EP1872107A1 - Procede et appareil permettant de categoriser des dommages sur un roulement - Google Patents

Procede et appareil permettant de categoriser des dommages sur un roulement

Info

Publication number
EP1872107A1
EP1872107A1 EP06722734A EP06722734A EP1872107A1 EP 1872107 A1 EP1872107 A1 EP 1872107A1 EP 06722734 A EP06722734 A EP 06722734A EP 06722734 A EP06722734 A EP 06722734A EP 1872107 A1 EP1872107 A1 EP 1872107A1
Authority
EP
European Patent Office
Prior art keywords
signal
analysis
function
feature
values
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.)
Withdrawn
Application number
EP06722734A
Other languages
German (de)
English (en)
Inventor
Jens Strackeljan
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.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
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 Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP1872107A1 publication Critical patent/EP1872107A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • 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
    • F16C19/00—Bearings with rolling contact, for exclusively rotary movement
    • F16C19/50—Other types of ball or roller bearings
    • 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

Definitions

  • the invention relates to a method for 'categorizing damage to an integrated device in a rolling bearing, comprising the steps of:
  • the invention further relates to a measuring and analyzing device for categorizing damage to a rolling element bearing integrated in a device, comprising a sensor for recording a signal representing structure-borne noise oscillations of the device, a digital data memory for storing the recorded signal,
  • a digital arithmetic unit for processing the stored signal a digital program memory for storing instructions, rules and default values for controlling the processing of the stored signal, output means for outputting a result of the processing of the stored signal, wherein the instructions, rules and default values stored in the program memory are adapted to perform an analysis of the stored signal according to at least one predetermined signal feature, assign the stored signal to a predetermined damage category based on the analysis result and have that damage category output as a result of the processing by the output means.
  • Detecting and categorizing damage to rolling bearings integrated into devices such as motors, machines, pumps, etc. is an essential measure to ensure safe operation of the devices and to avoid major damage such as bearing failure, rough running shafts and axes etc. can arise. It is of ' great economic importance that for the detection and categorization of the damage to be examined warehouse does not have to be removed from the device and disassembled in order to be made available to a, for example, optical inspection.
  • the analysis comprises a statistical evaluation of an inferred from the recorded signal analysis function of the signal to determine the expression of the predetermined signal characteristics, wherein the analysis function a Derivative level of the signal representing the jerk of the signal Body chord vibration equals or is a higher derivative level.
  • the basic idea of the present invention is to carry out a statistical evaluation of the so-called "jerk”, ie the second time derivative of the velocity-proportional structure-borne sound signal, or a higher derivative step, in order to base the damage categorization on this, which corresponds in principle to a special investigation of properties of the extrexvalue ranges Empirically, it has been shown that it is precisely the information content in the region of the extreme values of the velocity-proportional structure-borne sound signal that is characteristic for various types of bearing damage.
  • a connection can indeed be made by the idea of micro-impacts that a rolling element experiences and in the case of smooth bearing shells very briefly and roughened, ie pre-damaged bearing shells, are longer, roughly illustrated, but a detailed physical model for this relationship is not known. Rather, the knowledge of the relationship between the shape of the extreme value ranges in the speed-proportional signal and the damage category must be regarded as a surprising discovery. This discovery takes advantage of the present invention in an advantageous manner.
  • the method according to the invention which considers a statistical analysis of the jerk, has various advantages.
  • the structure-borne sound vibrations of the current device it is possible, but not necessary, for the structure-borne sound vibrations of the current device to be proportional to the speed detect.
  • a deflection or acceleration-proportional signal measurement can also be realized.
  • the relevant jerk would be calculated in these cases as the third or the first time derivative of the recorded signal.
  • the method according to the invention has the advantage that a statistical analysis of a signal is much simpler and less complicated to compute than the separate examination of a large number of individual extreme values in a speed-proportional time signal.
  • signal feature is to be understood as a general property, that is, a function of the signal under consideration, whereas, under "expression” of a signal feature in the context of this description, the concrete property, i. the special values of the function are understood by the signal that has been specifically examined.
