JPWO2019221251A1 - Bearing condition monitoring method and condition monitoring device - Google Patents

Abstract

The bearing condition monitoring device calculates spectrum data by performing frequency analysis on the signal and a sensor that detects a signal based on vibration, sound, or strain value of the inner ring, outer ring, shaft, and housing generated from the bearing. The waveform processing unit compares the frequency at which the peak of the spectrum data appears with the rotation of the rolling element when there is no slip between the inner and outer rings of the bearing and the rolling element, and the theoretical frequency due to revolution, and the number of rotations of the rolling element of the bearing. It is provided with a calculation unit for obtaining fluctuations and fluctuations in the number of revolutions.

Description

The present invention relates to a bearing condition monitoring method and a condition monitoring device.

Conventionally, a technique has been proposed in which a sensor detects a sound or vibration generated in an outer ring or an inner ring of a bearing, and the presence or absence of an abnormality is determined based on the detection signal.

In Patent Document 1, the frequency feature amount and the time feature amount are extracted from the output of the vibration sensor by the feature amount extraction unit and input to the abnormality diagnosis unit, and the abnormality diagnosis unit uses the frequency feature amount, the time feature amount, and the reference data. Describes a method for diagnosing an abnormality in a rotating device and its device, which makes it possible to determine the presence or absence of an abnormality and the type of abnormality by collating.

Further, in Patent Document 2, vibration generated from a bearing is detected, the detected signal waveform is subjected to envelope processing and frequency analysis, and the peak value of the obtained envelope spectrum is measured in a predetermined frequency range. A method and an apparatus for diagnosing an abnormality in a bearing have been proposed in which a calculated value is obtained by dividing by an overall value which is an integrated value of, and the calculated value is compared with a reference value to determine the presence or absence of an abnormality.

Japanese Patent No. 3449194 Japanese Patent No. 41209999

On the other hand, in the method of diagnosing abnormalities in bearings, the number of revolutions due to abnormal heat generation, revolution slippage that causes skidding, rotation slippage, or excessive preload of deep groove ball bearings and angular contact ball bearings used in the preload state, and loss of preload. It is desired to monitor fluctuations or fluctuations in the number of revolutions due to roller skew of self-aligning roller bearings. However, in any of the methods for diagnosing abnormalities of bearings in Patent Documents 1 and 2, rotation slip, revolution slip, or fluctuation of the number of revolutions is not taken into consideration.

The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to perform frequency analysis of vibration and sound of a mechanical device or strain values generated in an inner ring, an outer ring, a shaft, and a housing to perform a rotation number. It is an object of the present invention to provide a bearing condition monitoring method and a condition monitoring device capable of measuring the fluctuation of the bearing and the fluctuation of the number of revolutions.

