Method and apparatus for determining the wear condition of a large rolling bearing
Patent Information
- Authority / Receiving Office
- DE · DE
- Patent Type
- Patents
- Current Assignee / Owner
- THYSSENKRUPP AG
- Filing Date
- 2022-07-07
- Publication Date
- 2026-07-09
AI Technical Summary
Existing methods for monitoring the wear of large roller bearings, such as slewing bearings in cranes, struggle to distinguish between load-induced deformation and wear, requiring significant effort and providing unclear distinctions in measurement data filtering.
A method involving reference and condition measurements of gap changes between bearing rings, using sensors to record data sets with operating parameters, dividing them into discrete intervals, and applying an evaluation algorithm to compare mean values within these intervals to isolate wear-induced gap changes.
Accurately determines the wear condition of large roller bearings by isolating wear-related gap changes, enabling timely maintenance and reducing unplanned downtime of the overall device.
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Abstract
Description
[0001] The invention relates to a method according to the preamble of claim 1.
[0002] Such a method is known from European patent EP 3 507 513 B1. In this known method, two contactless measuring sensors are used. The sensors are preferably arranged in a stationary (i.e. non-rotating) first bearing ring. Both sensors have a sensor surface. One of the sensors (referred to as the “second sensor” in EP 3 507 513 B1) measures the distance between its sensor surface and a reference surface formed on the second bearing ring. The other sensor (referred to as the “first sensor” in EP 3 507 513 B1) is arranged opposite a step-shaped reference edge and is provided for measuring the degree of overlap of its sensor surface with the reference edge.
[0003] In the method according to EP 3 507 513 B1, during operation of the bearing, in particular during rotation of the second bearing ring relative to the first bearing ring, the degree of overlap of its sensor surface with the reference edge is measured with the first sensor, and the distance of its sensor surface from the reference surface is measured with the second sensor.
[0004] The problem with this known method is that the changes in distance or degree of contact measured by the sensors are caused by several overlapping influencing factors. One part of the measured changes is caused by the elastic deformation of the bearing rings, which is caused by the operational loads (forces, bending moments) present at the time of measurement. Another part of the measured changes is caused by the wear of the slewing bearing. It is not easily possible to separate the part attributable to the load-induced deformation of the bearing rings from that caused by wear. EP 3 507 513 B1, particularly in claim 8 and in paragraphs
[0022] and
[0023] , does specify measures for distinguishing bearing wear from load-induced deformation of the bearing rings.However, these measures involve considerable effort, and the proposed filtering of the measurement data does not provide a clear distinction between wear and load-induced deformation of the bearing rings.
[0005] The object of the invention is to provide an improved method for determining the wear condition of a slewing bearing based on the wear monitoring method known from EP 3 507 513 B1. The object of the invention is also to provide a device for implementing the method.
[0006] This object is achieved with regard to the method by a method having the features of patent claim 1. Advantageous further developments of the method result from the independent claims which directly or indirectly refer back to the independent method claim, the following description and the drawings.
[0007] With regard to the device, the object is achieved by a device having the features of patent claim 5. Advantageous further developments of the device result from the independent claims which directly or indirectly refer back to the independent device claim, the following description and the drawings.
[0008] The method according to the invention is used to determine the wear condition of a slewing bearing, wherein the slewing bearing has an inner ring, an outer ring, and a gap between the inner ring and the outer ring. The slewing bearing is arranged in an overall device. For example, the slewing bearing is a pivot bearing of a crane, and the crane, which has a crane boom and a trolley movable along the crane boom and a suspension device for the load to be lifted, is the overall device. Within the scope of the method according to the invention, changes in the gap between the inner ring and outer ring of the slewing bearing are measured using at least one sensor. The wear condition of the slewing bearing is determined at a given measuring time, taking into account the measured gap changes.
[0009] The method according to the invention comprises the following process steps: V1) Carrying out reference measurements over a reference period, wherein reference measured values (Ri) are measured with the sensors within the reference period, wherein each reference measured value (Ri) is determined by a combination of several operating parameters (P1, P2, P3) of the overall device, wherein the combination of the operating parameters (P1, P2, P3) belonging to each reference measured value (Ri) is recorded, and wherein the reference measured values (Ri) are stored together with the associated combination of operating parameters (P1, P2, P3) as reference data sets; V2) Carrying out condition measurements over a measuring period, wherein condition measurement values (Zi) are measured with the sensors within the measuring period, wherein each condition measurement value (Zi) is determined by a combination of the operating parameters (P1, P2, P3) of the overall device, wherein the combination of the operating parameters (P1, P2, P3) belonging to each condition measurement value (Zi) is recorded, and wherein the condition measurement values (Zi) are stored together with the associated combination of operating parameters (P1, P2, P3) as condition data records; V3) defining a division of the recorded values of each operating parameter (P1, P2, P3) into discrete value intervals (IP1, IP2, IP3) so that each combination of value intervals (IP1, IP2, IP3) forms a class (Ki); V4) Evaluating the reference data sets and the condition data sets with the aid of an evaluation algorithm, wherein concrete classes (Ki) are assigned to the reference measured values (Ri) and the condition measured values (Zi), wherein for each class (Ki) a mean value of the reference measured values (MRi) and a mean value of the condition measured values (MZi) are formed, wherein for each class (Ki) the difference between the mean value of the condition measured values (MZi) and the mean value of the reference measured values (MRi) is formed, so that mean values (MZi, MRi) of the same classes (Ki) are compared with one another, wherein the results of the mean value comparison in each class (Ki) are stored in a comparison data set (DV), and wherein a wear condition of the slewing bearing is directly derived from the mean value comparisons in each class (Ki).
