EP1972793A1 - Procédé de détection de défauts dans des unités de pompage - Google Patents

Procédé de détection de défauts dans des unités de pompage Download PDF

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Publication number
EP1972793A1
EP1972793A1 EP07005995A EP07005995A EP1972793A1 EP 1972793 A1 EP1972793 A1 EP 1972793A1 EP 07005995 A EP07005995 A EP 07005995A EP 07005995 A EP07005995 A EP 07005995A EP 1972793 A1 EP1972793 A1 EP 1972793A1
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EP
European Patent Office
Prior art keywords
cepstral
electric motor
module
diagram
vibration
Prior art date
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Granted
Application number
EP07005995A
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German (de)
English (en)
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EP1972793B1 (fr
Inventor
Hakon Børsting
Flemming Munk
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Grundfos Management AS
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Grundfos Management AS
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Filing date
Publication date
Priority to DE502007004387T priority Critical patent/DE502007004387D1/de
Application filed by Grundfos Management AS filed Critical Grundfos Management AS
Priority to EP07005995A priority patent/EP1972793B1/fr
Priority to AT07005995T priority patent/ATE474140T1/de
Priority to PL07005995T priority patent/PL1972793T3/pl
Priority to US12/532,284 priority patent/US8401806B2/en
Priority to CN200880008952.0A priority patent/CN101636589B/zh
Priority to PCT/EP2008/001449 priority patent/WO2008116538A1/fr
Publication of EP1972793A1 publication Critical patent/EP1972793A1/fr
Application granted granted Critical
Publication of EP1972793B1 publication Critical patent/EP1972793B1/fr
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Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
    • F04D15/0066—Control, e.g. regulation, of pumps, pumping installations or systems by changing the speed, e.g. of the driving engine
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
    • F04D15/0088—Testing machines
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D29/00—Details, component parts, or accessories
    • F04D29/66—Combating cavitation, whirls, noise, vibration or the like; Balancing
    • F04D29/669—Combating cavitation, whirls, noise, vibration or the like; Balancing especially adapted for liquid pumps
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/70—Type of control algorithm
    • F05D2270/709—Type of control algorithm with neural networks