The above object of the present invention is achieved by the following configuration.
(1) A bearing condition monitoring method for monitoring the bearing operating condition.
A step of detecting a signal based on vibration, acoustics, or strain values of an inner ring, an outer ring, a shaft, and a housing generated from the bearing, a step of performing frequency analysis on the signal, and calculating spectrum data, and the spectrum data. The frequency at which the peak appears is compared with at least one of the theoretical frequency due to the rotation of the rolling element and the theoretical frequency due to the revolution when the inner and outer rings of the bearing and the rolling element do not slip, and the rotation of the rolling element of the bearing is compared. The process of finding at least one of the fluctuation of the number and the fluctuation of the number of revolutions,
A method for monitoring the condition of a bearing, which comprises.
(2) A bearing condition monitoring device that monitors the operating condition of the bearing.
A sensor that detects a signal based on vibration, acoustics, or strain values of an inner ring, an outer ring, a shaft, and a housing generated from the bearing, a waveform processing unit that performs frequency analysis on the signal and calculates spectrum data, and the above. The frequency at which the peak of the spectrum data appears is compared with at least one of the theoretical frequency due to the rotation of the rolling element and the theoretical frequency due to the revolution when the inner and outer rings of the bearing and the rolling element do not slip, and the rolling element of the bearing is compared. A bearing condition monitoring device comprising: a calculation unit for obtaining at least one of a variation in the number of rotations and a variation in the number of revolutions.
(3) A bearing condition monitoring method for monitoring the operating condition of each row of a plurality of bearings or a double row bearing.
A step of detecting a signal based on vibration, acoustics, or strain values of an inner ring, an outer ring, a shaft, and a housing generated from each row of the plurality of bearings or the double row bearing, and frequency analysis of the signals are performed. The process of calculating the spectrum data, the ratio of the peak frequencies of the spectrum data due to the rotation and revolution of each row of the bearing or the double row bearing, and the inner and outer rings of each row of the bearing or the double row bearing. Compare with at least one of the ratio of the theoretical frequency generated by the rotation of the rolling element and the ratio of the theoretical frequency generated by the revolution when the rolling element does not slip, and each of the bearings or the double row bearings. A method for monitoring a state of a bearing, which comprises a step of obtaining at least one variation in the number of rotations and a variation in the number of revolutions of the rolling elements in a row.
(4) A bearing condition monitoring device that monitors the operating condition of each row of multiple bearings or double row bearings.
A sensor that detects a signal based on vibration, acoustics, or strain values of the inner ring, outer ring, shaft, and housing generated from each row of the plurality of bearings or the double row bearing, and frequency analysis are performed on the signals. The ratio of the peak frequency of the spectrum data due to the rotation and revolution of each row of the bearing or the double row bearing to the waveform processing unit that calculates the spectrum data, and each row of the bearing or the double row bearing. Comparing at least one of the ratio of the theoretical frequency generated by the rotation of the rolling element and the ratio of the theoretical frequency generated by the revolution when there is no slip between the inner and outer rings and the rolling element, each bearing or the double row bearing is compared. A bearing state monitoring device, comprising: a calculation unit for obtaining at least one of a variation in the number of rotations and a variation in the number of revolutions of the rolling element in each row of the above.

According to the bearing condition monitoring method and condition monitoring device of the present invention, a sensor detects a signal based on vibration, sound, or strain value of the inner ring, outer ring, shaft, and housing generated from the bearing, and the waveform processing unit detects the signal. After calculating the spectrum data by performing frequency analysis on the bearing, the calculation unit determines the frequency at which the peak of the spectrum data appears, the theoretical frequency due to the rotation of the rolling element when there is no slip between the inner and outer rings of the bearing and the rolling element, and the revolution. By comparing with at least one of the theoretical frequencies according to the above, at least one of the fluctuation of the rotation number of the rolling element of the bearing and the fluctuation of the revolution number can be obtained. As a result, it is possible to monitor the operating state of the bearing such as slippage of the rolling element and the inner and outer rings, excessive preload, preload release, fluctuation of the rotation number due to roller skew, and fluctuation of the revolution number, which cause a malfunction of the bearing.

According to the bearing condition monitoring method and condition monitoring device of the present invention, a sensor detects a signal based on vibration, sound, or strain value of the inner ring, outer ring, shaft, and housing generated from the bearing, and the waveform processing unit detects the signal. After calculating the spectrum data by performing frequency analysis on the bearing, the calculation unit calculates the ratio of the frequency at which the peak of the spectrum data appears, and the theory generated by the rotation of the rolling element when there is no slip between the inner and outer rings of the bearing and the rolling element. By comparing at least one of the frequency ratio and the theoretical frequency ratio due to the revolution, at least one of the fluctuation of the rotation number of the rolling element of the bearing and the fluctuation of the revolution number can be obtained. As a result, it is possible to monitor the operating state of the bearing such as slippage of the rolling element and the inner and outer rings, excessive preload, preload release, fluctuation of the rotation number due to roller skew, and fluctuation of the revolution number, which cause a malfunction of the bearing.

It is a schematic block diagram of the bearing condition monitoring apparatus which concerns on 1st Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 2nd Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 3rd Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 4th Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the two detectors of FIG. 7. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 5th Embodiment of this invention. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 6th Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 7th Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG. It is a schematic block diagram of the bearing state monitoring apparatus which concerns on 8th Embodiment of this invention. It is an image diagram of the graph of the envelope spectrum measured by the bearing condition monitoring device of FIG.

Hereinafter, each embodiment of the bearing condition monitoring device according to the present invention will be described in detail with reference to the drawings.

