Vibration measurement of large rotating machinery with MEMS accelerometer-based Internet of Things measurement device

Ivar Koene

Vibration measurement of large rotating machinery with MEMS accelerometer-based Internet of Things measurement device

Julkaisun otsikon käännös: Värähtelymittaus isoista pyörivistä koneista MEMS-kiihtyvyysantureihin perustuvalla esineiden internetin mittalaitteella

Ivar Koene

Tutkimustuotos: Doctoral Thesis › Collection of Articles

Abstrakti

Pyöriviä koneita käytetään laajasti erilaisissa käyttökohteissa, kuten voimalaitoksissa, tuulivoimaloissa, paperikoneissa ja laivojen voimalinjoissa. Jokaisessa edellä mainitussa kohteessa kunnonvalvonta on tärkeässä roolissa, jotta voidaan ennakoida koneen vikaantuminen ja optimoimaan huollon aikataulutus sekä koneen käyttö. Tyypillisesti koneiden kunnonvalvonta toteutetaan langallisilla värähtelyantureilla, joista yksi esimerkki on pietsosähköinen kiihtyvyysanturi. Näiden antureiden haasteena on kaapeloinnin kalleus ja työläys, mikä voi joissain tilanteissa rajoittaa niiden käyttöä. Tutkimuksessa keskityttiin kustannustehokkaiden ja helposti asennettavien antureiden käyttöön pyörivien koneiden kunnonvalvonnassa. Tutkimuksessa esiteltiin kolme prototyyppiä langattomista esineiden internetin (IoT) mittalaitteista, joissa on mikrosysteemikiihtyvyysanturi (MEMS-kiihtyvyysanturi) mittamaan värähtelyä. Ensimmäisellä prototyypillä tutkittiin MEMS-kiihtyvyysanturin soveltuvuutta suurten pyörivien koneiden poikittaisten värähtelyiden mittauksessa. Toinen prototyyppi oli avoimen lähdekoodin IoT-mittalaite, jossa oli pitkät mittaukset mahdollistava tiedontallennusjärjestelmä. Mittalaitetta operoitiin selainpohjaisella käyttöliittymällä, joka yhdessä tiedon tallennuksen kanssa mahdollisti laitteen itsenäisen käytön pelkällä selainyhteydellä. Kolmas prototyyppi kiinnitettiin suoraan pyörivään akseliin, mikä mahdollisti sekä vääntö- että poikittaisvärähtelyiden mittauksen. Akseliin kiinnitetyn prototyypin tueksi kehitettiin signaalinkäsittelymenetelmä, jolla pystyttiin erottamaan vääntö- ja poikittaisvärähtelyt toisistaan sekä edelleen jakamaan poikittaisvärähtelyt vaaka- ja pystysuuntaisiin värähtelyihin. Prototyyppien tutkimuksessa hyödynnettiin kolmea eri testiympäristöä: täysikokoista paperikoneen telaa, lineaarista toimilaitetta ja laivan voimansiirron pienoismallia. Paperikoneen telaa sekä laivan voimansiirron pienoismallia käytettiin värähtelyn mittaamisen tutkimiseen. Lineaarisen toimilaitteen avulla tutkittiin etenemisliikkeen mittaamista. Referenssiantureina käytettiin perinteisiä pietsosähköisiä kiihtyvyysantureita, pulssiantureita ja vääntöantureita. Tulokset osoittivat, että langattomat IoT-mittalaitteet ovat varteenotettava vaihtoehto värähtelyn mittaamiseen pyörivistä koneista. Nämä mittalaitteet voidaan asentaa jälkeenpäin olemassa oleviin koneisiin helposti sekä kustannustehokkaasti. Akseliin kiinnitetty prototyyppi pystyi mittamaan ja erottamaan vääntö- ja poikittaisvärähtelyt toisistaan, mikä mahdollistaa eri värähtelytyypeille tarkoitettujen erillisten antureiden korvaamisen yhdellä anturikokonaisuudella. MEMS-kiihtyvyysantureilla on kuitenkin haasteensa kohinatiheyden kanssa, mikä kuitenkin pienenee koko ajan MEMS-teknologian kehittyessä.

