A bearing quality detection method, system and medium

Abstract

The present invention relates to the field of bearing detection. In order to solve the problem that the existing bearing quality detection operation is relatively cumbersome, a bearing quality detection method is provided, including: S100, respectively collecting the offset data and noise data of the bearing in the first working state, the second working state and the third working state; S200, obtaining the relationship curve between the offset data and the noise data in each working state, obtaining the influence weight μ1 of the outer ring offset data on the noise data and the influence weight μ2 of the inner ring offset data on the noise data, and obtaining the quality detection threshold I0; S300, obtaining the difference △I between the quality detection value I and I0, if △I>0, the quality of the bearing is unqualified. The present invention analyzes the offset and noise of the inner and outer rings of the bearing in correlation, obtains the influence weight of the inner and outer ring offset on the noise size, and then obtains the quality detection threshold according to the existing offset threshold. In actual detection, the quality of the bearing can be judged by comparing the quality detection threshold and the quality detection value.

Description

Technical Field

[0001] The present invention relates to the field of bearing detection, and in particular to a bearing quality detection method, system and medium. Background Art

[0002] Bearings are components used in machinery to reduce friction between rotating and fixed parts. They play a vital role in all types of mechanical equipment. By supporting the shaft and allowing it to rotate, bearings not only reduce friction and wear, but also improve efficiency, reduce energy consumption, and help extend the service life of the equipment. Quality inspection of bearings can evaluate the manufacturing quality, performance, and life expectancy of bearings. Among them, the dynamic performance inspection of bearings mainly ensures rotation accuracy, noise level, temperature rise, etc. In the dynamic performance inspection, different types of data need to be collected separately, and then compared with the threshold separately to judge the quality of the bearing, which is a cumbersome operation. Summary of the invention

[0003] The purpose of the present invention is to provide a bearing quality detection method, system and medium to solve the problem that the existing bearing quality detection operation is relatively complicated.

[0004] The embodiments of the present invention are implemented by the following technical solutions:

[0005] A bearing quality detection method, comprising:

[0006] S100, respectively collecting displacement data and noise data when the bearing is in a first working state, a second working state, and a third working state;

[0007] When the bearing is in the first working state, the outer ring of the bearing is fixed and the inner ring rotates; when the bearing is in the second working state, the outer ring of the bearing rotates and the inner ring is fixed; when the bearing is in the third working state, both the inner and outer rings of the bearing rotate;

[0008] S200, obtaining the relationship curve between the offset data and the noise data under each working state, and obtaining the influence weight μ of the outer ring offset data on the noise data 1 And the influence weight μ of inner circle offset data on noise data 2 , and obtain the quality detection threshold I 0 ;

[0009] S300, obtaining quality detection values ​​I and I 0 The difference △I, if △I>0, the quality of the bearing is unqualified, if △I≤0, the quality of the bearing is qualified.

[0010] Preferably, the S200 includes:

[0011] A100, obtain the relationship curve between the offset data and the noise data under each working state;

[0012] A200, obtaining a first noise correlation curve, where the first noise correlation curve is a relationship curve of noise data in the first working state and the third working state when the inner circle offset data in the two working states are the same;

[0013] Obtaining a second noise correlation curve, wherein the second noise correlation curve is a relationship curve of noise data in the second working state and the third working state when the outer ring offset data of the second working state and the third working state are the same;

[0014] A300, according to the first noise correlation curve, the influence weight μ of the outer ring offset data on the noise data is obtained 1 ; According to the second noise correlation curve, the influence weight μ of the inner circle offset data on the noise data is obtained 2 ;

[0015] The S200 0 =μ 1 D 1+ μ 2 D 2 , where D 1 is the outer ring offset data threshold, D 2 is the inner circle offset data threshold; in S300, I=a 1 M 1 + a 2 M 2 , where M 1 is the measured value of the outer ring offset data, a 1 M 1 The corresponding impact weight; M 2 is the measured value of the inner ring offset data, a 2 M 2 The corresponding impact weight.

[0016] Preferably, the specific operations of A300 include:

[0017] Obtain a first weight curve, where the first weight curve is a relationship curve between the third outer ring offset data and the first slope; the first slope is the slope of a line between a corresponding point of the third outer ring offset data on the first noise correlation curve and the origin; the third outer ring offset data is the offset data of the outer ring under the third working state;

[0018] Obtain a second weight curve, where the second weight curve is a relationship curve between the third inner circle offset data and the second slope; the second slope is the slope of a line between a corresponding point of the third inner circle offset data on the second noise correlation curve and the origin; the third inner circle offset data is the offset data of the inner circle under the third working state;

[0019] In the S200, μ 1 D 1 The first slope corresponding to the first weight curve, μ 2 D 2 a corresponding second slope on the second weight curve;

[0020] In the S300, a 1 M 1 The first slope corresponding to the first weight curve, a 2 M 2 A corresponding second slope on the second weight curve.

