JP7788258B2 - Stick-slip frequency identification method and device - Google Patents

Description

The present invention relates to a method and device for identifying stick-slip frequencies.

When an object moves while in contact with another object, a phenomenon known as stick-slip can occur. Stick-slip is a phenomenon in which an object does not move continuously and smoothly, but instead moves intermittently, alternating between slipping and sticking to other objects.

Technologies related to analyzing the stick-slip phenomenon have been proposed in the past. For example, Patent Document 1 discloses a method for evaluating the susceptibility of stick-slip between a mating material and a rubber test piece, in which the test piece and the mating material are brought into contact with each other under a predetermined load and rotated, based on the maximum friction force at the start of rotation and the kinetic friction force after the friction force has settled to a constant value after rotation. Furthermore, Patent Document 2 discloses a method for evaluating the wear resistance of a test sample by pressing the test sample against the circumferential surface of a rotating body rotated by a drive motor, and for calculating the occurrence period of the stick-slip phenomenon occurring in the test sample based on fluctuations in the power required to rotate the drive motor.

Japanese Patent Application Laid-Open No. 2005-17064 Patent No. 6794684

When an object moves while in contact with a contact surface, the object vibrates due to the stick-slip phenomenon. In this specification, the frequency of the object's vibration caused by the stick-slip phenomenon is referred to as the stick-slip frequency.

The stick-slip frequency can vary depending on the composition and shape of the object or contact surface, but there are cases where identifying the stick-slip frequency is useful. For example, it is thought that the sound caused by stick-slip between the tire and road surface, i.e., sound containing many frequency components of the stick-slip frequency, contributes to tire noise. Therefore, if the stick-slip frequency can be identified, it may be possible to control the noise level at the stick-slip frequency by changing the tire's composition, pattern shape, etc.

The objective of this invention is to identify the stick-slip frequency.

The present invention provides a stick-slip frequency identification method that includes a vibration data acquisition step of acquiring vibration data that indicates the time change in vibration frequency components for each vibration frequency of a rubber test piece when the test piece is pressed against a contact surface and moved relative to the contact surface in the planar direction of the contact surface, and a frequency identification step of identifying a vibration frequency in the vibration data that has a relatively large vibration frequency component as the stick-slip frequency between the test piece and the contact surface.

When the stick-slip phenomenon occurs, the test piece vibrates at the stick-slip frequency. Therefore, with the above configuration, it is possible to identify a vibration frequency with a relatively large vibration frequency component in the vibration data as the stick-slip frequency.

The present invention also provides a stick-slip frequency identification method that includes an acoustic data acquisition step of acquiring acoustic data that indicates the time change in acoustic frequency components for each acoustic frequency of sound generated when a rubber test piece is pressed against a contact surface and the test piece is moved relative to the contact surface in the planar direction of the contact surface, and a frequency identification step of identifying, in the acoustic data, an acoustic frequency with a relatively large acoustic frequency component as the stick-slip frequency between the test piece and the contact surface.

When the stick-slip phenomenon occurs, the test piece vibrates at the stick-slip frequency, generating a sound whose main component is the stick-slip frequency. Therefore, with the above configuration, it is possible to identify, in the acoustic data, an acoustic frequency with a relatively large acoustic frequency component as the stick-slip frequency.

According to the present invention, it is possible to identify the stick-slip frequency.

FIG. 1 is a schematic diagram of a test device according to the present embodiment. 1 is a schematic diagram illustrating the configuration of a stick-slip frequency identifying device according to an embodiment of the present invention. FIG. 10 is a diagram illustrating a first example of vibration data. FIG. 2 is a diagram illustrating a first example of acoustic data. 10 is a graph showing an example of coherence data. FIG. 10 is a diagram illustrating a second example of vibration data. FIG. 10 is a diagram illustrating a second example of acoustic data. 1 is a graph showing an example of wavelet coherence. 4 is a flowchart showing a flow of processing of the stick-slip frequency identifying device according to the present embodiment.