Julkaisun otsikon käännös	Värähtelymittaus isoista pyörivistä koneista MEMS-kiihtyvyysantureihin perustuvalla esineiden internetin mittalaitteella
Alkuperäiskieli	Englanti
Pätevyys	Tohtorintutkinto
Myöntävä instituutio	Aalto-yliopisto
Valvoja/neuvonantaja	Viitala, Raine, Vastuuprofessori
Kustantaja	Aalto University
Painoksen ISBN	978-952-64-0754-8
Sähköinen ISBN	978-952-64-0755-5
Tila	Julkaistu - 2022
OKM-julkaisutyyppi	G5 Artikkeliväitöskirja

Tutkimusalat

kiihtyvyysanturi
vääntövärähtely
poikittaisvärähtely
kunnonvalvonta
esineiden internet

Pääsy asiakirjaan

http://urn.fi/URN:ISBN:978-952-64-0755-5

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@phdthesis{5c81b7aca65540c6846a938aaf6e267b,

title = "Vibration measurement of large rotating machinery with MEMS accelerometer-based Internet of Things measurement device",

abstract = "Rotating machines are widely used in different applications, such as power plants, windmills, paper machines, and ship powertrains. For each of these applications, condition monitoring is important for machine failure prevention, maintenance schedule optimisation, and machine operation. Commonly, machine condition monitoring systems are based on wired vibration sensors such as piezoelectric accelerometers. The disadvantage of these commonly used sensors is the requirement for cables. Cabling such systems can be a laborious and expensive process. This research focused on more cost-effective and easier-to-install solutions for condition monitoring of rotating machinery. More specifically, these studies revolved around wireless Internet of Things (IoT) measurement devices with accelerometers. The research introduces three prototypes, which all contribute to the research topic. The first prototype demonstrated microelectromechanical systems (MEMS) accelerometer performance in vibration measurement of a large rotating machine. The second prototype was an open-source measurement device with a data storing system enabling long measurements and a browser-based graphical user interface. These features enabled standalone operation, requiring only a browser connection for the prototype operation. The third prototype was directly installed on the rotating shaft of the machine. The on-shaft mounting enabled measurement of lateral and torsional vibration. Alongside the on-shaft prototype, a signal processing method was developed to separate the torsional and lateral vibration from the measurement data, and to further separate the lateral vibration into horizontal and vertical vibration. Three different test environments were employed in the prototype studies: a full-size paper machine roll, a linear actuator, and a small-scale model of a maritime powertrain. The full-size paper machine roll and the small-scale model of a maritime powertrain served as the research environment for vibration measurements. The linear actuator was a platform to study translational movement measurements. Conventional sensors, such as piezoelectric accelerometers, encoders, and torque transducers, were used as the reference sensors. The results show that the MEMS accelerometer-based IoT measurement devices are a viable solution for vibration measurement of rotating machinery. These measurement devices can be easily and cost-effectively retrofitted to already existing machines. The on-shaft prototype can measure lateral and torsional vibration, which eliminates the need for separate sensors for each type of vibration. However, MEMS accelerometers still have their drawbacks compared to conventional accelerometers, such as a noise density. Nevertheless, MEMS sensor technology advances constantly, making them more accurate.",

keywords = "MEMS, accelerometer, torsional vibration, lateral vibrations, condition monitoring, Internet of things, kiihtyvyysanturi, v{\"a}{\"a}nt{\"o}v{\"a}r{\"a}htely, poikittaisv{\"a}r{\"a}htely, kunnonvalvonta, esineiden internet, MEMS, accelerometer, torsional vibration, lateral vibrations, condition monitoring, Internet of things",

author = "Ivar Koene",

year = "2022",

language = "English",

isbn = "978-952-64-0754-8",

series = "Aalto University publication series DOCTORAL THESES",

publisher = "Aalto University",

number = "48",

address = "Finland",

school = "Aalto University",

}

TY - BOOK

T1 - Vibration measurement of large rotating machinery with MEMS accelerometer-based Internet of Things measurement device

