Patent Description:
In a related art, various techniques are proposed for detecting vibration generated from a rolling bearing and diagnosing the presence or absence of an abnormality or an abnormal part in the rolling bearing in an actual operating state of a mechanical device without disassembling the mechanical device in which the rolling bearing is incorporated.

Further, since rolling bearings used in large rotating machines such as wind turbine drive trains and mining equipment are not easy to replace, these bearings are often used continuously even when some damage occurs. Thus, it is required to clearly grasp a replacement timing of bearings according to the progress of damage.

For example, in a state monitoring device of a rolling bearing described in Patent Literature <NUM>, a relative displacement between an inner ring and an outer ring in a radial direction is detected by a displacement sensor, and a state of the rolling bearing is diagnosed according to a stepwise increase pattern of the relative displacement between the inner ring and the outer ring corresponding to an increase in the total number of times of load received by the inner ring of a stationary wheel from a plurality of rolling elements.

Further, in a state monitoring device described in Patent Literature <NUM>, after a vibration waveform is divided into a plurality of damage filter frequency bands and extracted, the waveform is subjected to envelope processing and frequency analysis to obtain spectrum data. Then, in the extracted frequency band, a bearing damage frequency calculated based on a rotational speed signal of a rolling bearing is compared with a frequency component included in the spectral data, an abnormal part of the rolling bearing is identified, and a degree of damage or a progress of damage of a part is diagnosed based on a vibration effective value calculated for each damage filter frequency band. Patent Literature <NUM> discloses an abnormality diagnosis method of a rolling bearing having the features of the preamble of claim <NUM>. Another abnormality diagnosis method of a rolling bearing is known from Non-Patent Literature <NUM>.

However, in the device described in Patent Literature <NUM>, degree of damage is divided into three stages based on the finding that the relative displacement of the inner ring and the outer ring gradually increases stepwise as the damage progresses, and this determination is limited to qualitative determination. Further, in the device described in Patent Literature <NUM>, the degree of damage is diagnosed in three stages, and specifically, the progress of flaking is not evaluated quantitatively.

The present invention has been made in view of the above-described problems, and an object thereof is to provide an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing capable of quantitatively evaluating a progress of flaking occurring in a bearing ring when the bearing ring receives a repeated load from a rolling element.

The above object of the present invention is achieved by the features as specified in the appended claims.

According to the invention, by acquiring the time when the rolling element enters the flaking region of the bearing ring and the time when the rolling element escapes from the flaking region of the bearing ring and estimating the flaking size from the time difference between the entry time and the escape time, a progress of the flaking occurring in the bearing ring can be quantitatively evaluated, and a replacement timing of the bearing can be clearly grasped.

Further, according to the invention, the gradation image is formed by repeatedly drawing the output signal in gradation with the entry time, at which the rolling element enters the flaking region of the bearing ring, as an origin for each rotation cycle of the rotation ring. Thereby, it is possible for an operator to quantitatively evaluate and visually recognize a progress of flaking occurring in the bearing ring from the gradation image, and clearly grasp the replacement timing of the bearing.

Hereinafter, preferred embodiments of an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing according to the present invention will be described with reference to the drawings.

Hereinafter, an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing according to a first embodiment will be described with reference to <FIG>. As illustrated in <FIG>, an abnormality diagnosis apparatus <NUM> of the present embodiment diagnoses an abnormality of a rolling bearing <NUM> incorporated in mechanical equipment <NUM>, and includes a vibration sensor <NUM> that detects vibration (a signal) generated from the rolling bearing <NUM>, a control device <NUM> including an arithmetic processing unit <NUM> that receives the signal detected by the vibration sensor <NUM> via a data transmission unit <NUM> and performs signal processing to estimate the presence or absence of flaking of a bearing ring (that is, an inner ring <NUM> or an outer ring <NUM>) of the rolling bearing <NUM> and a flaking size in real time, and a control unit <NUM> that drives and controls the mechanical equipment <NUM>, and an output device <NUM> including a monitor, an alarm, and the like.