Definitions

  • the invention relates to a method for detecting faults in a pump unit with an electric motor or in an electric motor.
  • the method according to the invention is used to detect faults in a pump unit, which has an electric motor for driving, or in an electric motor. These units always have at least one rotating shaft. This shaft is mounted in bearings, in which, for example, errors may occur, as they can be detected by the method according to the invention.
  • a vibration signal is detected in the electric motor or in the case of a pump unit in the pump unit or, if appropriate, its drive motor.
  • known sensors can be used for vibration detection.
  • the detected vibration signal is then processed in a first processing step such that the influence of the current speed of the shaft is eliminated.
  • the processed signal is speed-independent, so that regardless of the current speed different operating conditions, in particular error types can be detected.
  • the processing for eliminating the speed increase is preferably carried out in such a way that the sampling frequency multiplied by the current speed and divided by a constant speed value, whereby the sampling frequency is practically related to this constant speed value, so that the further frequency analysis carried out without the influence of the current speed can be.
  • the vibration signal can be filtered in a low pass before being processed, for example in a 20th order Butterworth filter with a cutoff frequency of 40% of the processed sampling frequency.
  • the processing of the vibration signal takes place, if appropriate after passing through the low-pass filter, by resampling or changing the sampling rate with the sampling rate related to the constant speed.
  • the resampling can be done, for example, by filtering the time-discrete signal using a non-causal sine function as a pulse-response function.
  • the required speed of the shaft can be determined in various known ways, for example by speed sensor or directly from the vibration signal in the sense of a virtual speed sensor, such as in US 7,031,873 B2 is disclosed.
  • the speed signal from the vibration signal may also be made by downsampling to 128 Hz and then determining the ten highest excursions of the spectrum for each time window. The highest swings of the current time window are placed over those of the subsequent time window within certain limits. Subsequently, a speed history is recorded based on the coincidence of the deflections.
  • the thus prepared vibration signal is then subjected to filtering in which periodic signals are filtered out of the conditioned vibration signal. Based on these periodic signals, the vibration-related operating state of the pump unit or electric motor can then be detected. In particular, it is possible to detect such vibration-like operating conditions, which indicate errors, such as bearing failures.
  • the periodic signals can be detected, for example, in such a way that the amplitude of certain characteristic signals, in particular characteristic error signals is detected and then the time intervals between these amplitudes are measured. Based on the time intervals between the amplitudes can then be determined whether these are periodic signals or not.
  • the conditioned vibration signal is preferably subjected directly to a cepstral analysis for filtering out the periodic signals or signal parts. This means that no further transformations or evaluations of the vibration signal are made before the cepstral analysis.
  • the operating state or possible errors are subsequently detected by the cepstral graph generated by the cepstral analysis. Certain operating states are characterized by certain characteristics in the cepstral diagram, in particular errors can be detected.
  • Cepstral analysis is a double frequency analysis, i. the result of a frequency analysis is subjected to a repeated frequency analysis. In this case, periodic signal components are filtered out or extracted from the vibration signal.
  • cepstral analysis or cepstral transformation short-term cepstral analysis can be performed on the spectrogram of the vibration signal by performing frequency domain frequency analysis.
  • high-pass filtering of the frequency domain may be performed prior to performing the Fourier transform of the frequency domain.
  • the resulting cepstral domain will then preferably contain only bearing influences, no engine influences.
  • the evaluation of the cepstral diagram for detecting the operating states or errors is preferably carried out by a pattern recognition, which takes into account in particular at which points in the cepstral diagram rashes occur.
  • the recognition is preferably performed on the distribution or position of individual rashes in the cepstral diagram, less on the absolute values of the rashes.
  • the operating states are detected on the basis of previously known patterns in the periodic signals and in particular the cepstral diagram.
  • certain types of errors are e.g. the patterns of the occurring signals, d. H. the position or distribution of individual rashes known.
  • By comparing the current signal pattern or cepstral diagram with the known patterns it is then possible to conclude certain operating states or known error types.
  • previously known patterns can be used in two ways for detecting operating states. On the one hand, it is possible for the previously known patterns to correspond to specific operating states and specific types of errors to be detected, so that it can be recognized if such a pattern or similar occurs and then concludes that such an operating state or fault exists.
  • the prior art patterns desired i. correspond in particular to error-free operating states and a comparison is carried out in such a way that undesired operating states are recognized by the fact that patterns occur in the current periodic signals or in the cepstral diagram which do not correspond to the previously known patterns.
  • the previously known patterns can be factory-stored in an electronic control unit of a pump unit or electric motor.
  • the patterns which correspond to specific operating states, in particular fault-free nominal operating states, for example are automatically detected by the control or regulating electronics when the pump unit or the electric motor is put into operation. It is then preferably assumed that the pump unit or the electric motor after delivery and works faultlessly during commissioning.
  • the detection of operating states, in particular errors in selected sections of the cepstral diagram, which are preferably predetermined sections takes place.
  • the recognition in particular the pattern recognition, not the entire cepstral diagram is considered, but only a relevant section.
  • predetermined sections can be considered, in which usually certain characteristic signals occur at certain operating conditions, in particular errors. In order to be able to recognize these specific operating states, it is then not necessary to evaluate the entire cepstral diagram or cepstrum. There are thus section enlargements instead.
  • Recognition of vibrational operating conditions or errors on the basis of the cepstral diagram is furthermore preferably carried out by means of a neural network and / or a fuzzy logic.
  • a neural network and / or a fuzzy logic.
