Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
  • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
  • F03D—WIND MOTORS
  • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
  • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
  • F16C17/00—Sliding-contact bearings for exclusively rotary movement
  • F16C17/12—Sliding-contact bearings for exclusively rotary movement characterised by features not related to the direction of the load
  • F16C17/24—Sliding-contact bearings for exclusively rotary movement characterised by features not related to the direction of the load with devices affected by abnormal or undesired positions, e.g. for preventing overheating, for safety
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
  • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
  • F16C41/00—Other accessories, e.g. devices integrated in the bearing not relating to the bearing function as such
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
  • G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
  • G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
• • 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
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
  • G01N29/04—Analysing solids
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
  • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
  • F16C2233/00—Monitoring condition, e.g. temperature, load, vibration
• • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
  • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
  • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
  • Y02E10/00—Energy generation through renewable energy sources
  • Y02E10/70—Wind energy
  • Y02E10/72—Wind turbines with rotation axis in wind direction

Definitions

• the present invention relates to a method for Studentswa ⁇ Chen an operating condition of a sliding bearing. Moreover be ⁇ , the present invention applies to a measuring arrangement for monitoring an operating condition of a plain bearing. Finally, the present invention relates to a sliding bearing assembly.
• Lubricant are detected. Moreover, the load torque can also be examined to monitor the operating state. Oscillations of the wave can be detected by analyzing vibrations in the low-frequency range.
• the friction bearing condition can not be detected with the above-described methods ⁇ nen however directly. Also, particles that are generated in the bearing and remain there can not be detected.
• the monitoring of the temperature of the sliding bearing is linked to many dependencies that prevent a reliable diagnosis of the sliding bearing. In addition, the damage to the plain bearing and particles in bearings are not directly detectable. Furthermore, that sinks Load moment under circumstances with increasing friction in the camp and thus can not be regarded as a reliable measuring means for Di ⁇ agnose the sliding bearing.
• sinks Load moment under circumstances with increasing friction in the camp and thus can not be regarded as a reliable measuring means for Di ⁇ agnose the sliding bearing.
• the inventive method for monitoring an operating condition of a plain bearing includes acquiring reco ⁇ th, characterize the acoustic emissions in the sliding bearing, with a sensor element which is mechanically coupled to the slide bearing, calculating a characteristic value on the basis of measured values acquired and the Classifying the operating condition of the sliding bearing as a function of the characteristic value.
• the sensor element which is connected to the slide bearing or a Ge ⁇ housing of the sliding bearing so that the Schallemis ⁇ ions transmitted via structure-borne noise to the sensor element who ⁇ can, the sound emissions can be detected.
• the sensor element can be designed as an acceleration sensor, pressure sensor or in the manner of a strain gauge. Ins ⁇ particular, the sensor element is designed as a micromechanical sensor.
• a characteristic value can be calculated with the aid of a computing device from the time profile of the measured values, which is detected by the sensor element.
• the classification of the Gleitla ⁇ gers can be performed automatically with the computing device.
• predetermined operating states and the associated characteristic values can be stored in the computing device or a corresponding memory device of the computing device.
• the operating conditions can be associated with a ⁇ from utilization, damage or wear of the bearing.
• the operating conditions may relate to a state of the lubricant in the sliding bearing or contamination of the lubricant by particles. In this case, the extent of contamination or the size, number or the material of the particles can be considered.
• ⁇ NEN the operating states of different friction conditions of sliding bearing such as a wear-rich mixed friction or low wear viscous be associated Kgs.
• the characteristic value is calculated as a function of a maximum value and / or an effective value of the measured values.
• the characteristic value can be calculated as a function of the maximum value and / or the effective value of the measured values for a predetermined time range or a time window.
• the characteristic value can also be calculated as a logarithmic measure. It is also conceivable to use a reciprocal characteristic value.
