Bearing damage detection system and bearing damage detection method

Abstract

This bearing damage detection system comprises: a rotation sensor that detects rotation of a rolling bearing and outputs a rotation signal; a rotation fluctuation extraction unit that extracts rotation fluctuations of the rolling bearing from the rotation signal and generates a rotation fluctuation signal; a frequency analysis unit that performs frequency analysis on the waveform of the rotation fluctuation signal to find a frequency characteristic; a peak intensity calculation unit that finds a peak intensity corresponding to bearing damage from the frequency characteristic; and a damage detection unit that detects bearing damage of the rolling bearing on the basis of the peak intensity. The rotation fluctuation extraction unit finds the waveform of the rotation fluctuation signal from which various types of noise have been removed.

Description

Bearing damage detection system and bearing damage detection method

[0001] The present invention relates to a bearing damage detection system and a bearing damage detection method.

[0002] The wheels that make up the wheels of an automobile, and the disc rotors that make up the braking devices, such as disc brakes and drum brakes, are rotatably supported on the vehicle body suspension via a rolling bearing unit (hereinafter referred to as a hub unit). The outer ring and hub ring of this hub unit bearing are manufactured by hot forging medium-carbon steel with a carbon content of 0.5 to 0.6% by mass, followed by heat treatment of the raceway surface. However, because the inner ring raceway surface of the hub ring is relatively thick while the outer ring raceway surface is thin, raceway damage such as flaking often occurs on the outer ring raceway surface. Furthermore, when a strong external force is applied to the hub unit, the rolling elements can form indentations on the outer ring raceway surface.

[0003] Furthermore, because the aforementioned medium-carbon steel has higher toughness than bearing steel (C: 1% by mass), cracks at the maximum dynamic shear stress location are less likely to propagate toward the raceway surface and instead propagate parallel to the raceway surface. In the case of such cracks, the surface does not initially peel off; instead, the portion extending from the crack to the raceway surface is simply depressed by the rolling elements, resulting in minimal deterioration of vibration and noise. However, as the crack propagates and appears on the raceway surface, the spalling rapidly progresses. Similarly, indentations also affect vibration and noise. This type of failure mode, in which spalling rapidly progresses from a certain point, is undesirable for vehicles such as large trucks, where the distance from the driver to the wheel bearing is long and the driver has difficulty detecting small damage. Furthermore, considering future driverless vehicles and platooning, it is desirable to detect damage such as the spalling and indentations described above in hub unit bearings at a minor stage.

[0004] For example, a hub unit bearing 300 in Patent Document 1 has an outer ring 301 with a double-row outer ring raceway 301a, a hub 302 with a double-row inner ring raceway 302a, and a plurality of rolling elements 303 provided so as to be able to roll between the outer ring raceway 301a and the inner ring raceway 302a, as shown in Figure 43. The hub unit bearing 300 has encoders 304 provided on both axial sides of the hub 302, and is able to detect the torque applied to the hub 302 based on the phase difference between detection signals from sensors (not shown) facing the respective encoders 304.

[0005] Japanese Patent Application Publication No. 2004-19934

[0006] Damage to the outer ring and hub of a hub unit bearing, particularly to the outer ring raceway, as described above, is a cause of increased vibration and noise, and early detection is desirable. However, the hub unit of Patent Document 1 can detect torque but cannot detect damage that has occurred. Furthermore, detection of such damage is not limited to vehicle hub unit bearings, but is similarly applicable to other support mechanisms that use rolling bearings, and early detection is desirable.

[0007] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a bearing damage detection system and a bearing damage detection method that are capable of detecting damage to various parts, such as the raceway surfaces, of a rolling bearing at an early stage.

[0008] The present invention has the following configuration: (1) A bearing damage detection system comprising: a rotation sensor that detects the rotation of a rolling bearing and outputs a rotation signal, a rotation fluctuation extraction unit that extracts rotation fluctuation of the rolling bearing from the rotation signal and generates a rotation fluctuation signal, a frequency analysis unit that performs frequency analysis on the waveform of the rotation fluctuation signal to determine frequency characteristics, a peak intensity calculation unit that determines peak intensity corresponding to bearing damage from the frequency characteristics, and a damage detection unit that detects bearing damage in the rolling bearing based on the peak intensity. (2) A bearing damage detection method that comprises: detecting the rotation of a rolling bearing to generate a rotation signal, extracting rotation fluctuation of the rotation from the rotation signal to generate a rotation fluctuation signal, frequency analyzing the waveform of the rotation fluctuation signal to determine vibration peaks, determining peak intensities corresponding to bearing damage from the vibration peaks, and detecting bearing damage in the rolling bearing based on the peak intensity.

[0009] According to the present invention, damage to various parts such as the raceway surfaces of a rolling bearing can be detected at an early stage.

[0010] FIG. 1 is a schematic diagram of a bearing damage detection system for a hub unit bearing according to a first embodiment. FIG. 2 is a functional block diagram of a control unit. FIG. 3 is an explanatory diagram schematically showing the arrangement of sensors. FIG. 4 is a schematic circuit diagram of a pulse signal generating unit. FIG. 5 is an explanatory diagram schematically showing how vibration occurs when flaking occurs in a portion of the outer ring raceway. FIG. 6 is an explanatory diagram showing how relative displacement between the inner ring and the outer ring due to flaking in the outer ring raceway affects the sensor output. FIG. 7 is an explanatory diagram schematically showing how the sensor output signal from the sensor changes when the rolling elements transition from a floating state, a riding state, and the original rolling state. FIG. 8 is a flowchart showing the procedure for determining damage to a hub unit bearing. FIG. 9 is an explanatory diagram showing a pulse signal corresponding to the sensor output signal from the sensor and a spatial waveform in which the period of each pulse of this pulse signal is plotted. FIG. 10 is an explanatory diagram schematically showing the period of an arbitrary pulse in the pulse signal and the pulses for one rotation of the hub axle centered around that pulse. FIG. 11 is an explanatory diagram schematically showing the period of an arbitrary pulse in the pulse signal and the pulses for one rotation of the hub axle centered around that pulse. FIG. 12 is an explanatory diagram showing an example of a waveform from the extraction of hub axle rotation fluctuation from the pulse output signal to the generation of a rotation fluctuation signal. FIG. 13 is an explanatory diagram showing an example of a period ratio average value distribution, which is the average value of period ratio differences for each pole of the magnetic encoder. FIG. 14 is an explanatory diagram schematically showing a period ratio fluctuation waveform. FIG. 15 is an explanatory diagram schematically showing frequency characteristics obtained by FFT processing of the period ratio fluctuation waveform. FIG. 16 is an explanatory diagram of frequency characteristics of a pulse period waveform shown as a reference example. FIG. 17 is a flowchart showing another procedure for damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 8. FIG. 18 is a flowchart showing another procedure 2 for damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 8. FIG. 19 is a flowchart showing another procedure 3 for damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 8. FIG. 20 is a flowchart showing another procedure 4 for damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 8. FIG. 21 is a schematic diagram of a damage detection system for a hub unit bearing according to the second embodiment.FIG. 22 is an explanatory diagram schematically showing the positional relationship between the inner ring, outer ring, and magnetic encoder of a hub unit bearing and the detection area of ​​a rotation sensor. FIG. 23 is a schematic circuit diagram of a pulse signal generating unit. FIG. 24 is an explanatory diagram showing example waveforms of a pulse signal and a phase difference signal. FIG. 25 is an explanatory diagram showing the effect on sensor output of relative displacement between the inner and outer rings due to peeling of the outer ring raceway. FIG. 26 is an explanatory diagram showing the relationship between encoder displacement and the phase difference of the detected pulse signal. FIG. 27 is an explanatory diagram showing example changes in pulse signals PL_A, PL_B, and phase difference signal PD. FIG. 28 is an explanatory diagram schematically showing specific waveforms of pulse signals PL_A, PL_B, and phase difference signal PD. FIG. 29 is a flowchart showing the procedure for determining damage to a hub unit bearing using two sensors. FIG. 30 is an explanatory diagram showing the waveforms of pulse signals PL_A and PL_B. FIG. 31 is an explanatory diagram showing the change in period Ti and phase difference, with the horizontal axis representing the order of pulses in the pulse signal and the vertical axis representing time. FIG. 32 is an explanatory diagram showing an example of a waveform from the extraction of hub axle rotation fluctuation from the pulse output signal to the generation of a rotation fluctuation signal. FIG. 33 is an explanatory diagram showing an example of a phase difference ratio average value distribution. FIG. 34 is an explanatory diagram schematically showing a phase difference ratio fluctuation waveform. FIG. 35 is an explanatory diagram showing an example of frequency characteristics obtained by FFT processing of the phase difference ratio fluctuation waveform. FIG. 36 is a flowchart showing another procedure 1 of damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 29. FIG. 37 is a flowchart showing another procedure 2 of damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 29. FIG. 38 is a flowchart showing another procedure 3 of damage determination, which is a partial modification of the procedure in the flowchart shown in FIG. 29. FIG. 39 is a control block diagram from the process of calculating a difference waveform from the detected pulse signal to obtain a rotation fluctuation waveform. FIG. 40 is an explanatory diagram showing a time chart 1 from the detection waveform to the process of performing damage determination on the rolling bearing. Fig. 41 is an explanatory diagram showing time chart 2 from the detection waveform to the implementation of damage determination of the rolling bearing. Fig. 42 is an explanatory diagram showing time chart 3 from the detection waveform to the implementation of damage determination of the rolling bearing. Fig. 43 is a configuration diagram of a conventional hub unit bearing.

[0011] Embodiments of the present invention will be described in detail below with reference to the drawings. In the following description, a hub unit bearing will be described as an example of a bearing, but the application of the present invention is not limited to this. <First Embodiment> (Configuration of Damage Detection System) FIG. 1 is a schematic configuration diagram of a bearing damage detection system 100 for a hub unit bearing according to a first embodiment. In this specification, the term "axially inner" in relation to a hub unit bearing refers to the vehicle body side of the hub unit bearing when mounted on the vehicle body, and refers to the right side indicated by the arrow Ax_in in FIG. 1 . Furthermore, the term "axially outer" refers to the wheel side of the hub unit bearing when mounted on the vehicle body, and refers to the left side indicated by the arrow Ax_out in FIG. 1 . Therefore, the bearing portions, outer ring raceways, and inner ring raceways arranged on the inner side are also referred to as inner row bearing portions, inner row outer ring raceways, and inner row inner ring raceways, and the bearing portions, outer ring raceways, and inner ring raceways arranged on the outer side are also referred to as outer row bearing portions, outer row outer ring raceways, and outer row inner ring raceways.

[0012] The hub unit bearing 11 shown in Figure 1 is a hub unit bearing for a driven wheel, and includes an outer ring 13 which is a fixed member, a hub 15 which is a rotating member, a plurality of rolling elements 17, and a rotation detection device 19. Figure 1 shows the hub 15 of the hub unit bearing 11 and a sensor 21, which will be described later, in horizontal cross section. The bearing damage detection system 100 for the hub unit bearing 11 includes the hub unit bearing 11, a pulse signal generation unit 23 which converts a detection signal from the sensor 21, which will be described later, of the rotation detection device 19 of the hub unit bearing 11 into a pulse signal and outputs it, and a control unit 24. Note that although a hub unit bearing for a driven wheel is shown here, bearing damage can also be detected in a hub unit bearing for a driving wheel in the same way.

