Fault Diagnosis in Wireless Sensor Networks Using a Neural Network Constructed by Deep Learning Technique

2020 ◽  
pp. 77-101
Author(s):  
Meenakshi Panda ◽  
Bhabani Sankar Gouda ◽  
Trilochan Panigrahi
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Deep Learning ◽  
Sensor Networks ◽  
Fault Diagnosis ◽  
Wireless Sensor ◽  
Learning Technique

scholarly journals Deep-Learning-Based Physical Layer Authentication for Industrial Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2440 ◽  
Author(s):  
Run-Fa Liao ◽  
Hong Wen ◽  
Jinsong Wu ◽  
Fei Pan ◽  
Aidong Xu ◽  
...  
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Deep Learning ◽  
Sensor Networks ◽  
Software Radio ◽  
Sensor Nodes ◽  
Gradient Algorithm ◽  
Wireless Sensor ◽  
Industrial Wireless Sensor Networks ◽  
Phy Layer

In this paper, a deep learning (DL)-based physical (PHY) layer authentication framework is proposed to enhance the security of industrial wireless sensor networks (IWSNs). Three algorithms, the deep neural network (DNN)-based sensor nodes’ authentication method, the convolutional neural network (CNN)-based sensor nodes’ authentication method, and the convolution preprocessing neural network (CPNN)-based sensor nodes’ authentication method, have been adopted to implement the PHY-layer authentication in IWSNs. Among them, the improved CPNN-based algorithm requires few computing resources and has extremely low latency, which enable a lightweight multi-node PHY-layer authentication. The adaptive moment estimation (Adam) accelerated gradient algorithm and minibatch skill are used to accelerate the training of the neural networks. Simulations are performed to evaluate the performance of each algorithm and a brief analysis of the application scenarios for each algorithm is discussed. Moreover, the experiments have been performed with universal software radio peripherals (USRPs) to evaluate the authentication performance of the proposed algorithms. Due to the trainings being performed on the edge sides, the proposed method can implement a lightweight authentication for the sensor nodes under the edge computing (EC) system in IWSNs.

scholarly journals Fault diagnosis of wind turbine bearing using wireless sensor networks

2017 ◽  
Vol 21 (suppl. 2) ◽  
pp. 523-531 ◽  
Author(s):  
Indhu Ramalingam ◽  
Sankaran Annamalai ◽  
Sugumaran Vaithiyanathan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wireless Sensor ◽  
Turbine Bearing
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