[0021] Preferably, the offset data includes at least one of axial offset data and radial offset data.

[0022] Preferably, the method for collecting the offset data of the third working state includes:

[0023] B100, establish a coordinate system with the bearing center as the center of the circle;

[0024] B200, collect the offset array of the outer ring center in the coordinate system in the third working state (m 1 , n 1 , …), where m 1 is the offset of the center of the outer ring in the x direction, n 1 is the offset of the center of the outer circle in the y direction; collect the offset array of the center of the inner circle in the coordinate system in the third working state (m 2 , n 2 , …), where m 2 is the offset of the inner circle center in the x direction, n 2 is the offset of the inner circle center in the y direction;

[0025] B300, obtaining the offset data (m, n, ...) of the third working state; wherein m= m 1 -m 2 , n = n 1 -n 2 ;

[0026] In the third working state, the relationship curve between the offset data and the noise data is a three-dimensional curve.

[0027] Preferably, the coordinate system in B100 is a three-dimensional coordinate system; in B200, the offset array of the center of the outer ring in the coordinate system is (m 1 , n 1 , k 1 ), the offset array of the inner circle center in the coordinate system is (m 2 , n 2, k 2 ); k 1 is the offset of the center of the outer ring in the z direction, k 2 is the offset of the inner ring center in the z direction; the offset data of the third working state in B300 is (m, n, k), k = k 1 -k 2 .

[0028] Preferably, in the third working state, the variables of the relationship curve between the offset data and the noise data are f, k and p, where f 2 =m 2 +n 2 , p is the noise intensity.

[0029] A bearing quality detection system comprises a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the bearing quality detection method.

[0030] A computer-readable storage medium stores a computer program, wherein the computer program is used to be programmed or configured by a microprocessor to execute the bearing quality detection method.

[0031] The present invention has at least the following beneficial effects:

[0032] The present invention conducts historical analysis on the associated data of the offset of the inner and outer rings of the bearing and the noise that can characterize the vibration intensity to a certain extent, and obtains the influence weight of the inner and outer ring offset on the noise size, and then obtains the quality detection threshold according to the existing offset threshold. In actual detection, by comparing the quality detection threshold and the quality detection value, it is possible to determine whether the runout and vibration of the bearing meet the quality standards, and the operation is more convenient. DETAILED DESCRIPTION

[0033] In order to make the purpose, method scheme and advantages of the embodiments of the present invention clearer, the method scheme in the embodiments of the present invention is clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0034] Embodiment 1: A bearing quality detection method, comprising:

[0035] S100, respectively collecting displacement data and noise data when the bearing is in a first working state, a second working state, and a third working state;

[0036] When the bearing is in the first working state, the outer ring of the bearing is fixed and the inner ring rotates; when the bearing is in the second working state, the outer ring of the bearing rotates and the inner ring is fixed; when the bearing is in the third working state, both the inner and outer rings of the bearing rotate;

[0037] S200, obtaining the relationship curve between the offset data and the noise data under each working state, and obtaining the influence weight μ of the outer ring offset data on the noise data 1 And the influence weight μ of inner circle offset data on noise data 2 , and obtain the quality detection threshold I 0 ;

[0038] S300, obtaining quality detection values ​​I and I 0 The difference △I, if △I>0, the quality of the bearing is unqualified, if △I≤0, the quality of the bearing is qualified.

[0039] In the specific implementation process, the bearing is usually rotated with one of the inner ring or outer ring relative to the other fixed part, while the other part remains stationary. For example, in most applications, the inner ring of the bearing rotates with the shaft, while the outer ring is installed in a fixed bearing seat or machine housing and remains stationary. However, in some special application scenarios, there are indeed situations where the inner and outer rings of the bearing need to rotate at the same time. For example, in some high-load or high-wear environments, by allowing both the inner and outer rings to participate in the rotation, the contact point can be continuously changed, thereby distributing wear and stress more evenly and extending the service life of the equipment. If the inner and outer rings of the bearing rotate, but when detecting the quality of the bearing, only the inner ring offset and the outer ring offset are compared with the corresponding threshold values, the vibration anomalies caused by the two rings moving away from, approaching, and deflecting each other are ignored in the quality judgment. This embodiment fully considers multiple working states of the bearing, so that its quality detection method can be applied to both one-way bearings and two-way bearings. During the test, if only the radial offset data of the inner and outer rings are collected, the bearing can be placed horizontally to reduce the influence of its own weight on the radial offset. If only the axial offset data of the inner and outer rings are collected, the bearing can be placed vertically to reduce the influence of its own weight on the axial offset. The offset data can be collected directly by displacement sensors or by image acquisition, and the offset data can be obtained by image comparison. Noise data can be collected by sound level meters and microphone arrays.