[0013] The outer ring 13 has a stationary flange 25 on its outer peripheral surface, and an outer row outer ring raceway 27 and an inner row outer ring raceway 29 on its inner peripheral surface. When in use, the stationary flange 25 is coupled to and fixed to a knuckle of a suspension device (not shown), thereby preventing the outer ring 13 from rotating while supported by the suspension device.

[0014] The hub 15 is composed of a hub axle 31 and an inner ring 33 that is fitted onto the hub axle 31 and fixed by crimping, and is arranged coaxially (concentrically) with the outer ring 13 radially inside the outer ring 13.

[0015] The hub axle 31 has a circular mounting flange 35 that extends radially outward from the portion that protrudes axially outward from the axially outer opening of the outer ring 13, for fixing a wheel (driven wheel) and a braking rotating member such as a disc rotor (neither of which are shown).

[0016] The mounting flange 35 is provided with a plurality of insertion holes 35a, and each insertion hole 35a is fitted with a serrated hub bolt 37. Note that the plurality of insertion holes 35a can also be made into female threaded holes and the mounting flange 35 can be fixed to a braking rotating member such as a wheel or a disc rotor by screwing in a hub bolt.

[0017] An outer row inner ring raceway 39 is provided on a portion of the outer peripheral surface of the hub axle 31 that faces the outer row outer ring raceway 27. A small diameter step 41 is provided on the axially inner end of the outer peripheral surface of the hub axle 31 that faces the inner row outer ring raceway 29. The hub axle 31 has a crimping portion 43 that partially constitutes the outer peripheral surface of the small diameter step 41 and whose axially inner end is deformed radially outward to fix the inner ring 33 by crimping.

[0018] An inner row inner ring raceway 45 is provided on the outer peripheral surface of the inner ring 33 in a portion facing the inner row outer ring raceway 29. The inner ring 33 is fitted onto the small diameter step 41 of the hub axle 31 with its axially outer end face abutting against the step surface of the small diameter step 41, and is fixed to the hub axle 31 by crimping at a crimping portion 43 which is formed by deforming the axially inner end of the small diameter step 41 radially outward.

[0019] The rolling elements 17 are arranged to roll freely between the outer ring raceway 27 of the outer row and the inner ring raceway 39 of the outer row, and between the outer ring raceway 29 of the inner row and the inner ring raceway 45 of the inner row, while being held by each retainer 47.

[0020] The outer row outer ring raceway 27, the outer row inner ring raceway 39, and the rolling elements 17 form the outer row bearing portion 49A, and the inner row outer ring raceway 29, the inner row inner ring raceway 45, and the rolling elements 17 form the inner row bearing portion 49B.

[0021] A seal ring 51 is fixed to the axially outer end of the inner peripheral surface of the outer ring 13. The seal ring 51 closes the axially outer end opening of an internal space 53, which is provided with a plurality of rolling elements 17 and exists between the inner peripheral surface of the outer ring 13 and the outer peripheral surface of the hub axle 31. The seal ring 51 comes into sliding contact with a large-diameter step on the outer peripheral surface of the hub axle 31 that is axially outer than the inner ring raceway 39 of the outer row.

[0022] The rotation detection device 19 is an axial type sensor that is arranged near the inner row bearing portion 49B, i.e., at the axial inner end of the hub unit bearing 11, and detects the rotational speed of the hub 15, and is equipped with a magnetic encoder 55 and a sensor 21.

[0023] The magnetic encoder 55 is composed of a support ring 55a and an encoder body 55b. The support ring 55a is formed into an L-shaped cross section and an annular shape by pressing a magnetic metal plate such as a ferritic stainless steel plate such as SUS430 or a rolled steel plate such as SPCC. The outer axial portion of the support ring 55a is fitted and fixed to the inner ring 33.

[0024] The encoder body 55b is made entirely in a circular ring shape and is made of a permanent magnet made of a magnetic material such as ferrite powder mixed into rubber or thermoplastic resin, and is attached and fixed to the inner side surface of the circular portion of the support ring 55a, which is bent radially inward. The inner side surface of the encoder body 55b is magnetized with S and N poles alternately and at equal pitches in the circumferential direction.

[0025] The sensor 21 is a magnetic sensor that detects rotation of the hub 15, particularly rotation of the inner portion of the hub 15. The sensor 21 is disposed with its detection surface 21a facing the magnetic encoder 55, and is fixed to a side cover 59 that closes the inner opening of the outer ring 13. The sensor 21 detects the rotation of the hub 15 by detecting changes in magnetism in the detection region DR of the magnetic encoder 55 that faces the detection surface 21a, which occurs as the hub 15 rotates. In other words, the sensor 21 and the magnetic encoder 55 function as a rotation sensor, and this rotation sensor and the pulse signal generator 23 constitute the rotation detection device 19.

[0026] The rotation sensor is not limited to the above configuration, but may be a combination of a cylindrical encoder and a radial sensor.Furthermore, it is not limited to a magnetic encoder, but may be an optical encoder, a proximity sensor, or other types of encoders, or a gear-shaped encoder, or a gear-shaped exciter ring used in trucks, etc. to detect rotation.

[0027] The sensor 21 may be, for example, an active wheel speed sensor provided in the hub unit bearing 11. In this case, a detection element such as a Hall IC element or MR element whose electrical characteristics change in response to magnetism can be used as the sensor 21. The active wheel speed sensor faces a magnetic encoder and outputs a high voltage when the magnetic flux density is below a threshold, and outputs a low voltage when the encoder poles approach and the magnetic flux density exceeds the threshold. The active wheel speed sensor generates a pulse wave corresponding to the rotational speed of the tire. This pulse wave is generally sent to an on-board controller and used for anti-lock braking systems (ABS) and traction control, but using this pulse wave to detect damage eliminates the need for a separate rotation sensor.

[0028] The sensor 21 outputs a rotation detection signal to the pulse signal generating unit 23. The pulse signal generating unit 23 generates a pulse signal based on the input detection signal, and outputs the generated pulse signal to the control unit 24.

[0029] 2 is a functional block diagram of the control unit 24. The control unit 24 includes a rotational fluctuation extraction unit 24A, a frequency analysis unit 24B, a peak intensity calculation unit 24C, and a damage detection unit 24D. The rotational fluctuation extraction unit 24A extracts rotational fluctuation of the rolling bearing from the rotation signal output from the rotation sensor to generate a rotational fluctuation signal. The frequency analysis unit 24B performs frequency analysis on the waveform of the rotational fluctuation signal to determine frequency characteristics. The peak intensity calculation unit 24C determines peak intensity corresponding to bearing damage from the frequency characteristics. The damage detection unit 24D detects bearing damage in the rolling bearing based on the peak intensity.

[0030] The control unit 24 executes a procedure for determining damage to the hub unit bearing 11 based on the pulse signal input from the pulse signal generating unit 23. The control unit 24 is configured as a computer equipped with a processor such as a CPU and a storage device such as a read-only memory (ROM), a random access memory (RAM), a hard disk drive (HDD), or a solid state drive (SSD). In this case, the functions of the rotation detection device 19 shown in FIG. 1 , the pulse signal generating unit 23, and the various units shown in FIG. 2 can be realized by the processor executing a predetermined program stored in the storage device. Furthermore, the control unit 24 is not limited to being directly or wirelessly connected to the hub unit bearing 11 and the rotation detection device 19, but may also be connected via communication such as a network. In this case, damage to the hub unit bearing 11 can be determined from a remote location, improving management convenience. It also facilitates integrated management of multiple hub unit bearings 11.

[0031] In the bearing damage detection system 100 for the hub unit bearing 11 of this embodiment configured as described above, the control unit 24 detects damage occurring in the outer ring raceway or the inner ring raceway with high accuracy based on the pulse signal generated by the rotation detection device 19. This pulse signal generally has a frequency that changes depending on the rotational speed of the tire, and also contains magnetization errors due to uneven tire rotation and the magnetization pitch and magnetization eccentricity of the encoder. Furthermore, if the bearing raceway surface is damaged, the pulse signal also contains errors due to the relative displacement between the outer and inner rings that occurs with the damage, and the relative displacement caused by the impact when the rolling elements enter and leave the damaged area. If this variety of information is included in the pulse signal, it becomes difficult to extract only the damage information. However, in the bearing damage detection system 100, by removing the above-mentioned noises included in the pulse signal, damage information can be extracted with high accuracy, allowing for accurate evaluation.

[0032] Next, the process of generating the pulse signal described above based on the detection signal from the sensor 21 will be described. FIG. 3 is an explanatory diagram schematically illustrating the arrangement of the sensor 21. In FIG. 3, the direction of the radial load applied from the inner ring 33 to the outer ring 13 (the vertical direction Z, which is generally the direction of gravity) is shown as the up-down direction. The sensor 21 is preferably arranged in the vertical intermediate region Wa of the annular encoder body 55b, particularly in the central position. When a radial load is applied from the inner ring 33 to the outer ring 13 and the rolling elements roll between the outer ring raceway and the inner ring raceway, damage to the raceway surface causes radial vibrations that tend to occur more prominently in the vertical direction Z where the radial load acts. Therefore, detecting rotation in the intermediate region Wa near the center of the inner ring 33 and the outer ring 13 in the vertical direction Z enables sensitive detection of vertical displacement. Note that while FIG. 3 shows the area where rotation is detected by the sensor 21 as a rectangular detection region DR, the actual detection region DR is very small.

[0033] For example, when a radial load is applied from the inner ring 33 to the outer ring 13 and the rolling elements roll between the outer ring raceway and the inner ring raceway, radial vibrations caused by damage to the raceway surfaces become prominent in the vertical direction Z where the radial load acts. Therefore, detecting rotation within an intermediate region Wa near the center of the inner ring 33 and outer ring 13 in the vertical direction Z allows for sensitive detection of vertical displacement. The intermediate region Wa can be exemplified as the range radially inward of the outer ring raceway surface or the inner ring raceway surface.

[0034] However, the detection area DR of the sensor 21 is not limited to being located in the intermediate area Wa, but may be set at any position such as the upper or lower end in the vertical direction. Even in this case, rotation detection is possible, and the degree of freedom in installing the sensor 21 is not reduced.

[0035] 4 is a schematic circuit diagram of pulse signal generating unit 23. Pulse signal generating unit 23 outputs, as a pulse signal, an output signal from sensor 21 when, for example, drive voltage E adjusted by resistance value R is applied to sensor 21. Specifically, if sensor 21 is a current output type, the current value output from sensor 21 changes depending on the magnetic flux, and voltage E based on the relationship between voltage value E, current value I, and resistance value R is output as a pulse signal.

