WO2011160650A1 - Acoustical machine condition monitoring - Google Patents
Acoustical machine condition monitoring Download PDFInfo
- 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
Links
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
In machine/bearing condition monitoring it is has been discovered that frequencies up to about 2.5 kHz, in most practical uses up to 1 kHz, only has background noise. Thus according to the invention, the energy in the frequency spectrum up to about 2.5 kHz at most and more commonly up to about 1 kHz, 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 for normalization directly on the values of the frequencies in the frequency spectrum of interest for analysis.
Description
ACOUSTICAL MACHINE CONDITION MONITORING
TECHNICAL FIELD
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.
BACKGROUND
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„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. Some plants can have as many as 5 to 8% of the conveyor idlers failing in a month.
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. Traditionally 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.
SUMMARY
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 aforementioned objects are achieved according to the invention by the use of machine condition monitoring unit according to the invention. To get predictable results from a machine condition monitoring unit, it is important that everything is properly calibrated. One difficulty is to calibrate measurement distances, or rather make sure that all measurements are taken at the same distances. If they are not, then, among other things, a problem of properly setting alarm levels arises. It is has been discovered that frequencies up to about 2.5 kHz, in most practical uses up to 1 kHz, oniy has machine/conveyor background noise. Thus according to the invention, 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.
The aforementioned objects are further achieved according to the invention by 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. According to the invention 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. Suitably the signal conditioning unit processes signals within a second frequency band to normalize the signals in the first frequency band. One preferred method is that 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.
Preferably 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.
Other advantages of the invention will become apparent from the detailed description below. BRIEF DESCRIPTION OF THE DRAWINGS
The invention will now be described in more detail for explanatory, and in no sense limiting, purposes, with reference to the following figures, in which:
Fig. 1A shows a view of a condition monitoring unit according to the
invention in a typical application monitoring a conveyor,
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,
DETAILED DESCRIPTION
In order to clarify the inventions, some examples of its use will now be described in connection with Figures 1 A to 4
Figure 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. Typically 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.
Figure 2 illustrates a functional block diagram of a typical condition monitoring unii according to the invention. There wiii be 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. Typically 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. For most further digital signal processing 274 it is advantageous that the signal is enveloped 273. 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.
Many of the digital signal processing diagnoses are dependent on signal amplitude not changing due to a varying distance between an acoustic sensor and the object under investigation, in these examples, a conveyor with idler rollers. If the amplitude varies due to a worker not walking completely parallel along the conveyor, the alarm levels have to be continuously changed due to this amplitude variation. One solution would be to continuously measure the distance between the acoustic sensor and the conveyor and then adjust the amplification and/or the alarm levels with regard to a varying measured distance. This would require one additional piece of hardware. However, according to the invention, it has been determined that a specific part of the measured signal itself can be used to determine any variation in distance between the acoustic sensor and a conveyor of interest. A self normalization of the signal attained from the acoustic sensor can be reached according to the invention by measuring the energy of a frequency band up to somewhere in the range of 1 kHz to 2.5 kH-c. ii has been discovered that the energy in this frequency band does not vary along the conveyor, the energy only varies in relation to the distance between the acoustic sensor and the conveyor.
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.
Figure 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. For further diagnostic processing 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.
For the self normalizing function, after the first processing block 471 , the signal is transformed into the frequency domain, suitably by a Fast Fourier Transformation 464. in the next stage 466, 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.
Alternatively, the normalizing controller 462, will only multiply/divide the measured values of the signals after they have been band pass filtered 472.
The invention is not restricted to the above-described embodiments, but may be varied within the scope of the following claims.
FIGURE 1A shows a view of a condition monitoring unit according to the invention in a typical application monitoring a conveyor,
100 A condition monitoring unit according to the invention
110 Conveyor
112 Right side idler roller,
114 Bottom idler roller,
116 Left side roller,
119 Conveyor belt.
FIGURE 1 B shows a cross section of a conveyor,
112 Right side idler roller,
114 Bottom jdler roller,
116 Left side roller,
119 Conveyor belt.
FIGURE 2 shows a functional block diagram of a condition monitoring unit according to the invention,
250 Acoustic sensor unit/microphone,
272 Amplification, A/D conversion, Filtering,
273 Enveloping,
274 Further digital signal processing,
276 Input/keyboard,
278 Output/Screen,
280 Optional output/headphones,
FIGURE 3 shows a functional block diagram of the self normalizing function according to the invention,
350 Acoustic sensor unit/microphone,
361 Low Pass Filter, preferably 1 kHz to 2.5 kHz cutoff frequency.
362 Normalizing controller,
371 Controllable input amplifier,
372 High Pass Filter or Band Pass Filter,
392 Further signal processing.
FIGURE 4 shows a block diagram of one embodiment of the self normalizing function according to the invention.