(First Embodiment)
FIG. 1 is a schematic configuration diagram of a bearing condition monitoring device for measuring the revolution slip and rotation slip of a deep groove ball bearing, and FIG. 2 is an image diagram of a graph of an envelope spectrum measured by the bearing condition monitoring device.

As shown in FIG. 1, the bearing state monitoring device 10 of the present embodiment is a device for monitoring the state of the deep groove ball bearing 1. The deep groove ball bearing 1 rotatably holds a plurality of balls 4 which are rolling elements arranged between the inner ring 2, the outer ring 3, the inner and outer rings 2 and 3, and the plurality of balls 4. The cage 5 and the cage 5 are provided. The inner ring 2 is fitted to the rotating shaft 6, and the outer ring 3 is fixed to a housing (not shown).

The bearing condition monitoring device 10 includes a vibration sensor 20, a rotation sensor 22, an A / D conversion unit 31, a waveform processing unit 32, a calculation unit 33, and a discrimination unit 34. The A / D conversion unit 31, the waveform processing unit 32, the calculation unit 33, and the discrimination unit 34 are mainly composed of an information processing device 30 such as a personal computer.

The vibration sensor 20 detects the vibration generated from the deep groove ball bearing 1 facing the outer ring 3 as an electric signal, amplifies the detected electric signal by the amplifier 21, and inputs the detected electric signal to the A / D conversion unit 31. The rotation sensor 22 is arranged so as to face the rotation shaft 6, detects the rotation of the rotation shaft 6, obtains the rotation speed of the rotation shaft 6 with the tachometer 23, and inputs it to the calculation unit 33.

The vibration data input from the vibration sensor 20 to the A / D conversion unit 31 is converted into a digital signal by the A / D conversion unit 31, and then the waveform processing unit 32 performs envelope processing and frequency analysis to calculate spectrum data. To do.

The calculation unit 33 further calculates the theoretical frequency due to the rotation and revolution of the ball 4 when the inner and outer rings 2 and 3 and the ball 4 do not slip, based on the rotation speed of the rotation shaft 6 detected by the rotation sensor 22. Then, the theoretical frequency and the frequency at which the peak of the spectrum data obtained by the waveform processing unit 32 appears (hereinafter referred to as "peak frequency") are compared to obtain the rotation slip and the revolution slip of the ball 4.
The peak frequency is selected by a conventional method such as comparison with a certain reference value.

FIG. 2 is an image diagram of a graph comparing the peak frequency of the spectrum data and the theoretical frequency in a state where slip does not occur. In the figure, A is a ball when the inner and outer rings 2 and 3 and the ball 4 have no slip. The theoretical frequency due to the rotation of 4 is shown, and B shows the theoretical frequency due to the revolution of the ball 4 when the inner and outer rings 2 and 3 and the ball 4 do not slip. The difference between the theoretical frequency A due to the rotation of the ball 4 and the peak frequency of the spectrum data corresponding to the theoretical frequency A obtained by the waveform processing unit 32 is the variation C of the rotation number, and the theoretical frequency B due to the revolution of the ball 4 The difference between the frequency and the peak frequency of the spectrum data corresponding to the theoretical frequency B is the variation D of the number of revolutions.
The peak frequency of the spectrum data corresponding to the theoretical frequencies A and B is usually the peak frequency most adjacent to the theoretical frequencies A and B, but this is not the case when the rotation slip and the revolution slip are large. , There is a possibility that resonance unrelated to rotation and revolution occurs in the vicinity of the theoretical frequency. In this case, it is determined whether or not it is the corresponding peak frequency by observing the change in the peak frequency of the spectrum data with respect to the change in the rotation speed of the axis. Alternatively, the corresponding peak frequency is determined by comparison with a state in which rotation slip and revolution slip do not occur (usually, an initial state or a steady state). Further, depending on the periodicity of the spectrum data, the comparison may be performed using the peak frequency of the second or higher harmonics. Alternatively, since the vibration generated from the bearing is affected by rotation and revolution, use a peak frequency other than the theoretical frequency from a state without rotation slip and revolution slip (usually, an initial state or a steady state). The state of rotation slip and revolution slip is investigated by the change of.