[0036] 5 is an explanatory diagram that schematically illustrates how vibration occurs when flaking occurs in a portion of the outer ring raceway 27. For example, consider a situation in which a radial load Pr is applied vertically upward from the inner ring 33 to the outer ring 13, resulting in a defective area Ad with flaking occurring vertically above the outer ring raceway 27. In this case, when a rolling element 17 rolling between the inner ring 33 and the outer ring 13 enters the defective area Ad, the internal gap between the outer ring raceway 27 and the inner ring raceway 45 widens due to the flaking, causing the rolling element 17 to float as it moves along the flaked surface. When the floating rolling element 17 moves through the defective area Ad along the inner ring rotation direction Ro, reaches the end of the defective area Ad, and then again enters between the outer ring raceway 27 and the inner ring raceway 45, which are free of flaking, the rolling element 17 collides with the inner ring 33 and the outer ring 13, generating an impact load that pushes the inner ring 33 downward. Note that loads on the inner ring occur in the horizontal direction in addition to the downward load, but here we will particularly explain the downward load. Repeated collisions of the rolling elements 17 cause vertical (and horizontal) vibrations. In other words, as the inner ring 33 rotates, the inner ring 33 and the outer ring 13 move vertically relative to each other in a defect cycle, and damage can be detected by detecting this vertical relative displacement with the sensor 21.

[0037] Figure 6 is an explanatory diagram showing the change in sensor output caused by relative displacement between the inner ring 33 and outer ring 13 due to flaking in the outer ring raceway. Figure 6 shows a case where flaking has occurred in the outer ring raceway 27 of the outer row bearing section 49A, of which the outer row bearing section 49A has the outer ring raceway 27 and the inner ring raceway 39, and the inner row bearing section 49B has the outer ring raceway 29 and the inner ring raceway 45. Note that this hub unit bearing is shown in the configuration of a hub unit bearing for a drive wheel.

[0038] Here, an example will be described in which a radial load Pr (preload) directed vertically upward is applied from the hub axle 31, which is the inner ring of the bearing portion 49A, to the outer ring 13, but damage can be detected using a similar procedure even when no preload is applied. When the rolling element 17A is in a floating state within a defective area Ad where flaking has occurred in the outer ring raceway 27, the relative velocity VR in the vertical direction between the hub axle 31 and the outer ring 13 is measured between a detection area DR on one side in the horizontal direction where a sensor (not shown) is located and the other side in the horizontal direction. ０and the vertical relative velocity VL on the other side ０ is equal to

[0039] Next, when the rolling element 17A reaches the end of the defective area Ad and rides up between the outer ring raceway 27 and the inner ring raceway 39, which are free of flaking, an impact load Pinp is applied to the hub axle 31. Then, the relative velocity between the hub axle 31 and the outer ring 13 in the detection area DR is the upward relative velocity VR in the floating state. ０ The displacement caused by the impact load Pinp causes a downward velocity Vp to be applied to the object, resulting in a relative velocity VR ０ Smaller speed VR １ On the other hand, on the other side of the detection region DR in the horizontal direction, the relative velocity VL ０ The velocity Vp due to the impact load Pinp in the same direction is applied, and the relative velocity VL in the floating state ０ Higher speed VL １ This becomes:

[0040] Then, as the hub axle 31 continues to rotate and the rolling element 17A returns to its original rolling state between the outer ring raceway 27 and the inner ring raceway 39, a return load Pbk acts on the hub axle 31. Then, the relative velocity between the hub axle 31 and the outer ring 13 in the detection range DR is the upward relative velocity VR in the floating state. ０ The displacement caused by the return load Pbk causes a velocity Vq in the same direction (upward), and the relative velocity VR in the floating state ０ Higher speed VR ２ On the other hand, on the other side of the detection region DR in the horizontal direction, the relative velocity VL ０ The velocity Vq due to the return load Pbk in the opposite direction (upward) is added, and the relative velocity VL in the floating state ０ Smaller speed VL ２ This becomes:

[0041] 7 is an explanatory diagram showing a change in the sensor output signal from the sensor 21 when the rolling element transitions from a floating state to a riding state and back to the original rolling state. The speed detected in the detection region DR is VR ０ , V.R. １ , V.R. ２ This VR ０ From VR １ , V.R.２ By detecting changes in the sensor output signal due to changes in speed, the presence of damage can be identified.

[0042] (Damage Determination Procedure) Figure 8 is a flowchart showing the procedure for determining damage to the hub unit bearing 11. Each of the following procedures is carried out based on commands from the control unit 24 shown in Figures 1 and 2. First, the rotation of the hub axle 31 that is driven to rotate in the hub unit bearing 11 is detected by the sensor 21, and a sensor output signal that is a rotation signal output from the sensor 21 is obtained (S11). This sensor output signal is converted into a pulse signal by the pulse signal generation unit 23.

[0043] FIG. 9 is an explanatory diagram showing a pulse signal corresponding to a sensor output signal and a spatial waveform plotting the period of each pulse of this pulse signal. This figure illustrates a pulse signal obtained when the rotation of the hub 31 is detected by a magnetic encoder and a magnetic sensor. The two pulse signals shown at the top of FIG. 9 represent magnetic changes in the magnetic encoder 55 that pass through the detection range DR of the sensor 21 as the hub axle 31 rotates. One of the pulse signals is an example of bipolar detection, in which the signal rises when a magnetic field of a north or south pole is detected. The other is an example of alternating detection, in which the signal rises when a magnetic field of a north or south pole is detected, and then falls when a magnetic field of a south or north pole is detected.

[0044] In the case of bipolar detection, when the pole of the magnetic encoder 55 reaches the detection region DR, the sensor output signal changes from a low voltage to a high voltage, and the timing of the transition from a low voltage to a high voltage is used as the timing of the rise described above. On the other hand, in the case of alternating polarity detection, when the pole of the magnetic encoder 55 reaches the detection region DR, the sensor output signal changes from a high voltage to a low voltage, and the timing of the transition from a high voltage to a low voltage is used as the timing of the rise described above.

[0045] For example, in the case of bipolar detection, a pair of HIGH voltages from the same type of poles is considered to be one pulse, and in the case of alternating detection, a pair of one HIGH voltage and the following LOW voltage is considered to be one pulse. If unevenness occurs in the rotation of the hub 31, the pulse period of each pulse (e.g., T1 to T7) will fluctuate.

[0046] Generally, in semiconductor design, the rise time of a signal is highly accurate, but the fall time of the signal is often low. Therefore, by using only the timing of the rise time of the signal as described above, it is possible to eliminate fall time errors from the spatial waveform. Depending on the characteristics of the signal, it is desirable to use either the transition from HIGH to LOW or the transition from LOW to HIGH, whichever is more accurate, as the rise time.

[0047] The change in the pulse period of each pulse of the pulse signal described above is shown in the spatial waveform at the bottom of Fig. 9. The spatial waveform shown here is a spatial waveform plotted from the starting point (any point) of the pulses for one rotation of the rotor 12, with the horizontal axis representing the i-th pulse (i = 1 to n (n is an integer)) and the vertical axis representing the period (time) of each pulse.

[0048] This spatial waveform shows the rotational irregularities of the hub 31 and the magnetization errors (pitch error and eccentricity error) of the magnetic encoder 55 as increases and decreases over time. If the pulse signal is corrected using this spatial waveform, each error can be reduced and a more accurate rotational speed of the hub 31 can be obtained.

[0049] 10 is an explanatory diagram showing another example of the definition of the pulse of the pulse signal. The definition of the pulse of the pulse signal described above is an example, and each of the repeatedly occurring HIGH voltages is defined as a pulse (T ａ１ , T ａ２ , ...) Also, each of the repeatedly occurring LOW voltages may be defined as a pulse (T ｂ１ , T ｂ２ , ...) In this case, the period of one pulse can be shortened, and more precise control becomes possible.

[0050] FIG. 11 shows an arbitrary pulse PL of the pulse signal. ｉ (i is an integer) and its pulse PL ｉ11 is an explanatory diagram showing pulses for one rotation of the hub axle 31 around the center. ｉ The pulse period of a pair of HIGH voltage and LOW voltage is Tp. ｉ The period of one rotation of the hub axle 31 around the center is defined as T.

[0051] Based on the spatial waveform, a pulse period waveform WF1 representing the transition of the pulse period Tp of each pulse is generated as damage detection data (S13). Also, a rotation period waveform WF2 representing the transition of the period T of one rotation around each pulse of the pulse signal is generated (S14).

[0052] 12 is an explanatory diagram showing an example of the waveforms from when rotational fluctuations of the hub axle 31 are extracted from the pulse output signal to generate a rotational fluctuation signal. Note that the waveform data described below is intended to explain the details of signal processing and does not necessarily represent information obtained from an actual automotive hub unit bearing. As an example, the horizontal axis of each waveform represents a spatial value equivalent to the number of pulses for five rotations of the hub axle 31. After generating the pulse period waveform WF1 and rotation period waveform WF2 described above, a period ratio waveform WF3 (=WF1 / WF2) is obtained, which represents the ratio Tp / T of the pulse period Tp to the rotation period T (S15).

[0053] While the vertical axis of the pulse period waveform WF1 and rotation period waveform WF2 described above represents time, the vertical axis of the period ratio waveform WF3 represents the ratio value to one rotation. Therefore, in the period ratio waveform WF3, the influence of rotation speed error is removed, as described above.

[0054] Next, the period ratio waveform WF3 is smoothed to obtain a smoothed period ratio waveform WF4 (S16). Smoothing can be performed, for example, by calculating a moving average of seven points before and after. This smoothed period ratio waveform WF4 is similar to the period ratio waveform WF3 processed by a low-pass filter, and the waveform is smoothed to allow low-frequency fluctuations such as rotation irregularities to be extracted.

[0055] Generally, low-pass filters (LPFs) are classified into IIR (infinite impulse response) and FIR (finite impulse response) types. However, IIR filters have a delay element, which may cause a phase lag in the averaged data. Furthermore, FIR filters produce stable processing results, but require a large amount of calculation, and unless a high-performance computing element (such as an expensive CPU) is used, a phase lag may occur in the averaged data. Therefore, here, data smoothing processing is performed using a moving average, which requires a small amount of calculation and allows for high-speed processing, but various smoothing processing methods may be used as appropriate depending on the situation.

[0056] The difference between the period ratio waveform WF3 and the period ratio smoothed waveform WF4 is then calculated, and a period ratio difference waveform WF5 (=WF3-WF4) is calculated from the extracted fluctuations (S17). This period ratio difference waveform WF5 is a waveform from which low-frequency fluctuations such as rotation irregularities have been removed, but displacement due to changes in the position of the rolling elements and magnetization errors of the encoder still remain. Furthermore, errors due to bearing damage when the bearing raceway surface or the like is damaged also remain. Note that, depending on the conditions, the period ratio waveform WF3 may be used as the period ratio difference waveform WF5 directly, without subtracting the period ratio smoothed waveform WF4 from the period ratio waveform WF3.

[0057] If the computer has sufficient processing power, the period ratio smoothed waveform WF4 may be calculated by applying an LPF that does not cause a phase delay to the period ratio waveform WF3, or the period ratio differential waveform WF5 may be calculated by applying a high-pass filter (HPF) that does not cause a phase delay to the period ratio waveform WF3.

[0058] Next, an average value is calculated for each rotational position from the period ratio difference waveform WF5, i.e., for each pole of the magnetic encoder 55 (S18). In other words, the period ratio difference waveform WF5 shown in Figure 12 shows a range of five rotations of the hub axle 31, but in the case of a magnetic encoder 55 with, for example, 48 poles per rotation, the values ​​of the period ratio difference waveform WF5 for each pole are extracted and averaged to determine a period ratio average value distribution WF6 that represents the distribution of the average values ​​for the number of rotations for each pole.