  • the evaluation can be adapted to different pumps or types of electric motors, which have different noise levels or different background noise. Because the deflections or signals are set in relation to these background noises, a uniform evaluation for different pumps or motor types can be carried out, since the evaluation takes place independently of the current noise level.
  • the invention is further achieved by a pump unit with an electric motor or by an electric motor, in which a device for carrying out an error detection according to the method described above is integrated.
  • Such a pump unit has an electric motor for its drive.
  • the electric motor or the pump unit has at least one rotating shaft about which rotates in a motor, the rotor or via which at least one impeller is driven in a pump unit.
  • an error detection system is integrated into the pump unit or the electric motor. This may include its own electronics or separate electronic components, but may also be integrated into electronic components, in particular microprocessors, that are present anyway for controlling or regulating the pump unit or electric motor, or use these.
  • the fault detection system has at least one vibration sensor and an evaluation device connected to the vibration sensor, wherein the evaluation device is preferably formed by one or more microprocessors.
  • the evaluation device is provided with a Aufbungsungsmodul, which is designed to eliminate the influence of the current speed of the shaft from a vibration signal detected by the sensor. This can be done in the manner described above by the method by the sampling rate is related to a constant speed and the vibration signal is then processed or resampled this sampling rate.
  • the editing module on predetermined computer structures, which can perform the corresponding calculations.
  • the error detection system further comprises a filter module which is adapted to receive periodic signals from that of filter out or extract the conditioned vibration signal. Furthermore, a detection module is provided, which is designed to be able to detect the vibration-related operating state of the pump unit or electric motor on the basis of the filtered-out periodic signals or signal components. In this case, an automatic recognition of certain operating conditions with respect to the vibrations occurring in the unit is performed in the detection module based on characteristic periodic signals. In particular, operating states can be detected, which suggest a faulty operation, for example, a bearing damage.
  • the evaluation device preferably has as filter module a cepstral analysis module, which is designed to carry out a cepstral analysis or cepstral transformation on the vibration signal prepared by the conditioning module in the manner described above.
  • the cepstral analysis module is a computer unit or a software component that performs the cepstral transformation or analysis of the vibration signal.
  • deep and / or high-pass filters can be integrated in front of the conditioning or the cepstral analysis module in order to eliminate interfering signal influences.
  • the evaluation device preferably has a recognition module, which is designed to detect operating states or errors on the basis of the cepstral diagram generated by the cepstral analysis module.
  • the recognition module can likewise be a hardware and / or software component of the rendering module, which is designed for the corresponding evaluation of the cepstral diagram.
  • the recognition module is designed such that, in the manner described above with reference to the method, it can recognize different operating states or errors from the cepstral diagram.
  • the recognition module preferably has fuzzy logic and / or a neural network in order to carry out the recognition on the basis of the cepstral diagram.
  • the evaluation device preferably has a memory module in which characteristic patterns of a periodic signal, in particular a cepstral diagram or sections of a cepstral diagram are stored for specific operating states, and the detection module is for detecting specific operating states on the periodic signal or cepstral diagram formed on the basis of the stored pattern.
  • the memory module can be a separate memory module, but it is also possible to share memory components which are present in any case in a control device of the pump unit or of the electric motor.
  • the recognition module compares the current signal patterns or cepstral diagrams or sections thereof with the previously known and stored patterns and recognizes, as soon as it identifies identity or similarities to the known patterns, the corresponding operating states. Via an output device can then be issued a message, in particular error message.
  • a warning light may be attached to the electric motor or the pump unit.
  • an error code or an error description in plain text can be output in a display. It is also conceivable to transmit the error type to an external evaluation device, for example a remote control, in order to be able to carry out a closer error evaluation here.
  • patterns may be stored which correspond to undesired operating states, for example characteristic errors. If the recognition module recognizes a corresponding pattern in the current signal, it can thus conclude such an undesired operating state.
  • the patterns can be stored at the factory.
  • a calibration module which is designed to detect the previously known patterns to be stored.
  • the calibration module can be designed in such a way that it can be used during commissioning, in particular during the first startup of the unit, i. of the pump unit or electric motor, detects the vibration-related operating state or detects various vibration-related operating states and deposits them as previously known patterns in the memory module. It is assumed that the unit operates essentially error-free during initial commissioning.
  • the calibration module can also be designed so that it can store patterns during later operation of the unit. So it is conceivable, for example, that the calibration module can be activated to store previously known patterns after a repair of the unit, if it works correctly.
  • the vibration sensor is preferably based on the mechanical structure of the Pump unit or the electric motor, arranged in a terminal box, within an array of electronic components and / or in a fluid line for a pump to be pumped by the fluid.
  • the vibration to be detected for example bearing errors or impeller errors in a pump unit
  • the arrangement of a vibration sensor within an assembly of electronic components or in a terminal box has the advantage that the wiring and assembly is simplified.
  • the vibration sensor with other electronic components can be dispensed with integrating additional sensors in the unit and then to wire control or display components in the terminal box. Furthermore, the sensor can be arranged protected in the terminal box. Overall, the assembly is considerably simplified, since the sensor can ideally be placed together with the other electronic components on a circuit board. Also, the vibration detection in a pumped by a pump unit fluid can be very beneficial, since this can be used a possibly anyway required pressure sensor, which dips into the fluid. For example impeller but possibly also bearing errors are transmitted as vibrations to the fluid to be delivered and can be detected by a sufficiently sensitive sensor also indirectly in the fluid here.