[0010] Method step V1) is preferably carried out on a new bearing that does not yet show any wear. During method step V1), reference measured values (Ri) are measured with the sensors over a reference period. Each reference measured value (Ri) is determined by a combination of several operating parameters (P1, P2, P3) of the overall device. If the slewing bearing is designed, for example, as a slewing bearing for a crane, the overall device can have a crane boom and a trolley that can be moved along the crane boom and has a suspension device for the load to be lifted. In this case, each measured reference measured value is determined by the operating parameters P1, P2, and P3 of the overall device. In this example, P1: “Radius [m]”, ie the position of the trolley with the suspension device along the crane boom, measured as a distance from a rotation axis of the slewing bearing (e.g. given in the unit meters), P2: “Load [t]”, ie the load hanging on the towing device (e.g. expressed in tonnes), and P3: “Circumferential position [°]”, ie the relative rotational position between the fixed and rotating bearing ring at which the reference measurement value (Ri) is measured.
[0011] The greater the distance of the trolley with the suspension device from the rotation axis of the pivot bearing P1, the greater the lever arm with which the load suspended from the suspension device exerts bending moments on the pivot bearing's bearing rings, and the greater the measured gap expansions of the bearing. The greater the load suspended from the suspension device, the greater the bending moments acting on the pivot bearing's bearing rings for a given radius, and in turn, the greater the measured gap expansions of the bearing. Finally, the magnitude of the measured reference value (Ri) depends on the relative torsional position between the fixed and rotating bearing rings of the pivot bearing at which the change in the gap between the bearing rings is measured for a given load and a given radius.Thus, each reference measurement value (Ri) depends on a specific combination of the operating parameters (P1, P2, P3) of the overall device.
[0012] During process step V1), the combination of operating parameters (P1, P2, P3) associated with each reference measured value (Ri) is recorded, and the reference measured values (Ri) are stored together with the corresponding combination of operating parameters (P1, P2, P3) as reference data sets. The reference data sets can be stored in files, or they can be stored in one or more databases, in a data cloud, or another storage medium and location.
[0013] Method step V2) is carried out during operation of the slewing bearing in the overall device at a time when the bearing has already reached a certain operating time and a certain amount of wear has occurred. Within the scope of method step V2), condition measurements are carried out over a measuring period, with condition measured values (Zi) being measured with the sensors within the measuring period. Each condition measured value (Zi) is determined by a combination of the operating parameters (P1, P2, P3) of the overall device.
[0014] The above statements regarding the dependence of the reference measured values (Ri) on the operating parameters (P1, P2, P3) also apply analogously to the state measured values (Zi). Each state measured value (Zi) is measured for a specific combination of the operating parameters (P1, P2, P3).
[0015] According to the invention, the combination of operating parameters (P1, P2, P3) associated with each measured condition value (Zi) is recorded, and the measured condition values (Zi) are stored together with the associated combination of operating parameters (P1, P2, P3) as condition data sets. The condition data sets can be stored in files, or they can be stored in one or more databases, in a data cloud, or another storage medium and location.
[0016] According to the invention, in method step V3), the recorded values of each operating parameter (P1, P2, P3) are divided into discrete value intervals (IP1, IP2, IP3). For example, the operating parameters (P1, P2, P3) described above using the example of a slewing bearing for a crane can be divided into value intervals (IP1, IP2, IP3) as follows: P1: Subdivision of the radius from 0 m to a maximum of 50 m (with a maximum length of the crane boom of 50 m) into 50 intervals of 1 m each (resolution 1 m); P2: Subdivision of the suspended load from 0 t to a maximum of 200 t (with a permissible maximum load of 200 t) into 100 intervals of 2 t each (resolution 2 t); P3: Division of the circumference of the pivot bearing from 0° to 360° into 80 intervals of 4.5° each (resolution 4.5°).
[0017] Through this classification, every possible combination of value intervals (IP1, IP2, IP3) forms a class (Ki), so that a total of 50 x 100 x 80 = 400,000 different classes (Ki) are defined. Each specific class is characterized by a specific combination of value intervals (IP1, IP2, IP3). A specific class is characterized, for example, by the radius in the first interval being 0 - 1 m (P1), while the load in the last interval is 198 - 200 t (P2), and the measurement is taken at the rotational position of the pivot bearing (P3), defined by the relative rotation angle of 0°. Another specific class, for example, is characterized by a parameter combination where the radius in the last interval is 49-50 m (P1), while the load in the first interval is 0-2 t (P2), and the measurement is performed at the rotation position of the pivot bearing defined by the relative rotation angle of 180° (P3). In this way, a total of 400000 classes (Ki) are formed, with each class (Ki) being assigned exactly one concrete combination of the value intervals (IP1, IP2, IP3).