Then, the discriminating unit 34 causes abnormal heat generation of the deep groove ball bearing 1 and slippage of the inner and outer rings 2 and 3 and the ball 4 which cause skidding, depending on the presence / absence and size of the fluctuation C of the rotation number or the fluctuation D of the revolution number. Monitor.

As described above, according to the bearing condition monitoring method and condition monitoring device 10 of the present embodiment, abnormal heat generation of the deep groove ball bearing 1 and skidding are performed by measuring fluctuations in the number of rotations and fluctuations in the number of revolutions. , It is possible to monitor the state of rotation slip and revolution slip that cause peeling.

(Second Embodiment)
FIG. 3 is a schematic configuration diagram of a bearing condition monitoring device for measuring fluctuations in the number of revolutions of deep groove ball bearings and angular contact ball bearings used in a preload state, and FIG. 4 is an envelope measured by the bearing condition monitoring device. It is an image diagram of the graph of the spectrum.

The bearing condition monitoring device 10 of the present embodiment is a bearing condition monitoring device of the first embodiment in that the bearing to be measured is a pair of bearings (deep groove ball bearings or angular contact ball bearings) to which a preload is applied. Different from. Since the other parts are the same as those of the bearing condition monitoring device according to the first embodiment of the present invention, the same parts are designated by the same reference numerals or equivalent reference numerals to simplify or omit the description.

As shown in FIG. 4, the peak frequency of the spectrum data obtained by the waveform processing unit 32 is compared with the theoretical frequency E due to revolution in the inner and outer rings 2 and 3 and the ball 4 in a state where there is no slip. The variation F of the number of revolutions is obtained. The determination unit 34 monitors the preload excess and preload release of the bearing 1 to which the preload is applied from the fluctuation F of the number of revolutions.

(Third Embodiment)
FIG. 5 is a schematic configuration diagram of a bearing condition monitoring device for measuring fluctuations in the number of revolutions of a self-aligning roller bearing, and FIG. 6 is an image diagram of a graph of an envelope spectrum measured by the bearing condition monitoring device.

The bearing condition monitoring device 10 of the present embodiment is different from the bearing condition monitoring device of the first embodiment in that the bearing to be measured is the self-aligning roller bearing 1A. Although the specific configuration of the self-aligning roller bearing 1A is not shown, barrel-shaped rolling elements are formed in the R1 row and the R2 row between the inner ring having two rows of orbits and the outer ring having a spherical orbit. The bearings are arranged in two rows, and the vibration corresponding to each row (R1 row and R2 row) is measured by the vibration sensor 20. Two vibration sensors 20 may be provided corresponding to the rolling elements in each row.

As shown in FIG. 6, the peak frequency of the spectrum data of each row (R1 row and R2 row) obtained from the waveform processing unit 32 and the theoretical frequency E due to the revolution in the state where the inner and outer rings and the rolling element do not slip are set. By comparison, the variation F of the number of revolutions in the R1 column and the variation G of the number of revolutions in the R2 column can be obtained. The discriminating unit 34 monitors the roller skew of the self-aligning roller bearing 1A from the fluctuations F and G of the number of revolutions in the R1 row and the R2 row, or the rotation slip and the revolution slip due to the preload excess and the preload release.

(Fourth Embodiment)
FIG. 7 is a schematic configuration diagram of a bearing condition monitoring device for measuring the rolling slip and rotation slip of two tapered roller bearings 11C and 12C by two vibration sensors 20A and 20B, and FIG. 8 is a schematic configuration diagram of a bearing condition monitoring device using the bearing condition monitoring device. It is an image diagram of the graph of the measured envelope spectrum.

As shown in FIG. 7, the vibration sensor 20A is arranged corresponding to one tapered roller bearing 11C, and the vibration sensor 20B is arranged corresponding to the other tapered roller bearing 12C. The vibration data of one cone bearing 11C measured by the vibration sensor 20A is amplified by the amplifier 21A, and the vibration data of the other cone bearing 12C measured by the vibration sensor 20B is amplified by the amplifier 21B and converted to A / D. It is input to the unit 31 and processed in the same manner as the bearing condition monitoring device 10 of the first embodiment.