  • other electronic components such as a control device or a frequency converter
  • the signal transmission between the vibration sensor and the evaluation device is wireless, particularly preferably by radio.
  • the sensor can be placed very easily in the electric motor or pump set, the arrangement being preferably selected according to where the vibrations required for the evaluation can best be detected.
  • the cabling does not have to be considered.
  • the vibration sensor may be provided with a battery, but it is also conceivable that the required electrical energy is provided by energy conversion, for example of vibration or heat energy in the vibration sensor itself.
  • the evaluation device has a normalization module, which is designed to normalize the cepstral diagram generated by the cepstral analysis module, such that the deflections in the diagram are set in relation to the background noise as described above.
  • This standardization module can be integrated as a hardware component in the error detection system or can also be provided as a pure software component in this.
  • the fault detection system as a whole may be constructed by separate hardware components that provide the described functions. It is also conceivable here that all or individual functions or modules of the error detection system are designed as software components which are executed in a computer unit which has a microprocessor. For this purpose, a separate computer unit may be provided, but it is also conceivable that the software components are integrated into a computer unit, which simultaneously performs other functions in the electric motor or pump unit, for example, controls or regulates this.
  • a vibration measurement or a vibration signal detection takes place by means of a suitable sensor, for example an acceleration sensor, an optical sensor, a microphone or a hydrophone.
  • the output signal of this sensor or the vibration measurement is provided in steps 2 and 3.
  • step 2 there is a signal preparation or conditioning, in which the influence of the current speed of the motor shaft or the pump impeller, depending on the device in which the error detection system according to the invention is integrated, is minimized or eliminated.
  • This processing of the vibration signal is carried out by resampling with a sampling frequency, which is related to a constant predetermined speed.
  • the current sampling frequency is multiplied by the current speed and by a constant speed, for example, 3,000 Revolutions per minute, divided.
  • the vibration signal appears to have been recorded at this constant speed, so that the subsequent evaluation is independent of the current engine speed.
  • the vibration signal is further filtered by a low-pass filter before resampling is performed.
  • the required speed signal is supplied to the processing step 2 via the step 3.
  • the speed signal can be detected directly by suitable sensors (f s ), or, for example, in step 3 also directly determined from the detected vibration signal, as described for example in the patent US 7,031,873 is described.
  • step 4 filtering is performed in the form of cepstral analysis to extract periodic signals from the vibration signal.
  • cepstral analysis comprises a Fourier transform, wherein the Fourier spectrogram is subjected to frequency domain frequency analysis.
  • the advantage of such a cepstral analysis is that the characteristic noise of the motor or the pump unit is set to zero and so can be separated from a periodic signal.
  • cepstral analysis in order to exclude influences of the motor design, high-pass filtering of the frequency domain is performed before the frequency domain Fourier transform. The resulting cepstral domain then contains substantially no influences of engine noise.
  • step 5 begins the actual detection of operating conditions or errors.
  • Fig. 5 Figure 12 shows a cepstral chart (cepstrum) as generated in step 4 of the method.
  • cepstrum cepstral chart
  • This section can either be determined by where in the cepstrum rashes occur, or predetermined sections can be considered, in which, as is known, characteristic signals, in particular error signals are to be expected.
  • a normalization of the cepstrum or signal of in Fig. 6 selected section This standardization serves to exclude influences of different engine or aggregate sizes. Depending on the size and power of the unit, the resulting deflections differ. By normalization, these deflections are set in relation to the background noise that occurs, which is also different according to the performance of the unit. The fact that the curve or the deflections are set in relation to the background noise, the evaluation is independent of the current dimension of the engine or the unit, so that one and the same error detection system can be used for different sized units.
  • step 7 the average of the background noise is shown as line 10. This value is used to refer to the rashes or signals to be examined.
  • the actual recognition of the operating states or errors then takes place in step 7 by means of a neural network or fuzzy logic, where pattern recognition takes place.
  • the operating states are determined by the distribution of the individual deflections in the cepstral diagram. Ie. It does not depend on the absolute values of the rashes, but only where or when in which temporal repetition rates the rashes occur.
  • the patterns may be compared with previously stored patterns representing particular operating conditions to detect faults such as bearing or wheel damage. If an error is detected, this is then output in step 8 in a suitable manner. For this purpose, error signals can be transmitted to other control or control modules or acoustically or visually the error can be signaled.
  • Fig. 2 shows examples of ways that a vibration sensor 20 or 22 can be placed on the electric motor.
  • the sensor 20 is placed in a terminal box 24 disposed on the motor housing 26. This arrangement is very advantageous because the sensor is protected on the one hand in the terminal box 24 and on the other there can be very easily arranged with other electronic components. In addition, the cabling routes are short.
  • the sensor 22 is arranged directly on the mechanical structure of the electric motor 23, here on the motor housing 26.
  • the sensor 22 is preferably arranged as close as possible to the bearing of the motor shaft in order to be able to detect particularly well the vibrations or noises occurring in the bearing.
  • a sensor 28 can be arranged directly on a pump housing 30 in order to detect vibrations here.
  • a sensor 32 may be integrated into the pump housing 30.
  • a vibration sensor 34 on the outside to arrange on the connecting piece of a pump unit.
  • a sensor 36 in the connecting piece, ie in the flow, and to detect the vibrations indirectly via the fluid to be delivered.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
  • Control Of Positive-Displacement Pumps (AREA)
  • Control Of Non-Positive-Displacement Pumps (AREA)
  • Electrical Discharge Machining, Electrochemical Machining, And Combined Machining (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Structures Of Non-Positive Displacement Pumps (AREA)
EP07005995A 2007-03-23 2007-03-23 Procédé de détection de défauts dans des unités de pompage Active EP1972793B1 (fr)