Examples of the mechanical equipment <NUM> to which the abnormality diagnosis apparatus <NUM> of the present embodiment is applied include a wind turbine, mining equipment, and the like.

The rolling bearing <NUM> includes an inner ring <NUM> externally fitted to a rotating shaft of the mechanical equipment <NUM>, an outer ring <NUM> fitted in a housing <NUM> or the like, a plurality of rolling elements <NUM> rotatably arranged between the inner ring <NUM> and the outer ring <NUM>, and a cage (not illustrated) rotatably holding the rolling elements <NUM>.

The vibration sensor <NUM> is fixed to a load zone of the housing <NUM> to which the outer ring <NUM>, which is a fixed ring of the rolling bearing <NUM>, is attached. <FIG> illustrates an embodiment in which an upper portion is the load zone. Examples of a fixing method of the vibration sensor <NUM> include bolt fixing, adhesion, a combination of bolt fixing and adhesion, and embedding with a resin material.

As the vibration sensor <NUM>, a piezoelectric acceleration sensor, an electro-dynamic speedy sensor, or a displacement sensor can be used. A sensor can be appropriately used to equivalently detect vibration and convert the vibration into an electric signal by detecting acceleration, velocity, displacement, and the like according to an operating state of the rolling bearing. For example, acceleration may be detected when the rolling bearing rotates at a high speed, and displacement may be detected when the rolling bearing rotates at a low speed. As will be described later, in the present embodiment, flaking is analyzed using a vibration velocity waveform represented by velocity. Therefore, when an acceleration signal is detected, an output signal is converted by integration processing, and when a displacement signal is detected, an output signal is converted by differential processing to obtain the vibration velocity waveform.

The control device <NUM> includes a microcomputer (IC chip, CPU, MPU, DSP, and the like) and an internal memory (not illustrated). Therefore, since each processing to be described later can be executed by a program of the microcomputer, the device can be simplified, downsized, and inexpensively configured.

The control device <NUM> stores a diagnosis result of the rolling bearing <NUM> determined by the arithmetic processing unit <NUM> in the internal memory, outputs an operation of the mechanical equipment <NUM> to the control unit <NUM>, and feeds back a control signal for driving the mechanical equipment <NUM> according to the diagnosis result to the operation of the mechanical equipment <NUM> (such as reducing a rotation speed). Further, the control device <NUM> transmits data to the output device <NUM> by a data transmission unit <NUM> using a wired or wireless communication in consideration of a network.

The output device <NUM> displays the diagnosis result of the rolling bearing <NUM> on a monitor and the like in real time. When an abnormality is detected, the alarm device such as a light or a buzzer may be used to alert an operator to the abnormality. Further, since the data transmission unit <NUM> of the signal may be capable of accurately transmitting and receiving the signal from the vibration sensor <NUM>, wired or wireless communication may be used in consideration of the network.

In the load zone of the rolling bearing <NUM>, the rolling element <NUM> comes into contact with the inner ring <NUM> and the outer ring <NUM> and bears a predetermined rolling element load when the rolling element <NUM> passes through a sound portion (a normal region without flaking). On the other hand, when the flaking occurs, generally, since a flaking depth is larger than an elastic approach amount of Hertzian contact between the rolling element <NUM> and the bearing ring, the rolling element <NUM> is in contact with only one of the inner ring <NUM> and the outer ring <NUM> while passing through a flaking region of the bearing ring, and the rolling element load is smaller than the rolling element load in the sound portion in a state in which the rolling element <NUM> passes through the inside of the flaking.