Figure 1 is a schematic diagram of a testing device 10 according to this embodiment. The testing device 10 is a device for acquiring data for determining the stick-slip frequency of a rubber test piece S. In this embodiment, to determine the stick-slip frequency when a rubber tire moves (slips) while in contact with a road surface, the test piece S is a test piece obtained by cutting out a portion of a rubber tire, or a rectangular rubber test piece with a tire pattern engraved on the tread surface. Note that the test piece S can be anything that can cause the stick-slip phenomenon when it moves while in contact with another object.

The testing device 10 is configured to include a contact surface 12 and a base 14. The contact surface 12 is the surface against which the test specimen S moves while in contact. As shown in Figure 1, in this specification, the direction parallel to the contact surface 12 is defined as the X-axis direction, the direction parallel to the contact surface 12 and perpendicular to the X-axis direction is defined as the Y-axis direction, and the direction perpendicular to the contact surface 12 is defined as the Z-axis direction.

As described above, in this embodiment, the stick-slip frequency when the tire moves while in contact with the road surface is identified, and therefore the contact surface 12 simulates the road surface. In particular, it is preferable that the contact surface 12 be one on which the stick-slip phenomenon is likely to occur on the test specimen S. Conditions for the contact surface 12 to be one on which the stick-slip phenomenon is likely to occur on the test specimen S include a dynamic friction coefficient of 1.4 or greater when the test specimen S is moved relative to the contact surface 12 in the surface direction of the contact surface 12, and a mean profile depth (MPD), which represents the roughness of the contact surface 12, of less than 0.1. An example of a contact surface 12 that satisfies these conditions is an aluminum surface.

The base 14 is a mechanism for moving the test specimen S in the direction of the contact surface 12 while abutting it against the contact surface 12. A rubber test specimen S is adhered to the underside of the base 14. A load is applied to the base 14 toward the contact surface 12 (negative Z-axis direction) by a mechanism (not shown), thereby pressing the test specimen S against the contact surface 12. In this state, the base 14 moves along the contact surface 12 at a constant speed due to the driving force of a motor (not shown). In this embodiment, the base 14 moves in the positive X-axis direction. As a result, the test specimen S moves while abutting against the contact surface 12. Note that in this embodiment, the base 14 is a movable part; however, since the testing apparatus 10 only requires that the contact surface 12 and the base 14 (i.e., the test specimen S) move relative to each other, the base 14 (test specimen S) may be fixed and the contact surface 12 moved in the direction of the surface.

The testing device 10 also has an acceleration sensor 16. The acceleration sensor 16 is a sensor that detects the vibration level of the test specimen S when the test specimen S moves in the planar direction of the contact surface 12 while being pressed against the contact surface 12. The acceleration sensor 16 continues to detect the vibration level of the test specimen S while the test specimen S is moving. The vibration level detected by the acceleration sensor 16 is transmitted to a stick-slip frequency identification device (described below). Note that the acceleration sensor 16 can be a conventional acceleration sensor, such as a capacitance-type acceleration sensor.

In this embodiment, the testing apparatus 10 has multiple acceleration sensors 16a-16f. Acceleration sensor 16a detects the vibration level in the X-axis direction on the front side of the test specimen S in the direction of movement. Acceleration sensor 16b detects the vibration level in the Z-axis direction on the front side of the test specimen S in the direction of movement. Acceleration sensor 16c detects the vibration level in the X-axis direction on the rear side of the test specimen S in the direction of movement. Acceleration sensor 16d detects the vibration level in the Z-axis direction on the rear side of the test specimen S in the direction of movement. Acceleration sensor 16e detects the vibration level in the X-axis direction of the base 14. Acceleration sensors 16e and 16f detect the vibration level in the Z-axis direction of the base 14. Although acceleration sensors 16e and 16f are attached to the base 14, they detect vibrations transmitted from the test specimen S to the base 14. Therefore, acceleration sensors 16e and 16f can also be said to detect vibrations of the test specimen S (particularly vibrations of the portion of the test specimen S facing the base 14).

