JP6686625B2 - Rolling bearing diagnostic device - Google Patents

Description

  The present invention relates to a rolling bearing diagnosis device.

  For rolling stock equipment, machine tools, wind speed generators, etc., in order to prevent malfunction of the rolling bearings from affecting the operation of the equipment, parts including rolling bearings are regularly disassembled and visually inspected. Was there. In recent years, in order to reduce the time and cost involved in visual inspection, there is one that detects an abnormality in a rolling bearing from the vibration or the like that occurs during operation without disassembling the machine. Such a configuration is described in Patent Document 1 and Patent Document 2, for example.

  The configuration described in Patent Document 1 detects the vibration of the device by any one of the proximity sensor, the optical sensor, and the magnetic sensor. Further, the configuration described in Patent Document 2 uses a strain sensor to detect the load on the rotating shaft and uses the detected load as one of the determination conditions.

Patent No. 5534875 Patent No. 5419472

  However, in the above-mentioned device, the rotation of the rotary shaft may be less than one rotation during one operation. For example, since the yaw drive device included in the wind power generator is a mechanism that rotates to adjust the orientation of the blades and the like according to the wind direction, the rotation axis may not make one rotation in one operation. In such a device, when vibration is measured during operation, there is a problem that the number of measurement data is insufficient and sufficient reliable measurement data cannot be obtained. Further, in the magnetic sensor, there is a problem that the mounting position and the like are restricted because it is necessary to eliminate the influence of the surrounding magnetism.

When detecting vibrations of rolling bearings by measuring vibration during operation of the equipment, the accuracy of the measurement data naturally affects the diagnosis result, and the detection result based on the measurement data with low accuracy is unreliable. Becomes
The present invention has been made in view of the above points, and a rolling bearing diagnosis capable of detecting abnormality of a rolling bearing with high reliability even when the rotation of the rotary shaft is low speed or less than one rotation. The purpose is to provide a device.

  In order to solve the above-mentioned problems, a rolling bearing diagnosis device according to one aspect of the present invention includes a shaft, an inner ring externally fitted to the shaft, an outer ring internally fitted to a housing, and the shaft between the outer ring and the inner ring. Of a rolling bearing having a rolling element that supports the load of, a strain sensor that detects revolution information related to the revolution performed by the rolling element around the shaft, and a data accumulation that accumulates the revolution information detected by the strain sensor. Section, an average value calculating section for calculating a revolution average value which is an average value of the revolution information from the revolution information accumulated by the data accumulating section, and diagnostic data for the rolling bearing using the revolution average value. And a data collating unit for collating the diagnostic data with the damage data output when the structure related to the rolling bearing is damaged. Including a failure detection unit for detecting an abnormality of the antifriction bearing based on a result of matching by parts.

Further, in the rolling bearing diagnosis device according to one aspect of the present invention, in the above aspect, the average value calculation unit accumulates information on the revolution number of the rolling element for each revolution number of the rolling element to calculate an average value. It is desirable to do.
Further, in the rolling bearing diagnosis device according to one aspect of the present invention, in the above aspect, the average value calculation unit stores information relating to the revolution number of the rolling element according to the preset revolution of the rolling element. It is desirable to calculate the average value.

In the above aspect, the bearing diagnostic device further includes a vibration sensor that detects vibration occurring in at least one of the shaft of the rolling bearing, the outer ring, and the inner ring, and the diagnostic data creation unit includes the vibration sensor. It is desirable to create the diagnostic data using the vibration information detected by the sensor.
Further, in the rolling bearing diagnosis device, in the above aspect, it is preferable that the strain sensor is provided on a peripheral surface of the outer ring or the inner ring that revolves around the shaft.

  The rolling bearing diagnosis method performed in the rolling bearing diagnosis device described above includes a shaft, an inner ring externally fitted to the shaft, an outer ring internally fitted to the housing, and a load on the shaft between the outer ring and the inner ring. A rolling bearing diagnosing method for detecting an abnormality of a rolling bearing having a rolling element for supporting the revolution information detected by a strain sensor for detecting revolution information relating to revolution performed by the rolling element around the shaft. A step of accumulating, a step of calculating a revolution average value that is an average value of the accumulated revolution information, a step of creating diagnostic data for the rolling bearing using the revolution average value, and A step of collating damage data output when the structure is damaged with the diagnostic data and detecting an abnormality of the rolling bearing is included.

