Data Analysis for Predictive Maintenance of Servo Motors

Vibration and temperature data of a servo motor are analyzed with PLC which is widely used in the industry. With this system, power supply can be detected on the servo motors. In this way, undesirable situations such as disruptions in production and productivity loss can be prevented from occurring....

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Main Authors: Oguz Girit, Gurcan Atakok, Sezgin Ersoy
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2020/8826802
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author Oguz Girit
Gurcan Atakok
Sezgin Ersoy
author_facet Oguz Girit
Gurcan Atakok
Sezgin Ersoy
author_sort Oguz Girit
collection DOAJ
description Vibration and temperature data of a servo motor are analyzed with PLC which is widely used in the industry. With this system, power supply can be detected on the servo motors. In this way, undesirable situations such as disruptions in production and productivity loss can be prevented from occurring. It is an important problem for businesses to detect malfunctions that may occur in servo motor dysfunction. Previously, methods such as ultrasonic sound measurements, thermal cameras, endoscopy equipment, and energy analysis have been used and discussed in the literature. Our study offers a PLC-based vibration and temperature measurement system designed as a solution of this problem. In this system, vibration and temperature measurements were made while the servo motor was kept running. These measurements were measured with or without load, considering the operating ranges of the servo motor, and the compatibility of the data was evaluated.
format Article
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institution Kabale University
issn 1070-9622
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language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Shock and Vibration
spelling doaj-art-98d0cade6fac41bd93d15b2b27469e0c2025-02-03T01:04:59ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/88268028826802Data Analysis for Predictive Maintenance of Servo MotorsOguz Girit0Gurcan Atakok1Sezgin Ersoy2Marmara University, Faculty of Technology, Department of Mechanical Engineering, Istanbul 34722, TurkeyMarmara University, Faculty of Technology, Department of Mechanical Engineering, Istanbul 34722, TurkeyMarmara University, Faculty of Technology, Department of Mechatronics Engineering, Istanbul 34722, TurkeyVibration and temperature data of a servo motor are analyzed with PLC which is widely used in the industry. With this system, power supply can be detected on the servo motors. In this way, undesirable situations such as disruptions in production and productivity loss can be prevented from occurring. It is an important problem for businesses to detect malfunctions that may occur in servo motor dysfunction. Previously, methods such as ultrasonic sound measurements, thermal cameras, endoscopy equipment, and energy analysis have been used and discussed in the literature. Our study offers a PLC-based vibration and temperature measurement system designed as a solution of this problem. In this system, vibration and temperature measurements were made while the servo motor was kept running. These measurements were measured with or without load, considering the operating ranges of the servo motor, and the compatibility of the data was evaluated.http://dx.doi.org/10.1155/2020/8826802
spellingShingle Oguz Girit
Gurcan Atakok
Sezgin Ersoy
Data Analysis for Predictive Maintenance of Servo Motors
Shock and Vibration
title Data Analysis for Predictive Maintenance of Servo Motors
title_full Data Analysis for Predictive Maintenance of Servo Motors
title_fullStr Data Analysis for Predictive Maintenance of Servo Motors
title_full_unstemmed Data Analysis for Predictive Maintenance of Servo Motors
title_short Data Analysis for Predictive Maintenance of Servo Motors
title_sort data analysis for predictive maintenance of servo motors
url http://dx.doi.org/10.1155/2020/8826802
work_keys_str_mv AT oguzgirit dataanalysisforpredictivemaintenanceofservomotors
AT gurcanatakok dataanalysisforpredictivemaintenanceofservomotors
AT sezginersoy dataanalysisforpredictivemaintenanceofservomotors