-Damping-Epoxy-Granite-Micro-Milling-Machine-Development

Development of an Epoxy Granite Micro-Milling Machine for Enhanced Thermal Stability and Machining Performance.

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