AU - Koene, Ivar

PY - 2022

Y1 - 2022

N2 - Rotating machines are widely used in different applications, such as power plants, windmills, paper machines, and ship powertrains. For each of these applications, condition monitoring is important for machine failure prevention, maintenance schedule optimisation, and machine operation. Commonly, machine condition monitoring systems are based on wired vibration sensors such as piezoelectric accelerometers. The disadvantage of these commonly used sensors is the requirement for cables. Cabling such systems can be a laborious and expensive process. This research focused on more cost-effective and easier-to-install solutions for condition monitoring of rotating machinery. More specifically, these studies revolved around wireless Internet of Things (IoT) measurement devices with accelerometers. The research introduces three prototypes, which all contribute to the research topic. The first prototype demonstrated microelectromechanical systems (MEMS) accelerometer performance in vibration measurement of a large rotating machine. The second prototype was an open-source measurement device with a data storing system enabling long measurements and a browser-based graphical user interface. These features enabled standalone operation, requiring only a browser connection for the prototype operation. The third prototype was directly installed on the rotating shaft of the machine. The on-shaft mounting enabled measurement of lateral and torsional vibration. Alongside the on-shaft prototype, a signal processing method was developed to separate the torsional and lateral vibration from the measurement data, and to further separate the lateral vibration into horizontal and vertical vibration. Three different test environments were employed in the prototype studies: a full-size paper machine roll, a linear actuator, and a small-scale model of a maritime powertrain. The full-size paper machine roll and the small-scale model of a maritime powertrain served as the research environment for vibration measurements. The linear actuator was a platform to study translational movement measurements. Conventional sensors, such as piezoelectric accelerometers, encoders, and torque transducers, were used as the reference sensors. The results show that the MEMS accelerometer-based IoT measurement devices are a viable solution for vibration measurement of rotating machinery. These measurement devices can be easily and cost-effectively retrofitted to already existing machines. The on-shaft prototype can measure lateral and torsional vibration, which eliminates the need for separate sensors for each type of vibration. However, MEMS accelerometers still have their drawbacks compared to conventional accelerometers, such as a noise density. Nevertheless, MEMS sensor technology advances constantly, making them more accurate.

AB - Rotating machines are widely used in different applications, such as power plants, windmills, paper machines, and ship powertrains. For each of these applications, condition monitoring is important for machine failure prevention, maintenance schedule optimisation, and machine operation. Commonly, machine condition monitoring systems are based on wired vibration sensors such as piezoelectric accelerometers. The disadvantage of these commonly used sensors is the requirement for cables. Cabling such systems can be a laborious and expensive process. This research focused on more cost-effective and easier-to-install solutions for condition monitoring of rotating machinery. More specifically, these studies revolved around wireless Internet of Things (IoT) measurement devices with accelerometers. The research introduces three prototypes, which all contribute to the research topic. The first prototype demonstrated microelectromechanical systems (MEMS) accelerometer performance in vibration measurement of a large rotating machine. The second prototype was an open-source measurement device with a data storing system enabling long measurements and a browser-based graphical user interface. These features enabled standalone operation, requiring only a browser connection for the prototype operation. The third prototype was directly installed on the rotating shaft of the machine. The on-shaft mounting enabled measurement of lateral and torsional vibration. Alongside the on-shaft prototype, a signal processing method was developed to separate the torsional and lateral vibration from the measurement data, and to further separate the lateral vibration into horizontal and vertical vibration. Three different test environments were employed in the prototype studies: a full-size paper machine roll, a linear actuator, and a small-scale model of a maritime powertrain. The full-size paper machine roll and the small-scale model of a maritime powertrain served as the research environment for vibration measurements. The linear actuator was a platform to study translational movement measurements. Conventional sensors, such as piezoelectric accelerometers, encoders, and torque transducers, were used as the reference sensors. The results show that the MEMS accelerometer-based IoT measurement devices are a viable solution for vibration measurement of rotating machinery. These measurement devices can be easily and cost-effectively retrofitted to already existing machines. The on-shaft prototype can measure lateral and torsional vibration, which eliminates the need for separate sensors for each type of vibration. However, MEMS accelerometers still have their drawbacks compared to conventional accelerometers, such as a noise density. Nevertheless, MEMS sensor technology advances constantly, making them more accurate.

KW - MEMS

KW - accelerometer

KW - torsional vibration

KW - lateral vibrations

KW - condition monitoring

KW - Internet of things

KW - kiihtyvyysanturi

KW - vääntövärähtely

KW - poikittaisvärähtely

KW - kunnonvalvonta

KW - esineiden internet

KW - MEMS

KW - accelerometer

KW - torsional vibration

KW - lateral vibrations

KW - condition monitoring

KW - Internet of things

M3 - Doctoral Thesis

SN - 978-952-64-0754-8

T3 - Aalto University publication series DOCTORAL THESES

PB - Aalto University

ER -

Vibration measurement of large rotating machinery with MEMS accelerometer-based Internet of Things measurement device

Abstrakti

Tutkimusalat

Pääsy asiakirjaan

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