The test device 10 also has a microphone 18. The microphone 18 is a sensor that detects the sound pressure level of the sound generated when the test piece S moves in the direction of the contact surface 12 while being pressed against the contact surface 12. The microphone 18 continues to detect the sound pressure level while the test piece S is moving. The microphone 18 is provided on the side of the moving direction of the test piece S. That is, in this embodiment, since the test piece S moves in the X-axis direction, the microphone 18 is provided on the Y-axis side of the test piece S. The sound pressure level detected by the microphone 18 is transmitted to the stick-slip frequency identification device.

Figure 2 is a schematic diagram of the configuration of a stick-slip frequency identifying device 30 according to this embodiment. As will be described in detail below, the stick-slip frequency identifying device 30 is a device that executes stick-slip frequency identification processing to identify the stick-slip frequency between the test piece S and the contact surface 12 based on the vibration level of the test piece S detected by the acceleration sensor 16 or the sound pressure level detected by the microphone 18. The stick-slip frequency identifying device 30 can be configured, for example, by a computer attached to the test device 10 or a server computer. Note that the stick-slip frequency identifying device 30 may also be configured from multiple computers. In other words, the functions performed by the stick-slip frequency identifying device 30 described below may be realized by the cooperation of multiple computers.

The communication interface 32 is composed of, for example, a network interface card (NIC) or various communication connectors. The communication interface 32 functions to communicate with other devices, including the acceleration sensor 16 and microphone 18, via a communication line. For example, the communication interface 32 receives a detection signal (vibration level of the test specimen S) from the acceleration sensor 16 and a detection signal (sound pressure level) from the microphone 18. The communication interface 32 also transmits the processing results of the stick-slip frequency identification process to other devices.

The input interface 34 is composed of, for example, a mouse and a keyboard. The input interface 34 is used by the user of the stick-slip frequency identification device 30 to input various commands.

The display 36 is composed of, for example, a liquid crystal panel or an organic EL panel. Various screens are displayed on the display 36. For example, the display 36 may display the results of the stick-slip frequency identification process.

The memory 38 may include, for example, a hard disk drive (HDD), a solid state drive (SSD), an embedded multi-media card (eMMC), a read-only memory (ROM), or a random access memory (RAM). The memory 38 stores a stick-slip frequency identification program for executing a stick-slip frequency identification process for the test piece S. The stick-slip frequency identification program can be stored in a computer-readable, non-transitory storage medium such as a universal serial bus (USB) memory or a compact disc (CD)-ROM. The stick-slip frequency identification device 30 can execute the stick-slip frequency identification program by reading the storage medium on which the stick-slip frequency identification program is stored.

Also, as shown in FIG. 2, vibration data 40 and sound data 42 are stored in memory 38. The vibration data 40 and sound data 42 will be described below along with the processing of the processor 44 (particularly the data acquisition unit 46).

The processor 44 is configured to include, for example, at least one of a CPU (Central Processing Unit) and a dedicated processing device (e.g., a GPU (Graphics Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or programmable logic device). The processor 44 may be configured not by a single processing device, but by multiple processing devices located in physically separate locations working together. As shown in FIG. 2 , the processor 44 functions as a data acquisition unit 46, a frequency identification unit 48, and a coherence acquisition unit 50 in accordance with a stick-slip frequency identification program stored in the memory 38 or a storage medium. Below, the details of the stick-slip frequency identification process are explained, along with details of the processing performed by the data acquisition unit 46, the frequency identification unit 48, and the coherence acquisition unit 50.

The data acquisition unit 46 performs an FFT (Fast Fourier Transform) on the vibration level of the test specimen S detected by the acceleration sensor 16, thereby dividing the vibration level of the test specimen S detected by the acceleration sensor 16 into vibration frequency components for each vibration frequency. As described above, the acceleration sensor 16 continuously detects the vibration level of the test specimen S. Therefore, the data acquisition unit 46 performs an FFT on the vibration levels sequentially detected by the acceleration sensor 16 to acquire vibration data 40 indicating the temporal change in the vibration frequency components for each vibration frequency of the test specimen S. In other words, the vibration data 40 is data indicating the temporal change in the vibration frequency components for each vibration frequency of the test specimen S when the test specimen S is pressed against the contact surface 12 and moved relative to the contact surface 12 in the planar direction of the contact surface 12. In this way, the data acquisition unit 46 corresponds to a vibration data acquisition unit. The data acquisition unit 46 stores the acquired vibration data 40 in the memory 38.