[0018] The method step V3) according to the invention now makes it possible to assign a specific class (Ki) to each data set of the reference data sets and each data set of the state data sets, which includes a specific measured value (Ri or Zi) and a specific combination of operating parameters (P1, P2, P3). Subsequently, for each class (Ki) a mean value (MRi or MZi) can be calculated for the reference measured values (Ri) and the state measured values (Zi), so that each class (Ki) is assigned exactly one mean value MRi and exactly one mean value MZi. This makes it possible according to the invention to compare the state measured values with the reference measured values for the same class (Ki) by forming the difference (MZi - MRi). Since this comparison allows the state measured values and the reference measured values of the same class (Ki), i.e.for the same combination of operating parameters (P1, P2, P3), the operating parameters (P1, P2, P3) no longer have any influence on the gap change determined by subtraction in a specific class (Ki).
[0019] In this way, according to the invention, only the gap change caused by the wear of the slewing bearing is directly determined by forming the difference (MZi - MRi).
[0020] Therefore, according to the invention, in method step V4), the reference data sets (DRi) and the condition data sets (DZi) are evaluated with the aid of an evaluation algorithm, wherein the reference measured values (Ri) and the condition measured values (Zi) are assigned concrete classes (Ki), wherein for each class (Ki) a mean value of the reference measured values (MRi) and a mean value of the condition measured values (MZi) are formed, wherein for each class (Ki) the difference between the mean value of the condition measured values (MZi) and the mean value of the reference measured values (MRi) is formed, so that mean values (MZi, MRi) of the same classes (Ki) are compared with one another, wherein the results of the mean value comparison in each class (Ki) are stored in a comparison file (DV), and wherein wear of the slewing bearing results directly from the mean value comparisons in each class (Ki).
[0021] In the simplest embodiment of the method according to the invention, the mean values of the reference measured values (MRi) and the state measured values (MZi) can be, for example, arithmetic means. However, the mean values can also be calculated in other ways, e.g., using Gaussian normal distributions or in another way.
[0022] According to one embodiment of the invention, the at least one sensor for measuring the change in the gap is designed as a contactless measuring sensor, in particular as an inductive distance sensor.
[0023] The method according to the invention already works with just a single sensor. To determine the wear condition of the slewing bearing as accurately as possible, it is advantageous to arrange several sensors distributed around the circumference of the slewing bearing.
[0024] In principle, the method according to the invention works when the single sensor or multiple sensors distributed around the circumference of the slewing bearing measure exclusively the gap changes occurring in the radial direction. Wear determination becomes even more accurate if, in addition to the gap changes in the radial direction, the gap changes in the axial direction are also measured and taken into account.
[0025] For example, the sensors can be designed and arranged as described in German patent application DE 10 2016 116 113 A1. This means that one of the sensors can measure a gap change in the radial direction, and a second sensor can measure a gap change in the axial direction. The gap change in the axial direction can also be referred to as a change in the overlap of the bearing rings in the axial direction. According to DE 10 2016 116 113 A1, a first and a second sensor are provided. The first sensor and the second sensor are non-contact measuring sensors, wherein the first sensor and the second sensor each have a sensor surface. The first sensor is arranged opposite an at least partially circumferential reference edge, wherein the second sensor is arranged opposite a reference surface. The first sensor is intended to measure a degree of overlap of the sensor surface with the reference edge.The second sensor is provided for measuring a distance, in particular a radial distance, between the sensor surface and the reference surface.
[0026] The first sensor and / or the second sensor may be a capacitive measuring sensor, an inductive measuring sensor, an ultrasonic sensor and / or an eddy current sensor.
[0027] The method according to the invention can be used not only for slewing bearings of slewing cranes in the manner described above. Other slewing bearings in other systems can also be monitored for wear using the method according to the invention.
[0028] For example, the slewing bearing can be a pivot bearing installed in an excavator. The excavator then forms the overall device. The excavator can, for example, have various hydraulic cylinders. In this case, different pressures in the hydraulic cylinders and different positions (e.g., different positions of the piston in the respective hydraulic cylinders) can be used as operating parameters within the scope of the method according to the invention.
[0029] Another example of a slewing bearing whose wear condition can be determined and monitored using the method according to the invention is a bearing for the rotatable support of a drill head of a tunnel boring machine. In this case, the contact pressure, for example, can be used as an operating parameter. Multiple contact pressures can also be measured as operating parameters at specific locations around the circumference of the drill head. The contact pressures measured at different locations at the same operating time can vary in magnitude.
[0030] Another example of a slewing bearing whose wear condition can be determined and monitored using the method according to the invention is a bearing for an offshore oil transfer station, which transfers offshore oil to one or more ships at sea. In this case, for example, the wind direction and the load generated by the wind can be used as operating parameters within the framework of the method according to the invention.
[0031] Another example of a slewing bearing whose wear condition can be determined and monitored using the method according to the invention is a bearing for a wind turbine (e.g., a blade bearing for pivotally supporting the rotor blades on the hub or a main bearing for rotatably supporting the generator shaft of the wind turbine). In this case, the speed of the rotor hub, the axial load acting on the bearing, and the tilting moment acting on the bearing can be used as operating parameters within the framework of the method according to the invention.
[0032] In all the aforementioned cases, the measures characterizing the method according to the invention (definition of the classes, assignment of reference measured values on the one hand and of condition measured values on the other hand to the defined classes, calculation of the difference) can be carried out analogously to the procedure for slewing cranes with a boom and trolley described in detail above and below.