As shown in FIG. 8A, for one of the conical roller bearings 11C, the peak frequency of the spectral data obtained by the waveform processing unit 32 and the theoretical frequency due to the rotation when the inner and outer rings and the rolling elements do not slip. A matches, and the peak frequency of the spectrum data obtained by the waveform processing unit 32 matches the theoretical frequency B caused by the revolution when there is no slip between the inner and outer rings and the rolling element. Revolution slip is not allowed either.

On the other hand, as shown in FIG. 8B, with respect to the conical roller bearing 12C, the peak frequency of the spectral data obtained by the waveform processing unit 32 and the theoretical frequency caused by the rotation when the inner and outer rings and the rolling element do not slip. Unlike A, fluctuation C in the number of rotations is observed, and the peak frequency of the spectral data obtained by the waveform processing unit 32 and the theoretical frequency B due to the revolution when there is no slip between the inner and outer rings and the rolling elements. Differently, the fluctuation D of the number of revolutions is recognized. Then, the discriminating unit 34 monitors the abnormal heat generation of the tapered roller bearing 12C and the state of the rotation slip and the revolution slip that cause skidding based on the presence / absence and size of the fluctuation C of the rotation number or the fluctuation D of the revolution number. ..

(Fifth Embodiment)
FIG. 9 is a schematic configuration diagram of a bearing condition monitoring device that measures the revolution slip by the cycle of the balls 4 at the strain gauge mounting position of the outer ring 3 by the strain gauge 24 attached to the outer ring 3 of the deep groove ball bearing 1.
In this case, the signal based on the strain value of the outer ring 3 detected by the strain measuring instrument 35 is frequency-analyzed by the waveform processing unit 32 to calculate the spectrum data, and thereafter, in the same manner as in the above embodiment, the deep groove ball bearing 1 Monitor the state of revolution slippage.

The strain measuring instrument 35 is not limited to the one that detects the strain value of the outer ring 3, and may detect the strain value of any one of the inner ring 2, the rotating shaft 6, and the housing.

As described above, according to the bearing state monitoring method and the state monitoring device of the first to fifth embodiments, vibration, sound, or distortion of the inner ring, outer ring, shaft, and housing generated from the bearing by the sensors 20 and 35. After detecting a signal based on the value, the waveform processing unit 32 performs frequency analysis on the signal to calculate spectrum data, the calculation unit 33 compares the peak frequency of the spectrum data with the theoretical frequency, and the bearing 1 Only the fluctuation of the number of rotations of the rolling element 4 and the fluctuation of the number of revolutions, or the fluctuation of the number of revolutions is obtained. As a result, the operating conditions of the bearing such as rotation slip, revolution slip, excessive preload of the bearing, preload release, fluctuation of the rotation number due to roller skew, and fluctuation of the revolution number, which cause abnormal heat generation, skidding, and early peeling, are monitored. can do.

(Sixth Embodiment)
FIG. 10 is a schematic configuration diagram of a bearing condition monitoring device for measuring the revolution slip and rotation slip of a plurality of deep groove ball bearings, and FIG. 11 is an image diagram of a graph of an envelope spectrum measured by the bearing condition monitoring device. is there.

As shown in FIG. 10, the bearing state monitoring device 10 of the present embodiment is a device for monitoring the state of a plurality of (one pair in this embodiment) deep groove ball bearings 1. Similar to FIG. 3, each of the plurality of deep groove ball bearings 1 has an inner ring 2 fitted to the rotating shaft 6, and each outer ring 3 is fixed to a housing (not shown).

The bearing condition monitoring device 10 includes a plurality of vibration sensors 20 corresponding to each deep groove ball bearing 1, a plurality of A / D conversion units 31 and a plurality of waveform processing units 32 provided corresponding to each vibration sensor 20. And a calculation unit 33, and a determination unit 34. The plurality of A / D conversion units 31, the plurality of waveform processing units 32, the calculation unit 33, and the discrimination unit 34 are mainly composed of the information processing device 30.

Each vibration sensor 20 detects vibration generated from the deep groove ball bearing 1 as an electric signal arranged opposite to the outer ring 3, amplifies the detected electric signal by each amplifier 21, and inputs the detected electric signal to each A / D conversion unit 31. To do.