Figure 3 shows a first example of vibration data 40. In Figure 3, the vibration data 40 is shown as a heat map, with the horizontal axis representing time, the vertical axis representing vibration frequency, and the concentration representing the vibration frequency component (vibration level at each vibration frequency). The vibration data 40 shown in Figure 3 is data based on the vibration level acquired by the acceleration sensor 16a, i.e., data based on the vibration level in the X-axis direction on the front side in the direction of movement of the test piece S. In this embodiment, since multiple acceleration sensors 16 are provided, the data acquisition unit 46 may acquire multiple pieces of vibration data 40 corresponding to each position and vibration direction of the test piece S based on the vibration levels acquired by each acceleration sensor 16.

The data acquisition unit 46 also performs an FFT on the sound pressure level detected by the microphone 18, thereby dividing the sound pressure level detected by the microphone 18 into acoustic frequency components for each acoustic frequency. As described above, the microphone 18 continuously detects the sound pressure level. Therefore, the data acquisition unit 46 performs an FFT on the sound pressure levels sequentially detected by the microphone 18, thereby acquiring acoustic data 42 that indicates the time change in the acoustic frequency components for each acoustic frequency of the sound emitted by the test piece S. In other words, the acoustic data 42 is data that indicates the time change in the acoustic frequency components for each acoustic frequency of the sound generated when the test piece S is moved relative to the contact surface 12 in the planar direction of the contact surface 12 while the test piece S is pressed against the contact surface 12. In this way, the data acquisition unit 46 corresponds to an acoustic data acquisition unit. The data acquisition unit 46 stores the acquired acoustic data 42 in the memory 38.

Figure 4 shows a first example of acoustic data 42. In Figure 4, the acoustic data 42 is shown as a heat map, with the horizontal axis representing time, the vertical axis representing acoustic frequency, and the concentration representing the acoustic frequency component (sound pressure level at each acoustic frequency).

The frequency identification unit 48 identifies the stick-slip frequency between the test piece S and the contact surface 12 based on the vibration data 40. Specifically, the frequency identification unit 48 identifies, in the vibration data 40, a vibration frequency with a relatively large vibration frequency component as the stick-slip frequency. Preferably, the frequency identification unit 48 identifies, in the vibration data 40, a vibration frequency that maintains a relatively large vibration frequency component for a predetermined period of time as the stick-slip frequency.

For example, if the vibration data 40 is as shown in Figure 3, the vibration frequency components are relatively large for approximately one second or more near 2 kHz, 4 kHz, and 6 kHz. Therefore, the frequency identification unit 48 can identify 2 kHz, 4 kHz, 6 kHz, and 8 kHz as stick-slip frequencies.

When the stick-slip phenomenon occurs, the test piece S (or at least a portion of it) vibrates at the stick-slip frequency. Therefore, the frequency identification unit 48 can identify a vibration frequency in the vibration data 40 that has a relatively large vibration frequency component as the stick-slip frequency.

In this embodiment, the frequency identification unit 48 identifies the stick-slip frequency based on vibration data 40 obtained from one acceleration sensor 16, but the frequency identification unit 48 may also identify the stick-slip frequency based on multiple vibration data 40 obtained from multiple acceleration sensors 16. For example, a representative value (such as the most frequent value or average value) of multiple stick-slip frequencies identified from each vibration data 40 may be used as the stick-slip frequency between the test piece S and the contact surface 12.