[0033] In principle, the reference data sets (DRi) and the condition data sets (DZi) can be saved in files, databases, data clouds, or other storage media. It is essential that the data sets can be processed using the evaluation algorithm in such a way that process steps V3) and V4) can be carried out. It is particularly advantageous that process steps V3) and V4) can be carried out by means of remote data processing (e.g. via the Internet), regardless of the location where the reference data sets (DRi) and the condition data sets (DZi) are stored. This offers the manufacturer of the slewing bearing the option of processing the reference data sets (DRi) and the condition data sets (DZi) from a location any distance away from the installation location of the slewing bearing and determining the wear condition of the slewing bearing.This allows a slewing bearing manufacturer to perform wear assessment and monitoring as a service for the operator of the entire system (e.g., the operator of a slewing crane). This can be advantageous because the operator of the entire system often has little or no knowledge of the slewing bearing used in the operation of the entire system. Remote data processing allows the slewing bearing manufacturer to monitor the wear condition and initiate timely maintenance, repair, or replacement measures, thus minimizing downtime for the entire system in which the slewing bearing is operated.
[0034] With regard to the device for carrying out the method according to the invention, it is provided that it comprises a slewing crane having a non-rotatable base and a rotatable part. A stationary bearing ring of a slewing bearing is connected to the non-rotatable base, and a rotatable bearing ring of the slewing bearing is connected to the rotatable part of the slewing crane. The rotatable part has a crane boom with a trolley that can be moved along the crane boom and a load attachment device arranged on the trolley. Within the scope of the method, at least the following operating parameters of the slewing crane are recorded and stored together with the reference measured values (Ri) or the condition measured values (Zi): - the distance of the trolley with the towing device from a rotation axis of the slewing bearing at the time of measuring the reference measured values (Ri) or condition measured values (Zi), - the load hanging on the towing device at the time of measuring the reference measured values (Ri) or condition measured values (Zi), and - the relative rotational position between the fixed and rotating bearing ring at the time of measuring the reference measured values (Ri) or condition measured values (Zi).
[0035] The device according to the invention further comprises at least one storage device in which the reference data sets (DRi) and the condition data sets (DZi) can be stored and from which these data sets (DRi and DZi) can be retrieved in order to evaluate them with the aid of an evaluation algorithm and to determine the wear condition of the large rolling bearing at the time of recording the condition measurement values (Zi).
[0036] With the help of the evaluation algorithm, the reference data sets (DRi) and the condition data sets (DZi) can be evaluated automatically. They can be read from the storage device using a computer system with the evaluation algorithm and evaluated according to process steps V3) and V4). The measured wear states can then be compared with specified permissible wear values. If the measured wear values reach or approach the permissible wear values, the necessary measures can be taken in a timely manner to prevent wear-related failure of the slewing bearing and thus an unplanned failure of the entire device in which the slewing bearing is installed. In this way, unwanted downtimes can be avoided and the availability of entire devices such as large unloading cranes in overseas ports can be optimized.Especially in the area of critical logistics chains, the optimized availability of critical systems such as unloading cranes is very important, so there is great interest in avoiding wear-related system failures.
[0037] In principle, the computer system with the evaluation algorithm can be physically provided in the same device as the storage devices for the reference data sets (DRi) and the state data sets (DZi).
[0038] According to one embodiment of the invention, an interface is provided via which a computer system separate from the device and having the evaluation algorithm can access the reference data sets (DRi) and the status data sets (DZi) in order to carry out the method steps V3) and V4). This ensures that, if the reference data sets (DRi) and the status data sets (DZi) are stored in files, databases, data clouds or other storage media, the method steps V3) and V4) can be carried out with the aid of the computer system by remote data processing, regardless of the location where the reference data sets (DRi) and the status data sets (DZi) are stored. This makes it possible, for example,the manufacturer of the slewing bearing to monitor its wear condition on behalf of the operator of the entire device and to plan and implement timely maintenance, servicing and repair work in order to avoid unforeseen operational failures of the slewing bearing and thus of the entire device.
[0039] The invention thus enables the implementation of a business model in which the wear monitoring service for slewing bearings is sold to the operator of an overall system in which the slewing bearing is installed. The operator of the overall system benefits from several advantages. On the one hand, they can improve the quality of wear monitoring and the maintenance, servicing, and repair work resulting from the evaluation of the measured values because they can have the wear monitoring and its evaluation carried out by a company that knows the product "slewing bearings" much better than they do and can therefore assess the wear condition of the slewing bearing much better than they can themselves. On the other hand, they improve the availability of their overall system because unplanned downtimes due to suddenly necessary maintenance, servicing, and repair work are avoided.In addition, the operator of the entire facility can save on personnel and material costs associated with wear monitoring of the slewing bearing. The service provider benefits from the ability to offer their services from any location. Using their computer system, which contains the evaluation algorithm, they can access any number of slewing bearings to be monitored in different integrated facilities worldwide.
[0040] The invention also relates to a device for carrying out a method according to the method claims. The device comprises an overall device with a large roller bearing, wherein the overall device has a non-rotatable first part and a rotatable second part.
[0041] For example, the overall device can be a slewing crane with a slewing bearing designed as a slewing or pivot bearing. A stationary (i.e., non-rotating) bearing ring of the slewing bearing is connected to the non-rotatable first part of the overall device, and a rotatable bearing ring of the slewing bearing is connected to the rotatable second part of the overall device. The stationary first part of an overall device designed as a slewing crane can be the non-rotatable base of the slewing crane. The rotatable second part of an overall device designed as a slewing crane can be the rotatable or pivotable part of the slewing crane, which comprises the crane boom with the trolley movable along the crane boom and the attachment device for loads.