Priority Applications (7)

Application Number Priority Date Filing Date Title
EP07005995A EP1972793B1 (fr) 2007-03-23 2007-03-23 Procédé de détection de défauts dans des unités de pompage
AT07005995T ATE474140T1 (de) 2007-03-23 2007-03-23 Verfahren zur detektion von fehlern in pumpenaggregaten
PL07005995T PL1972793T3 (pl) 2007-03-23 2007-03-23 Sposób wykrywania usterek w zespołach pompowych
DE502007004387T DE502007004387D1 (de) 2007-03-23 2007-03-23 Verfahren zur Detektion von Fehlern in Pumpenaggregaten
US12/532,284 US8401806B2 (en) 2007-03-23 2008-02-23 Method for the detection of errors in pump units
CN200880008952.0A CN101636589B (zh) 2007-03-23 2008-02-23 用于检测泵机组中的故障的方法及检测系统
PCT/EP2008/001449 WO2008116538A1 (fr) 2007-03-23 2008-02-23 Procédé de détection de défauts dans des groupes de pompage

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP07005995A EP1972793B1 (fr) 2007-03-23 2007-03-23 Procédé de détection de défauts dans des unités de pompage

Publications (2)

Publication Number Publication Date
EP1972793A1 true EP1972793A1 (fr) 2008-09-24
EP1972793B1 EP1972793B1 (fr) 2010-07-14

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Application Number Title Priority Date Filing Date
EP07005995A Active EP1972793B1 (fr) 2007-03-23 2007-03-23 Procédé de détection de défauts dans des unités de pompage

Country Status (7)

Country Link
US (1) US8401806B2 (fr)
EP (1) EP1972793B1 (fr)
CN (1) CN101636589B (fr)
AT (1) ATE474140T1 (fr)
DE (1) DE502007004387D1 (fr)
PL (1) PL1972793T3 (fr)
WO (1) WO2008116538A1 (fr)