The frequency identification unit 48 can also identify the stick-slip frequency between the test piece S and the contact surface 12 based on the acoustic data 42 instead of the vibration data 40. Specifically, the frequency identification unit 48 identifies an acoustic frequency in the acoustic data 42 that has a relatively large acoustic frequency component as the stick-slip frequency. Preferably, the frequency identification unit 48 identifies an acoustic frequency in the acoustic data 42 that maintains a relatively large acoustic frequency component for a predetermined period of time as the stick-slip frequency.

For example, if the acoustic data 42 has the content shown in Figure 4, the acoustic frequency components are relatively large for approximately one second or more near 2 kHz, 4 kHz, and 6 kHz. Therefore, the frequency identification unit 48 can identify 2 kHz, 4 kHz, 6 kHz, and 8 kHz as stick-slip frequencies.

When the stick-slip phenomenon occurs, the test piece S vibrates at the stick-slip frequency, generating a sound (noise) whose main component is the stick-slip frequency. Therefore, the frequency identification unit 48 can identify, in the acoustic data 42, an acoustic frequency with a relatively large acoustic frequency component as the stick-slip frequency.

The information indicating the stick-slip frequency identified by the frequency identification unit 48 is provided to, for example, a tire designer. For example, the processor 44 transmits the information indicating the stick-slip frequency from the communication interface 32 to a computer used by the tire designer. Alternatively, the processor 44 displays the information indicating the stick-slip frequency on the display 36. By referring to the information indicating the stick-slip frequency, the tire designer can design the tire composition and pattern shape to suppress the occurrence of the stick-slip phenomenon.

The coherence acquisition unit 50 acquires coherence data indicating a correlation value between a vibration frequency component and an acoustic frequency component for each frequency based on the vibration data 40 and the acoustic data 42. In this embodiment, the coherence acquisition unit 50 calculates the coherence data C _xy (f) using the following equation (1).
In the above formula (1), f represents frequency, P _xx (f) represents vibration data 40, P _yy (f) represents acoustic data 42, and P _xy (f) represents the cross spectrum of the vibration data 40 and acoustic data 42. The cross spectrum is obtained by multiplying certain frequency components of the spectra of the vibration data 40 and acoustic data 42 and averaging the multiplied results. When the cross spectrum shows a large value at a certain frequency, it means that there is a high correlation between the frequency components of the vibration data 40 and acoustic data 42 at that frequency, and the magnitudes of the frequency components of both are also large. Note that the vibration data 40 and acoustic data 42 are data having a time axis, and the above formula (1) is a formula for calculating coherence data at a certain timing.

Figure 5 is a diagram showing an example of coherence data acquired based on the vibration data 40 shown in Figure 3 and the acoustic data 42 shown in Figure 4. The frequency identification unit 48 may identify, in the coherence data, frequencies at which the correlation value is relatively large as stick-slip frequencies. For example, in the example of Figure 5, the correlation values are relatively large near 2 [kHz], 4 [kHz], 6 [kHz], and 8 [kHz]. Therefore, the frequency identification unit 48 can identify 2 [kHz], 4 [kHz], 6 [kHz], and 8 [kHz] as stick-slip frequencies.

In the vibration data 40, it is possible that the vibration frequency component becomes relatively high due to factors other than the stick-slip phenomenon. Therefore, when identifying a stick-slip frequency based solely on the vibration data 40, it is possible that a frequency other than the true stick-slip frequency will be identified as the stick-slip frequency. Furthermore, in the acoustic data 42, it is possible that the acoustic frequency component becomes relatively high due to factors other than the stick-slip phenomenon. Therefore, when identifying a stick-slip frequency based solely on the acoustic data 42, it is possible that a frequency other than the true stick-slip frequency will be identified as the stick-slip frequency.

Here, it can be said that a vibration frequency or acoustic frequency where the vibration frequency component is relatively high in the vibration data 40 and the acoustic frequency component is relatively high in the acoustic data 42 is likely to have been increased by the stick-slip phenomenon. In other words, it can be said that the vibration frequency or acoustic frequency in question is likely to be the true stick-slip frequency. Therefore, by having the frequency identification unit 48 identify the stick-slip frequency based on the coherence data, it is possible to identify the stick-slip frequency with high accuracy.