[0042] The device according to the invention comprises a storage device with which the reference measured values (Ri) and condition measured values (Zi) acquired within the scope of the method according to the invention, together with the associated operating parameters (P1, P2, P3) of the entire device, can be stored as reference data sets (DRi) and condition data sets (DZi). The storage device has an interface via which the reference data sets (DRi) and condition data sets (DZi) can be accessed by a computer system. The reference data sets are then read out by the computer system and processed and evaluated according to method steps V3) and V4) with the aid of the computer system and the evaluation algorithm in order to determine the wear condition of the slewing bearing.
[0043] The method and device according to the invention can be applied in conjunction with different overall devices, i.e., with regard to the method and device for carrying out the method, the invention is not limited to the exemplary application of a slewing crane with a slewing bearing designed as a rotary or pivot bearing. Those skilled in the art will be aware that the type and number of operating parameters (P1, P2, P3) to be recorded depend on the design of the overall device and the loads the slewing bearing is subjected to during operation.
[0044] According to one embodiment of the device according to the invention, the overall device comprises a slewing crane having a non-rotatable base and a rotatable part, wherein a stationary bearing ring of a slewing bearing is connected to the non-rotatable base and a rotatable bearing ring of the slewing bearing is connected to the rotatable part, wherein the rotatable part comprises a crane boom with a trolley movable along the crane boom and a load attachment device arranged on the trolley, wherein, within the scope of the method, at least the following operating parameters (P1, P2, P3) of the slewing crane are recorded and stored together with the reference measured values (Ri) or the condition measured values (Zi) in the storage device as reference data sets (DRi) and condition data sets (DZi): - the distance of the trolley (4) with the towing device (5) from a rotation axis of the slewing bearing at the time of measuring the reference measured values (Ri) or condition measured values (Zi), - the load hanging on the towing device at the time of measuring the reference measured values (Ri) or condition measured values (Zi), and - the relative rotational position between the fixed and rotating bearing ring at the time of measuring the reference measured values (Ri) or condition measured values (Zi).
[0045] According to one embodiment of the device according to the invention, it is provided that the storage device comprises data files or a database or a data cloud, wherein the reference data sets (DRi) and the status data sets (DZi) can be retrieved by the computer system via the Internet or another data transmission network and evaluated using the evaluation algorithm.
[0046] The computer system can in particular be a system separate from the storage device.
[0047] The accessibility of the reference data sets (DRi) and the condition data sets (DZi) via the internet or another data transmission network ensures that the computer system can be decoupled from the storage device and, for example, can be set up and operated at a different location. The reference data sets (DRi) and condition data sets (DZi) can thus be processed and evaluated from any location. For example, the manufacturer of the slewing bearing can operate the computer system with the evaluation algorithm at its factory in Germany and access, process, and evaluate the reference data sets (DRi) and condition data sets (DZi) via the internet, which an operator of a slewing crane for unloading ships in the port of Shanghai or Rio de Janeiro has recorded and stored in a data cloud.In this way, the bearing manufacturer can ensure optimal availability of the unloading crane without the crane operator having to maintain equipment, know-how and personnel capacity for wear monitoring of the slewing bearing.
[0048] According to one embodiment of the device according to the invention, the evaluation algorithm is provided separately from the computer system in a separate data memory, wherein the computer system can access the separate data memory in order to use the evaluation algorithm for the evaluation of the reference data sets (DRi) and the status data sets (DZi). This ensures that the evaluation algorithm can be updated, modified, improved, and maintained independently of the computer system. It is then also conceivable for the evaluation algorithm to be provided not by the operator of the computer system (e.g., the slewing bearing manufacturer), but by another company, which may in turn be located at a different location than the operator of the computer system.
[0049] The invention is explained in more detail below with reference to the figures, each of which shows schematically Fig. 1 shows a representation of the process sequence according to the invention; Fig. 2 shows a first embodiment of the device according to the invention; Fig. 3 a second embodiment of the device according to the invention.
[0050] Fig. 1 shows the sequence of the method according to the invention. In method step V1), the reference measured values Ri on the slewing bearing and the associated operating parameters of the overall device P1, P2, P3, ..., Pn, which are present at the time of measurement of the reference measured values Ri, are measured. The reference measured values Ri and the operating parameters P1, P2, P3, ..., Pn present for each reference measured value Ri at the time of measurement are then stored as reference data sets DRi. The reference data sets DRi are preferably measured on a new slewing bearing shortly after its installation in the overall device, when the slewing bearing has not yet shown any wear.
[0051] The reference data sets DZi contain both the portion of the measured gap change caused by the wear of the slewing bearing at the time of their measurement, as well as the portion of the gap change caused by the load on the slewing bearing present at the time of the measurement and the associated deformations.
[0052] At a given point in time (e.g., one year after commissioning of the slewing bearing in the overall device), in process step V2), the condition measurement values Zi of the slewing bearing and the associated operating parameters of the overall device P1, P2, P3, ..., Pn, which are present at the time of measurement of the condition measurement values Zi, are measured. The condition measurement values Zi and the operating parameters P1, P2, P3, ..., Pn present for each condition measurement value Zi at the time of measurement are then stored as condition data sets DZi.