[0040] During the use of the bearing, when the bearing quality detection method provided in this embodiment is used, an early warning system can also be set up. When △I>0, a warning signal is issued. After receiving the warning signal, the staff can perform maintenance operations. For example, based on the sudden and rapid increase of noise data on the relationship curve between offset data and noise data, it can be judged that the impact of offset in a certain direction on noise is greater, and then a targeted maintenance strategy can be formulated to reduce offset or improve lubrication conditions to reduce vibration and wear risks. The user interface can also allow operators to easily view test results, historical trend charts, and receive instant alarm information.

[0041] In the process of historical data collection, a large amount of data under the same bearing working condition can be collected, and outliers in the data can be removed through data noise reduction. Then, new data points can be inserted between data points through interpolation to fill the missing values ​​caused by noise, making the data more continuous and smooth. Outliers in the data can be identified and eliminated through methods such as statistical analysis, outlier detection and outlier point identification. Collecting a large amount of historical data can make the relationship curve between offset data and noise data more consistent with the actual situation.

[0042] Embodiment 2: In order to better obtain the offset data threshold, an improvement is made on the basis of Embodiment 1. In this embodiment, S200 includes:

[0043] A100, obtain the relationship curve between the offset data and the noise data under each working state;

[0044] A200, obtaining a first noise correlation curve, where the first noise correlation curve is a relationship curve of noise data in the first working state and the third working state when the inner circle offset data in the two working states are the same;

[0045] Obtaining a second noise correlation curve, wherein the second noise correlation curve is a relationship curve of noise data in the second working state and the third working state when the outer ring offset data of the second working state and the third working state are the same;

[0046] A300, according to the first noise correlation curve, the influence weight μ of the outer ring offset data on the noise data is obtained 1 ; According to the second noise correlation curve, the influence weight μ of the inner circle offset data on the noise data is obtained 2 ;

[0047] The S200 0 =μ 1 D 1+ μ 2 D 2 , where D 1 is the outer ring offset data threshold, D 2 is the inner circle offset data threshold; in S300, I=a 1 M 1 + a 2 M 2 , where M 1 is the measured value of the outer ring offset data, a 1 M 1 The corresponding impact weight; M 2 is the measured value of the inner ring offset data, a 2 M 2 The corresponding impact weight.

[0048] In the specific implementation process, D 1 and D 2The value of can be set according to actual needs, for example, refer to the requirements for bearing offset in the P0-P6 level in the existing radial runout standard. Since the data is not continuous when collecting historical data, this embodiment first fits the curve through the collected point values ​​in A100 to estimate the noise data corresponding to all offset data. The first noise correlation curve can characterize the influence of the outer ring offset data on the rise and fall of the noise data, and the second noise correlation curve can characterize the influence of the inner ring offset data on the rise and fall of the noise data, and then the influence weight of the inner and outer ring offsets on the noise data can be obtained.

[0049] Embodiment 3: In order to obtain the influence weight corresponding to any offset data and make the weight assignment more reasonable, an improvement is made on the basis of Embodiment 2. In this embodiment, the specific operations of A300 include:

[0050] Obtain a first weight curve, where the first weight curve is a relationship curve between the third outer ring offset data and the first slope; the first slope is the slope of a line between a corresponding point of the third outer ring offset data on the first noise correlation curve and the origin; the third outer ring offset data is the offset data of the outer ring under the third working state;

[0051] Obtain a second weight curve, where the second weight curve is a relationship curve between the third inner circle offset data and the second slope; the second slope is the slope of a line between a corresponding point of the third inner circle offset data on the second noise correlation curve and the origin; the third inner circle offset data is the offset data of the inner circle under the third working state;

[0052] In the S200, μ 1 D 1 The first slope corresponding to the first weight curve, μ 2 D 2 a corresponding second slope on the second weight curve;

[0053] In the S300, a 1 M 1 The first slope corresponding to the first weight curve, a 2 M 2 A corresponding second slope on the second weight curve.