[0059] 13 is an explanatory diagram showing an example of a period ratio average distribution WF6, which is the average value of period ratio differences for each pole of a magnetic encoder. In the period ratio average distribution WF6, the deviation from the 0 level on the vertical axis represents the magnetization error. In FIG. 13, a line (not shown) connecting the average values ​​for each pole of the period ratio average distribution is the period ratio average waveform.

[0060] Next, a period ratio fluctuation waveform WF7 is obtained, which represents the difference between the period ratio difference waveform WF5 and the period ratio average waveform WF6 (S19). The period ratio fluctuation waveform WF7 is obtained by subtracting the value for each pole shown in the period ratio average waveform WF6 from the value for each pole of the period ratio difference waveform WF5. Hereinafter, the period ratio difference waveform WF5 will also be referred to as the "detection waveform," the period ratio average waveform WF6 as the "reference waveform," and the period ratio fluctuation waveform WF7 as the "rotation fluctuation waveform."

[0061] 14 is an explanatory diagram that schematically shows the period ratio variation waveform WF7. This period ratio variation waveform WF7 has been removed of the magnetization error of the magnetic encoder 55. In other words, since the period ratio variation waveform WF7 has been removed of fluctuations due to changes in rotation speed, rotation unevenness, and magnetization error, the fluctuations that appear here can be said to be caused by displacements associated with changes in the position of the rolling elements, and displacements associated with bearing damage in the case where the bearing is damaged.

[0062] The period ratio fluctuation waveform WF7 may be a waveform in which the vertical axis is converted from period ratio to speed fluctuation by geometric calculation (S20). In this case, the level of fluctuation can be easily grasped intuitively as the magnitude of speed. The processes from S12 to S19 and S20 above are performed by the rotation fluctuation extraction unit 24A of the control unit 24 shown in FIG. 2.

[0063] Next, the frequency analysis unit 24B performs frequency analysis on the period ratio variation waveform WF7 to determine the frequency characteristics (S21). For the frequency analysis, various analysis methods can be used, such as a discrete Fourier transform method such as FFT (Fast Fourier Transform) or a maximum entropy method.

[0064] FIG. 15 is an explanatory diagram showing a schematic diagram of the frequency characteristic WF8 obtained by FFT processing of the period ratio variation waveform WF7. The period ratio variation waveform WF7 includes speed fluctuations associated with damage to the bearing raceway surface if such damage occurs. If the raceway surface or other surface suffers from damage such as peeling or indentations, the frequency characteristic WF8 will exhibit a peak corresponding to the spatial frequency of the defect (the number of times the defect impacts per rotation), calculated using variables including the diameter d (mm) of the bearing's rolling elements, the pitch circle diameter D (mm) of the rolling elements, the number Z of rolling elements, and the contact angle α (rad). If such a peak due to bearing damage is equal to or exceeds a threshold value, the bearing is determined to be damaged (S22). The same frequency characteristic WF8 can be obtained even if the vertical axis of the period ratio variation waveform WF7 is converted to speed fluctuation.

[0065] In the frequency characteristic WF8 shown in FIG. 15 , major peaks due to bearing damage appear as, for example, a defect primary peak Pk1 and a defect secondary peak Pk2. The frequencies at which the peaks appear can generally be determined by calculation depending on the type of defect. Although numerous peaks appear in the low-frequency region (e.g., spatial band BD0), these are due to the system's natural frequency and not due to bearing damage. When determining bearing damage based on the peaks Pk1 and Pk2 due to bearing damage, for example, the outer ring defect primary peak Pk1 is relatively close to the system's natural frequency and is therefore easily mixed with the peaks of the system's natural frequency. On the other hand, if the defect secondary peak Pk2 is far away and difficult to mix with, the defect secondary peak Pk2 may also be used for determination. Furthermore, sidebands may occur around the defect primary peak Pk1 and the defect secondary peak Pk2 due to modulation with the system's low-frequency natural frequency or other factors other than the target of detection. Therefore, to determine the peak intensity due to bearing damage, spatial bands BD1 and BD2 of specific lengths may be set for peaks Pk1 and Pk2, respectively, and bearing damage may be determined based on the sum of the peak intensities within each spatial band BD1 and BD2. Because the contact angle of the rolling element varies slightly depending on the preload and load conditions described above, the theoretical defect frequency may deviate by several percent from the actually measured peak frequency. Even in such cases, setting spatial bands BD1 and BD2 of the specific lengths described above can reliably prevent missed detections. In addition to the above determination examples, the extraction and determination of desired peaks and their intensities can be performed using an appropriate algorithm depending on the situation.

[0066] FIG. 16 is an explanatory diagram showing the frequency characteristics of a pulse period waveform WF1 shown as a reference example. Because the pulse period waveform WF1 contains defect information other than bearing damage, such as rotational irregularities and magnetization errors, frequency analysis of this waveform results in the appearance of Nth-order rotational peaks (N is an integer) and many peaks at system-specific frequencies. In this case, it is more difficult to select and extract peaks due to bearing damage defects than in the case shown in FIG. 15, and the accuracy of bearing damage assessment is inevitably reduced. Therefore, by removing defect information other than bearing damage from the pulse period waveform WF1 as in the present method, bearing damage information can be easily extracted from the frequency analysis results, improving the accuracy of damage assessment. The peak intensity calculation unit 24C shown in FIG. 2 calculates the peak intensity from the frequency characteristics, and the damage detection unit 24D assesses bearing damage based on the peak intensity.

[0067] The damage determination procedure described above can be modified as appropriate. Figure 17 is a flowchart showing another damage determination procedure 1, which is a partial modification of the procedure in the flowchart shown in Figure 8. In this procedure shown in Figure 17, the above-mentioned steps S11 to S14 and S18 to S22 are common, and the pulse period (Tp) waveform WF1 generated in S13 is smoothed before being converted to a period ratio, thereby removing errors due to rotation unevenness.

[0068] That is, the pulse period waveform WF1 generated in S13 is smoothed using a technique such as the moving average described above to obtain a pulse period smoothed waveform WF1A (S31). The pulse period smoothed waveform WF1A is then divided by the rotation period waveform WF2 generated in S14 to obtain a period ratio waveform WF3A (=WF1A / WF2), which is the period ratio described above, and a period ratio waveform WF3 is obtained by dividing the pulse period (Tp) waveform WF1 by the rotation period (T) waveform WF2 as described above (S32). Furthermore, a period ratio difference waveform WF5 (=WF3-WF3A), which is the difference between the period ratio waveform WF3 and the period ratio waveform WF3A, is obtained (S33). Subsequent processing is the same as described above.

[0069] This procedure is the same as the flowchart shown in Fig. 8 except that smoothing processing is performed before the period ratio is calculated. As in this procedure, the timing for making the period ratio dimensionless is arbitrary, and approximately the same results can be obtained regardless of the timing.

[0070] Fig. 18 is a flowchart showing another procedure 2 of damage determination, which is a partial modification of the procedure in the flowchart shown in Fig. 8. In the another procedure 2 shown in Fig. 18, a constant offset value WF4 is set as WF4 (S36) instead of the period ratio smoothed waveform WF4 obtained in S16 described above. This offset value WF4 may be, for example, 1 / number of poles n (n = 48) ≈ 0.02083.

[0071] Fig. 19 is a flowchart showing another procedure 3 of damage assessment, which is a partial modification of the procedure in the flowchart shown in Fig. 8. In this procedure 3, the period ratio smoothed waveform WF4 calculated in S16 and the period ratio difference waveform WF5 calculated in S17 are omitted, and a period ratio average distribution WF6, which is the average value of the period ratio for each pole, is calculated from the period ratio waveform WF3 calculated in S15 (S35). The value of the period ratio average distribution WF6 is then subtracted from the period ratio waveform WF3 to calculate a period ratio fluctuation waveform WF7 (S36).

[0072] Figure 20 is a flowchart showing another procedure 4 of damage determination, which is a partial modification of the procedure in the flowchart shown in Figure 8. In this procedure 4, the period ratio smoothed waveform WF4 obtained in S16 described above is subjected to a seven-term moving average process in which the moving average of data for seven poles of the period ratio waveform WF3 is calculated (S37). By calculating the moving average between terms corresponding to a portion of the total number of poles (n = 48) of the magnetic encoder, an appropriate noise reduction effect can be achieved. The number of terms in the moving average may be set to, for example, 1 / 5 to 1 / 10 of the total number of poles of the magnetic encoder.

[0073] <Second Embodiment> (Configuration of Damage Detection System) Figure 21 is a schematic diagram of a bearing damage detection system 200 for a hub unit bearing according to a second embodiment. Figure 21 shows a horizontal cross section of the hub 15 and sensors 21, 22 of the hub unit bearing 11A. While the first embodiment shown in Figure 1 was configured to detect rotation of the hub axle 31 using a single sensor 21, the second embodiment has a hub unit bearing configuration similar to that of the first configuration example, except that rotation is detected using two sensors 21, 22.

[0074] When there is only one sensor, the output signal from the sensor contains errors due to the displacement of the raceway caused by changes in the position of the rolling elements, and as a result, the fluctuations in each waveform described above include the displacement caused by changes in the position of the rolling elements, and peaks due to this effect also appear in the frequency characteristics.

[0075] On the other hand, the bearing damage detection system 200 shown in FIG. 21 is equipped with a sensor (first rotation sensor) 21 that detects rotation at one horizontal end, located at the vertical midpoint of the hub unit bearing 11A, and a sensor 22 (second rotation sensor) that detects rotation at the other horizontal end. Data processing is performed using the phase difference between the output signals from the sensors 21 and 22. The sensor 22 is positioned with its detection surface 22a facing the magnetic encoder 55. The sensor output signals from the two sensors 21 and 22, positioned opposite each other in the horizontal direction, exhibit phase delays or advances in opposite directions due to the displacement of the rolling wheels associated with changes in the rolling element positions. Therefore, by using the differential signal between the sensor output signals from the two sensors 21 and 22, the phase delays or advances are canceled out, and the vertical displacement is calculated. When frequency characteristics are determined by data processing based on this differential signal, noise in the frequency characteristics is reduced, and if the bearing is damaged, peaks appear clearly at a period calculated from the rolling element pitch and orbital speed of the rolling elements, or in the case of inner ring damage, at a period calculated from the rotational speed, improving the accuracy of damage detection.

[0076] Fig. 22 is an explanatory diagram that schematically shows the positional relationship between the inner ring 33, outer ring 13, and magnetic encoder 55 of the hub unit bearing 11A, and the detection area DRa of the sensor 21 and the detection area DRb of the sensor 22. Fig. 23 shows the direction of action of the radial load applied from the inner ring 33 to the outer ring 13 (vertical direction Z, which is generally the direction of gravity) as the up and down direction.

[0077] It is preferable that the center positions Pc of the detection areas DRa and DRb of the sensors 21 and 22 are both set at positions that are shifted a distance δ downward from the horizontal line Lh that passes through the central axis O of the hub unit bearing 11A. In this case, as will be described in detail later, it becomes easier to detect the shift using a phase difference signal. Furthermore, the center positions Pc of the detection areas DRa and DRb may be located on the horizontal line Lh described above.

