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WO2011160650A1 - Contrôle d'état de machine acoustique - Google Patents

Contrôle d'état de machine acoustique Download PDF

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Publication number
WO2011160650A1
WO2011160650A1 PCT/EP2010/003726 EP2010003726W WO2011160650A1 WO 2011160650 A1 WO2011160650 A1 WO 2011160650A1 EP 2010003726 W EP2010003726 W EP 2010003726W WO 2011160650 A1 WO2011160650 A1 WO 2011160650A1
Authority
WO
WIPO (PCT)
Prior art keywords
frequency band
condition monitoring
monitoring unit
khz
machine condition
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/EP2010/003726
Other languages
English (en)
Inventor
Robert Andrew Hall
Allan Alexander Todd
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SKF AB
Original Assignee
SKF AB
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SKF AB filed Critical SKF AB
Priority to PCT/EP2010/003726 priority Critical patent/WO2011160650A1/fr
Publication of WO2011160650A1 publication Critical patent/WO2011160650A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/04—Bearings
    • G01M13/045—Acoustic or vibration analysis

Definitions

  • the invention is related to condition monitoring of machines, especially bearings of the machines, in particular in relation to bearings of idler rollers of for example conveyor belts.
  • Bearings are a very important component in rotating machinery. If a bearing fails, then the complete functionality of the machinery usually also fails. In some applications it might be very difficult or just extremely expensive to replace a failed bearing constitutional outside_r_egular scheduled maintenance. Such applications might be continuous manufacturing lines, including conveyors of for example mines and cement plants.
  • a trough type conveyor will traditionally comprise a conveyor belt that is typically supported by three idler rollers for approximately every meter. Each idler roller will usually comprise two bearings each, giving six bearings per meter of conveyor. Other types of conveyors, such as pipe conveyors, will also comprise idler rollers for support. Conveyors in mines and cement plants can easily be several kilometers long, resulting in more than ten thousand bearings being incorporated in a single conveyor system. If a bearing of an idler roller fails, then most likely the idler roller will seize. A seized idler roller can fray and cut the conveyor beit. Conveyor belt damage can result in expensive belt repair/replacement, risk of workers' safety, and/or unplanned downtime if no parallel belt or buffer stock exists.
  • Condition monitoring is done in an attempt to predict when a bearing needs to be replaced before it fails, suitably enabling replacement in an orderly scheduled manner. It is difficult to overcome the logistical problem of monitoring possibly more than ten thousand bearings of a single conveyor system.
  • condition monitoring has been done with a worker walking along the conveyor belt listening and looking for failing or failed conveyor idler rollers. It is hard to detect failing idlers over commonly a very high background noise level.
  • a more advanced method of condition monitoring is to use a thermographic camera to detect failing idlers. Unfortunately it is very time consuming and only catches failing idlers at a very late stage of failure. Thus there seems to be room for improvement in the ways of assessing the condition of a bearing, especially a bearing of an idler roller.
  • An object of the invention is to define a method and means to monitor the condition of a machine, with a focus on the bearings of the machine, especially a bearing of an idler roller.
  • the energy in the frequency spectrum up to about 2.5 kHz at most and more commonly up to about 1 kHz, or somewhere in between is determined and used as a normalization factor, an indication of the distance between machine/conveyor and measurement by for example an acoustic sensor.
  • the normalization factor can then be used directly for normalization on the values of the frequencies in the frequency spectrum of interest for analysis. This can for example be a spectrum with frequencies between 5 kHz and 40 kHz.
  • a machine condition monitoring unit comprising an acoustic sensor arranged to convert acoustic pressure waves to an electrical signal, and digital signal processing means.
  • the machine condition monitoring unit is arranged to process electrical signals from the acoustic sensor within a first frequency band, to thereby perform diagnosis on the machine and its bearings.
  • the machine condition monitoring unit further comprises a signal conditioning unit arranged to normalize the signals within the first frequency band to thereby address a problem of a varying distance between the acoustic sensor and investigated machine/bearings.
  • the signal conditioning unit processes signals within a second frequency band to normalize the signals in the first frequency band.
  • the signal conditioning unit is arranged to determine a total energy of the signals in the second frequency band and to normalize the signals in the first frequency band based on the determined total energy.
  • the first frequency band is not overlapping the second frequency band, and the second frequency band in most applications in a lower frequency band than the first frequency band.
  • the second frequency band can be up to 2.5 kHz, up to anywhere in between 2.5 kHz and 1 kHz, or up to 1 kHz.
  • the first frequency band can start at 3.5 kHz or above, in most cases it is suitable that the first frequency band starts at 5 kHz or even above.
  • a suitable upper limit of the first frequency band can be 40 kHz.
  • the signal conditioning unit can be arranged to normalize the first frequency band by varying an amplification of a signal amplifier, by varying a dampening of a signal dampener. If the signal conditioning unit is in the digital domain then the signal conditioning unit can arranged to normalize the first frequency band by varying a multiplication factor of the signals of the first frequency band, or by varying a multiplication factor of the signals from the acoustic sensor.
  • Fig. 1A shows a view of a condition monitoring unit according to the
  • Fig. 1B shows a cross section of a conveyor
  • Fig. 2 shows a functional block diagram of a condition monitoring unit according to the invention
  • Fig. 3 shows a functional block diagram of the self normalizing function according to the invention
  • Fig. 4 shows a block diagram of one embodiment of the self normalizing function according to the invention