  According to the above aspect, it is possible to provide a rolling bearing diagnosis device capable of detecting abnormality of a rolling bearing with high reliability even when the rotation of the shaft is low speed or less than one rotation.

It is a figure for demonstrating the wind power generator provided with the rolling bearing diagnostic apparatus of 1st Embodiment of this invention. It is sectional drawing for demonstrating the slewing bearing of 1st Embodiment of this invention. It is a functional block diagram of a control part of a 1st embodiment of the present invention. FIG. 4 is a diagram for explaining a process in which the data storage unit shown in FIG. 3 stores distortion data. It is a flow chart for explaining processing performed with a rolling bearing diagnostic device of a 1st embodiment of the present invention. It is a figure for demonstrating another process in which the data storage part shown in FIG. 3 stores distortion data. It is a figure for demonstrating the wind power generator provided with the rolling bearing diagnostic apparatus of 2nd Embodiment of this invention. It is a functional block diagram of a control part of a 2nd embodiment of the present invention. It is a flow chart for explaining processing performed by a rolling bearing diagnostic device of a 2nd embodiment of the present invention.

Hereinafter, the rolling bearing diagnosis device according to the first and second embodiments of the present invention will be described with reference to the drawings. In the following description of the drawings, the same or similar parts are denoted by the same or similar reference numerals. However, the drawings are schematic, and it is needless to say that the drawings include portions in which dimensional relationships and ratios are different from each other.
The following first and second embodiments exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention is Materials, shapes, structures, arrangements, etc. are not specified as below. Various changes can be added to the technical idea of the present invention within the technical scope defined by the claims described in the claims.

[First Embodiment]
(Rolling bearing diagnostic device)
In the first embodiment, the rolling bearing diagnosis device of the first embodiment will be described by taking a rolling bearing diagnosis device provided in a wind power generator as an example.
FIG. 1 is a diagram showing a wind power generator 12 provided with the rolling bearing diagnosis device according to the first embodiment. The wind power generator 12 includes a blade (wing) 20, a main shaft 22 connected to the blade 20, a main shaft bearing 21 that supports the main shaft 22, a speed increaser 23 to which the rotational force of the blade 20 is input via the main shaft 22, and an increase gear. It has a generator 24 that is connected to the output shaft 28 of the speed machine 23 and rotates. Further, the wind power generator 12 has a nacelle 41 that houses the main shaft 22, the main shaft bearing 21, the speed increaser 23, and the generator 24, and a tower 42 that supports the nacelle 41.

  The main shaft bearing 21 has a spherical roller bearing (not shown). The speed increaser 23 has a low speed shaft, a medium speed shaft, and a high speed shaft (not shown). A large number of bearings such as planetary gears, tapered roller bearings, and cylindrical roller bearings are used for such shafts. A ball bearing or the like is used for the generator 24. Further, the wind power generator 12 includes a slewing bearing (yaw bearing) 30. The swivel bearing 30 is a rolling bearing that supports the nacelle 41 so that the nacelle 41 can swivel. The first embodiment will be described assuming that the rolling bearing diagnosis device is applied to the slewing bearing 30.

<Slewing bearing>
FIG. 2 is a diagram for explaining the slewing bearing 30 which is the rolling bearing of the first embodiment. As shown in FIG. 2, the slewing bearing 30 includes a rotating shaft 31, an inner ring 33 externally fitted to the rotating shaft 31, an outer ring 37 internally fitted to the housing 39, and an outer ring 37 between the outer ring 37 and the inner ring 33. It has a plurality of rolling elements 35 that support the load. In the slewing bearing 30 of the first embodiment, the outer ring 37 is a fixed ring and the inner ring 33 is a rotating ring. However, the first embodiment is not limited to such a configuration, and the outer ring 37 may be a rotating wheel and the inner ring 33 may be a fixed ring.

  The rolling elements 35 are metal members having a spherical shape, and the plurality of rolling elements 35 are held by a retainer 38 and are kept at constant intervals. The slewing bearing 30 is incorporated inside the housing 39. The slewing bearing 30 in which the rolling elements 35 are metal balls is a so-called angular contact ball bearing.

<Strain sensor>
In addition, the configuration shown in FIG. 2 includes a strain sensor 27 that detects revolution information related to revolution performed by the rolling element 35 of the orbiting bearing 30 about the rotation shaft 31. The strain sensor 27 is directly attached to the outer peripheral surface of the outer ring 37, and detects the number of revolutions of the rolling element 35 about the rotation shaft 31 per minute (hereinafter, simply referred to as “revolution number”). The number of revolutions of the rolling element 35 is equal to the number of revolutions performed by the retainer 38 around the rotation shaft 31.
Further, in the first embodiment, a strain gauge is used as the strain sensor 27. The strain gauge is a sensor that is attached to an object to be measured with an adhesive and deforms together with the object to be measured. The electrical resistance of the strain gauge changes due to deformation. Therefore, the electric signal output from the strain gauge indicates the timing and the number of times the strain gauge is distorted, and the degree of distortion.By performing Fourier analysis on the electric signal, the relationship between the signal strength and the signal frequency can be obtained. To be

  In the first embodiment, as shown in FIG. 2, a notch is provided on the outer peripheral surface of the outer ring 37, and the strain sensor 27 is attached to the notch with an adhesive. According to such a configuration, when the rolling element 35 passes through the inner peripheral surface of the outer ring 37, the strain data which is an electric signal output from the strain sensor 27 is detected, and the rolling element 35 is centered on the rotation shaft 31. The number of revolutions can be detected.

  Further, in the first embodiment, the strain sensor 27 outputs an electric signal every time each of the plurality of rolling elements 35 passes through the strain sensor 27. According to such a configuration of the first embodiment, strain data is generated by the number of rolling elements 35 while the inner ring 33 revolves once. Therefore, in the first embodiment, a plurality of strain data can be acquired even with the mechanism in which the inner ring 33 makes only one rotation during one operation. Further, in the first embodiment, a plurality of strain data can be acquired even when the inner ring 33 does not make one rotation during one operation.

Since the strain sensor 27 of the first embodiment is directly attached to the outer ring 37, it is not necessary to secure a space for attachment, and the degree of freedom in designing the housing 39 is not reduced.
Note that the first embodiment is not limited to the configuration in which the strain sensor 27 is attached to the outer peripheral surface of the outer ring 37. The strain sensor 27 may be provided with a notch on the inner peripheral surface of the outer ring 37, or may be provided with a notch on the outer peripheral surface of the inner ring 33 and attached inside the notch.

<Control part>
Returning to FIG. 1, the rolling bearing diagnosis device of the first embodiment accumulates strain data, which is information related to the revolution of the slewing bearing 30 detected by the strain sensor 27, and calculates a revolution average value that is an average value of the strain data. The slewing bearing 30 is calculated and the orbital average value is used to create diagnostic data for the slewing bearing. The control unit 25 for detecting the abnormality is provided.

FIG. 3 is a functional block diagram for explaining the control unit 25. The control unit 25 includes a data storage unit 251, a diagnostic data creation unit 253, a diagnostic data collation unit 255, and a diagnostic result output unit 257.
(I) The data storage unit 251 reads and stores a plurality of strain data output from the strain sensor 27. In the first embodiment, the strain data is stored for each revolution number of the rolling element 35 indicated by the strain data. In the first embodiment, in order to realize such processing, a plurality of values are arbitrarily set in advance for the revolution number of the rolling element 35. When the number of revolutions calculated from the strain data output from the strain sensor 27 corresponds to the set number of revolutions, the strain data is accumulated for each corresponding number of revolutions.

FIG. 4 is a diagram for explaining a process in which the data storage unit 251 of the first embodiment stores distortion data. The vertical axis of FIG. 4 represents the revolution number (times / min) of the rolling element 35, and in the first embodiment, seven revolution number values are set. The strain data can be converted into the revolution number of the rolling element 35 depending on the input timing of the strain data and the specifications (specifications) of the slewing bearing 30.
The horizontal axis of FIG. 4 indicates time (t). The straight line ω indicates the number of revolutions from when the rolling element 35 starts revolving to when it ends. According to FIG. 4, the number of revolutions of the rolling element 35 increases at a constant rate from the start of revolution, and takes a constant value of 7 or more. Then, the revolution number decreases from the value 7 at a constant rate to 0.

  The data storage unit 251 of the first embodiment stores the distortion data d1 and d2 as distortion data whose revolution number is 7. The data storage unit 251 also stores the distortion data d3 and d4 as distortion data whose revolution number is 4. With such an operation, the data storage unit 251 can store the strain data for each revolution number of the rolling element.

(Ii) Diagnostic Data Creating Unit The diagnostic data creating unit 253 Fourier transforms the strain data accumulated for each revolution number. Then, a synchronous addition average of each Fourier-transformed data is calculated. Further, the diagnostic data creation unit 253 performs diagnostic signal processing such as filter processing, envelope processing, and frequency analysis on the synchronous arithmetic mean. Since the diagnostic signal processing is performed, the synchronous average of strain data for each revolution number becomes diagnostic data for diagnosing the slewing bearing 30. The diagnostic data is in the form of frequency spectrum.

(Iii) Diagnostic Data Collating Unit In the first embodiment, a publicly known calculation is performed based on design specifications and usage conditions of the slewing bearing 30 to calculate a frequency component generated when the slewing bearing 30 is damaged. . The calculated frequency component is stored in advance in a storage unit (not shown) of the diagnostic data matching unit 255. The frequency component generated when the slewing bearing 30 stored in the storage unit is damaged is hereinafter referred to as “damage data”. The damage data has different frequency components depending on the damage location. Here, as the damage data, inner ring damage data when the inner ring 33 is damaged, outer ring damage data when the outer ring 37 is damaged, rolling element damage data when the rolling element 35 is damaged, and a cage 38 are damaged. If there is any, four pieces of cage damage data are calculated and stored in advance.

  The diagnostic data collating unit 255 extracts frequency components corresponding to the inner ring damage data, the outer ring damage data, the rolling element damage data, and the cage damage data from the frequency spectrum obtained as the diagnostic data. Next, the diagnostic data matching unit 255 determines that there is no abnormality in the slewing bearing 30 when the intensities of all the extracted frequency components are smaller than the preset reference value. If any of the intensities of the extracted frequency components is larger than the reference value, the diagnostic data matching unit 255 determines that the location corresponding to the frequency component larger than the reference value is damaged.

  Further, the first embodiment is not limited to comparing the above-mentioned four damage data and diagnostic data. For example, it is known that a characteristic frequency spectrum appears even when a gear (not shown) of the slewing bearing 30 is damaged. In the first embodiment, a publicly-known calculation is performed based on gear design specifications and use conditions, and a frequency component generated when the gear is damaged is stored in advance in the storage unit as gear damage data. The diagnostic data collating unit 255 extracts the frequency component of the gear damage data from the diagnostic data and compares the intensity of the extracted frequency component with a reference value. If the strength of the extracted frequency component is larger than the reference value, it is determined that the gear is damaged, and if the strength of the frequency component is smaller than the reference value, it is determined that the gear is not damaged.

(Iv) Diagnostic Result Output Unit The diagnostic result output unit 257 outputs the result of the collation performed by the diagnostic data collating unit 255 to the outside. For example, when the diagnostic data and the damage data when the slewing bearing is damaged match, the diagnosis result output unit 257 indicates that “the slewing bearing is damaged” or “the slewing bearing is damaged”. Output the indicated output information.
The output information may be a signal output to a higher level control device. Further, it may be a signal for displaying a character indicating the content of the output information, a signal for generating an alarm sound, or a signal for lighting a lamp.

(Rolling bearing diagnosis method)
Next, processing performed in the rolling bearing diagnosis device of the first embodiment described above will be described.
FIG. 5 is a flowchart for explaining the process performed by the rolling bearing diagnosis device of the first embodiment. The flowchart shown in FIG. 5 is executed by the control unit 25 shown in FIG. The data storage unit 251, the diagnostic data creation unit 253, the diagnostic data collation unit 255, and the diagnostic result output unit 257 in the control unit 25 of the first embodiment are computer programs that operate in cooperation with hardware. .

In step 51, the data storage unit 251 inputs the strain data output from the strain sensor 27. Since the signal output from the strain sensor 27 is minute, it is amplified after being A / D converted in steps 52 and 53.
Next, in step 54, the data storage unit 251 calculates the revolution number of the rolling element 35 from the input strain data. In step 55, the data storage unit 251 classifies the calculated number of revolutions into preset values and stores the values for each value.

Next, in step 56, the diagnostic data creation unit 253 synchronously averages the accumulated revolution numbers for each value. Further, in step 57, the diagnostic data creation unit 253 performs diagnostic signal processing such as filter processing, envelope processing, and frequency analysis on the distortion data after the synchronous averaging.
Next, in step 58, the diagnostic data creation unit 253 determines whether or not the number of additions performed when calculating the synchronous addition average in step 56 has reached a preset N times. As a result of the determination in step 58, when the number of times of synchronous addition averaging has not reached N times (step 58: No), the data storage unit 251 inputs the distortion data again. The “N times” in step S58 is arbitrarily determined in consideration of the reliability of diagnosis of the slewing bearing 30 and the time related to the diagnosis.

  When the diagnostic data creation unit 253 determines in step 58 that the number of times of synchronous addition averaging has reached N times (step 58: Yes), in step 59, the diagnostic data collation unit 255 damages the diagnostic data. Match with the data. In the first embodiment, damage data when the slewing bearing 30 is damaged and when the gear is damaged is stored in advance in a storage unit (not shown) of the diagnostic data collating unit 255. The diagnostic data collating unit 255 collates such damage data with the diagnostic data.

The diagnostic data collating unit 255 extracts the frequency component of the damage data from the diagnostic data and compares the intensity of the extracted frequency component with a predetermined reference value. Then, the magnitude relationship between the intensity of the frequency component and the reference value is determined. When the strength of the frequency component is larger than the reference value, damage to the location of the slewing bearing 30 or the gear corresponding to this frequency component is detected.
In the first embodiment, a plurality of pieces of diagnostic data are generated for each revolution number of rolling elements. The diagnostic data collating unit 255 collates a plurality of diagnostic data with the damage data and comprehensively determines the strength of the frequency component of the damage data included in the diagnostic data.
In step 59, the diagnostic result output unit 257 displays the diagnostic result of the diagnostic data collating unit 255.

The rolling bearing diagnosis device according to the first embodiment described above can detect the number of revolutions of the rolling element 35 from the actual measurement data obtained when the rolling element 35 passes through the strain sensor 27. Therefore, the accurate revolution number of the rolling element 35 can be used to create the diagnostic data of the slewing bearing 30.
Further, the rolling bearing diagnosis device of the first embodiment accumulates the actual measurement data of the strain sensor 27 obtained every time the rolling element 35 passes through the strain sensor 27, and creates diagnostic data by using the arithmetic mean thereof. There is. Therefore, even if the number of revolutions of the rolling element is small, or even if it is less than once, a sufficient number of strain data can be aggregated to create diagnostic data. In the first embodiment as described above, the reliability of the diagnostic data can be improved, and thus the reliability of the diagnosis of the slewing bearing 30 can be improved.

  Further, the first embodiment is not limited to the configuration described above. For example, the data storage unit 251 of the first embodiment is not limited to one that classifies the revolution number of the rolling element into a plurality of values and stores strain data for each of the plurality of values. The data storage unit 251 may be one that determines one value of the revolution number of the rolling element 35 in advance, stores only the strain data corresponding to the determined value, and performs synchronous addition averaging.

FIG. 6 is a diagram for explaining that only strain data corresponding to one rotation speed value is accumulated. In the example shown in FIG. 6, the distortion data d5 and d6 in which the number of rotations shows the value 6 are accumulated and subjected to the synchronous addition and averaging process to be diagnostic data.
As a matter of course, such a configuration is performed with respect to the revolution number at which the damage data in the diagnostic data remarkably appears. When an appropriate number of revolutions is selected, the processing amount related to the calculation is smaller than that in the configuration shown in FIG. 4, and the load on the control unit 25 can be reduced.

  Further, the diagnostic data creation unit 253 of the first embodiment is not limited to the one that obtains the average value of the distortion data by using the synchronous addition average. The first embodiment may use any process as long as it is a process of calculating an average value of accumulated strain data.

[Second Embodiment]
(Rolling bearing diagnostic device)
Next, a rolling bearing diagnosis device according to a second embodiment of the present invention will be described.
FIG. 7: is the figure which showed the wind power generator 72 with which the control part 75 which is the rolling bearing diagnostic apparatus of 2nd Embodiment was provided. In the second embodiment, the members described in the first embodiment are designated by the same reference numerals, and the description thereof will be partially omitted.
The wind power generator 72 has, in addition to the wind power generator 12 of the first embodiment, a vibration sensor 29 that detects at least one vibration of the rotating shaft 31, the outer ring 37, and the inner ring 33 of the slewing bearing 30.

  The vibration sensor 29 is attached to the slewing bearing 30 itself. The strength of the signal output from the vibration sensor 29 indicates the magnitude of vibration of at least one of the rotating shaft 31, the outer ring 37, and the inner ring 33 of the slewing bearing 30. As the vibration sensor 29, it is conceivable to use a piezoelectric sensor that detects acceleration, an electrokinetic sensor that detects speed, an eddy current sensor that detects displacement, an electrostatic capacity sensor, an optical sensor, or the like. The signal output from the vibration sensor 29 is Fourier-analyzed and represents the magnitude of the vibration and the frequency corresponding to the vibration.

  FIG. 8 is a functional block diagram for explaining the control unit 75. The data storage unit 751 of the control unit 75 inputs the strain data output by the strain sensor 27, as in the first embodiment. Further, the vibration data output from the vibration sensor 29 is input in synchronization with the strain data. The vibration data is classified according to the number of revolutions indicated by the synchronized strain data, and is accumulated for each number of revolutions.

Similar to the first embodiment, the diagnostic data creation unit 753 performs synchronous signal averaging on strain data for each revolution number of the rolling elements 35 to perform diagnostic signal processing, and also for vibration data for each revolution number of the rolling elements 35. The signal processing for diagnosis is performed by synchronously averaging. The diagnostic signal processing for the vibration data is performed for the natural frequency band of the rotating shaft, the gear, and the like.
Through the above processing, the diagnostic data creation unit 753 can create diagnostic data from strain data and also create diagnostic data from vibration data. In the second embodiment, the diagnostic data created from the strain data will be referred to as “distortion diagnostic data” hereinafter. The diagnostic data created from the vibration data will be referred to as "vibration diagnostic data" hereinafter.

  The diagnostic data collating unit 755 stores damage data related to strain data and damage data related to vibration data in advance. The diagnostic data collating unit 755 collates the strain diagnostic data with the damage data generated from the strain data. The diagnostic data collating unit 755 also collates the vibration diagnostic data with the damage data generated from the vibration data. Further, the diagnostic data collating unit 755 comprehensively judges the results of collating the strain diagnostic data and the vibration diagnostic data, and detects an abnormality of the slewing bearing 30 or the gear.

  The diagnostic result output unit 757 outputs the result comprehensively judged by the diagnostic data collating unit 755 as character data, an alarm, a signal lighting, or the like.

(Rolling bearing diagnosis method)
FIG. 9 is a flow chart for explaining the processing performed in the rolling bearing diagnosis device of the second embodiment. In the second embodiment, the vibration diagnosis data is created in parallel with the creation of the strain diagnosis data described in the first embodiment.
In the flowchart shown in FIG. 9, steps 51 to 57 are the same as the processing described in the first embodiment. In step 61, the data storage unit 751 inputs the vibration data as well as the strain data. Then, in step 62, the vibration data is A / D converted, and in step 63, the A / D converted vibration data is amplified.

Next, in step 65, the diagnostic data creation unit 753 assigns the value of the revolution number indicated by the strain data input in synchronization with this vibration data to the amplified vibration data. Then, the diagnostic data creation unit 753 accumulates vibration data for each assigned revolution number.
Further, in step 66, the diagnostic data creation unit 753 performs a synchronous addition averaging process on the vibration data accumulated for each revolution number. The vibration data subjected to synchronous addition averaging is subjected to diagnostic signal processing in step 67 to become vibration diagnostic data.

In step 68, the diagnostic data creation unit 753 determines whether or not the number of additions of strain data and the number of additions of vibration data when calculating the synchronous addition average has reached N times. As a result of the determination in step 68, when the number of times of synchronous addition averaging has not reached N times (step 68: No), the data storage unit 251 inputs the distortion data again.
In step 68, when the diagnostic data creation unit 253 determines that the number of times of synchronous addition averaging has reached N times (step 68: Yes), in step 69, the diagnostic data collating unit 755 damages the diagnostic data. Match the data.

In the second embodiment, damage data when the slewing bearing 30 is damaged and damage data when the gear is damaged are stored in advance for both strain data and vibration data. The diagnostic data collating unit 755 collates the strain diagnostic data and the vibration diagnostic data with the corresponding damage data. Then, the result of the collation is comprehensively determined and the diagnosis result is output to the diagnosis result output unit 757.
The diagnostic result output unit 757 displays the diagnostic result output from the diagnostic data collating unit 755.

  In the second embodiment described above, strain diagnosis data is created, vibration diagnosis data is created, and both are processed independently. However, in the second embodiment, one diagnostic data may be created using both the value obtained by synchronously averaging the strain data and the vibration data and the value obtained by the synchronous averaging.

The first embodiment and the second embodiment described above exemplarily describe the rolling bearing diagnosis device. The respective technical ideas described in the first embodiment and the second embodiment can be combined with each other. For example, the configuration for accumulating only the distortion data of a specific revolution number shown in FIG. 6 in the first embodiment can be applied to the vibration data in the second embodiment.
Further, in the first embodiment and the second embodiment, a plurality of diagnostic results may be accumulated and the diagnostic result may be adopted when the same diagnostic result is repeated a plurality of times. In addition, when there are more diagnostic results that indicate anomalies in the latter half of the cumulative period than in the first half, the diagnostic results may be settled according to the number of times of abnormality detection.

Further, the first embodiment and the second embodiment can be applied not only to the wind speed generator but also to an application that swings, rotates, or turns. An example of such an application is a swing drive unit of a hydraulic excavator which is a self-propelled construction machine.
Furthermore, it goes without saying that the present invention includes various embodiments and the like not described here. Therefore, the technical scope of the present invention is defined only by the matters specifying the invention described in the claims appropriate from the above description.

  The present invention described above can be applied to any field in the case of monitoring a rolling bearing having rolling elements.

12, 72 Wind power generator 20 Blade 21 Main shaft bearing 22 Main shaft 23 Speed increaser 24 Generator 25, 75 Control unit 27 Strain sensor 28 Output shaft 29 Vibration sensor 30 Slewing bearing 31 Rotating shaft 33 Inner ring 35 Rolling body 37 Outer ring 38 Cage 39 housing 251,751 data storage unit 253,753 diagnostic data creation unit 255,755 diagnostic data collation unit 257,757 diagnostic result output unit

Claims (3)

The rolling element of a rolling bearing having a shaft, an inner ring externally fitted to the shaft, an outer ring internally fitted to the housing, and a plurality of rolling elements for supporting the load of the shaft between the outer ring and the inner ring. A strain sensor that detects revolution information related to revolution performed around the axis,
A data storage unit that stores the revolution information detected by the strain sensor,
From the revolution information accumulated by the data accumulating unit, an average value calculating unit that calculates a revolution average value that is an average value of the revolution information,
A diagnostic data creation unit that creates diagnostic data for the rolling bearing using the revolution average value;
A data collating unit that collates the damage data output when the configuration related to the rolling bearing is damaged, and the diagnostic data,
Look including a abnormality detecting unit for detecting an abnormality of the antifriction bearing based on a result of matching by the data verification unit,
The revolution information includes strain data which is an electric signal output from the strain sensor when one of the rolling elements passes through the inner peripheral surface of the outer ring,
The data storage unit converts the revolution information to the revolution number of the rolling element per preset time according to the timing at which the strain sensor detects the revolution information and the specifications of the rolling bearing, and further, From the start to the end of the revolution of the rolling element, the revolution information is accumulated for each revolution number of the rolling element,
The average value calculation unit calculates the revolution average value using the plurality of revolution information accumulated for each revolution number by the data accumulation unit,
The diagnostic data creation unit creates the diagnostic data using the revolution average value at the time when the number of times the average value calculation unit calculates the revolution average value reaches a preset number. Rolling bearing diagnostic device.   The rolling bearing diagnosis device according to claim 1, wherein the average value calculation unit accumulates information on the revolution number of the rolling element for each revolution number of the rolling element to calculate an average value.   The rolling bearing according to claim 1, wherein the average value calculation unit accumulates information regarding the number of revolutions of the rolling element according to a preset revolution of the rolling element to calculate an average value. Diagnostic device.

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