[0078] 24 is a schematic circuit diagram of pulse signal generating unit 23A. In this case, pulse signal generating unit 23A receives, for example, the output signal from sensor 21 (sensor A) as pulse signal PL_A and the output signal from sensor 22 (sensor B) as pulse signal PL_B. Also, pulse signal generating unit 23A outputs the differential signal between pulse signal A and pulse signal B as phase difference signal PD (=PL_A-PL_B).

[0079] 24 is an explanatory diagram showing an example of the waveforms of the pulse signals PL_A, PL_B and the phase difference signal PD. The pulse period of the pulse signal PL_A is T Ａ , the pulse period of the pulse signal PL_B is T Ｂ and the phase difference between the pulse signals PL_A and PL_B is T ＰＤ For example, when the voltages of the pulse signals PL_A and PL_B are +V and +2V, the phase difference signal PD has a waveform that changes in the range of +V to −V, and the period when it is −V is the period when the phase difference T ＰＤ is equivalent to

[0080] The above-mentioned pulse signals PL_A, PL_B and phase difference signal PD change due to damage to the hub unit bearing 11A. Figure 25 is an explanatory diagram showing the effect on the sensor output of relative displacement between the inner and outer rings due to flaking in the outer ring raceway. This diagram shows how the hub axle 31 moves up and down due to flaking or indentations in the outer ring raceway 27 of the outer row bearing portion 49A, similar to the case shown in Figure 6.

[0081] Assume that a radial load Pr (preload) is applied vertically upward from the hub axle 31 to the outer ring 13 in the bearing portion 49A. When a floating rolling element 17 in a defective area where flaking has occurred in the outer ring raceway 27 moves from the edge of the defective area to an area without flaking, the hub axle 31 is subjected to the aforementioned impact load greater than the radial load Pr, causing the hub axle 31 to displace downward. If the hub axle 31 subsequently rotates further and an impact load is generated in the opposite direction, the hub axle 31 will displace upward. As a result, the magnetic encoder 55 affixed to the hub axle 31 will first descend and then ascend in response to the displacement of the hub axle 31. Even if the above-described preload is not applied to the hub axle 31, the magnetic encoder 55 will behave in the same manner as described above, descending and ascending in response to the displacement of the hub axle 31.

[0082] In other words, in the floating state, the hub axle 31 is displaced upward, and the center O of the outer ring 13 ｏｕｔ The center O of the hub axle 31 relative to ｉｎ is displaced upward. At this time, the pulse signals PL_A and PL_B detected from the detection regions DRa and DRb have a phase lead or lag from the neutral position. Specifically, in the detection region DRa, the hub axle 31 is displaced upward in the same direction as the rotation direction Ro, so the phase of the pulse signal PL_A is advanced. In the detection region DRb, the hub axle 31 is displaced upward in the opposite direction to the rotation direction Ro, so the phase of the pulse signal PL_B is delayed. As a result, the phase difference signal PD, which is the difference signal between the pulse signals PL_B and PL_A, has a phase difference T ＰＤ A period of time will occur.

[0083] On the other hand, when the hub axle 31 is displaced downward, in the detection region DRa, the hub axle 31 is displaced downward in the opposite direction to the rotation direction Ro, causing a delay in the phase of the pulse signal PL_A. In the detection region DRb, the hub axle 31 is displaced downward in the same direction as the rotation direction Ro, causing an advance in the phase of the pulse signal PL_B. As a result, the phase difference signal PD, which is the difference signal between the pulse signals PL_B and PL_A, has a phase difference T that is different from when the hub axle 31 is displaced upward. ＰＤ A period of time will occur.

[0084] That is, the phase difference T ＰＤ Since the value of changes according to the amount of vertical movement of the hub axle 31, the relative displacement between the inner ring 33 and the outer ring 13 can be calculated from the phase difference between the pulse signals from the two sensors 21 and 22. ＰＤ changes depending on the positions of the detection regions DRa and DRb, and the phase difference T ＰＤ As described above, by setting the center position Pc of the detection areas DRa, DRb to a position shifted downward from the horizontal line Lh passing through the central axis O of the hub unit bearing 11A, the pulse length of the specific pulse does not become 0, preventing it from becoming undetectable.

[0085] The above-mentioned phase difference and pulse period are not limited to being calculated from waveforms obtained by subtracting pulse signals PL_A and PL_B in real time by pulse signal generating unit 23A, but may also be calculated from each pulse signal after individually monitoring the waveforms of pulse signals PL_A and PL_B.

[0086] The above explanation is a rough outline of the behavior of signal changes, and the following will explain the state of signal changes that are closer to the actual signal. Fig. 26 is an explanatory diagram showing the relationship between the displacement of the encoder and the phase difference of the detected pulse signal. Fig. 27 is an explanatory diagram showing an example of changes in the pulse signals PL_A, PL_B and the phase difference signal PD. Figs. 26 and 27 show the state of displacement when flaking occurs in the outer ring raceway shown in Fig. 6 above, in the order of sections SC1, SC2, SC3, and SC4 in chronological order. In the initial state SC1, the speed (VR) detected in the detection area DRa and the detection area DRb shown in Fig. 26 is ０ , VL ０ The relative speeds (VR) are equal to each other. Then, at SC2 when the hub axle 31 rotates, the rolling element reaches the end of the defective area of ​​the outer ring raceway, and again enters between the outer ring raceway and the inner ring raceway, where there is no flaking. At this time, the hub axle 31 is displaced downward, as explained in FIG. 6 for the single sensor case. Therefore, the speed (VR) detected in the detection area DRa is １ ) decreases, and the velocity (VL １ ) increases.

[0087] At SC3, when the hub axle 31 further rotates and the rolling elements transition back to the rolling state between the outer ring raceway and the inner ring raceway, the speed (VR ２ ) increases, and the velocity (VL １ ) decreases. Then, at SC4, where the hub axle 31 has rotated further, the state returns to the same state as the initial state SC1.

[0088] The pulse signals PL_A, PL_B and phase difference signal PD (= PL_A - PL_B) in each of the sections SC1, SC2, SC3, and SC4 produce the distributions of speed, pulse width, and pulse period of the phase difference signal shown in Figure 27. For example, the amount of vertical displacement can be determined from the pulse width of the phase difference signal, and the displacement speed can be determined from the pulse period of the pulse signals PL_A and PL_B. Note that while actual displacement of the hub axle 31 occurs between SC1 and SC4, the displacement is detected between SC2 and SC4.

[0089] 28 is an explanatory diagram showing the waveforms of specific pulse signals PL_A, PL_B and phase difference signal PD. Pulse signals PL_A and PL_B have a phase delay or advance depending on the height position of detection regions DRa, DRb. In addition, in the aforementioned section SC2, the period of pulse signal PL_A becomes longer and the period of pulse signal PL_B becomes shorter. In section SC3, the period of pulse signal PL_A becomes shorter and the period of pulse signal PL_B becomes longer. Therefore, the phase difference T appearing in the phase difference signal PD between sections SC3 and SC4 ＰＤ This phase difference T ＰＤ The change in is quantitatively determined during the frequency analysis of the waveform, which will be described later, and is used to determine damage.

[0090] (Damage Determination Procedure) Fig. 29 is a flowchart showing the procedure for determining damage to the hub unit bearing 11A using the above-mentioned two sensors 21, 22. Each of the following procedures is carried out based on commands from the control unit 24 shown in Fig. 21.

[0091] First, the rotation of the hub unit bearing 11A that is driven to rotate is detected by the sensors 21 and 22, and sensor output signals that are rotation signals output from the sensors 21 and 22 are acquired (S41). These sensor output signals are converted by the pulse signal generating unit 23 into pulse signals PL_A and PL_B, respectively.

[0092] 30 is an explanatory diagram showing the waveforms of the pulse signal PL_A and the pulse signal PL_B. ｉ and a phase difference PD between the pulse signal PL_B and the pulse signal PL_A. ｉ (i is an integer that represents the order of the pulse) ｉ The phase difference signal PD generated by the pulse signal generating unit 23A shown in FIG. 23 may be used, or the pulse signals PL_A and PL_B may be individually AD converted into a phase difference and used.

[0093] 31, the horizontal axis represents the space representing the order of pulses of the pulse signal PL_B, and the vertical axis represents time. ｉ and phase difference PD ｉ In this procedure, the phase difference PD ｉ The spatial waveform of the signal is calculated (S42), and damage is determined based on the waveform. That is, instead of the sensor output signal from one sensor 21, data processing is performed using the phase difference between the sensor output signals from the two sensors 21 and 22. The subsequent steps are basically the same as those in the first embodiment, except that the aforementioned "pulse period" is changed to "phase difference," and therefore detailed explanations of each step will be omitted.

[0094] 32 is an explanatory diagram showing an example of a waveform from which the rotational fluctuation of the hub axle 31 is extracted from the pulse output signal to generate a rotational fluctuation signal. ｉ (S43), and the rotation period waveform WF12 is a waveform obtained by determining the transition of the period T of one rotation centered on each pulse of the pulse signal PL_B (which may be determined from PL_A), as shown in FIG. 23 described above (S44).

[0095] Next, the phase difference waveform WF11 is divided by the rotation period waveform WF12 to obtain a phase difference ratio waveform WF13 (=WF11 / WF12) (S45). In this phase difference ratio waveform WF13, the influence of the rotation speed error is removed.

[0096] Then, the phase difference ratio waveform WF13 is smoothed in the same manner as described above to obtain a phase difference ratio smoothed waveform WF14 (S46), and a phase difference ratio differential waveform WF15 (=WF13-WF14) that represents the difference between the phase difference ratio waveform WF13 and the phase difference ratio smoothed waveform WF14 is obtained (S47). Note that, depending on the conditions, the phase difference ratio waveform WF13 may be used as the phase difference ratio differential waveform WF15 directly, without subtracting the phase difference ratio smoothed waveform WF14 from the phase difference ratio waveform WF13.

[0097] Next, a phase difference ratio average distribution WF16, which is the average value for each pole of the magnetic encoder, is obtained from the phase difference ratio difference waveform WF15 (S48). Fig. 33 is an explanatory diagram showing an example of the phase difference ratio average distribution WF16. The deviation from the 0 level on the vertical axis in the phase difference ratio average waveform WF16 represents the magnetization error of the magnetic encoder. In Fig. 33, the line (not shown) connecting the average values ​​for each pole of the phase difference ratio average distribution is the phase difference ratio average waveform.

[0098] Next, a phase difference ratio fluctuation waveform WF17 is obtained, which represents the difference between the phase difference ratio difference waveform WF15 and the phase difference ratio average waveform WF16 (S19). The phase difference ratio fluctuation waveform WF17 is obtained by subtracting the value for each pole shown in the phase difference ratio average waveform WF16 from the value for each pole of the phase difference ratio difference waveform WF15. Hereinafter, the phase difference ratio difference waveform WF15 will also be referred to as the "detection waveform," the phase difference ratio average waveform WF16 as the "reference waveform," and the phase difference ratio fluctuation waveform WF17 as the "rotation fluctuation waveform."