• the product of the maximum value and the effective value can also be used as the characteristic value.
• Measured values are calculated.
• the reference values can be determined in a simple manner, since these values are only very slightly dependent on the rotational speed, the temperature of the lubricant and the bearing load in the desired operation in fluid friction.
• the characteristic value is calculated on the basis of an envelope signal determined from the measured values.
• an envelope signal can be determined, for example, by rectification and low-pass filtering of the measured values.
• the envelope signal can be determined by calculating a moving effective value or a moving average of the measured values.
• Another possibility is to determine the envelope signal by a Hilbert transform.
• the characteristic value is preferably calculated on the basis of a frequency spectrum of the envelope signal.
• a frequency analysis for example by a Fast Fourier Transformation (FFT) of the envelope signal, the perio ⁇ disch recurring signals and pulses in the measured values or the acoustic emission signals can be determined.
• FFT Fast Fourier Transformation
• the characteristic value is calculated from a correlation of the measured values.
• the characteristic value can be calculated from the correlation or autocorrelation of the measured values.
• By varying the time window different frequency ranges of the measured values can be investigated .
• a similar correlation methods can also be used for frequency analysis of the measured values, the special ⁇ when the frequencies to be tested are known. This results in a simple and fast algorithm and the signal-to-noise ratio, in particular when averaging over several shaft revolutions, can thereby be significantly improved.
• the measuring arrangement according to the invention for monitoring a Be ⁇ operating condition of a plain bearing includes a sensor element for detecting measured values which characterize the acoustic emissions in the slide bearing, wherein mechanical coupling with the sliding bearing and a computing device which is designed to use the detected with the sensor unit measuring values a characteristic value to calculate and the operating state of
• the measuring arrangement comprises an amplifier element for amplifying the detected measured values, a filter element for filtering the measured values amplified by the amplifier element and an analog-to-digital converter which is coupled to an input of the computing device.
• the sensor element can detect the noise emissions in the sliding bearing.
• the output signal of the sensor element which is present for example as electrical voltage or electric current, can be raised or amplified by the amplifier element.
• the ver ⁇ amplified signal is adjusted with an analog filter element of troublefree ⁇ leaders or non-relevant frequency bands before being fed to the analog-digital converter. Through this Order, the signal-to-noise ratio can be improved.
• the filter element can also be used to determine an envelope curve ⁇ signal from the measured values.
• the computing device can be designed as a PC or microprocessor. With the computing device, the information compression can be performed by feature extraction and characteristic value formation.
• the sensor element, the amplifier element, the filter element, the analog-to-digital converter and the computing device are arranged in a common housing.
• the susceptibility can be reduced.
• the plain bearing arrangement according to the invention comprises a sliding bearing and a previously described measuring arrangement, which is connected to the
• Plain bearing is mechanically coupled. With Gleitlageranord ⁇ tion wear phenomena of the plain bearing can be detected early.
• the operating conditions of mixed friction and fluid friction can be distinguished in a simple manner. The identification of the operating state can take place independently of the bearing load and the shaft speed.
• the condition of the lubricant and impurities or particles can be detected in the Schmiermit ⁇ tel. For new hydrodynamic bearings or solid friction bearings, it is possible to monitor the run-in process and to assess the extent to which it has been completed.
• 1 shows a slide bearing arrangement in a perspective view
• 2 shows a schematic representation of steps one
• FIG. 3 shows a measuring arrangement in a first embodiment
• 4 shows a measuring arrangement in a second embodiment
• FIG. 5 shows a measuring arrangement in a third embodiment
• the slide bearing assembly 10 includes a slide bearing 12 which carries a shaft 14.
• the sliding bearing 12 is arranged in a housing 16.
• the Gleitla ⁇ geran Aunt 10 includes a port 18 through which the sliding bearing 12, a lubricant, in particular an oil, is supplied.
• a measuring arrangement 20 is arranged on the housing 16 of the sliding bearing 12.
• the measuring arrangement 20 is arranged directly on the housing 16. Thus, acoustic emissions generated in the slide bearing 12, are transmitted via acoustic emission to an in FIG 1 is not notified Darge ⁇ sensor element 22nd
• the sensor element 22, which is located within the measuring arrangement 20, is designed to detect sound emissions with frequencies in the ultrasonic range, which are also referred to as acoustic emission.