The coherence acquisition unit 50 may also acquire wavelet coherence data indicating the time change in the correlation value between the vibration frequency component and the acoustic frequency component for each frequency based on the vibration data 40 and the acoustic data 42. Specifically, the coherence acquisition unit 50 acquires the wavelet coherence data by calculating the coherence data at each time point using the above formula (1) based on the vibration data 40 and the acoustic data 42.

Figure 6 shows a second example of vibration data 40, Figure 7 shows a second example of acoustic data 42, and Figure 8 shows wavelet coherence data acquired based on the vibration data 40 shown in Figure 6 and the acoustic data 42 shown in Figure 7. In Figure 8, the wavelet coherence data is shown as a heat map, with the horizontal axis representing time, the vertical axis representing frequency, and the concentration representing the correlation value between the vibration frequency component and the acoustic frequency component.

The frequency identification unit 48 may determine a calculation target region 60, which is a region in the wavelet coherence data where the correlation value is relatively large, and identify the stick-slip frequency based on the correlation value included in the calculation target region 60. Specifically, the frequency identification unit 48 identifies, in the wavelet coherence data, a region of a predetermined area or larger where the correlation value is a predetermined value (e.g., 0.9) or greater as the calculation target region 60. The frequency identification unit 48 then performs an FFT on the data included in the calculation target region 60, and identifies the frequency at which the correlation value spectrum obtained by the FFT peaks as the stick-slip frequency.

As in the vibration data 40 shown in FIG. 6 or the acoustic data 42 shown in FIG. 7, there are cases where the vibration frequency (or acoustic frequency) at which the vibration frequency component (or acoustic frequency component) becomes relatively large is not stable along the time axis. In such cases, the identified stick-slip frequency can vary depending on the timing of coherence acquisition. Therefore, after the coherence acquisition unit 50 acquires the wavelet coherence data, the frequency identification unit 48 identifies a calculation target region 60 where the correlation value is relatively high in the two-dimensional space of frequency and time of the wavelet coherence data, and identifies the frequency within the calculation target region 60 where the correlation value peaks as the stick-slip frequency. This makes it possible to identify the stick-slip frequency with higher accuracy. Furthermore, because the peak correlation value is detected from the calculation target region 60, which is a partial region of the wavelet coherence data, the amount of calculation can be reduced at least compared to detecting the peak correlation value from the entire wavelet coherence data.

The above is an overview of the stick-slip frequency identifying device 30 according to this embodiment. Below, the processing flow of the stick-slip frequency identifying device 30 (particularly the processor 44) will be explained according to the flowchart shown in Figure 9.

In step S10, the data acquisition unit 46 acquires vibration data 40 (see FIG. 3 or FIG. 6) by performing an FFT on the vibration level of the test piece S detected by the acceleration sensor 16. The data acquisition unit 46 also acquires acoustic data 42 (see FIG. 4 or FIG. 7) by performing an FFT on the sound pressure level detected by the microphone 18. Step S10 corresponds to a vibration data acquisition step or an acoustic data acquisition step.

In step S12, the coherence acquisition unit 50 acquires coherence data (see Figure 5) indicating the relationship between the correlation value between the vibration frequency component and the acoustic frequency component for each frequency based on the vibration data 40 and acoustic data 42 acquired in step S10. Note that the coherence acquisition unit 50 may also acquire wavelet coherence data (see Figure 8) based on the vibration data 40 and acoustic data 42 acquired in step S10. Step S12 corresponds to a coherence data acquisition step.

In step S14, the frequency identification unit 48 identifies, in the vibration data 40 acquired in step S10, a vibration frequency with a relatively large vibration frequency component as the stick-slip frequency between the test piece S and the contact surface 12. Alternatively, the frequency identification unit 48 identifies, in the acoustic data 42 acquired in step S10, an acoustic frequency with a relatively large acoustic frequency component as the stick-slip frequency between the test piece S and the contact surface 12. The frequency identification unit 48 may also identify, as the stick-slip frequency, a frequency with a relatively large correlation value in the coherence data acquired in step S12. The frequency identification unit 48 may also determine a calculation target region 60, which is a region with a relatively large correlation value in the wavelet coherence data acquired in step S12, and identify the stick-slip frequency based on the correlation value included in the calculation target region 60. Step S14 corresponds to a frequency identification step.