[0099] 34 is an explanatory diagram schematically showing the phase difference ratio fluctuation waveform WF17. This phase difference ratio fluctuation waveform WF17 has been removed of the magnetization error of the magnetic encoder 55. In other words, since the phase difference ratio fluctuation waveform WF17 has been removed of rotational speed changes, rotation unevenness, and magnetization errors, the fluctuations that appear here can be said to be caused by displacements accompanying changes in the positions of the rolling elements and displacements accompanying damage to the bearing raceway surface if such damage occurs.

[0100] The phase difference ratio fluctuation waveform WF17 may be a waveform whose vertical axis is converted from period ratio to displacement fluctuation by geometric calculation (S50). In this case, the level of the fluctuation can be easily grasped intuitively as the magnitude of the displacement.

[0101] Next, the phase difference ratio fluctuation waveform WF17 is subjected to frequency analysis (S51). FIG. 35 is an explanatory diagram showing an example of frequency characteristics WF18 obtained by FFT processing of the phase difference ratio fluctuation waveform WF17. The phase difference ratio fluctuation waveform WF17 includes displacement fluctuations associated with changes in the position of the rolling elements and, if the bearing is damaged, displacement fluctuations associated with bearing damage. Therefore, the frequency characteristics WF18 include spatial frequency peaks (primary to several orders) calculated from the ball revolution speed, peaks occurring at periods calculated from the ball pitch and ball revolution speed if the bearing is damaged, and peaks occurring at periods calculated from the rotational speed if the outer ring is damaged. If such peaks due to bearing damage are equal to or greater than a threshold, it is determined that the bearing has been damaged. Note that the same frequency characteristics WF18 can be obtained even if the vertical axis of the phase difference ratio fluctuation waveform WF17 is converted to displacement fluctuation.

[0102] In the frequency characteristic WF18 shown in Fig. 35, the main peaks caused by bearing damage appear as, for example, a primary defect peak Pk1 and a secondary defect peak Pk2. As described above, bearing damage is determined based on the sum of the peak intensities within the set spatial bands BD1 and BD2.

[0103] In addition to the above procedure, bearing damage may be determined using the following procedure. Figure 36 is a flowchart showing another procedure 1 for damage determination, which is a partial modification of the procedure in the flowchart shown in Figure 29. In another procedure 1 shown in Figure 36, the phase difference ratio waveform WF13 determined in the above-mentioned S45 is subjected to 48-term moving average processing, which calculates a moving average of data for all poles (48 poles) of the magnetic encoder, to determine a phase difference ratio smoothed waveform WF14. This phase difference ratio smoothed waveform WF14 is a generally flat waveform with a generally constant offset value overall. In S47, the difference between the phase difference ratio waveform WF13 and the phase difference ratio smoothed waveform WF14 is determined as a phase difference ratio differential waveform WF15.

[0104] Fig. 37 is a flowchart showing another procedure 2 of damage determination, which is a partial modification of the procedure in the flowchart shown in Fig. 29. In another procedure 2 shown in Fig. 37, the phase difference ratio waveform WF13 obtained in S45 described above is averaged for each pole of the magnetic encoder to obtain a phase difference ratio average distribution WF16 (S52). Then, the value of the phase difference ratio average distribution WF16 is subtracted from the phase difference ratio waveform WF13 to obtain a phase difference ratio fluctuation waveform WF17 (S53). In S51, this phase difference ratio fluctuation waveform WF17 is subjected to frequency analysis.

[0105] Figure 38 is a flowchart showing another procedure 3 for damage determination, which is a partial modification of the procedure in the flowchart shown in Figure 29. In this procedure 3, the phase difference ratio waveform WF13 obtained in S45 described above is subjected to a seven-term moving average process, which calculates a moving average of data for seven poles of the phase difference ratio waveform WF13, to obtain a smoothed phase difference ratio waveform WF14 (S54). By calculating the moving average between terms corresponding to a portion of the total number of poles (n = 48) of the magnetic encoder, an appropriate noise reduction effect can be achieved. The number of terms in the moving average may be set to, for example, 1 / 5 to 1 / 10 of the total number of poles of the magnetic encoder.

[0106] <Control Time Sequence> Next, the control time sequence in each of the above-described embodiments will be described. FIG. 39 is a control block diagram showing the process of obtaining a rotation fluctuation waveform by calculating a differential waveform from a detected pulse signal. In this process, the control unit 24 calculates the detection waveform K described above based on the output signal from the sensor (sensor 21 in FIG. 1 , sensors 21 and 22 in FIG. 21 ). The control unit 24 then calculates the detection waveform K described above based on the output signal from the sensor. The control unit 24 then averages and integrates the calculated detection waveform K for each rotation angle (pole) to create a composite average waveform C, which is then stored in a storage device as a reference waveform. A new detection waveform K is then calculated from the output signal output from the sensor. The reference waveform value stored in the storage device is subtracted from this new detection waveform K for each rotation angle to calculate a differential waveform. The resulting differential waveform (rotation fluctuation waveform) is a waveform from which unnecessary fluctuations have been removed, and frequency analysis reveals a frequency characteristic from which unnecessary peaks have been removed.

[0107] In this control, a reference waveform calculated from a detection waveform K based on an output signal from a sensor is used to subtract the detection waveform K itself. In other words, a reference waveform is generated from the detection waveform K, including fluctuations due to defects, and the original detection waveform K is processed using the resulting reference waveform to remove unnecessary fluctuations from the detection waveform K in real time. For example, when processing measurement data using a reference waveform, if a reference waveform based on past measurement data or calculations is prepared in advance and processed using this prepared reference waveform, the reference waveform may not necessarily match the timing at which the measurement data was actually acquired. This could result in inaccuracies in the processing results. On the other hand, in this control, the reference waveform used in the subtraction process of the detection waveform K is generated from the pulse signal used to calculate the detection waveform K or a pulse signal subsequent to that pulse signal. In other words, the reference waveform is calculated using the pulse signal used to generate the reference waveform, or a pulse signal output consecutively following that pulse signal while the rolling bearing continues to rotate while that pulse signal is being output. Therefore, since the measurement data to be evaluated and the reference waveform are information of timing that can be considered to be simultaneous or approximately simultaneous in time series, there is almost no change in the rotation conditions, and the above-mentioned incompatibility does not occur.

[0108] A specific example of control for performing damage detection for a rolling bearing will be described below. Figure 40 is an explanatory diagram showing a time chart 1 from the detection waveform K to performing damage detection for a rolling bearing. In the time chart of Figure 40, the horizontal axis represents elapsed time, and the vertical axis represents the processing content for each elapsed time. In this control, damage detection target sections SC1, SC2, SC3, SC4, ... for detecting damage are set intermittently and sequentially. First, elapsed time t ０ ~t １ The output signal from the sensor is acquired during the next elapsed period t １ ~t ２During this time, a detection waveform K is generated, a reference waveform is generated from this detection waveform K, the reference waveform is subtracted from the detection waveform K to obtain a difference waveform (rotation fluctuation waveform), and this rotation fluctuation waveform is subjected to frequency analysis using FFT or the like to determine damage. ０ ~t ２ During the period (period surrounded by the dashed line TM), the elapsed time t ０ ~t １ This completes the damage detection for the damage detection target section SC1 in the above step 1. Thereafter, the same process is repeatedly executed for SC2, SC3, SC4, and so on.

[0109] 41 is an explanatory diagram showing a time chart 2 from the detection waveform K to the determination of damage to the rolling bearing. The time chart 2 in FIG. 41 is an example of control that can be executed even when the calculation processing capacity of the control unit 24 is relatively low. In this control, first, the elapsed time t ０ ~t １ The output signal from the sensor is acquired during the next elapsed period t １ ~t ２ A detection waveform K is generated during the elapsed period t ２ ~t ３ During this time, the output signal from the sensor is acquired to generate the detection waveform K, and the detection waveform K is generated during the previous elapsed period t １ ~t ２ The reference waveform obtained during the period is subtracted from the detection waveform K to obtain a difference waveform (rotation fluctuation waveform). ３ ~t ４ The rotational fluctuation waveform is subjected to frequency analysis using FFT (Fast Fourier Transform) or the like to determine damage during this period. ０ ~t ４ The period up to the elapsed time t ２ ~t ３ In this case, the damage detection for SC1 is completed after the elapsed time t ０ ~t １ However, since this is close to the period of SC1, no significant changes occur and no incompatibility occurs.

[0110] Furthermore, the elapsed time t ４ ~t ５ During this time, the output signal from the sensor is acquired to generate the detection waveform K, and the detection waveform K is generated during the previous elapsed period t １ ~t ２ The reference waveform obtained during the period is subtracted from the detection waveform K to obtain a difference waveform (rotation fluctuation waveform). ５ ~t ６ The rotational fluctuation waveform is subjected to frequency analysis using FFT or the like during this period to determine damage. ４ ~t ６ The period up to the elapsed time t ４ ~t ５ The abnormality determination for the damage detection target section SC2 at t ６ ~t ８ The period up to the elapsed time t ６ ~t ７ The damage detection for the damage detection target section SC3 at time t is completed. Thereafter, the same process is repeatedly executed in order. ０ ~t ８ The period up to (period surrounded by dashed line TM) is the elapsed period t １ ~t ２ The damage determination for the damage detection target sections SC1, SC2, and SC3 is completed using the reference waveforms obtained between the sections SC1, SC2, and SC3 in common.

[0111] In this control, damage determination for the periods SC1, SC2, and SC3 is performed for the elapsed period t １ ~t ２ This is based on the results of using a common reference waveform obtained between the two. This reduces the calculation load on the control unit while still enabling damage assessment.

[0112] 42 is an explanatory diagram showing a time chart 3 from the detection waveform K to the determination of damage to the rolling bearing. The time chart 3 in FIG. 42 is an example of control that can be executed even if the calculation processing capacity of the control unit 24 is further lower. In this control, first, the elapsed time t ０ ~t １ Next, the output signal from the sensor is acquired during the elapsed period t １ ~t ２ A detection waveform K is generated during the elapsed time t２ ~t ３ The output signal from the sensor is acquired during the elapsed period t ３ ~t ４ and t １ ~t ２ The reference waveform generated during this period is subtracted from the detection waveform K to obtain the difference waveform (rotation fluctuation waveform). １ ~t ２ The differential waveform between these is subjected to frequency analysis.

[0113] Next, the elapsed time t ４ ~t ５ The output signal from the sensor is acquired during t ５ ~t ６ and t １ ~t ２ The reference waveform generated during this period is subtracted from the detection waveform K to obtain the difference waveform (rotation fluctuation waveform). ４ ~t ５ The differential waveform between these is subjected to frequency analysis.

[0114] Similarly, the elapsed time t ６ ~t ７ The output signal from the sensor is acquired during t ６ ~t ７ and t １ ~t ２ The reference waveform generated during this period is subtracted to obtain the difference waveform (rotation fluctuation waveform). ６ ~t ７ The differential waveform between the elapsed period t is subjected to frequency analysis. ８ ~t ９ So, t ３ ~t ４ (corresponding to SC1), t ５ ~t ６ (corresponding to SC2), t ７ ~t ８ The results of the frequency analysis obtained in (corresponding to SC3) are averaged to determine damage during the periods SC1, SC2, and SC3.

[0115] In this control, damage determination for the periods SC1, SC2, and SC3 is performed for the elapsed period t １ ~t ２ The analysis is performed based on the results of a common reference waveform obtained during the period. In addition, by dividing the frequency analysis into periods, damage determination can be performed while further reducing the calculation burden on the control unit.

[0116] In each of the control examples described above, by setting the intervals for reference waveform subtraction processing and frequency analysis, which have a large computational load, outside the damage detection target interval, efficient computation can be performed even if the computational capacity of the control unit 24 is relatively low. Furthermore, because the difference waveform (rotation fluctuation waveform) is obtained using a reference waveform generated based on information under the same conditions as when the detection waveform K was measured, or a reference waveform generated under conditions similar to those during measurement, the accuracy of the reference waveform is high, enabling more accurate damage determination.

[0117] The bearing damage detection method described above can also be applied to single-row bearings. Hub unit bearings used as vehicle support mechanisms are equipped with an encoder, wheel speed sensor, and a circuit for processing the signals from the sensor. In this case, by improving the performance of this hardware, the processing of the bearing damage inspection method described above can be easily achieved by changing the control content, i.e., by changing or adding software, and improving the performance of the hardware (such as by improving processing speed), without adding a new system. Furthermore, in double-row bearings such as hub unit bearings, damage can be detected in either row by providing a sensor and encoder only in one row, rather than providing them individually in each row.

[0118] As such, the present invention is not limited to the above-described embodiments. The present invention contemplates the mutual combination of the various configurations of the embodiments, as well as modifications and applications by those skilled in the art based on the description in the specification and well-known techniques, and these modifications and applications are within the scope of the claimed protection. For example, depending on the type of sensor, the output signal may contain waveform distortions or superimposition of additional information. Even in such cases, the desired pulse waveform described above can be generated by adding appropriate signal processing, processing circuits, etc. In other words, the necessary processing may be added depending on the waveform of the signal obtained from the sensor, and each of the damage detection steps described above may be performed.

[0119] As described above, this specification discloses the following: (1) A bearing damage detection system comprising: a rotation sensor that detects the rotation of a rolling bearing and outputs a rotation signal; a rotation fluctuation extraction unit that extracts rotation fluctuations of the rolling bearing from the rotation signal and generates a rotation fluctuation signal; a frequency analysis unit that performs frequency analysis on the waveform of the rotation fluctuation signal to determine frequency characteristics; a peak intensity calculation unit that determines peak intensities corresponding to bearing damage from the frequency characteristics; and a damage detection unit that detects bearing damage in the rolling bearing based on the peak intensities. With this bearing damage detection system, if a rolling bearing has bearing damage, by obtaining a rotation fluctuation signal that selectively extracts rotation fluctuations due to the bearing damage, it is possible to easily obtain peak intensities corresponding to the bearing damage from the results of frequency analysis of the rotation fluctuation signal.

[0120] (2) A bearing damage detection system according to (1), comprising a pulse signal generation unit that converts the rotation signal into a pulse signal synchronized with the rotation of the rolling bearing, wherein the rotation fluctuation extraction unit obtains, for each pulse of the pulse signal, a pulse period waveform that indicates the progression of the pulse period Tp of the individual pulse, and a rotation period waveform that indicates the progression of the rotation period T for one rotation of the rolling bearing centered on any one of the pulses of the pulse signal, and obtains the waveform of the rotation fluctuation signal based on a period ratio waveform that indicates the ratio Tp / T of the pulse period Tp to the rotation period T. According to this bearing damage detection system, the influence of rotational speed error can be removed from the rotation fluctuation signal by using the period ratio waveform that indicates the ratio Tp / T of the pulse period Tp to the rotation period T.

[0121] (3) The bearing damage detection system according to (2), wherein the rotation fluctuation extraction unit determines the waveform of the rotation fluctuation signal based on a period ratio difference waveform that represents the difference between the period ratio waveform and a period ratio smoothed waveform obtained by smoothing the period ratio waveform. With this bearing damage detection system, the influence of rotation unevenness error can be removed from the rotation fluctuation signal by using the period ratio difference waveform.

[0122] (4) The bearing damage detection system according to (3), wherein the rotation fluctuation extraction unit calculates a period ratio average waveform by averaging the differences in the period ratio difference waveform that correspond to the same rotational position of the rolling bearing for each rotational position, and calculates the waveform of the rotation fluctuation signal based on a period ratio fluctuation waveform calculated for each rotational position by calculating the difference between the period ratio difference waveform and the period ratio average waveform. With this bearing damage detection system, the use of the period ratio fluctuation waveform can remove the influence of detection error of the rotational position of the rotation sensor from the rotation fluctuation signal.

[0123] (5) The bearing damage detection system according to (4), wherein the period ratio average value waveform is a waveform calculated using the rotation signal from which the period ratio difference waveform was calculated, or a rotation signal output consecutively following that rotation signal. According to this bearing damage detection system, the period ratio average value waveform is calculated from the rotation signal from which the period ratio difference waveform was calculated, or a rotation signal following that, thereby calculating the difference between the period ratio difference waveform and the period ratio average value waveform, which are obtained at the same or approximately the same time in a time series. This enables accurate damage detection without being affected by changes in conditions over time.

[0124] (6) The bearing damage detection system according to (1), wherein the rotation sensors include a first rotation sensor that detects rotation at one end in the horizontal direction at a vertically intermediate position of the rolling bearing, and a second rotation sensor that detects rotation at the other end in the horizontal direction. With this bearing damage detection system, the differential signal of the sensor output signals from the two rotation sensors cancels out the phase delay or advance of each sensor output signal, thereby obtaining a rotation signal waveform with less noise.

[0125] (7) The bearing damage detection system according to (6), wherein the rotation signals are a first pulse signal output from the first rotation sensor and a second pulse signal output from the second rotation sensor, and the system calculates, for a pulse of the first pulse signal or the second pulse signal, a rotation period waveform that indicates progress in a rotation period T for one rotation of the rolling bearing centered on the pulse, and a phase difference waveform that indicates progress in a phase difference PD between the pulses of the first pulse signal and the second pulse signal, and calculates the waveform of the rotation fluctuation signal based on a phase difference ratio waveform that indicates a ratio PD / T of the phase difference PD to the rotation period T. According to this bearing damage detection system, the influence of rotational speed errors can be removed from the rotation fluctuation signal by using the phase difference ratio waveform that indicates the ratio PD / T of the phase difference PD to the rotation period T.

[0126] (8) The bearing damage detection system according to (7), wherein the rotational fluctuation extraction unit determines the waveform of the rotational fluctuation signal based on a phase difference ratio differential waveform that represents the difference between the phase difference ratio waveform and a phase difference ratio smoothed waveform obtained by smoothing the phase difference ratio waveform. With this bearing damage detection system, the influence of rotational unevenness error can be removed from the rotational fluctuation signal by using the phase difference ratio differential waveform.

[0127] (9) The bearing damage detection system according to (8), wherein the rotation fluctuation extraction unit calculates a phase difference ratio average waveform by averaging the differences corresponding to the same rotational position of the rolling bearing in the phase difference ratio difference waveform for each rotational position, and calculates the waveform of the rotation fluctuation signal based on a phase difference ratio fluctuation waveform calculated for each rotational position by calculating the difference between the phase difference ratio difference waveform and the phase difference ratio average waveform. With this bearing damage detection system, the use of the phase difference ratio fluctuation waveform can remove the influence of detection errors of the rotational position of the rotation sensor from the rotation fluctuation signal.

[0128] (10) The bearing damage detection system according to (9), wherein the phase difference ratio average value waveform is a waveform calculated using the rotation signal from which the phase difference ratio differential waveform was calculated, or a rotation signal output consecutively following that rotation signal. According to this bearing damage detection system, the phase difference ratio average value waveform is calculated from the rotation signal from which the phase difference ratio differential waveform was calculated, or a rotation signal following that rotation signal, thereby calculating the difference between the phase difference ratio differential waveform and the phase difference ratio average value waveform, which are obtained at the same or approximately the same timing in a time series. This enables accurate damage detection without being affected by changes in conditions over time.

[0129] (11) The bearing damage detection system according to any one of (1) to (10), wherein the rolling bearing is a single-row bearing or a double-row bearing. This bearing damage detection system can detect damage that occurs in either a single-row bearing or a double-row bearing.

[0130] (12) The rolling bearing is a hub unit bearing comprising an inner ring member, an outer ring member, a plurality of rolling elements arranged between the inner ring member and the outer ring member, a flange provided on at least one of the inner ring member and the outer ring member, and a wheel speed sensor that detects the rotation speed of the inner ring member, and the wheel speed sensor functions as the rotation sensor. With this bearing damage detection system, the wheel speed sensor provided in the hub unit bearing can be used as the rotation sensor as is.

[0131] (13) A bearing damage detection method comprising: detecting the rotation of a rolling bearing to generate a rotation signal; extracting rotational fluctuations of the rotation from the rotation signal to generate a rotation fluctuation signal; determining vibration peaks by frequency analyzing the waveform of the rotation fluctuation signal; determining peak intensities corresponding to bearing damage from the vibration peaks; and detecting bearing damage in the rolling bearing based on the peak intensities. According to this bearing damage detection method, when a rolling bearing has bearing damage, by obtaining a rotation fluctuation signal that selectively extracts rotational fluctuations due to the bearing damage, it is possible to easily obtain peak intensities corresponding to bearing damage from the results of frequency analysis of the rotation fluctuation signal.

[0132] (14) The bearing damage detection method according to (13), wherein the rotation signal is a pulse signal synchronized with the rotation of the rolling bearing, and a rotation period waveform is obtained for each pulse of the pulse signal, the rotation period waveform representing the transition of the rotation period for one rotation of the rolling bearing centered on that pulse, a pulse period waveform representing the transition of the pulse period of each pulse in the pulse signal, and a waveform of the rotation fluctuation signal is obtained based on a period ratio waveform representing the ratio Tp / T of the pulse period Tp to the rotation period T. According to this bearing damage detection method, the influence of rotational speed error can be removed from the rotation fluctuation signal by using the period ratio waveform representing the ratio Tp / T of the pulse period Tp to the rotation period T.

[0133] (15) A bearing damage detection method according to (14), further comprising the step of: determining a waveform of the rotation fluctuation signal based on a period ratio difference waveform that represents the difference between the period ratio waveform and a period ratio smoothed waveform obtained by smoothing the period ratio waveform. According to this bearing damage detection method, the use of the period ratio difference waveform makes it possible to remove the influence of rotation unevenness error from the rotation fluctuation signal.

[0134] (16) A bearing damage detection method according to (15), comprising: averaging, for each rotational position, the differences in the period ratio difference waveforms that correspond to the same rotational position of the rolling bearing, to determine a period ratio average waveform; and determining the waveform of the rotation fluctuation signal based on a period ratio fluctuation waveform that is obtained for each rotational position by calculating the difference between the period ratio difference waveform and the period ratio average waveform. According to this bearing damage detection method, by using the period ratio fluctuation waveform, it is possible to remove the influence of detection error of the rotational position of the rotation sensor from the rotation fluctuation signal.

[0135] (17) A bearing damage detection method according to (16), in which the period ratio average waveform is determined using the rotation signal from which the period ratio difference waveform was determined, or a rotation signal output consecutively following that rotation signal. According to this bearing damage detection method, the period ratio average waveform is determined from the rotation signal from which the period ratio difference waveform was determined, or a rotation signal following that, thereby determining the difference between the period ratio difference waveform and the period ratio average waveform, which are obtained simultaneously or at approximately the same timing in a time series. This enables accurate damage detection without being affected by changes in conditions over time.

