MOTOR ABNORMALITY DETECTION SYSTEM BASED ON DEEP LEARNING

The present invention relates to a deep learning based motor abnormality detection system and a method thereof. The system comprises an abnormality detection server which outputs whether or not each motor is abnormal based on vibration data of each motor collected from vibration sensors respectively...

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Hauptverfasser: LIM BYUNG KUL, SEONG TAE JIN, KANG JAE WOO, LEE JEONG JOO
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Sprache:eng ; kor
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creator LIM BYUNG KUL
SEONG TAE JIN
KANG JAE WOO
LEE JEONG JOO
description The present invention relates to a deep learning based motor abnormality detection system and a method thereof. The system comprises an abnormality detection server which outputs whether or not each motor is abnormal based on vibration data of each motor collected from vibration sensors respectively disposed in the at least one or more motors. The abnormality detection server includes a memory in which an abnormality detection program is stored and a processor executing the abnormality detection program. The abnormality detection program uses a machine learning model machine-learned based on the vibration data of each motor, and inputs the vibration data input for each motor to the machine learning model so as to output whether or not an abnormality has occurred in each motor and the cause of the abnormality. According to the present invention, specific inference about the cause of the abnormality is also possible. 본 발명은 딥러닝 기반의 모터 이상 감지 시스템 및 그 방법에 관한 것으로서, 적어도 하나 이상의 모터에 각각 배치된 진동 센서로부터 수집된 각 모터의 진동데이터에 기반하여, 각 모터의 이상 여부를 출력하는 이상 감지 서버를 포함하되, 상기 이상 감지 서버는, 이상 감지 프로그램이 저장된 메모리 및 상기 이상 감지 프로그램을 실행하는 프로세서를 포함하고, 상기 이상 감지 프로그램은, 상기 각 모터의 진동데이터를 기초로 기계학습된 기계학습모델을 이용하여, 각 모터별로 입력된 진동데이터를 상기 기계학습모델에 입력하여, 각 모터의 이상 발생 여부 및 이상 원인을 출력하는 시스템에 관한 것이다.
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The system comprises an abnormality detection server which outputs whether or not each motor is abnormal based on vibration data of each motor collected from vibration sensors respectively disposed in the at least one or more motors. The abnormality detection server includes a memory in which an abnormality detection program is stored and a processor executing the abnormality detection program. The abnormality detection program uses a machine learning model machine-learned based on the vibration data of each motor, and inputs the vibration data input for each motor to the machine learning model so as to output whether or not an abnormality has occurred in each motor and the cause of the abnormality. According to the present invention, specific inference about the cause of the abnormality is also possible. 본 발명은 딥러닝 기반의 모터 이상 감지 시스템 및 그 방법에 관한 것으로서, 적어도 하나 이상의 모터에 각각 배치된 진동 센서로부터 수집된 각 모터의 진동데이터에 기반하여, 각 모터의 이상 여부를 출력하는 이상 감지 서버를 포함하되, 상기 이상 감지 서버는, 이상 감지 프로그램이 저장된 메모리 및 상기 이상 감지 프로그램을 실행하는 프로세서를 포함하고, 상기 이상 감지 프로그램은, 상기 각 모터의 진동데이터를 기초로 기계학습된 기계학습모델을 이용하여, 각 모터별로 입력된 진동데이터를 상기 기계학습모델에 입력하여, 각 모터의 이상 발생 여부 및 이상 원인을 출력하는 시스템에 관한 것이다.</description><language>eng ; kor</language><subject>ALARM SYSTEMS ; CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES ; MEASURING ; ORDER TELEGRAPHS ; PHYSICS ; SIGNALLING ; SIGNALLING OR CALLING SYSTEMS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR ; TESTING</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20221025&amp;DB=EPODOC&amp;CC=KR&amp;NR=102458080B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,781,886,25566,76549</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20221025&amp;DB=EPODOC&amp;CC=KR&amp;NR=102458080B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LIM BYUNG KUL</creatorcontrib><creatorcontrib>SEONG TAE JIN</creatorcontrib><creatorcontrib>KANG JAE WOO</creatorcontrib><creatorcontrib>LEE JEONG JOO</creatorcontrib><title>MOTOR ABNORMALITY DETECTION SYSTEM BASED ON DEEP LEARNING</title><description>The present invention relates to a deep learning based motor abnormality detection system and a method thereof. The system comprises an abnormality detection server which outputs whether or not each motor is abnormal based on vibration data of each motor collected from vibration sensors respectively disposed in the at least one or more motors. The abnormality detection server includes a memory in which an abnormality detection program is stored and a processor executing the abnormality detection program. The abnormality detection program uses a machine learning model machine-learned based on the vibration data of each motor, and inputs the vibration data input for each motor to the machine learning model so as to output whether or not an abnormality has occurred in each motor and the cause of the abnormality. According to the present invention, specific inference about the cause of the abnormality is also possible. 