Analysis of fault diagnosis of DC motors by power consumption pattern recognition

Early detection of faults in DC motors extends their life and lowers their power usage. There are a variety of traditional and soft computing techniques for detecting faults in DC motors. Many diagnostic techniques have been developed in the past to detect such fault-related patterns. These methods...

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Autores principales:	Hasan Shakir Majdi, Sameera Sadey Shijer, Abduljabbar Owaid Hanfesh, Laith Jaafer Habeeb, Ahmad H. Sabry
Formato:	article
Lenguaje:	EN RU UK
Publicado:	PC Technology Center 2021
Materias:	monitoring dc servomotor power consumption pattern recognition power profile mechanical faults Technology (General) T1-995 Industry HD2321-4730.9
Acceso en línea:	https://doaj.org/article/5c585ebea0ac4fd48fbc63e9a894ec2b
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id	oai:doaj.org-article:5c585ebea0ac4fd48fbc63e9a894ec2b
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spelling	oai:doaj.org-article:5c585ebea0ac4fd48fbc63e9a894ec2b2021-11-08T08:04:06ZAnalysis of fault diagnosis of DC motors by power consumption pattern recognition1729-37741729-406110.15587/1729-4061.2021.240262https://doaj.org/article/5c585ebea0ac4fd48fbc63e9a894ec2b2021-10-01T00:00:00Zhttp://journals.uran.ua/eejet/article/view/240262https://doaj.org/toc/1729-3774https://doaj.org/toc/1729-4061Early detection of faults in DC motors extends their life and lowers their power usage. There are a variety of traditional and soft computing techniques for detecting faults in DC motors. Many diagnostic techniques have been developed in the past to detect such fault-related patterns. These methods for detecting the aforementioned potential failures of motors can be utilized in a variety of scientific and technological domains. Motor Power Pattern Analysis (MPPA) is a technology that analyzes the current and voltage provided to an electric motor using particular patterns and protocols to assess the operational status of the motors without disrupting production. Engineers and researchers, particularly in industries, face a difficult challenge in monitoring spinning types of equipment. In this work, we are going to explain how to use the motor power pattern/signature analysis (MPPA) of a power signal driving a servo to find mechanical defects in a gear train. A hardware setup is used to simplify the demonstration of obtaining spectral metrics from the power consumption signals. A DC motor, a set of metal or nylon drive gears, and a control circuit are employed. The speed control circuit was eliminated to allow direct monitoring of the DC motor's current profiles. Infrared (IR) photo-interrupters with a 35 mm diameter, eight-holed, standard servo wheel were employed to gather the tachometer signal at the servo's output. The mean value of the measurements was 318 V for the healthy profile, while it was 330 V for the faulty gears power data. The proposed power consumption profile analysis approach succeeds to recognize the mechanical faults in the gear-box of a DC servomotor via examining the mean level of the power consumption pattern as well as the extraction of the Power Spectral Density (PSD) through comparing faulty and healthy profilesHasan Shakir MajdiSameera Sadey ShijerAbduljabbar Owaid HanfeshLaith Jaafer HabeebAhmad H. SabryPC Technology Centerarticlemonitoringdc servomotorpower consumptionpattern recognitionpower profilemechanical faultsTechnology (General)T1-995IndustryHD2321-4730.9ENRUUKEastern-European Journal of Enterprise Technologies, Vol 5, Iss 5 (113), Pp 14-20 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU UK
topic	monitoring dc servomotor power consumption pattern recognition power profile mechanical faults Technology (General) T1-995 Industry HD2321-4730.9
spellingShingle	monitoring dc servomotor power consumption pattern recognition power profile mechanical faults Technology (General) T1-995 Industry HD2321-4730.9 Hasan Shakir Majdi Sameera Sadey Shijer Abduljabbar Owaid Hanfesh Laith Jaafer Habeeb Ahmad H. Sabry Analysis of fault diagnosis of DC motors by power consumption pattern recognition
description	Early detection of faults in DC motors extends their life and lowers their power usage. There are a variety of traditional and soft computing techniques for detecting faults in DC motors. Many diagnostic techniques have been developed in the past to detect such fault-related patterns. These methods for detecting the aforementioned potential failures of motors can be utilized in a variety of scientific and technological domains. Motor Power Pattern Analysis (MPPA) is a technology that analyzes the current and voltage provided to an electric motor using particular patterns and protocols to assess the operational status of the motors without disrupting production. Engineers and researchers, particularly in industries, face a difficult challenge in monitoring spinning types of equipment. In this work, we are going to explain how to use the motor power pattern/signature analysis (MPPA) of a power signal driving a servo to find mechanical defects in a gear train. A hardware setup is used to simplify the demonstration of obtaining spectral metrics from the power consumption signals. A DC motor, a set of metal or nylon drive gears, and a control circuit are employed. The speed control circuit was eliminated to allow direct monitoring of the DC motor's current profiles. Infrared (IR) photo-interrupters with a 35 mm diameter, eight-holed, standard servo wheel were employed to gather the tachometer signal at the servo's output. The mean value of the measurements was 318 V for the healthy profile, while it was 330 V for the faulty gears power data. The proposed power consumption profile analysis approach succeeds to recognize the mechanical faults in the gear-box of a DC servomotor via examining the mean level of the power consumption pattern as well as the extraction of the Power Spectral Density (PSD) through comparing faulty and healthy profiles
format	article
author	Hasan Shakir Majdi Sameera Sadey Shijer Abduljabbar Owaid Hanfesh Laith Jaafer Habeeb Ahmad H. Sabry
author_facet	Hasan Shakir Majdi Sameera Sadey Shijer Abduljabbar Owaid Hanfesh Laith Jaafer Habeeb Ahmad H. Sabry
author_sort	Hasan Shakir Majdi
title	Analysis of fault diagnosis of DC motors by power consumption pattern recognition
title_short	Analysis of fault diagnosis of DC motors by power consumption pattern recognition
title_full	Analysis of fault diagnosis of DC motors by power consumption pattern recognition
title_fullStr	Analysis of fault diagnosis of DC motors by power consumption pattern recognition
title_full_unstemmed	Analysis of fault diagnosis of DC motors by power consumption pattern recognition
title_sort	analysis of fault diagnosis of dc motors by power consumption pattern recognition
publisher	PC Technology Center
publishDate	2021
url	https://doaj.org/article/5c585ebea0ac4fd48fbc63e9a894ec2b
work_keys_str_mv	AT hasanshakirmajdi analysisoffaultdiagnosisofdcmotorsbypowerconsumptionpatternrecognition AT sameerasadeyshijer analysisoffaultdiagnosisofdcmotorsbypowerconsumptionpatternrecognition AT abduljabbarowaidhanfesh analysisoffaultdiagnosisofdcmotorsbypowerconsumptionpatternrecognition AT laithjaaferhabeeb analysisoffaultdiagnosisofdcmotorsbypowerconsumptionpatternrecognition AT ahmadhsabry analysisoffaultdiagnosisofdcmotorsbypowerconsumptionpatternrecognition
_version_	1718442811999649792

Analysis of fault diagnosis of DC motors by power consumption pattern recognition

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