More specifically, as illustrated in <FIG>, before the rolling element <NUM> enters the flaking region of the inner ring <NUM>, the rolling element load is borne by the housing <NUM> via the outer ring <NUM>, but when the rolling element <NUM> enters the flaking region of the inner ring <NUM>, the rolling element load decreases. A change in the rolling element load is regarded as a negative maximum value (a bottom portion) of the vibration velocity when a direction toward a radially outer side is defined as a positive direction. In <FIG>, reference sign λ denotes a flaking length (unit: [m], [mm] and the like), and reference sign v denotes a revolution velocity of the rolling element (unit: [m/s] and the like).

As illustrated in <FIG>, when the rolling element <NUM> escapes from the flaking region of the inner ring <NUM>, the rolling element load borne by the housing <NUM> via the outer ring <NUM> increases and recovers, and the change in the rolling element load is regarded as a positive maximum value (a top portion) of the vibration velocity.

That is, when the rolling element <NUM> enters or escapes from the flaking region of the inner ring <NUM>, since directions of the changes in the rolling element load are different, the decrease in the rolling element load appears as the negative maximum value (the bottom portion) of the vibration velocity, and the increase in the rolling element load appears as the positive maximum value (the top portion) of the vibration velocity.

Further, in practice, in one rotation cycle of the inner ring <NUM>, which is a rotation ring, a number of collisions caused when the rolling element <NUM> passes through the flaking region of the inner ring in the load zone appear as vibration, but in the present embodiment, the vibration velocity which is the negative or positive maximum value generated when the rolling element <NUM> in the load zone passes through the flaking region of the inner ring is acquired for diagnosis.

Incidentally, since flaking propagates in a rotation direction, an axial direction, and a depth direction of the inner ring microscopically, whether the flaking occurs is determined by comparing an absolute value of the negative or positive maximum value of the vibration velocity with a threshold, and when the absolute value is larger than the threshold, it is determined that the flaking occurs.

When the flaking occurs, the arithmetic processing unit <NUM> acquires, from the vibration velocity waveform output as illustrated in <FIG>, a time indicated by the negative maximum value of the vibration velocity (the bottom portion) as an entry time when the rolling element <NUM> enters the flaking region of the bearing ring, and a time indicated by the positive maximum value (the top portion) of the vibration velocity within a predetermined time from the entry time as an escape time when the rolling element <NUM> escapes from the flaking region of the bearing ring.

Here, the predetermined time is set to be a period slightly longer than a vibration cycle of bearing damage (a time interval at which the rolling element passes through the flaking region of the inner ring). For example, the predetermined time is set to be equal to or less than twice the interval at which the rolling element passes through the flaking region of the inner ring.

Since it is possible to select which direction is the positive direction, the output of the vibration sensor <NUM> may be represented as the positive maximum value (the top portion) when the rolling element enters the flaking region of the inner ring, and may be represented as the negative maximum value (the bottom portion) when the rolling element escapes from the flaking region. In this case, the time indicated by the positive maximum value (the top portion) of the vibration velocity is set as the entry time, and the time indicated by the negative maximum value (the bottom portion) of the vibration velocity is set as the escape time.

As illustrated in <FIG>, depending on the outputs of the vibration sensor <NUM>, the maximum value (the top portion) and the minimum value (the bottom portion) of the vibration velocity indicating the entry time and the escape time may both be positive values or negative values.

In this case, in the vibration velocity waveform acquired from the output signal, the time indicating either one of the maximum value of the vibration velocity larger than the predetermined upper limit value and the minimum value of the vibration velocity smaller than the predetermined lower limit value within the rotation cycle of the inner ring may be acquired as the entry time, and the time indicating the other of the maximum value and the minimum value of the vibration velocity within the predetermined time from the entry time may be acquired as the escape time.

Next, the arithmetic processing unit <NUM> estimates the flaking size based on a flaking passage time, which is a time difference between the entry time and the escape time. Specifically, in the present embodiment where the inner ring is rotated and the outer ring is fixed, when the flaking occurs in the inner ring, the flaking size is given by the following Formula (<NUM>). [Formula <NUM>] <MAT>.

Further, when the flaking occurs in the outer ring, the flaking size is given by the following Formula (<NUM>). [Formula <NUM>] <MAT>.

Different from the present embodiment, in a rolling bearing whose inner ring is fixed and outer ring is rotated, the flaking size is given by the following Formula (<NUM>) when the flaking occurs in the inner ring, and the flaking size is given by the following Formula (<NUM>) when the flaking occurs on the outer ring. In this case, the vibration sensor <NUM> may be attached to a stationary side shaft. [Formula <NUM>] <MAT>
[Formula <NUM>] <MAT>.

The following represents the meaning of each reference sign in Formulas (<NUM>) to (<NUM>). τ: flaking passage time.

Here, the determination of whether the flaking occurs in the inner ring or the outer ring may be determined based on an interval between time points of entering the flaking region of the rolling elements <NUM> in the rotation cycle of the inner ring <NUM>, or may be determined by using a method of determining a damage position based on whether measured frequency components generated by performing analysis processing such as envelope analysis on measured data detected from the rolling bearing match theoretical frequency components of the inner ring and the outer ring obtained by calculation.

Accordingly, the control unit <NUM> may stop the mechanical equipment <NUM> based on the obtained flaking size, or may perform control so as to reduce the rotation speed.

Further, if it is determined that the flaking size will not cause serious damage by the time the rolling bearing <NUM> is replaced even if the rolling bearing <NUM> is operated as it is, the control unit <NUM> does not perform the control described above and may continue the operation of the mechanical equipment <NUM> as it is.

As described above, the abnormality diagnosis method and the abnormality diagnosis apparatus <NUM> according to the present embodiment include a step of acquiring, from the output signal detected by the vibration sensor <NUM> during the rotation of the rolling bearing <NUM>, the entry time when the rolling element <NUM> enters the flaking region of the inner ring <NUM> or the outer ring <NUM> which is the bearing ring, and the escape time when the rolling element <NUM> escapes from the flaking region of the bearing ring, and a step of estimating the flaking size based on the flaking passage time, which is the time difference between the entry time and the escape time. Thus, the progress of the flaking occurring in the bearing ring can be quantitatively evaluated, and a replacement timing of the bearing can be clearly grasped.

Next, an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing according to a second embodiment will be described with reference to <FIG>. Similar components as those in the first embodiment are denoted by the same or corresponding reference numerals, and a description thereof is omitted or simplified.

The present embodiment is different from the first embodiment in that after the entry time of the inner ring <NUM> into the flaking region is acquired from the output signal obtained by using the vibration sensor <NUM>, a gradation image (see <FIG>) based on a vibration velocity waveform is displayed with an entry time as an origin, and an escape time is acquired.

Specifically, as illustrated in <FIG>, from the obtained vibration velocity waveform data, data is clipped for each rotation cycle (for example, <NUM>) of the inner ring <NUM> and a desired number of pieces of data (I), (II), (III). (n) is obtained. For example, (I), (II), and (III) in <FIG> indicate that the vibration velocity waveform data for three rotations of the inner ring <NUM> is obtained.

Then, from each of the cut-off data, as illustrated in <FIG>, the vibration velocity of the negative maximum value (the bottom portion) is acquired as the entry time. Further, vibration velocity waveform data having a cycle of <NUM> × [<NUM>/bearing damage frequency] from the entry time, that is, vibration velocity waveform data having a cycle slightly longer than a bearing damage cycle (a time interval at which adjacent rolling elements reach the flaking region of the inner ring) is acquired from each of the clipped data. In this case, the bearing damage frequency uses the frequency of the inner ring <NUM> in occurrence interval frequencies corresponding to the damage of each part due to the rotational speed illustrated in <FIG>.

As illustrated in <FIG>, the vibration velocity waveform data is replaced with coordinate data with the entry time as the origin.

Then, drawing is performed in which the entry time is set as the origin, the positive vibration velocity in the rotation cycle of the inner ring <NUM> is set to white, and the negative vibration velocity is set to black, the gradation drawing is repeated for each rotation cycle of the inner ring <NUM> so as to be stacked along a vertical axis of a graph, and then a gradation image as illustrated in <FIG> is formed. The gradation image is output by the output device <NUM>.

The color arrangement of the gradation drawing is not limited to black and white as long as the magnitude of the positive and negative vibration velocities can be visually recognized. Further, in order to clarify the gradation, noise may be removed by using a low-pass filter that processes <NUM> or less.

On the basis of the acquired gradation image, the control device <NUM> performs image processing to acquire the most white position as the escape time.

The image processing is preferably performed by automatic processing. An example of the automatic processing is a method using machine learning. As teacher data used in the learning, a gradation image A of the above method is created using a bearing having a known flaking size. A learning model is obtained by learning the flaking size and the gradation image A in association with each other. New gradation image data is applied to the learning model, and the flaking size is estimated.

A general machine learning software may be used, and examples thereof include TensorFlow (registered trademark) and scikit-learn. However, the machine learning software is not limited to these.

Thereafter, similar to the first embodiment, the flaking size is estimated based on the flaking passage time of the inner ring, which is the time difference between the obtained entry time and the escape time.

Therefore, also in the present embodiment, when the bearing ring receives repeated load from the rolling element, the progress of the flaking occurring in the bearing ring can be quantitatively evaluated, and the replacement timing of the bearing can be clearly grasped. Further, it is possible for the operator to visually recognize the progress of the flaking occurring in the bearing ring by the gradation image, and correctly determine the abnormality of the mechanical equipment.

Third embodiment not covered by the claimed subject-matter.

Next, an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing according to a third embodiment will be described. Similar components as those in the first or second embodiment are denoted by the same or corresponding reference numerals, and a description thereof is omitted or simplified.

In the above embodiment, the change in the rolling element load is diagnosed as a change in the vibration velocity by using the vibration sensor, but in the present embodiment, the rolling element load is directly detected by using a load sensor that detects the rolling bearing load.

The load sensor may be a piezoelectric force sensor <NUM>, and in this case, as illustrated in <FIG>, the piezoelectric force sensor <NUM> may be installed in a notch 114a provided in the housing <NUM> to measure the change in the rolling element load between the housing <NUM> and the outer ring <NUM>.

Alternatively, the load sensor may be a piezoelectric film 40a as illustrated in <FIG> or an optical fiber 40b as illustrated in <FIG>. In either case, when the piezoelectric film 40a or the optical fiber 40b is sandwiched between the housing <NUM> and the outer ring <NUM>, the change in the rolling element load is measured.

Therefore, since a waveform representing the load is acquired from the load sensor, in the time acquisition step, a time when the load decreases below a threshold in a rotation cycle of the rotation ring in a waveform representing the load is set as the entry time, and a time when the load increases above the threshold within a predetermined time from the entry time is set as the escape time.

Further, in the present embodiment, similar to the first embodiment, the flaking size is estimated based on the flaking passage time, which is the time difference between the obtained entry time and the escape time.

Therefore, as in the present embodiment, in the case where the load sensor is used, when the bearing ring receives repeated load from the rolling element, the progress of the flaking occurring in the bearing ring can be quantitatively evaluated, and the replacement timing of the bearing can be clearly grasped.

In the present invention, similar to the second embodiment, when the rolling element load is detected using the load sensor, the gradation image may be formed by acquiring the entry time from the waveform representing the load, drawing the load in gradation in the rotation cycle of the rotation ring with the entry time as the origin, and repeating the gradation drawing for each rotation cycle of the rotating ring. Further, the escape time may be acquired from the gradation image.