본 발명은 딥러닝 기반의 모터 이상 감지 시스템 및 그 방법에 관한 것으로서, 적어도 하나 이상의 모터에 각각 배치된 진동 센서로부터 수집된 각 모터의 진동데이터에 기반하여, 각 모터의 이상 여부를 출력하는 이상 감지 서버를 포함하되, 상기 이상 감지 서버는, 이상 감지 프로그램이 저장된 메모리 및 상기 이상 감지 프로그램을 실행하는 프로세서를 포함하고, 상기 이상 감지 프로그램은, 상기 각 모터의 진동데이터를 기초로 기계학습된 기계학습모델을 이용하여, 각 모터별로 입력된 진동데이터를 상기 기계학습모델에 입력하여, 각 모터의 이상 발생 여부 및 이상 원인을 출력하는 시스템에 관한 것이다.</description><subject>ALARM SYSTEMS</subject><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES</subject><subject>MEASURING</subject><subject>ORDER TELEGRAPHS</subject><subject>PHYSICS</subject><subject>SIGNALLING</subject><subject>SIGNALLING OR CALLING SYSTEMS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLD09Q_xD1JwdPLzD_J19PEMiVRwcQ1xdQ7x9PdTCI4MDnH1VXByDHZ1UQDyXVxdAxR8XB2D_Dz93HkYWNMSc4pTeaE0N4Oym2uIs4duakF-fGpxQWJyal5qSbx3kKGBkYmphYGFgZOToTFxqgA50Cm9</recordid><startdate>20221025</startdate><enddate>20221025</enddate><creator>LIM BYUNG KUL</creator><creator>SEONG TAE JIN</creator><creator>KANG JAE WOO</creator><creator>LEE JEONG JOO</creator><scope>EVB</scope></search><sort><creationdate>20221025</creationdate><title>MOTOR ABNORMALITY DETECTION SYSTEM BASED ON DEEP LEARNING</title><author>LIM BYUNG KUL ; SEONG TAE JIN ; KANG JAE WOO ; LEE JEONG JOO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_KR102458080BB13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; kor</language><creationdate>2022</creationdate><topic>ALARM SYSTEMS</topic><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES</topic><topic>MEASURING</topic><topic>ORDER TELEGRAPHS</topic><topic>PHYSICS</topic><topic>SIGNALLING</topic><topic>SIGNALLING OR CALLING SYSTEMS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>LIM BYUNG KUL</creatorcontrib><creatorcontrib>SEONG TAE JIN</creatorcontrib><creatorcontrib>KANG JAE WOO</creatorcontrib><creatorcontrib>LEE JEONG JOO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LIM BYUNG KUL</au><au>SEONG TAE JIN</au><au>KANG JAE WOO</au><au>LEE JEONG JOO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MOTOR ABNORMALITY DETECTION SYSTEM BASED ON DEEP LEARNING</title><date>2022-10-25</date><risdate>2022</risdate><abstract>The present invention relates to a deep learning based motor abnormality detection system and a method thereof. The system comprises an abnormality detection server which outputs whether or not each motor is abnormal based on vibration data of each motor collected from vibration sensors respectively disposed in the at least one or more motors. The abnormality detection server includes a memory in which an abnormality detection program is stored and a processor executing the abnormality detection program. The abnormality detection program uses a machine learning model machine-learned based on the vibration data of each motor, and inputs the vibration data input for each motor to the machine learning model so as to output whether or not an abnormality has occurred in each motor and the cause of the abnormality. According to the present invention, specific inference about the cause of the abnormality is also possible. 본 발명은 딥러닝 기반의 모터 이상 감지 시스템 및 그 방법에 관한 것으로서, 적어도 하나 이상의 모터에 각각 배치된 진동 센서로부터 수집된 각 모터의 진동데이터에 기반하여, 각 모터의 이상 여부를 출력하는 이상 감지 서버를 포함하되, 상기 이상 감지 서버는, 이상 감지 프로그램이 저장된 메모리 및 상기 이상 감지 프로그램을 실행하는 프로세서를 포함하고, 상기 이상 감지 프로그램은, 상기 각 모터의 진동데이터를 기초로 기계학습된 기계학습모델을 이용하여, 각 모터별로 입력된 진동데이터를 상기 기계학습모델에 입력하여, 각 모터의 이상 발생 여부 및 이상 원인을 출력하는 시스템에 관한 것이다.</abstract><oa>free_for_read</oa></addata></record>
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subjects ALARM SYSTEMS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES
MEASURING
ORDER TELEGRAPHS
PHYSICS
SIGNALLING
SIGNALLING OR CALLING SYSTEMS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
TESTING
title MOTOR ABNORMALITY DETECTION SYSTEM BASED ON DEEP LEARNING
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