  • an average of analysis function values, ie of specific values of the calculated jerk, at the locations of local extreme values of a velocity function derived from the recorded signal is a predetermined signal feature.
  • the velocity function is therefore equal to the recorded signal, however, in the case of a displacement-proportional measurement, the velocity signal is calculated from the first time derivative of the recorded signal or with acceleration-proportional measurement from the first temporal integration of the recorded signal.
  • a mean value is formed over those values of the jerk that correlate in time with the local extreme values of the velocity function.
  • a frequency distribution of analysis function values at the locations of local extreme values of a speed function derived from the recorded signal is a predetermined signal characteristic.
  • a histogram of the jerk values at the points of the speed extrema is calculated and used for the damage categorization. Since such a histogram has a greater information content than a simple average, it is understood that a finer subdivision of different damage categorizations can be made with this embodiment.
  • a fluctuation of distances of adjacent locations of local extreme values of the speed function is an additional predetermined signal feature.
  • This value which may for example correspond to the statistical variance of the extrema distances, is preferably derived directly from the
  • the distance determination can be carried out between next adjacent extreme values of the same or opposite sign or between less closely adjacent extreme values of the same or opposite sign. Preferably, the distance determination between next adjacent extreme values of the same sign in each case.
  • a frequency distribution of values of distances of adjacent locations of local extreme values of the speed function is an additional predetermined signal feature.
  • the calculation of a histogram of the extrema distances is proposed, which can lead to a finer differentiation between different types of damage. Note, however, that calculating a histogram involves significantly more computational effort than calculating a single value and this additional effort must be in a reasonable relationship to the achievable advantage of a finer categorization.
  • the number of local extreme values of the speed function with absolute values above a predetermined threshold value is an additional predetermined signal characteristic.
  • This essentially corresponds to an amplitude analysis of the speed signal.
  • the absolute value determination is advantageously preceded by normalization of the speed function, favorably with the effective value of the speed function. This standardization leads to an independence of the method from the absolute "volume" of the recorded structure-borne sound signal.
  • the actual damage classification ie the assignment of the measured signal to a damage category, takes place after the determination of the specific characteristics of the selected signal characteristic (s).
  • the assignment preferably takes place on the basis of a defined metric in a multi-dimensional feature space.
  • the signal to be assigned is classified according to its characteristics of the feature space spanning the feature space in the feature space, and the distance, calculated according to the defined metric, is calculated to predetermined points or areas representing the damage category in the multi-dimensional space. This means that in the multi-dimensional feature space empirically or computationally determined points or areas represent certain categories of damage, of which the recorded signal is to be assigned to a concrete. This.
  • the signal space spanning the feature space may be divided into generalized units and the distance defined as n-dimensional Euclidean metric.
  • the special transformation of the signal characteristics to the generalized units of the feature space can be chosen so that the respective significance of the feature for a category distinction is taken into account.
  • the signal is preferably assigned to the damage category to which its distance in the feature space according to the defined metric is minimal.
  • the distance minimum value can not be uniquely determined. This can occur, in particular, when tolerances are allowed during the distance determination, for example to take into account measurement inaccuracies. Then it can happen that two or more calculated distances are within the permissible tolerances and thus a definite minimum can not be determined.
  • the feature space is extended by at least one feature dimension and a new classification and distance determination of the signal takes place. This corresponds to the refinement of categorization by additional consideration of a further signal feature.
  • the arithmetic unit can be designed as a specially equipped microprocessor, in particular a specially programmed DSP (digital signal processor), wherein the individual instructions and rules can be implemented in software or hardware.
  • DSP digital signal processor
  • the default values, ie in particular the comparison values required for the categorization, can be implemented in a separate database, preferably in software. It is particularly advantageous if the database can be expanded by taking concrete measurements.
  • machines to be checked for rolling bearing damage include several rolling bearings of the same and / or different types.
  • the measurement according to the invention can then be at several points of the machine surface by lead, wherein in each case that rolling bearing which is most efficient acoustically coupled to the measurement point, most to ⁇ the recorded signal contributes.
  • Figure 1 a schematic representation of a measuring and • analysis device according to the invention
  • FIG. 2 shows a schematic sketch to illustrate different rolling bearing damage categories
  • ⁇ FIG. 3 a schematic representation of the categorization of a measured rolling bearing damage in a two-dimensional feature space.
  • Figure 1 shows a schematic representation of a measuring and analyzing device for categorizing Wälzlager sea.
  • the overall device comprises a hand-held portable device 10 and a connectable sensor 20.
  • the sensor is attached to the surface 30 of the device (s) containing the bearing (s).
  • the senor 20 essentially consists of a permanent magnet 22 on which a spiral coil 24 is applied, for example glued.
  • the sensor adheres to a surface 30 of a machine to be examined with integrated rolling bearings, which are not shown in Figure 1.
  • structure-borne sound vibrations of the surface 30 are generated, to which the rolling bearing movements also contribute.
  • the structure-borne sound vibrations are shown schematically as waves of the surface 30 (solid and dashed).
  • the adhesion of the sensor 20 to the surface 30 is preferably effected by a ferromagnetic surface 30 by the force of the permanent magnet 22.
  • the constant magnetic field of the permanent magnet 22 passes through the coil 24, which is insulated from the surface 30, and the surface 30 itself.
  • the vibrations of the surface 30 distort the magnetic field lines 40, so that the coil 24 is in a time-varying magnetic field. which leads to the induction of a voltage Ui nd .
  • the voltage u ina represents a velocity-proportional representation of the vibrations of the surface 30.
  • the voltage U in a is digitized by means of an A / D converter 11 and sent to a microprocessor, ⁇ p, 12 for further processing.
  • the microprocessor 12 communicates with both a data memory, MemD, 13, in which the recorded signal can be stored, as well as with a program memory, MemP, 13, are stored in the rules, instructions and default values for processing the recorded signal.
  • the result of the data processing is displayed to the user on an output 15 (out), which may be realized in the form of a conventional screen display, as light signals in a special display panel or otherwise.
  • a / D converter 11, microprocessor 12, the memories 13 and 14, which may be separate or unitary, and the output 15 are integrated in a portable handset (dashed box).
  • the connection to the sensor 20 is realized as a cable connection, preferably as a coaxial cable connection.
  • FIG. 2 shows in a highly schematized and simplified manner two different types of rolling bearing damage categories in order to suggestively illustrate the relationship between damage category and the concrete formation of extreme values in the recorded speed signal. Note, however, that this is not a physical model, but merely an attempt to illustrate.
  • a rolling element 50 which may be formed, for example, as a ball or roller, rolls on the surface of a bearing shell 60.
  • the bearing shell surface 60 has very small bumps 61, while in the case of FIG. 2 b it has wider and higher bumps 62.
  • the micro-shocks that result when rolling over the unevenness by the rolling body 50 are very short, whereas in the case of 2b, they are much longer. This results in a change in the shape of the extreme values of the velocity-proportional signal.
  • FIG. 3 shows a simplified representation of the actual damage categorization.
  • a received signal is analyzed according to a plurality of signal characteristics m 1 and m 2 (in the illustrated case only two) and positioned in the feature space spanned by m 1 and m 2.
  • the current signal is shown as an asterisk 70.
  • a plurality of points 72 are further positioned, each representing an earlier measured signal associated with a known damage category. It has been found that the analysis method according to the invention is suitable, Delimit damage categories as areas in the feature space. In the example shown, three areas A, B and C are shown.
  • the distances between the signal 70 and the points 72 or in each case one point representative of an area A, B, C are measured and compared.
  • the signal 70 is then assigned to the damage category to which the distance is minimal, in this example category A.
  • the embodiments illustrated in the specific description and the figures represent only illustrative embodiments of the present invention.
  • the dimensionality of the feature space depends on the desired fineness of the categorization.
  • the sensor 20 described above, in its illustrated embodiment is not a prerequisite for the invention. Rather, any type of sensor capable of generating a body sound vibration signal can be used.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Mechanical Engineering (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

L'invention concerne un procédé ainsi qu'un appareil de mesure et d'analyse permettant de catégoriser des dommages sur un roulement. L'invention se caractérise en ce que l'analyse précédant la catégorisation comprend une évaluation statistique de la 'saccade' d'un signal de bruits d'impact, auquel contribue le mouvement du roulement à examiner.
EP06722734A 2005-04-04 2006-03-31 Procede et appareil permettant de categoriser des dommages sur un roulement Withdrawn EP1872107A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102005015465.4A DE102005015465B4 (de) 2005-04-04 2005-04-04 Verfahren und Gerät zum Kategorisieren von Wälzlagerschäden
PCT/DE2006/000583 WO2006105767A1 (fr) 2005-04-04 2006-03-31 Procede et appareil permettant de categoriser des dommages sur un roulement

Publications (1)

Publication Number Publication Date
EP1872107A1 true EP1872107A1 (fr) 2008-01-02

Family

ID=36579386

Family Applications (1)

Application Number Title Priority Date Filing Date
EP06722734A Withdrawn EP1872107A1 (fr) 2005-04-04 2006-03-31 Procede et appareil permettant de categoriser des dommages sur un roulement

Country Status (4)

Country Link
US (1) US20080195333A1 (fr)
EP (1) EP1872107A1 (fr)
DE (1) DE102005015465B4 (fr)
WO (1) WO2006105767A1 (fr)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102009009308A1 (de) 2009-02-17 2010-08-19 Robert Bosch Gmbh Linearbewegungsvorrichtung mit Abtastvorrichtung
DE102009016161B4 (de) 2009-04-03 2023-11-16 Schaeffler Technologies AG & Co. KG Vorrichtung zur Geräuschprüfung eines Radiallagers
DE102009024981A1 (de) 2009-06-16 2010-12-23 Schaeffler Technologies Gmbh & Co. Kg Verfahren zur Ermittlung und Analyse von Schäden an umlaufenden Maschinenelementen
DE102015201121A1 (de) 2015-01-23 2016-07-28 Robert Bosch Gmbh Schadenszustandsermittlung bei einer Linearbewegungsvorrichtung
WO2017021984A1 (fr) * 2015-07-31 2017-02-09 Stanley Works (Europe) Gmbh Dispositif et procédé pour surveiller un outil
DE102022100439A1 (de) 2022-01-11 2023-07-13 Berger Holding GmbH & Co. KG Technik zur Messung des Verschleißes eines Kugelgewindetriebs

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JPS58150859A (ja) * 1982-03-03 1983-09-07 Hitachi Ltd 回転体の亀裂診断装置
JPS6219755A (ja) * 1985-07-19 1987-01-28 Hitachi Ltd Ａｅ方式回転機異常診断システム
EP0297729B1 (fr) * 1987-06-03 1992-10-21 Koyo Seiko Co., Ltd. Dispositif pour la détection de défauts dans des paliers
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DE4017449A1 (de) * 1989-06-05 1990-12-06 Siemens Ag Verfahren zur diagnose der mechanischen eigenschaften von maschinen
JPH068774B2 (ja) * 1989-06-10 1994-02-02 高砂熱学工業株式会社 ベアリングの余寿命推定方法
US5210704A (en) * 1990-10-02 1993-05-11 Technology International Incorporated System for prognosis and diagnostics of failure and wearout monitoring and for prediction of life expectancy of helicopter gearboxes and other rotating equipment
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DE19721364A1 (de) * 1997-05-22 1998-11-26 Asea Brown Boveri Verfahren zum Schutz vor Vibration bei Rotationsmaschinen
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US20050072234A1 (en) * 2003-05-20 2005-04-07 Weidong Zhu System and method for detecting structural damage
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Also Published As

Publication number Publication date
WO2006105767A1 (fr) 2006-10-12
DE102005015465A1 (de) 2006-10-12
DE102005015465B4 (de) 2014-02-20
US20080195333A1 (en) 2008-08-14

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