450 Microphone/Acoustic sensor unit,
462 Normalizing controller,
464 Fast Fourier Transform (FFT),
466 Root Sum Squares (RSS) of low frequencies up to at least 1 kHz and suitably as an upper limit 2.5 kHz,
471 Controllable amplifier,
472 Band Pass Filter.
473 Enveloping,
480 Headphones,
482 Headphone amplifier
492 Further digital signal processing.
Claims
1. A machine condition monitoring unit comprising an acoustic sensor arranged to convert acoustic pressure waves to an electrical signal, and digital signal processing means, where the bearing condition monitoring unit is arranged to process electrical signals from the acoustic sensor within a first frequency band, to thereby perform diagnosis on bearings, characterized in that the bearing 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 bearings.
2. A machine condition monitoring unit according to claim 1 characterized in that the signal conditioning unit processes signals within a second frequency band to normalize the signals in the first frequency band.
3. A machine condition monitoring unit according to claim 2 characterized in that 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.
4. A machine condition monitoring unit according to claim 2 or 3characterized in that the first frequency band is not overlapping the second frequency band.
5. A machine condition monitoring unit according to any one of claims 2 to 4 characterized in that the second frequency band is a lower frequency band than the first frequency band.
6. A machine condition monitoring unit according to any one of claims 2 to 5 characterized in that the second frequency band is up to 2.5 kHz.
7. A machine condition monitoring unit according to any one of claims 2 to 5 characterized in that the second frequency band is up to 1 kHz.
8. A machine condition monitoring unit according to any one of claims 1 to 7 characterized in that the first frequency band starts at 3.5 kHz or above.
9. A machine condition monitoring unit according to any one of claims 1 to 7 characterized in that the first frequency band starts at 5 kHz or above.
10. A machine condition monitoring unit according to any one of claims 1 to 9 characterized in that the signal conditioning unit is arranged to normalize -the first frequency band by-varying an amplification of-a-signal-amplifier.
11. A machine condition monitoring unit according to any one of claims 1 to 9 characterized in that the signal conditioning unit is arranged to normalize the first frequency band by varying a dampening of a signal dampener.
12. A machine condition monitoring unit according to any one of claims 1 to 9 characterized in that processing of the signal conditioning unit is in the digital domain and in that the signal conditioning unit is arranged to normalize the first frequency band by varying a multiplication factor of the signals of the first frequency band.
13. A machine condition monitoring unit according to any one of claims 1 to 9 characterized in that processing of the signal conditioning unit is in the digital domain and in that the signal conditioning unit is arranged to normalize the first frequency band by varying a multiplication factor of the signals from the acoustic sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/EP2010/003726 WO2011160650A1 (en) | 2010-06-21 | 2010-06-21 | Acoustical machine condition monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/EP2010/003726 WO2011160650A1 (en) | 2010-06-21 | 2010-06-21 | Acoustical machine condition monitoring |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2011160650A1 true WO2011160650A1 (en) | 2011-12-29 |
Family
ID=43587618
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/EP2010/003726 Ceased WO2011160650A1 (en) | 2010-06-21 | 2010-06-21 | Acoustical machine condition monitoring |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2011160650A1 (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104344949A (en) * | 2013-08-08 | 2015-02-11 | 珠海格力电器股份有限公司 | Quality detection system of moving part |
| EP3247658B1 (en) * | 2015-01-21 | 2025-09-03 | Vayeron Pty Ltd | Improvements in conveyor and components therefor, monitoring methods and communication systems |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0623921A1 (en) * | 1993-04-05 | 1994-11-09 | Sony Corporation | Signal detecting method and signal detecting apparatus |
| WO1999058061A1 (en) * | 1998-05-14 | 1999-11-18 | Koninklijke Philips Electronics N.V. | A method for doppler imaging moving tissue and fluids in a body and ultrasonic doppler imaging system for carrying out this method |
| GB2340942A (en) * | 1998-08-28 | 2000-03-01 | Nsk Ltd | Bearing rigidity evaluation |
| WO2002073150A2 (en) * | 2001-03-13 | 2002-09-19 | Ab Skf | System and method for analyzing vibration signals |
| EP1612458A2 (en) * | 2004-06-28 | 2006-01-04 | General Electric Company | System and method for monitoring the condition of a drive train |
| DE102008021360A1 (en) * | 2008-04-29 | 2009-11-05 | Siemens Aktiengesellschaft | Method and device for detecting bearing damage |
-
2010
- 2010-06-21 WO PCT/EP2010/003726 patent/WO2011160650A1/en not_active Ceased
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0623921A1 (en) * | 1993-04-05 | 1994-11-09 | Sony Corporation | Signal detecting method and signal detecting apparatus |
| WO1999058061A1 (en) * | 1998-05-14 | 1999-11-18 | Koninklijke Philips Electronics N.V. | A method for doppler imaging moving tissue and fluids in a body and ultrasonic doppler imaging system for carrying out this method |
| GB2340942A (en) * | 1998-08-28 | 2000-03-01 | Nsk Ltd | Bearing rigidity evaluation |
| WO2002073150A2 (en) * | 2001-03-13 | 2002-09-19 | Ab Skf | System and method for analyzing vibration signals |
| EP1612458A2 (en) * | 2004-06-28 | 2006-01-04 | General Electric Company | System and method for monitoring the condition of a drive train |
| DE102008021360A1 (en) * | 2008-04-29 | 2009-11-05 | Siemens Aktiengesellschaft | Method and device for detecting bearing damage |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104344949A (en) * | 2013-08-08 | 2015-02-11 | 珠海格力电器股份有限公司 | Quality detection system of moving part |
| EP3247658B1 (en) * | 2015-01-21 | 2025-09-03 | Vayeron Pty Ltd | Improvements in conveyor and components therefor, monitoring methods and communication systems |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10609482B2 (en) | Speaker operation checking device and method | |
| US20100268489A1 (en) | Method and system for registering and measuring leaks and flows | |
| EP0227138A1 (en) | Means for detecting faults or defects in moving machine parts | |
| KR20090094171A (en) | Abnormality diagnostic method and device of extremely low speed rotary machine | |
| JP2016153138A (en) | Vibration abnormality detection method and apparatus in cold rolling or temper rolling | |
| CN103376291A (en) | Abnormality detection method and abnormality detection device | |
| WO2019079785A3 (en) | Recording module for processing at least one electronic auscultatory sound signal | |
| CN1319035A (en) | Method and apparatus for detecting chattering of cold rolling mill | |
| CN202033101U (en) | Vibration and noise measuring instrument | |
| JP2009115537A (en) | Vibration measurement method | |
| JPH09506974A (en) | Device and method for detecting ultrasonic waves propagated from a selected distance | |
| CN103442811A (en) | Hydrocyclone with wear detector | |
| WO2011160650A1 (en) | Acoustical machine condition monitoring | |
| JP3875981B2 (en) | Anomaly diagnosis method and apparatus for rolling bearing | |
| JP4101381B2 (en) | Weighing device | |
| CN1011080B (en) | Apparatus and method for measuring property of continuous strand of fibrous materials | |
| JP4581860B2 (en) | Machine equipment abnormality diagnosis apparatus and abnormality diagnosis method | |
| JP2015114294A (en) | Acoustic device inspection apparatus, acoustic device inspection method, and acoustic device inspection program | |
| JPH0344520A (en) | Abnormality detection method of rotating roller for belt conveyor and its vibration sensor | |
| JP2009276334A (en) | Allophone pickup tool | |
| WO2011160652A1 (en) | Acoustical machine condition monitoring | |
| JP5900296B2 (en) | Vibration analysis apparatus, vibration analysis method, and vibration analysis program | |
| JP5463188B2 (en) | Governor room abnormality detection method and governor room abnormality detection system | |
| WO2011160651A1 (en) | Acoustic sensor unit comprising a paraboloidal collector, and a machine condition monitoring unit adapted to be coupled to such acoustic sensor unit | |
| KR20150061906A (en) | Apparatus for nondestructive crack inspection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 10729786 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 10729786 Country of ref document: EP Kind code of ref document: A1 |