  • FIG. 1A shows a view of a condition monitoring unit 100 according to the invention in a typical application monitoring a conveyor 110.
  • a conveyor 1 0 will convey goods, such as gravel, on a conveyor belt 119 from a first place to a second place. The conveyed distance can be in the range of kilometers.
  • the illustrated conveyor section 110 is of a trough conveyor and will typically require three idler rollers 112, 114, 116 approximately every meter along the length of the conveyor 110.
  • One idler roller 114 is located directly underneath the belt 119 and one idler roller 112, 116 is located on each side, bending up the belt, to thereby create a trough.
  • Figure 1B illustrates a cross section of such a conveyor.
  • Each idler roller 112 " 114, 116 along the whole conveyor will typically comprise two bearings, one on each end of an idler roller 112, 114, 116.
  • a complete conveyor will then easily comprise more than a thousand bearings. It is these bearings that the condition monitoring unit 100 according to the invention is monitoring the condition of.
  • a worker will walk along the length of the conveyor 110 and point the condition monitoring unit 100, or at least an acoustic sensor of the condition monitoring unit, towards the idler rollers 112, 114, 116 carrying the bearings of interest. It has been found that by analyzing sound pressure signals within the acoustic frequency range, an assessment of the condition of a bearing can be made.
  • Acoustics cover frequencies from zero Hertz up to several mega Hertz and is usually subdivided into infrasound covering 0 Hz to about 20 Hz, sound covering about 20 Hz to 20 kHz and ultra sound being above 20 kHz up to several mega Hz.
  • FIG. 2 illustrates a functional block diagram of a typical condition monitoring devis according to the invention.
  • an acoustic sensor 250 typicaiiy a microphone, with a wide enough bandwidth to be able to sense sound pressure in the frequency range of interest.
  • an acoustic sensor 250 for the purposes of the invention should have a bandwidth of 20 Hz to at least 40 kHz.
  • the acoustic sensor 250 is coupled to a pre-processing block 272, which will suitably comprise amplification, analog to digital conversion, filtering and possibly automatic normalization. It is possible to implement the invention completely in the analog domain, but normally it is desirable to do as much processing as possible in the digital domain, thus putting the analog to digital conversion as close as possible to any analog input.
  • the core digital signal processing 274 will have some user interface input 276, such as a keyboard, for changing parameters and limits. There will also be an output 278, such as a screen, to show the results of the analysis. In some applications it is desirable to have an audio output 280, for example in the form of headphones.
  • FIGURE 3 shows a functional block diagram of the self normalizing function according to the invention.
  • An acoustic sensor unit/microphone 350 converts a sound pressure to an electric signal that is then entered into a first signal processing block 371.
  • the first signal processing block 371 comprises a gain controllable amplifier and suitably also analog to digital conversion, and signal filters.
  • the signal will then enter both a high pass or band pass filter 372 suitable for further signal processing 392 necessary for the signal condition monitoring diagnosis, and a low pass filter, suitably with a cutoff frequency in the range of 1 kHz to 2.5 kHz, for the self normalizing function.
  • the low pass filtered signal then enters the normalizing controller 362, which in turn controls the controllable amplifier of the first signal processing block 371 to thereby form a complete confrol loop.
  • the normalizing controller will determine the energy content of the low pass filtered signal and then convert this into a suitable control signal for the controllable amplifier such that the signal out of the first signal processing block 371 is normalized.
  • FIG. 4 illustrates a block diagram of one embodiment of the self normalizing function according to the invention.
  • a microphone/acoustic sensor unit 450 converts a sound pressure into an electrical signal.
  • the electrical signal will be amplified and preprocessed, such as converted into the digital domain in a first processing block 471.
  • the signal will then pass a band pass filter 472, suitably having cut off frequencies at 3.5 kHz to 5 kHz and at around 40 kHz.
  • the band pass filtered signal will pass into further digital signal processing 492 both directly and via an enveloping stage 473.
  • the signal is transformed into the frequency domain, suitably by a Fast Fourier Transformation 464.
  • the iow frequencies up to at least 1 kHz and possibly up to a limit of 2.5 kHz are processed by a Root Sum Squares algorithm to determine the energy in these low frequencies. Effectively the signal is low pass filtered to then determine the energy left in the frequency band.
  • Root Sum Squares (RSS) squares the values for each frequency in the desired spectrum, sums the resulting values and then takes the square root of this sum. This will give a measure of the total energy in the desired spectrum; that is frequencies between 20 Hz and at least 1 kHz, possibly up to 2.5 kHz.
  • the measure of the total energy in the spectrum is then fed to a normalizing controller 462.
  • the normalizing controller will convert the measure of the total energy in the spectrum to a signal that will control a controllable and adjustable amplifier in the first processing block 471. It can also be a controllable and adjustable damper in the first processing block 471.
  • the normalizing controller will control the amplifier or damper in such a way as to keep the total energy in the spectrum, that is frequencies between 20 Hz and at least 1 kHz, possibly up to 2.5 kHz, as constant as possible.
  • the normalizing controller 462 will only multiply/divide the measured values of the signals after they have been band pass filtered 472.
  • FIGURE 1A shows a view of a condition monitoring unit according to the invention in a typical application monitoring a conveyor
  • FIGURE 1 B shows a cross section of a conveyor
  • FIGURE 2 shows a functional block diagram of a condition monitoring unit according to the invention
  • FIGURE 3 shows a functional block diagram of the self normalizing function according to the invention
  • FIGURE 4 shows a block diagram of one embodiment of the self normalizing function according to the invention.

Landscapes

  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

Lors du contrôle de l'état d'une machine/d'un palier, il a été découvert que les fréquences allant jusqu'à environ 2,5 kHz, et jusqu'à 1 kHz dans la plupart des cas pratiques, ne comprennent que du bruit de fond. Ainsi, selon l'invention, l'énergie dans le spectre de fréquences allant jusqu'à environ 2,5 kHz au plus et plus couramment jusqu'à environ 1 kHz est déterminée et utilisée comme un facteur de normalisation, une indication de la distance entre la machine et le transporteur, et une mesure par un capteur acoustique par exemple. Le facteur de normalisation peut alors être utilisé afin de normaliser directement les valeurs des fréquences dans le spectre de fréquences présentant un intérêt pour analyse.
PCT/EP2010/003726 2010-06-21 2010-06-21 Contrôle d'état de machine acoustique Ceased WO2011160650A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/EP2010/003726 WO2011160650A1 (fr) 2010-06-21 2010-06-21 Contrôle d'état de machine acoustique

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/EP2010/003726 WO2011160650A1 (fr) 2010-06-21 2010-06-21 Contrôle d'état de machine acoustique

Publications (1)

Publication Number Publication Date
WO2011160650A1 true WO2011160650A1 (fr) 2011-12-29

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Family Applications (1)

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PCT/EP2010/003726 Ceased WO2011160650A1 (fr) 2010-06-21 2010-06-21 Contrôle d'état de machine acoustique

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WO (1) WO2011160650A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104344949A (zh) * 2013-08-08 2015-02-11 珠海格力电器股份有限公司 一种运动零件的质量检测系统
EP3247658B1 (fr) * 2015-01-21 2025-09-03 Vayeron Pty Ltd Améliorations dans un transporteur et éléments pour ce dernier, procédés de surveillance et systèmes de communication

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0623921A1 (fr) * 1993-04-05 1994-11-09 Sony Corporation Procédé de détection d'un signal et dispositif de détection d'un signal
WO1999058061A1 (fr) * 1998-05-14 1999-11-18 Koninklijke Philips Electronics N.V. Procede d'imagerie doppler de la mobilite de tissus et de fluides corporels et systeme d'imagerie doppler ultrasonore pour appliquer ce procede
GB2340942A (en) * 1998-08-28 2000-03-01 Nsk Ltd Bearing rigidity evaluation
WO2002073150A2 (fr) * 2001-03-13 2002-09-19 Ab Skf Systeme et procede d'analyse de signaux de vibrations
EP1612458A2 (fr) * 2004-06-28 2006-01-04 General Electric Company Système et procédé pour surveiller l'état d'un train d'engrenages
DE102008021360A1 (de) * 2008-04-29 2009-11-05 Siemens Aktiengesellschaft Verfahren und Vorrichtung zum Erkennen eines Lagerschadens

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0623921A1 (fr) * 1993-04-05 1994-11-09 Sony Corporation Procédé de détection d'un signal et dispositif de détection d'un signal
WO1999058061A1 (fr) * 1998-05-14 1999-11-18 Koninklijke Philips Electronics N.V. Procede d'imagerie doppler de la mobilite de tissus et de fluides corporels et systeme d'imagerie doppler ultrasonore pour appliquer ce procede
GB2340942A (en) * 1998-08-28 2000-03-01 Nsk Ltd Bearing rigidity evaluation
WO2002073150A2 (fr) * 2001-03-13 2002-09-19 Ab Skf Systeme et procede d'analyse de signaux de vibrations
EP1612458A2 (fr) * 2004-06-28 2006-01-04 General Electric Company Système et procédé pour surveiller l'état d'un train d'engrenages
DE102008021360A1 (de) * 2008-04-29 2009-11-05 Siemens Aktiengesellschaft Verfahren und Vorrichtung zum Erkennen eines Lagerschadens

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104344949A (zh) * 2013-08-08 2015-02-11 珠海格力电器股份有限公司 一种运动零件的质量检测系统
EP3247658B1 (fr) * 2015-01-21 2025-09-03 Vayeron Pty Ltd Améliorations dans un transporteur et éléments pour ce dernier, procédés de surveillance et systèmes de communication

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