[0136] (18) The bearing damage detection method according to (13), comprising determining a rotation period waveform representing the transition of a rotation period T for one rotation of the rolling bearing centered on a pulse of a first pulse signal based on the rotation signal detected at one end in the horizontal direction at a vertical intermediate position of the rolling bearing, or a pulse of a second pulse signal based on the rotation signal detected at the other end in the horizontal direction, and a phase difference waveform representing the transition of a phase difference PD between the pulses of the first pulse signal and the second pulse signal, and determining the waveform of the rotation fluctuation signal based on a phase difference ratio waveform representing the ratio PD / T of the phase difference PD to the rotation period T. With this bearing damage detection system, the influence of rotational speed errors can be removed from the rotation fluctuation signal by using the phase difference ratio waveform representing the ratio PD / T of the phase difference PD to the rotation period T.

[0137] (19) A bearing damage detection method according to (18), further comprising the step of: determining a waveform of the rotation fluctuation signal based on a phase difference ratio differential waveform that represents the difference between the phase difference ratio waveform and a phase difference ratio smoothed waveform obtained by smoothing the phase difference ratio waveform. According to this bearing damage detection method, the use of the phase difference ratio differential waveform makes it possible to remove the influence of rotation unevenness error from the rotation fluctuation signal.

[0138] (20) A bearing damage detection method according to (19), comprising: determining a phase difference ratio average waveform by averaging the differences in the phase difference ratio difference waveform that correspond to the same rotational position of the rolling bearing for each rotational position; and determining the waveform of the rotation fluctuation signal based on a phase difference ratio fluctuation waveform that is determined for each rotational position as the difference between the phase difference ratio difference waveform and the phase difference ratio average waveform. According to this bearing damage detection method, by using the phase difference ratio fluctuation waveform, the influence of detection error of the rotational position of the rotation sensor can be removed from the rotation fluctuation signal.

[0139] (21) A bearing damage detection method according to (20), in which the phase difference ratio average value waveform is determined using the rotation signal from which the phase difference ratio difference waveform was determined, or a rotation signal output consecutively following that rotation signal. According to this bearing damage detection method, the phase difference ratio average value waveform is determined from the rotation signal from which the phase difference ratio difference waveform was determined, or a rotation signal following that, thereby determining the difference between the phase difference ratio difference waveform and the phase difference ratio average value waveform, which are obtained simultaneously or at approximately the same timing in a time series. This enables accurate damage detection without being affected by changes in conditions over time.

[0140] This application is based on a Japanese patent application filed on December 27, 2023 (Patent Application No. 2023-220644) and a Japanese patent application filed on October 8, 2024 (Patent Application No. 2024-176654), the contents of which are incorporated by reference into this application.

[0141] 11, 11A Hub unit bearing 13 Outer ring 15 Hub 17, 17A Rolling element 19 Rotation detection device 21, 22 Sensor 21a, 22a Detection surface 23, 23A Pulse signal generation unit 24 Control unit 24A Rotation fluctuation extraction unit 24B Frequency analysis unit 24C Peak intensity calculation unit 24D Damage detection unit 25 Stationary side flange 27, 29 Outer ring raceway 31 Hub axle 33 Inner ring 35 Mounting flange 35a Insertion hole 37 Hub bolt 39, 45 Inner ring raceway 41 Small diameter step portion 43 Caulking portion 47 Cage 49A Outer row bearing portion 49B Inner row bearing portion 51 Seal ring 53 Internal space 55 Magnetic encoder 55a Support ring 55b Encoder body 59 Side cover 100, 200 Bearing damage detection system

Claims

1. A bearing damage detection system comprising: a rotation sensor that detects the rotation of a rolling bearing and outputs a rotation signal; a rotation variation extraction unit that extracts the rotation variation of the rolling bearing from the rotation signal and generates a rotation variation signal; a frequency analysis unit that performs frequency analysis on the waveform of the rotation variation signal to obtain frequency characteristics; a peak intensity calculation unit that obtains a peak intensity corresponding to bearing damage from the frequency characteristics; and a damage detection unit that detects the bearing damage of the rolling bearing based on the peak intensity.

2. The bearing damage detection system according to claim 1, further comprising a pulse signal generation unit that converts the rotation signal into a pulse signal synchronized with the rotation of the rolling bearing, wherein the rotation variation extraction unit obtains, for each pulse of the pulse signal, a pulse period waveform representing the transition of the pulse period Tp of each pulse, and a rotation period waveform representing the transition of the rotation period T of one rotation of the rolling bearing centered on one of the pulses of the pulse signal, and obtains the waveform of the rotation variation signal based on a period ratio waveform representing the ratio Tp / T of the pulse period Tp to the rotation period T.

3. The bearing damage detection system according to claim 2, wherein the rotation variation extraction unit obtains the waveform of the rotation variation signal based on a period ratio difference waveform representing the difference between the period ratio waveform and a period ratio smoothed waveform obtained by smoothing the period ratio waveform.

4. The bearing damage detection system according to claim 3, wherein the rotation variation extraction unit obtains a period ratio average value waveform obtained by averaging, for each rotation position, the differences corresponding to the same rotation position of the rolling bearing in the period ratio difference waveform, and obtains the waveform of the rotation variation signal based on a period ratio variation waveform obtained by obtaining, for each rotation position, the difference between the period ratio difference waveform and the period ratio average value waveform.

5. The bearing damage detection system according to claim 4, wherein the period ratio average value waveform is a waveform obtained using the rotation signal for which the period ratio difference waveform was obtained, or a rotation signal that was continuously output following the rotation signal.

6. The bearing damage detection system according to claim 1, wherein the rotation sensor includes a first rotation sensor that detects rotation at an intermediate position in the vertical direction and at one end in the horizontal direction of the rolling bearing, and a second rotation sensor that detects rotation at the other end in the horizontal direction.

7. The rotation signal is a first pulse signal output from the first rotation sensor and a second pulse signal output from the second rotation sensor. For the pulse of the first pulse signal or the second pulse signal, a rotation period waveform representing the transition of the rotation period T for one rotation of the rolling bearing centered on the pulse, and a phase difference waveform representing the transition of the pulse phase difference PD between the first pulse signal and the second pulse signal are obtained. The waveform of the rotation fluctuation signal is obtained based on the phase difference ratio waveform representing the ratio PD / T of the phase difference PD to the rotation period T. The bearing damage detection system according to claim 6.

8. The rotation fluctuation extraction unit obtains the waveform of the rotation fluctuation signal based on the phase difference ratio difference waveform representing the difference between the phase difference ratio waveform and the phase difference ratio smoothed waveform obtained by smoothing the phase difference ratio waveform. The bearing damage detection system according to claim 7.

9. The rotation fluctuation extraction unit obtains a phase difference ratio average value waveform obtained by averaging the differences corresponding to the same rotation position of the rolling bearing in the phase difference ratio difference waveform for each rotation position, and based on the phase difference ratio fluctuation waveform obtained by obtaining the difference between the phase difference ratio difference waveform and the phase difference ratio average value waveform for each rotation position, obtains the waveform of the rotation fluctuation signal. The bearing damage detection system according to claim 8.

10. The phase difference ratio average value waveform is a waveform obtained using the rotation signal for which the phase difference ratio difference waveform was obtained, or a rotation signal continuously output following the rotation signal. The bearing damage detection system according to claim 9.

11. The rolling bearing is a single-row bearing or a multi-row bearing. The bearing damage detection system according to any one of claims 1 to 10.

12. The rolling bearing is a hub unit bearing including an inner ring member, an outer ring member, a plurality of rolling elements disposed between the inner ring member and the outer ring member, a flange provided on at least one of the inner ring member and the outer ring member, and a wheel speed sensor for detecting the rotational speed of the inner ring member. The wheel speed sensor functions as the rotation sensor. The bearing damage detection system according to claim 11.

13. A bearing damage detection method comprising: detecting rotation of a rolling bearing to generate a rotation signal; extracting rotational fluctuations of the rotation from the rotation signal to generate a rotational fluctuation signal; performing frequency analysis on a waveform of the rotational fluctuation signal to obtain vibration peaks; obtaining peak intensities corresponding to bearing damage from the vibration peaks; and detecting bearing damage of the rolling bearing based on the peak intensities.

14. The bearing damage detection method according to claim 13, wherein the rotation signal is a pulse signal synchronized with the rotation of the rolling bearing, and for each pulse of the pulse signal, a rotation period waveform representing a transition of a rotation period for one rotation of the rolling bearing centered on the pulse is obtained, a pulse period waveform representing a transition of a pulse period of each individual pulse in the pulse signal is obtained, and a waveform of the rotational fluctuation signal is obtained based on a period ratio waveform representing a ratio Tp / T of the pulse period Tp to the rotation period T.

15. The bearing damage detection method according to claim 14, wherein a waveform of the rotational fluctuation signal is obtained based on a period ratio difference waveform representing a difference between the period ratio waveform and a period ratio smoothed waveform obtained by smoothing the period ratio waveform.

16. The bearing damage detection method according to claim 15, wherein a period ratio average value waveform is obtained by averaging the differences corresponding to the same rotation position of the rolling bearing in the period ratio difference waveform for each rotation position, and a waveform of the rotational fluctuation signal is obtained based on a period ratio variation waveform obtained by obtaining a difference between the period ratio difference waveform and the period ratio average value waveform for each rotation position.

17. The bearing damage detection method according to claim 16, wherein the period ratio average value waveform is obtained using the rotation signal for which the period ratio difference waveform was obtained, or a rotation signal continuously output subsequent to the rotation signal.

18. The bearing damage detection method according to claim 13, wherein for a pulse of a first pulse signal based on the rotation signal detected at one end in the horizontal direction or a pulse of a second pulse signal based on the rotation signal detected at the other end in the horizontal direction at an intermediate position in the vertical direction of the rolling bearing, a rotation period waveform representing a transition of a rotation period T for one rotation of the rolling bearing centered on the pulse is obtained, and a phase difference waveform representing a transition of a phase difference PD between the first pulse signal and the second pulse signal is obtained, and a waveform of the rotational fluctuation signal is obtained based on a phase difference ratio waveform representing a ratio PD / T of the phase difference PD to the rotation period T.

19. The method for detecting bearing damage according to claim 18, wherein the waveform of the rotational fluctuation signal is obtained based on a phase difference ratio difference waveform representing a difference between the phase difference ratio waveform and a phase difference ratio smoothed waveform obtained by smoothing the phase difference ratio waveform.

20. The method for detecting bearing damage according to claim 19, wherein a phase difference ratio average value waveform is obtained by averaging the differences corresponding to the same rotational position of the rolling bearing in the phase difference ratio difference waveform for each rotational position, and the waveform of the rotational fluctuation signal is obtained based on a phase difference ratio fluctuation waveform obtained by obtaining a difference between the phase difference ratio difference waveform and the phase difference ratio average value waveform for each rotational position.

21. The method for detecting bearing damage according to claim 20, wherein the phase difference ratio average value waveform is obtained using the rotational signal for which the phase difference ratio difference waveform is obtained, or a rotational signal continuously output following the rotational signal.

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