The above describes an embodiment of the present invention, but the present invention is not limited to the above embodiment, and various modifications are possible without departing from the spirit of the present invention.

10 Testing apparatus, 12 Contact surface, 14 Base, 16 Acceleration sensor, 18 Microphone, 30 Stick-slip frequency identification device, 32 Communication interface, 34 Input interface, 36 Display, 38 Memory, 40 Vibration data, 42 Acoustic data, 44 Processor, 46 Data acquisition unit, 48 Frequency identification unit, 50 Coherence acquisition unit, 60 Calculation target area, S Test piece.

Claims (7)

a vibration data acquisition step of acquiring vibration data indicating time changes in vibration frequency components for each vibration frequency of the test piece when the test piece is moved relative to the contact surface in a planar direction of the contact surface while the rubber test piece is pressed against the contact surface;
a frequency identifying step of identifying the vibration frequency at which the vibration frequency component is relatively large in the vibration data as a stick-slip frequency between the test piece and the contact surface;
A stick-slip frequency identification method comprising: an acoustic data acquiring step of acquiring acoustic data indicating a time change in acoustic frequency components for each acoustic frequency of a sound generated when the test piece is moved relative to the contact surface in a planar direction of the contact surface while the test piece is pressed against the contact surface;
a coherence data acquisition step of acquiring coherence data indicating a correlation value between the vibration frequency component and the acoustic frequency component for each frequency based on the vibration data and the acoustic data;
Furthermore,
In the frequency identifying step, a frequency at which the correlation value is relatively large in the coherence data is identified as the stick-slip frequency.
2. The stick-slip frequency identification method according to claim 1. In the coherence data acquisition step, wavelet coherence data indicating a time change of the correlation value for each frequency is acquired based on the vibration data and the acoustic data;
In the frequency identification step, a calculation target region is determined as a region in the wavelet coherence data where the correlation value is relatively large, and the stick-slip frequency is identified based on the correlation value included in the calculation target region.
3. The stick-slip frequency identification method according to claim 2. the contact surface has a dynamic friction coefficient of 1.4 or more when the test piece is moved relative to the contact surface in a surface direction of the contact surface, and an average profile depth representing the roughness of the contact surface is less than 0.1;
4. The stick-slip frequency identifying method according to claim 1, wherein the stick-slip frequency is determined by the rotation of the rotor. an acoustic data acquisition step of acquiring acoustic data indicating time variations in acoustic frequency components for each acoustic frequency of a sound generated when a rubber test piece is moved relative to a contact surface in a planar direction of the contact surface while the rubber test piece is pressed against the contact surface;
a frequency identifying step of identifying an acoustic frequency in which the acoustic frequency component is relatively large in the acoustic data as a stick-slip frequency between the test piece and the contact surface;
A stick-slip frequency identification method comprising: a vibration data acquisition unit that acquires vibration data indicating time changes in vibration frequency components for each vibration frequency of a rubber test piece when the test piece is pressed against a contact surface and the test piece is moved relative to the contact surface in the surface direction of the contact surface; and
a frequency specifying unit that specifies the vibration frequency at which the vibration frequency component is relatively large in the vibration data as a stick-slip frequency between the test piece and the contact surface;
A stick-slip frequency identifying device comprising: an acoustic data acquisition unit that acquires acoustic data indicating time variations in acoustic frequency components for each acoustic frequency of a sound generated when a rubber test piece is pressed against a contact surface and the test piece is moved relative to the contact surface in the planar direction of the contact surface;
a frequency specifying unit that specifies an acoustic frequency in which the acoustic frequency component is relatively large in the acoustic data as a stick-slip frequency between the test piece and the contact surface;
A stick-slip frequency identifying device comprising: