Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol

The breakdown in a machine created by a fault will greatly affect the plant operation. The frame work of fault diagnosis of machines using machine learning techniques is an established area. Here, the fault diagnosis system is implemented with the help of wireless sensor networks (WSN). Each machine...

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Main Authors: Indhu Ramalingam, R. A. Sankaran
Format: Article
Language:English
Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2018-01-01
Series:Tehnički Vjesnik
Subjects:
Online Access:https://hrcak.srce.hr/file/298267
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spelling doaj-28a806ba55304700a422650048c81c042020-11-25T00:25:39ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek Tehnički Vjesnik1330-36511848-63392018-01-01253759765Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH ProtocolIndhu Ramalingam0R. A. Sankaran1Salem College of Engineering and Technology, NH-68, Salem-Attur Main Road, Mettupatty, Perumapalayam, Selliamman, Nagar, Salem, Tamil Nadu 636111, IndiaSalem College of Engineering and Technology, NH-68, Salem-Attur Main Road, Mettupatty, Perumapalayam, Selliamman, Nagar, Salem, Tamil Nadu 636111, IndiaThe breakdown in a machine created by a fault will greatly affect the plant operation. The frame work of fault diagnosis of machines using machine learning techniques is an established area. Here, the fault diagnosis system is implemented with the help of wireless sensor networks (WSN). Each machine in the plant is fitted with sensors (node) from which the fault diagnosis is carried out. The signals/messages from each node are transmitted to a base station, which acts as a central control unit for the entire plant. Fault diagnosis using WSN in a factory setup has few challenges. The major issue in WSN is the life time of the nodes, as they are situated far away from base station in many plants like thermal power plant, refinery, and petroleum industries. To address the life time of the nodes many researchers have developed many protocols like LEACH, SEP, ERP, HCR, HEED, and PEGASIS. The plants need customisation in terms of choosing suitable algorithms and choosing location of the base station within the plant for better life time of the nodes. This paper presents results of both experimental and simulation studies of a typical plant, where the vibration signals from each machine are acquired and through machine learning techniques the fault diagnosis is performed with the help of wireless sensor networks. For illustrative purpose, a well reported bearing fault diagnosis data set is taken up and fault diagnosis case study was performed from wireless sensor networks point of view (experimental study). Here, at every stage, the computational time is taken as a primary concern which affects the life time of the sensor nodes. Then, the WSN of 18 sensor nodes representing 18 machines with LEACH protocol is simulated in Matlab© to study the life time characteristics of each node while keeping base station at different locations. The life time of different nodes is heavily dependent on the location of the base station. Finding the right location of the base station for a given plant is another contribution of this work.https://hrcak.srce.hr/file/298267fault diagnosislife time maximizationmachine learningwireless sensor networks
collection DOAJ
language English
format Article
sources DOAJ
author Indhu Ramalingam
R. A. Sankaran
spellingShingle Indhu Ramalingam
R. A. Sankaran
Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
Tehnički Vjesnik
fault diagnosis
life time maximization
machine learning
wireless sensor networks
author_facet Indhu Ramalingam
R. A. Sankaran
author_sort Indhu Ramalingam
title Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
title_short Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
title_full Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
title_fullStr Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
title_full_unstemmed Lifetime Maximization of Wireless Sensor Networks for a Fault Diagnosis System Using LEACH Protocol
title_sort lifetime maximization of wireless sensor networks for a fault diagnosis system using leach protocol
publisher Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
series Tehnički Vjesnik
issn 1330-3651
1848-6339
publishDate 2018-01-01
description The breakdown in a machine created by a fault will greatly affect the plant operation. The frame work of fault diagnosis of machines using machine learning techniques is an established area. Here, the fault diagnosis system is implemented with the help of wireless sensor networks (WSN). Each machine in the plant is fitted with sensors (node) from which the fault diagnosis is carried out. The signals/messages from each node are transmitted to a base station, which acts as a central control unit for the entire plant. Fault diagnosis using WSN in a factory setup has few challenges. The major issue in WSN is the life time of the nodes, as they are situated far away from base station in many plants like thermal power plant, refinery, and petroleum industries. To address the life time of the nodes many researchers have developed many protocols like LEACH, SEP, ERP, HCR, HEED, and PEGASIS. The plants need customisation in terms of choosing suitable algorithms and choosing location of the base station within the plant for better life time of the nodes. This paper presents results of both experimental and simulation studies of a typical plant, where the vibration signals from each machine are acquired and through machine learning techniques the fault diagnosis is performed with the help of wireless sensor networks. For illustrative purpose, a well reported bearing fault diagnosis data set is taken up and fault diagnosis case study was performed from wireless sensor networks point of view (experimental study). Here, at every stage, the computational time is taken as a primary concern which affects the life time of the sensor nodes. Then, the WSN of 18 sensor nodes representing 18 machines with LEACH protocol is simulated in Matlab© to study the life time characteristics of each node while keeping base station at different locations. The life time of different nodes is heavily dependent on the location of the base station. Finding the right location of the base station for a given plant is another contribution of this work.
topic fault diagnosis
life time maximization
machine learning
wireless sensor networks
url https://hrcak.srce.hr/file/298267
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