[0053] The condition data sets DZi include both the portion of the measured gap change caused by the wear of the slewing bearing at the time of their measurement, as well as the portion of the gap change caused by the load on the slewing bearing present at the time of the measurement and the associated deformations.
[0054] In process step V3), as already described above, the recorded values for each operating parameter (P1, P2, P3) are divided into discrete value intervals (IP1, IP2, IP3). For example, the operating parameters (P1, P2, P3) described above using the example of a slewing bearing for a crane can be divided into value intervals (IP1, IP2, IP3) as follows: P1: Subdivision of the radius from 0 m to a maximum of 50 m (with a maximum length of the crane boom of 50 m) into 50 intervals of 1 m each (resolution 1 m); P2: Subdivision of the suspended load from 0 t to a maximum of 200 t (with a permissible maximum load of 200 t) into 100 intervals of 2 t each (resolution 2 t); P3: Division of the circumference of the pivot bearing from 0° to 360° into 80 intervals of 4.5° each (resolution 4.5°).
[0055] Through this classification, every possible combination of value intervals (IP1, IP2, IP3) forms a class (Ki), so that a total of 50 x 100 x 80 = 400,000 different classes (Ki) are defined. Each specific class Ki is characterized by a specific combination of value intervals (IP1, IP2, IP3). A specific class is characterized, for example, by the radius in the first interval being 0 - 1 m (P1), while the load in the last interval is 198 - 200 t (P2), and the measurement is taken at the rotational position of the pivot bearing (P3) defined by the relative rotation angle of 0°. Another specific class, for example, is characterized by a parameter combination where the radius in the last interval is 49-50 m (P1), while the load in the first interval is 0-2 t (P2), and the measurement is performed at the rotation position of the pivot bearing defined by the relative rotation angle of 180° (P3). In this way, a total of 400000 classes (Ki) are formed, with each class (Ki) being assigned exactly one concrete combination of the value intervals (IP1, IP2, IP3).
[0056] Each reference data set DRi comprises the specifically measured reference value Ri and the specific combination of operating parameters P1, P2, P3 present at the time of its measurement. Since each specific combination of operating parameters P1, P2, P3 corresponds exactly to a specific class Ki, each reference data set DRi containing the reference value Ri can be assigned a specific class Ki. This step can be referred to as "classifying the reference data sets DRi." One then has an overall reference data set with a specific number of individual reference data sets DRi, where each individual reference data set DRi has a measured reference value Ri assigned to a specific class Ki.
[0057] Of course, there can be several reference measured values Ri to which the same class Ki is assigned.
[0058] The same applies to the condition measurements Zi. When measuring the condition measurements Zi, the operating parameters P1, P2, P3 present at the time of their measurement are also recorded. Each condition data set DZi comprises the specifically measured condition measurement value Zi and the specifically present combination of the operating parameters P1, P2, P3 at the time of its measurement. Since each specific combination of the operating parameters P1, P2, P3 corresponds exactly to a specific class Ki, each condition data set DZi containing the condition measurement value Zi can be assigned a specific class Ki. This step can be referred to as “classifying the condition data sets DZi”. One then has an overall condition data set with a specific number of individual condition data sets DZi, where each individual condition data set DZi has a measured condition measurement value Zi to which a specific class Ki is assigned.
[0059] Of course, there can be several state measurements Zi to which the same class Ki is assigned.
[0060] After each reference data set DRi and each state data set DZi has been assigned a concrete class Ki, the “classification” step is complete.
[0061] It should be noted that a reference data set DRi and a condition data set DZi are not necessary for each class Ki in order to carry out the method according to the invention and to determine the wear condition of the slewing bearing.
[0062] In process step V4), an average value is calculated for each class Ki from the reference measured values Ri or from the condition data sets Zi. In the simplest case, this can be the arithmetic mean, for example. However, other averaging methods can also be used here. After that, there is an average reference measured value Rim and an average condition measured value Zim for each class Ki.
[0063] Within the scope of method step V4), the computer system 20 then uses the evaluation algorithm 21 to search for classes Ki that contain both mean reference measured values Rim and mean state measured values Zim. The mean state measured values Zim of a specific class Ki are then compared with the mean reference measured values Rim of the same class Ki by calculating the difference (Zim - Rim). This step is described in Fig. 1 is called “differentiation of equal classes”.
[0064] Because in the method according to the invention the difference is always formed only for mean condition measured values Zim and mean reference measured values Rim of the same class Ki, the load-dependent part of the gap change is eliminated and only the part of the gap change remains which is attributable to the actual wear of the slewing bearing.
[0065] The results of this value comparison are saved in a comparison data set.
[0066] The wear data can then be determined from the comparison data set, i.e. it can be determined whether the measured, wear-induced gap changes in the individual classes Ki have reached or even exceeded a predefined critical limit. It can also be determined whether, for individual classes Ki, the gap change has approached a predefined critical value so closely that maintenance, servicing, or repair measures are necessary. These measures can then be planned and carried out, for example, as part of required plant inspections with planned plant downtime. In this way, unplanned plant failures and downtimes are avoided and the plant availability of, for example, an unloading crane is increased or optimized.
[0067] Fig. Figure 2 shows the device according to the invention for carrying out the method according to the invention in a first embodiment. The overall device 40 comprises the slewing bearing 50 installed in the overall device 40. Distance sensors are installed in the slewing bearing 50, which measure the changes in the gap between the non-rotatable and the rotatable bearing rings. Measuring devices are also installed in the overall device 40, with which the operating parameters P1, P2, P3, ..., Pn can be recorded.
[0068] On the not yet worn bearing (usually immediately after installation and initial commissioning of the bearing), the reference measured values Ri and the operating parameters P1, P2, P3, ..., Pn present at the time of a specific reference value measurement Ri are recorded and stored as reference data sets DRi in the storage device 10. Each reference data set DRi thus comprises the data (Ri; P1; P2; P3; ...; Pn).
[0069] At a predeterminable time after commissioning of the slewing bearing 50, at which the wear condition of the slewing bearing 50 is to be determined, the condition measurement values Zi of the slewing bearing 50 as well as the operating parameters P1, P2, P3, ..., Pn present at the time of a specific condition value measurement Zi are recorded and stored as condition data sets DZi in the storage device 10. Each condition data set DZi thus comprises the data (Zi; P1; P2; P3; ...; Pn).
[0070] The storage device 10 can, for example, comprise a data cloud 14 in which the reference data sets DRi and the status data sets DZi are stored. Furthermore, the storage device has an interface 11 via which the computer system 20 can access the reference data sets DRi and the status data sets DZi. Access can be achieved via a suitable data transmission network 30, such as the Internet.
[0071] The above-described classification of the reference data sets DRi and the condition data sets DZi can be performed with the aid of the computer system 20. With the aid of the evaluation algorithm 21, the wear data describing the wear condition of the slewing bearing 50 are determined from the classified reference data sets DRi and condition data sets DZi as described above.
[0072] In the Fig. In the first embodiment of the device shown in Figure 2, the evaluation algorithm 21 is stored on a data carrier that is part of the computer system 20. The computer system 20 with the evaluation algorithm 21 can be operated, for example, in the factory of the manufacturer of the slewing bearing 50, so that the slewing bearing manufacturer can determine the wear condition of the slewing bearing 50 as a service for the operator of the overall device 40.
[0073] The Fig. The second embodiment of the device shown in Figure 3 differs from that shown in Fig. 2 is that the evaluation algorithm 21 is stored separately from the computer system 20 on a separate data storage device. The computer system 20 can access the evaluation algorithm 21 via a suitable data transmission network 30, such as the Internet, in order to use the evaluation algorithm 21 for evaluating the reference data sets DRi and the condition data sets DZi. This allows the evaluation algorithm 21 to be provided independently of the computer system 20, which further increases the flexibility of the business model for recording the wear condition of the slewing bearing 50 as a service. List of reference symbols 1 base 2 rotating part 3 crane booms 4 trolley 5 Trailer hitch 6 Last 10 Storage device 11 Interface 12 data files 13 Database 14 Data Cloud 20 computer system 21 Evaluation algorithm 30 Data transmission network; Internet 40 total device 50 slewing bearings Ri reference measured values Zi condition measurements P1, P2, P3, ... , Pn operating parameters of the entire device DRi reference data sets DZi condition data sets QUOTES CONTAINED IN THE DESCRIPTION
[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature
[0000] EP 3507513 B1 [0002, 0003, 0004, 0005] DE 102016116113 A1
[0025]
Claims
[1] Method for determining a wear condition of a large rolling bearing (50), wherein the large rolling bearing has an inner ring, an outer ring and a gap between the inner ring and the outer ring and is arranged in an overall device (40), wherein, within the scope of the method, changes in the gap between the inner ring and outer ring of the large rolling bearing (50) are measured by means of at least one sensor, wherein, taking into account the measured gap changes, a wear condition of the large rolling bearing (50) is determined at a given measuring time, characterized by , that the procedure includes the following steps: V1) Carrying out reference measurements over a reference period, whereby within the reference period reference measured values (R i ), where each reference measurement value (R i) is determined by a combination of several operating parameters (P1, P2, P3) of the overall device (40), wherein the combination of the operating parameters (P1, P2, P3) belonging to each reference measured value (Ri) is recorded, and wherein the reference measured values (Ri) are stored together with the associated combination of operating parameters (P1, P2, P3) as reference data sets (DRi); V2) Carrying out condition measurements over a measuring period, wherein condition measurement values (Zi) are measured within the measuring period, wherein each condition measurement value (Zi) is determined by a combination of the operating parameters (P1, P2, P3) of the overall device (40), wherein the combination of the operating parameters (P1, P2, P3) belonging to each condition measurement value (Zi) is recorded, and wherein the condition measurement values (Zi) are stored together with the associated combination of operating parameters (P1, P2, P3) as condition data records (ZRi); V3) defining a division of the recorded values of each operating parameter (P1, P2, P3) into discrete value intervals (IP1, IP2, IP3) so that each combination of value intervals (IP1, IP2, IP3) forms a class (Ki); V4) Evaluating the reference data sets (DRi) and the condition data sets (DZi) with the aid of an evaluation algorithm (21), wherein concrete classes (Ki) are assigned to the reference measured values (Ri) and the condition measured values (Zi), wherein for each class (Ki) a mean value (MRi) of the reference measured values (Ri) and a mean value (MZi) of the condition measured values (Zi) are formed, wherein for each class (Ki) the difference between the mean value (MZi) of the condition measured values (Zi) and the mean value (MRi) of the reference measured values (Ri) is formed, so that mean values (MZi, MRi) of the same classes (Ki) are compared with one another, wherein the results of the mean value comparison in each class (Ki) are stored in a comparison data set (DV), and wherein a wear state of the slewing bearing is directly derived from the mean value comparisons in each class (Ki). [2] Method