• the sensor element 22 is designed to detect sound emissions in the range from 50 kHz to 150 kHz.
• the sensor element 22 may be formed as Accelerat ⁇ n Trentssensor or as a pressure sensor.
• the sensor device may be designed in the manner of a strain gauge.
• the sensor element 22 is designed as mik ⁇ romechanischer sensor, which may include, for example, a seismic mass.
• the sensor element 22 may comprise a piezoelectric sensor element.
• 2 shows a schematic representation of a method for monitoring of operating conditions of a plain bearing 12.
• an external DEMANDS ⁇ monitoring of the sliding bearing is made in step S10 12. This can be provided for example by the ingress of particles or impurities in the sliding bearing 12th
• the external stress on the sliding bearing 12 S12 mechanical stresses occur in one step in the material of the sliding bearing 12. This mechanical ⁇ rule voltages stimulate Acoustic emission sources
• Step S14 high-frequency sound emissions or structure-borne noise are generated in the material of the sliding bearing 12 and propagate in the sliding bearing 12 in step S16.
• the frequencies of the sound emissions are dependent on the material and are usually in the range of 50 to 150 kHz.
• step S18 the sound emissions are detected with the sensor element of the measuring arrangement 20. He then be ⁇ follows in a step S20, an information compression by feature extraction and characteristic value calculation. In step S22, an evaluation of the data takes place. Finally, in a step S24, a classification of the operating state of the sliding bearing 12 is performed.
• FIGS. 3, 4 and 5 each show a measuring arrangement 20 in various embodiments.
• Each of the measuring arrangements 20 comprises a sensor element 22, with which sound emissions in the sliding bearing 12 are detected as a time course of measured values in the case of mechanical coupling with the sliding bearing 12.
• the output signal is amplified by the Verstär ⁇ kerelement 24th
• the amplified signal is corrected with an analog filter element 26 of interfering or irrelevant frequency bands before it is sent to the analog-digital converter.
• the filter element can also be used to determine an envelope signal from the measured values by rectification and low-pass filtering.
• the digitized measured values are transmitted to a computing device 30, which may be designed as a PC or microprocessor.
• a characteristic value is calculated from the time profile of the measured values. Based on this characteristic, the operating state of the plain bearing 12 can be classi ⁇ fied.
• the classification of the sliding bearing 12 can also be carried out automatically with the computing device 30.
• the wear of the sliding bearing 12 can be determined.
• the condition of the lubricant in the sliding bearing 12 or contamination of the lubricant by particulates may be detected.
• the different ⁇ friction states of the friction bearing 12, such as a wear-rich mixed friction or a wear ⁇ schl constitutionarme fluid friction can be determined.
• the sensor element 22 is arranged separately, for example in a housing. This is illustrated by the bracket 32.
• the signal processing is carried out (illustrated by the bracket 34).
• the processing of the signal represented by the bracket 36 is performed in the computing device 30.
• the amplifier element 24 is integrated in the sensor element 22.
• an integrated sensor (bracket 38) is realized, which has the advantage of lower susceptibility.
• the further signal processing by the filter element 26 and the analog-to-digital converter 28 can be done in a further module, which is indicated by the bracket 34.
• the acquisition of the measured values, the amplification, the filtering, digitalization are carried out. tion and processing in a diagnostic module, which is indicated by the bracket 40.
• the sensor element 22, the amplifier element 24, the filter element 26, the analog-digital converter 28 and the computing device 30 are arranged in a common housing. This variant has a ⁇ be Sonder low susceptibility to interference.

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Engineering & Computer Science (AREA)
• General Physics & Mathematics (AREA)
• Mechanical Engineering (AREA)
• Chemical & Material Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Acoustics & Sound (AREA)
• General Health & Medical Sciences (AREA)
• Analytical Chemistry (AREA)
• Immunology (AREA)
• Pathology (AREA)
• Biochemistry (AREA)
• Health & Medical Sciences (AREA)
• Sustainable Development (AREA)
• Sustainable Energy (AREA)
• Combustion & Propulsion (AREA)
• Signal Processing (AREA)
• Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Applications Claiming Priority (1)

Publications (1)

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ID=45999829

Family Applications (1)

Country Status (4)

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• 2012
  • 2012-04-19 WO PCT/EP2012/057177 patent/WO2013156068A1/de active Application Filing
  • 2012-04-19 US US14/394,042 patent/US20150059478A1/en not_active Abandoned
  • 2012-04-19 CN CN201280072437.5A patent/CN104246247B/zh not_active Expired - Fee Related
  • 2012-04-19 EP EP12716393.9A patent/EP2805072A1/de not_active Withdrawn

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