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WO2015197141A1 (fr) 2014-10-15 2015-12-30 Grundfos Holding A/S Procédé et système pour détection de défauts dans un ensemble de pompe à l'aide d'un dispositif de communication portable
WO2016146967A1 (fr) * 2015-03-18 2016-09-22 Edwards Limited Appareil et procédé de surveillance d'une pompe
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US11761909B2 (en) 2021-05-28 2023-09-19 Saudi Arabian Oil Company Nanosensor coupled with radio frequency for pump condition monitoring
US11828160B2 (en) 2021-05-28 2023-11-28 Saudi Arabian Oil Company Vibration monitoring and data analytics for vertical charge pumps
US11795960B2 (en) 2021-05-28 2023-10-24 Saudi Arabian Oil Company Molten sulfur pump vibration and temperature sensor for enhanced condition monitoring
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DE3520734A1 (de) 1985-06-10 1986-12-11 Kraftwerk Union AG, 4330 Mülheim Verfahren und einrichtung zum betrieb einer kreiselpumpe
GB2298239A (en) 1995-02-21 1996-08-28 Inst Francais Du Petrole Regulating multiphase pump unit
WO1997008459A1 (fr) 1995-08-30 1997-03-06 Baker Hughes Incorporated Pompe electrique submersible amelioree et procedes pour une meilleure utilisation de pompes electriques submersibles dans la completion et l'exploitation des puits de forage
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DE102013017828A1 (de) * 2013-10-24 2015-04-30 Fresenius Medical Care Deutschland Gmbh Verfahren und Vorrichtung zur Überwachung einer in einem extrakorporalen Blutkreislauf oder einer in einem Dialysatkreislauf angeordneten Impellerpumpe und Blutbehandlungsvorrichtung
DE102013017828B4 (de) * 2013-10-24 2015-05-13 Fresenius Medical Care Deutschland Gmbh Verfahren und Vorrichtung zur Überwachung einer in einem extrakorporalen Blutkreislauf oder einer in einem Dialysatkreislauf angeordneten Impellerpumpe und Blutbehandlungsvorrichtung
US10125772B2 (en) 2013-10-24 2018-11-13 Fresenius Medical Care Deutschland Gmbh Method of monitoring an impeller pump used in a medical application
WO2015197141A1 (fr) 2014-10-15 2015-12-30 Grundfos Holding A/S Procédé et système pour détection de défauts dans un ensemble de pompe à l'aide d'un dispositif de communication portable
WO2016059112A1 (fr) * 2014-10-15 2016-04-21 Grundfos Holding A/S Procédé et système de détection de défaillances dans un ensemble pompe à l'aide d'un dispositif de communication portable
CN107076155A (zh) * 2014-10-15 2017-08-18 格兰富控股联合股份公司 用于通过手持通信装置检测泵组件中的故障的方法和系统
US10316849B2 (en) 2014-10-15 2019-06-11 Grundfos Holding A/S Method and system for detection of faults in pump assembly via handheld communication device
WO2016146967A1 (fr) * 2015-03-18 2016-09-22 Edwards Limited Appareil et procédé de surveillance d'une pompe
US10670016B2 (en) 2015-03-18 2020-06-02 Edwards Limited Pump monitoring apparatus and method
WO2020094334A1 (fr) 2018-11-05 2020-05-14 Grundfos Holding A/S Agencement de capteur et procédé de surveillance d'un système de pompe de circulation
US11811270B2 (en) 2019-03-06 2023-11-07 Ebm-Papst Mulfingen Gmbh & Co. Kg Device for continuous oscillation monitoring during rotating field machine operation
EP4361582A1 (fr) 2022-10-24 2024-05-01 Wilo Se Procédé d'inspection de l'état d'un groupe motopompe ainsi qu'application logicielle, support de stockage et appareil d'inspection pour la mise en oeuvre du procédé

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ATE474140T1 (de) 2010-07-15
PL1972793T3 (pl) 2010-12-31
CN101636589A (zh) 2010-01-27
DE502007004387D1 (de) 2010-08-26
EP1972793B1 (fr) 2010-07-14
US8401806B2 (en) 2013-03-19
WO2008116538A1 (fr) 2008-10-02
US20100082275A1 (en) 2010-04-01
CN101636589B (zh) 2014-10-01

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