according to claim 1, characterized bythat the at least one sensor for measuring the change in the gap is designed as a contactless measuring sensor, in particular as an inductive distance sensor. [3] Method according to claim 1 or 2, characterized by that the overall device (40) is a slewing crane having a rotationally fixed base (1) and a rotatable part (2), wherein a fixed bearing ring of the slewing bearing (50) is connected to the rotationally fixed base (1) and a rotatable bearing ring of the slewing bearing (50) is connected to the rotatable part (2), wherein the rotatable part (2) comprises a crane boom (3) with a trolley (4) that can be moved along the crane boom (3) and a suspension device (5) for a load (6) arranged on the trolley (4), wherein at least the following operating parameters (P1, P2, P3) of the overall device are taken into account within the scope of the method: - the distance of the trolley (4) with the towing device (5) from a rotation axis of the slewing bearing (50) at the time of measuring the reference measured values (Ri) or condition measured values (Zi), - the load hanging on the towing device at the time of measuring the reference measured values (Ri) or condition measured values (Zi), and - the relative rotational position between the fixed and rotating bearing ring at the time of measuring the reference measured values (Ri) or condition measured values (Zi). [4] Method according to claim 1 or 2, characterized by , that the overall device (40) is an excavator and the large roller bearing (50) is a rotary bearing which is installed in the excavator, wherein the excavator has various hydraulic cylinders, and wherein different pressures in the hydraulic cylinders and different positions of the piston in the respective hydraulic cylinders are used as operating parameters (P1, P2, P3), or that the overall device (40) is a tunnel boring machine and the large roller bearing (50) is a bearing for the rotatable mounting of a drill head of the tunnel boring machine, wherein contact pressures acting on the drill head at different circumferential positions are used as operating parameters (P1, P2, P3), or that the overall device (40) is a bearing for an offshore oil transfer station and the large roller bearing (50) is a rotary bearing installed therein, wherein the wind direction and the loads generated by the wind are used as operating parameters (P1, P2, P3), or that the overall device (40) is a wind turbine and the slewing bearing (50) is a bearing installed in the wind turbine, the speed of the rotor hub, the axial load acting on the slewing bearing (50) and the tilting moment acting on the slewing bearing (50) being used as operating parameters (P1, P2, P3). [5] Method according to one of the preceding claims, characterized bythat the reference data sets (DRi) and the status data sets (DZi) are stored in files, databases, data clouds or other storage media in such a way that the process steps V3) and V4) can be carried out by means of remote data processing regardless of the location at which the reference data sets (DRi) and the status data sets (DZi) are stored. [6] A device for carrying out a method according to one of the preceding claims, comprising an overall device with a slewing bearing, the overall device having a non-rotatable first part and a rotatable second part, a stationary bearing ring of the slewing bearing being connected to the non-rotatable first part and a rotatable bearing ring of the slewing bearing being connected to the rotatable second part, a storage device (10) being provided with which the reference measured values (Ri) and state measured values (Zi) acquired within the scope of the method can be stored together with the associated operating parameters (P1, P2, P3) of the overall device as reference data sets (DRi) and state data sets (DZi), the storage device (10) having an interface (11) via which the reference data sets (DRi) and the state data sets (DZi) can be accessed by a computer system (20),to evaluate them with an evaluation algorithm (21) for determining the wear condition of the large rolling bearing according to one of the preceding claims., [7] Device according to claim 6, characterized bythat the overall device comprises a slewing crane having a rotationally fixed base (1) and a rotatable part (2), wherein a stationary bearing ring of a slewing bearing is connected to the rotationally fixed base (1) and a rotatable bearing ring of the slewing bearing is connected to the rotatable part (2), wherein the rotatable part (2) comprises a crane boom (3) with a trolley (4) movable along the crane boom (3) and a hitch (5) for a load (6) arranged on the trolley (4), wherein within the scope of the method at least the following operating parameters (P1, P2, P3) of the slewing crane are recorded and stored together with the reference measured values (Ri) or the condition measured values (Zi) in the storage device (10) as reference data sets (DRi) and condition data sets (DZi): - the distance of the trolley (4) with the towing device (5) from a rotation axis of the slewing bearing at the time of measuring the reference measured values (Ri) or condition measured values (Zi), - the load hanging on the towing device at the time of measuring the reference measured values (Ri) or condition measured values (Zi), and - the relative rotational position between the fixed and rotating bearing ring at the time of measuring the reference measured values (Ri) or condition measured values (Zi). [8] Device according to claim 6 or 7, characterized by in that the storage device (10) comprises data files (12) or a database (13) or a data cloud (14), wherein the reference data sets (DRi) and the status data sets (DZi) can be retrieved by the computer system (20) via the Internet or another data transmission network and evaluated using the evaluation algorithm (21). [9] Device according to one of claims 6 to 8, characterized bythat the computer system (20) is a separate system from the storage device (10). [10] Device according to one of claims 6 to 9, characterized by that the evaluation algorithm (21) is provided separately from the computer system (20) in a separate data memory, wherein the computer system (20) can access the separate data memory in order to use the evaluation algorithm (21) for the evaluation of the reference data sets (DRi) and the state data sets (DZi).