The vibration data input from each vibration sensor 20 to each A / D conversion unit 31 is converted into a digital signal by each A / D conversion unit 31, and then envelope processing and frequency analysis are performed by each waveform processing unit 32. Calculate the spectrum data.

The calculation unit 33 calculates the ratio of the peak frequencies of the spectral data generated by the rotation or revolution of each bearing obtained by the waveform processing unit 32, and the rotation of the rolling element when the inner and outer rings of the bearing and the rolling element do not slip. Or, by comparing with the ratio of the theoretical frequencies due to revolution, the fluctuation of the rotation number of the rolling element of the bearing and the fluctuation of the revolution number are obtained.
The peak frequency is selected by a conventional method such as comparison with a certain reference value.

FIG. 11 is an image diagram of the peak frequency of the spectral data of each bearing. In the figure, A1 is the peak frequency caused by the revolution of one bearing, and A2 is the peak frequency caused by the revolution of the other bearing. .. Compare the peak frequency ratio (A1 / A2) of the spectral data of each bearing obtained by the waveform processing unit 32 with the theoretical frequency ratio (A1'/ A2') due to the revolution of each bearing, and either one. Check if there is any revolution slippage in the bearings or both bearings. Note that FIG. 11 shows a case where the peak frequency A1 due to the revolution of one of the bearings deviates from the theoretical frequency A1', and by the above comparison, A1 / A2 ≠ A1'/ A2'. It is detected that there is a fluctuation in the number of revolutions. Further, the theoretical frequencies A1'and A2'of each bearing are given by the rotation speed and the bearing specifications, respectively, but the ratio of the theoretical frequencies A1'/ A2' is given by the bearing specifications, and the rotation speed is unnecessary. Become.
Similarly, when determining the fluctuation of the number of rotations, the ratio of the peak frequency caused by the rotation of each bearing is compared with the ratio of the theoretical frequency caused by the rotation of each bearing.

Then, the discriminating unit 34 determines the abnormality of the deep groove ball bearing 1 from the presence / absence and magnitude of the fluctuation of the rotation number or the fluctuation of the revolution number based on the comparison result of the ratio of the peak frequency of the spectrum data and the ratio of the theoretical frequency of each bearing. Monitor the slippage of the inner and outer rings 2 and 3 and the ball 4 that cause heat generation and skidding.

By measuring the fluctuation of the rotation number and the fluctuation of the revolution number in this way, it is possible to monitor the abnormal heat generation of the deep groove ball bearing 1, the rotation slip that causes skidding and peeling, and the state of the revolution slip. ..

(7th Embodiment)
FIG. 12 is a schematic configuration diagram of a condition monitoring device that monitors two preloaded tapered roller bearings with one vibration sensor, and FIG. 13 is a graph of an envelope spectrum measured by the bearing condition monitoring device. It is an image diagram.

This embodiment is different from the sixth embodiment in which the vibration sensor 20 is used for each bearing, whereas the one vibration sensor 20 that detects the vibration of the housing 7 monitors the bearing. Since the other parts are the same as those of the bearing condition monitoring device according to the sixth embodiment of the present invention, the same parts are designated by the same reference numerals or equivalent reference numerals to simplify or omit the description.

As shown in FIG. 13, the ratio (A3 / A4) of the peak frequency A3 caused by the revolution of one bearing 11C and the peak frequency A4 caused by the revolution of the other bearing 12C in the spectrum data obtained by the waveform processing unit 32. ) And the ratio of the theoretical frequencies (A3'/ A4') caused by the revolution of the respective bearings 11C and 12C, the variation of the number of revolutions is obtained.
Similarly, when determining the fluctuation of the number of rotations, the ratio of the peak frequency caused by the rotation of each bearing is compared with the ratio of the theoretical frequency caused by the rotation of each bearing.
Then, also in this embodiment, the slippage that causes abnormal heat generation and skidding is monitored from the presence / absence and magnitude of the fluctuation of the rotation number or the fluctuation of the revolution number.

(8th Embodiment)
FIG. 14 is a schematic configuration diagram of a bearing condition monitoring device for measuring fluctuations in the number of revolutions of a self-aligning roller bearing, and FIG. 15 is an image diagram of a graph of an envelope spectrum measured by the bearing condition monitoring device.

The bearing condition monitoring device 10 of the present embodiment is different from the bearing condition monitoring device of the sixth embodiment in that the bearing to be measured is the self-aligning roller bearing 1A. Although the specific configuration of the self-aligning roller bearing 1A is not shown, barrel-shaped rolling elements are formed in the R1 row and the R2 row between the inner ring having two rows of orbits and the outer ring having a spherical orbit. The bearings are arranged in two rows, and the vibration corresponding to each row (R1 row and R2 row) is measured by the vibration sensor 20.

As shown in FIG. 15, the ratio (A5 / A6) of the peak frequencies A5 and A6 of the spectrum data of each row (R1 row and R2 row) obtained from the waveform processing unit 32, and the inner / outer ring and the rolling element slip. By comparing the ratio of the theoretical frequencies (A5'/ A6') due to the revolution of each row in the absence state, the variation of the number of revolutions of the R1 row or the R2 row can be obtained. The discriminating unit 34 monitors the roller skew of the self-aligning roller bearing 1A from the fluctuation of the number of revolutions in the R1 row and the R2 row, or the rotation slip and the revolution slip due to the preload excess and the preload release.

As described above, according to the bearing state monitoring method and the state monitoring device of the sixth to eighth embodiments, vibration, sound, or distortion of the inner ring, outer ring, shaft, and housing generated from the bearing by the sensors 20 and 35. After detecting a signal based on the value and performing frequency analysis on the signal in the waveform processing unit 32 to calculate spectrum data, the calculation unit 33 rotates and revolves in each row of each bearing or double-row bearing. Comparing at least one of the peak frequency ratio of the data with the ratio of the theoretical frequency generated by the rotation of each row of each bearing or the double row bearing and the ratio of the theoretical frequency generated by the revolution, the number of rotations of the bearing Find at least one of the fluctuations and the fluctuations of the number of bearings. As a result, without using the rotation speed of the rotation sensor, rotation slip, revolution slip, bearing preload overload, preload release, rotation number fluctuation due to roller skew, and revolution number, which cause abnormal heat generation, skidding, and premature peeling. It is possible to monitor the operating condition of the bearing such as the fluctuation of the bearing.

The present invention is not limited to the above-described embodiments, and can be appropriately modified, improved, and the like.
For example, in order to improve the measurement accuracy, it is permissible to indent or scratch any component of the bearing while ensuring the required performance such as life and allowable rotation speed. As a result, the absolute value of the peak frequency of the spectrum data becomes large, and it becomes easy to monitor the fluctuation of the rotation number and the fluctuation of the revolution number.
Further, the rotation speed may be measured by using a tachometer that emits a signal in synchronization with the rotation without using a tachometer. Alternatively, vibration generated in synchronization with rotation (for example, vibration of gears) may be used without using an external signal.

Further, in each of the above-described embodiments, the vibration sensor is used to detect the vibration generated from the bearing, but an acoustic sensor such as a microphone may be used to detect the sound generated from the bearing.

Further, in the above embodiment, the case where both the fluctuation of the rotation number of the rolling element of the bearing and the fluctuation of the revolution number are obtained and the case where the fluctuation of the revolution number of the rolling element of the bearing is obtained are described. May obtain the fluctuation of the number of rotations of the rolling element of the bearing.

In the above embodiment, deep groove ball bearings, angular contact ball bearings, self-aligning roller bearings, and tapered roller bearings are used as measurement targets, but any bearing can be measured, for example, a cylindrical roller bearing. It may be measured.

This application is based on Japanese Patent Application 2018-094544 filed May 16, 2018, the contents of which are incorporated herein by reference.

1 Deep groove ball bearing (bearing)
1A self-aligning roller bearing (bearing)
11C, 12C Tapered Roller Bearings (Bearings)
10 Bearing condition monitoring device 20, 20A, 20B Vibration sensor (sensor)
24 Strain gauge 32 Waveform processing unit 33 Calculation unit 34 Discrimination unit 35 Strain measuring instrument (sensor)
A Theoretical frequency due to rotation when there is no slip between the inner and outer rings and the rolling element B Theoretical frequency due to revolution when there is no slip between the inner and outer rings and the rolling element C Revolution slip D Revolution slip E, F, G Fluctuations in the number of revolutions A1 Fig. 10 Peak frequency A1 ′ due to the revolution of the rolling element of the left column bearing of Fig. 10 Theoretical frequency A2 due to the revolution of the rolling element of the left column bearing of Fig. 10 Peak frequency A2 ′ due to the revolution of the rolling element of the right column bearing of Fig. 10 Right row bearing of Fig. Theoretical frequency due to the revolution of the rolling element A3 Peak frequency due to the revolution of the rolling element of the left bearing in Fig. 12 A3'Theoretical frequency due to the revolution of the rolling element of the left bearing in Fig. 12 Peak due to the revolution of the rolling element of the right bearing in Fig. Frequency A4'Theoretical frequency due to the revolution of the rolling element of the right side bearing in FIG. 12 A5 Peak frequency due to the revolution of the rolling element in the R1 row of FIG. 14 A5'Theoretical frequency due to the revolution of the rolling element in the R1 row of FIG. Peak frequency due to revolution of the rolling elements in the row A6'Theoretical frequency due to the revolution of the rolling elements in the R2 row in FIG.

Claims (4)

A bearing condition monitoring method that monitors the operating condition of bearings.
A process of detecting vibration, sound, or a signal based on the strain value of the inner ring, outer ring, shaft, and housing generated from the bearing, and
The process of performing frequency analysis on the signal and calculating the spectrum data,
The frequency at which the peak of the spectral data appears is compared with at least one of the theoretical frequency due to the rotation of the rolling element and the theoretical frequency due to the revolution when the inner and outer rings of the bearing and the rolling element do not slip, and the rolling of the bearing is compared. The process of finding at least one of the fluctuations in the number of rotations and the number of revolutions of a moving body,
A method for monitoring the condition of a bearing, which comprises. A bearing condition monitoring device that monitors the operating condition of bearings.
A sensor that detects vibration, sound, or a signal based on the strain values of the inner ring, outer ring, shaft, and housing generated from the bearing.
A waveform processing unit that performs frequency analysis on the signal and calculates spectrum data,
The frequency at which the peak of the spectral data appears is compared with at least one of the theoretical frequency due to the rotation of the rolling element and the theoretical frequency due to the revolution when the inner and outer rings of the bearing and the rolling element do not slip, and the rolling of the bearing is compared. An arithmetic unit that obtains at least one of the fluctuations in the number of rotations and the number of revolutions of a moving object,
A bearing condition monitoring device comprising. A bearing condition monitoring method that monitors the operating condition of each row of multiple bearings or double row bearings.
A step of detecting a signal based on vibration, acoustics, or strain values of an inner ring, an outer ring, a shaft, and a housing generated from each row of the plurality of bearings or the double row bearings.
The process of performing frequency analysis on the signal and calculating the spectrum data,
When there is no slip between the ratio of the peak frequencies of the spectral data due to the rotation and revolution of each row of the bearing or the double row bearing and the inner and outer rings and the rolling element of each row of the bearing or the double row bearing. Compare with at least one of the ratio of the theoretical frequency generated by the rotation of the rolling element and the ratio of the theoretical frequency generated by the revolution, and the number of rotations of the rolling element in each row of the bearing or the double row bearing. And the process of finding at least one of the fluctuations in the number of revolutions,
A method for monitoring the condition of a bearing, which comprises. A bearing condition monitoring device that monitors the operating condition of each row of multiple bearings or double row bearings.
A sensor that detects vibration, acoustics, or signals based on strain values of the inner ring, outer ring, shaft, and housing generated from each row of the plurality of bearings or the double row bearings.
A waveform processing unit that performs frequency analysis on the signal and calculates spectrum data,
When there is no slip between the ratio of the peak frequencies of the spectral data due to the rotation and revolution of each row of the bearing or the double row bearing and the inner and outer rings and the rolling element of each row of the bearing or the double row bearing. Compare with at least one of the ratio of the theoretical frequency generated by the rotation of the rolling element and the ratio of the theoretical frequency generated by the revolution, and the number of rotations of the rolling element in each row of the bearing or the double row bearing. And the arithmetic unit that obtains at least one of the fluctuations of the number of revolutions,
A bearing condition monitoring device comprising.

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