Skip to content

Implementing Deep Neural Network Binary Classification Algorithm for AMR Reley Differential Curve

Notifications You must be signed in to change notification settings

taherfattahi/dnn-amr-reley-differential-curve

Repository files navigation

Machine Learning AMR Reley Differential Curve

Implementing Deep Neural Network Binary Classification Algorithm for AMR Reley Differential Curve.

A novel approach to the implementation differential protection scheme by using a Deep Neural Network Dataset has been obtained from Differential Characteristic plane in the Vebko AMPro software.

Features

  • Using Python Tensorflow to build a Deep Neural Network model
  • Converting the Tensorflow model to tflite for running on Embedded Board ARM Architecture
  • Using Golang TFLite to be able to easily run tflite model
  • Running on Xilinx Zynq-7020 Embedded Board
  • Usable via Docker file

Installation

First you need install TensorFlow for C

  1. Install bazel
curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -
echo "deb [arch=amd64] https://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
sudo apt update && sudo apt install bazel
sudo apt install openjdk-11-jdk
  1. Build tensorflowlite c lib from source
cd ~/workspace
git clone https://github.com/tensorflow/tensorflow.git && cd tensorflow
./configure
bazel build --config opt --config monolithic --define tflite_with_xnnpack=false //tensorflow/lite:libtensorflowlite.so
bazel build --config opt --config monolithic --define tflite_with_xnnpack=false //tensorflow/lite/c:libtensorflowlite_c.so

# Check status
file bazel-bin/tensorflow/lite/c/libtensorflowlite_c.so
# ELF 64-bit LSB shared object, x86-64
  1. Build go-tflite
export CGO_LDFLAGS=-L$HOME/workspace/tensorflow/bazel-bin/tensorflow/lite/c
export CGO_CFLAGS=-I$HOME/workspace/tensorflow/

Build

For Linux/MacOs amd64:

  export CGO_LDFLAGS=-L$HOME/workspace/tensorflow/bazel-bin/tensorflow/lite/c

  go build main.go

For xilinx Zynq-7020 (ARM-based computers):

  sudo apt-get install gcc-arm-linux-gnueabihf
  
  export CGO_LDFLAGS=-L$HOME/workspace/tensorflow/bazel-bin/tensorflow/lite/c
  
  CGO_ENABLED=1 GOOS=linux GOARCH=arm CC=arm-linux-gnueabihf-gcc go build -o main

Running

This running for ubuntu/MacOs amd64:

  ./main

This running for xilinx Zynq-7020 (ARM-based computers):

  export LD_LIBRARY_PATH=./arm
  
  ./main

Running with Docker

First of all, clone and the repo then run

  docker build -t dnn .

After pulling and building the image, You can get the result like this

  docker run --rm -t amr ./main

Or you can go to the container for running it manually like this

  docker run -it amr

More Info

Differential Characteristic in the AMPro software

Graph

Graph of the Deep Neural Network

Graph

Model Accuracy Plot

Graph

Model Loss Plot

Graph

Note:

If you had issue and got standard_init_linux.go:211: exec user process caused "exec format error error, try this solution.

Collaborators

License

MIT

About

Implementing Deep Neural Network Binary Classification Algorithm for AMR Reley Differential Curve

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published