Next, an abnormality diagnosis method and an abnormality diagnosis apparatus of a rolling bearing according to a fourth embodiment will be described. Similar components as those in the first to third embodiments are denoted by the same or corresponding reference numerals, and a description thereof is omitted or simplified.

In the second embodiment, the gradation image is formed by drawing the vibration waveform in gradation in the rotation cycle of the inner ring <NUM> with the entry time as the origin, repeating the gradation drawing for each rotation cycle of the inner ring <NUM>, and stacking the gradation drawing along the vertical axis of the graph. However, in the present embodiment, the gradation image is acquired over a longer period of time.

In the present embodiment, the gradation image is formed by repeating, for each rotation cycle of the inner ring <NUM>, the gradation drawing in which the vibration waveform in the rotation cycle of the inner ring <NUM> is drawn along the vertical axis using the entry time as the origin, and stacking the gradation drawing along a horizontal axis. Further, <FIG> shows an excerpt from the above gradation image in the range of the vertical axis of one pitch (= a distance between points on outer peripheral surface of the inner ring with which adjacent rolling elements are in contact) with an operation time from <NUM> hours to <NUM> hours.

Accordingly, from the gradation image illustrated in <FIG>, it is possible to visually grasp, as an inclination, that a flaking length becomes longer with the progress of the operation time, and a degree of the progress of the flaking becomes easier to determine. Further, in <FIG>, by comparing the inclinations of the regions A and B, it can be seen that when the flaking length exceeds one pitch, a progress speed of the flaking rapidly increases.

In the present embodiment, it is possible to estimate the flaking length after a predetermined time (predetermined operation time) from the inclination obtained in the region A of <FIG>. Further, by using the result, it is possible to estimate the predetermined time (predetermined operation time) until the progress speed of the flaking increases rapidly and the flaking length reaches one pitch.

The estimation of the flaking length using the gradation image according to the present embodiment can also be applied to the gradation image obtained from the waveform representing the load described in the third embodiment.

The abnormality diagnosis method and the abnormality diagnosis apparatus of the present invention are not limited to the embodiment described above, and modifications, improvements, or the like can be made as appropriate. For example, a bearing type to which the present invention can be applied is not limited, and the present invention can be applied to all types of rolling bearings including ball bearings.

In a case where a time difference occurs between the time at which the rolling element enters the flaking region of the bearing ring and the time indicated by the negative maximum value of the vibration velocity in accordance with the flaking size occurring in the bearing ring and the size of the rolling element, for example, the time exceeding the threshold immediately before the negative maximum value may be set as the time at which the rolling element enters the flaking region of the bearing ring.

Claim 1:
An abnormality diagnosis method of a rolling bearing (<NUM>) used in rotating machinery comprising steps of:
acquiring by a control device, from an output signal detected by a sensor during a rotation of the rolling bearing (<NUM>), an entry time when a rolling element enters a flaking region of a bearing ring, and an escape time when the rolling element escapes from the flaking region of the bearing ring; and
estimating by the control device a flaking size based on a flaking passage time, which is a time difference between the entry time and the escape time,
wherein the sensor is a vibration sensor (<NUM>) configured to detect a vibration of the rolling bearing (<NUM>),
characterized in that
the acquiring the entry time and the escape time includes:
setting a time indicating a maximum value of either one of negative and positive vibration velocities whose absolute value is larger than a threshold in a rotation cycle of a rotation ring in a vibration velocity waveform acquired from the output signal as the entry time, or setting a time indicating either one of a maximum value of a vibration velocity larger than a predetermined upper limit value and a minimum value of the vibration velocity smaller than a predetermined lower limit value in a rotation cycle of a rotation ring in a vibration velocity waveform acquired from the output signal as the entry time; and
acquiring the escape time from a gradation image formed by drawing the vibration velocity in gradation in the rotation cycle of the rotation ring with the entry time as an origin and repeating and stacking the drawing for each rotation cycle of the rotation ring along a vertical or horizontal axis of a graph by an output device.