[0054] In the specific implementation process, the two variables of the first noise correlation curve are the noise data of the bearing in the first working state and the noise data of the bearing in the third working state, and the first slope can represent the multiple relationship of the two noise data. The two variables of the second noise correlation curve are the noise data of the bearing in the second working state and the noise data of the bearing in the third working state, and the second slope can represent the multiple relationship of the two noise data. The first weight curve can represent the influence of the third outer ring offset data on the noise when the bearing is in the third working state. The second weight curve can represent the influence of the third inner ring offset data on the noise when the bearing is in the third working state.

[0055] Embodiment 4: In order to be applicable to different scenarios, an improvement is made on the basis of Embodiment 1. In this embodiment, the offset data includes at least one of axial offset data and radial offset data.

[0056] In the specific implementation process, when the bearing accuracy requirement is relatively low, if the bearing is placed vertically during use and the counterweight is along its radial direction, only the radial offset data can be collected; if the bearing is placed horizontally during use and the counterweight is along its axial direction, only the axial offset data can be collected. When the bearing accuracy requirement is high, both the axial offset data and the radial offset data can be collected at the same time.

[0057] Embodiment 5: Based on Embodiment 1, this embodiment provides a method for collecting offset data in a third working state, including:

[0058] B100, establish a coordinate system with the bearing center as the center of the circle;

[0059] B200, collect the offset array of the outer ring center in the coordinate system in the third working state (m 1 , n 1 , …), where m 1 is the offset of the center of the outer ring in the x direction, n 1 is the offset of the center of the outer circle in the y direction; collect the offset array of the center of the inner circle in the coordinate system in the third working state (m 2 , n 2 , …), where m 2 is the offset of the inner circle center in the x direction, n 2 is the offset of the inner circle center in the y direction;

[0060] B300, obtaining the offset data (m, n, ...) of the third working state; wherein m= m 1 -m 2 , n = n 1 -n 2 ;

[0061] In the third working state, the relationship curve between the offset data and the noise data is a three-dimensional curve.

[0062] During the specific implementation, the offset data in the first working state and the second working state only involves the inner ring or the outer ring, so the offset array of the outer / inner ring center in the coordinate system can be directly used as the offset data of the corresponding working state. When the offset data only collects radial offset or axial offset, the relationship curve between the offset data and the noise data in the first working state is a two-dimensional curve, and the relationship curve between the offset data and the noise data in the second working state is a two-dimensional curve. When the offset data collects radial offset and axial offset at the same time, the relationship curves between the offset data and the noise data in the three working states are all three-dimensional curves. For the elements in the offset array, this embodiment only limits the x-direction offset and the y-direction offset, and can also add the z-direction offset and the deflection angle. The coordinate system can be a two-dimensional rectangular coordinate system or a three-dimensional rectangular coordinate system, with the bearing center as the origin, which helps to accurately quantify the displacement of the inner and outer ring centers in different directions.

[0063] Since the third working state involves the offset of the inner and outer rings, and the offset process involves the same-direction offset and the opposite-direction offset, the relative offset direction of the inner and outer rings can be characterized by the difference in the offset of the inner and outer rings. For example, when the inner ring offsets 0.1mm upward, it is counted as +0.1. When the outer ring offsets 0.1mm downward, it is counted as -0.1, and the final offset data is 0.1-(-0.1)=0.2. When the inner ring offsets 0.1mm upward, it is counted as +0.1. When the outer ring offsets 0.05mm upward, it is counted as +0.05, and the final offset data is 0.1-(0.05)=0.05.

[0064] Example 6: In order to increase the reliability of the quality inspection method, an improvement is made on the basis of Example 5. In this example, the coordinate system in B100 is a three-dimensional coordinate system; in B200, the offset array of the center of the outer ring in the coordinate system is (m 1 , n 1 , k 1 ), the offset array of the inner circle center in the coordinate system is (m 2 , n 2 , k 2 ); k 1 is the offset of the center of the outer ring in the z direction, k 2 is the offset of the inner circle center in the z direction; the offset data of the third working state in B300 is (m, n, k), k=k 1 -k 2 .

[0065] During the specific implementation process, this embodiment uses the offsets in the x, y, and z directions when collecting the offset data in the third working state. The offset in the z direction can characterize the axial offset of the inner and outer rings of the bearing along the rotating shaft. The offsets in the x and y directions can characterize the radial offset of the inner and outer rings of the bearing. In the first working state and the second working state, the offset data of the bearing can also increase the offset in the z direction. At this time, in the first working state and the second working state, the relationship curve between the offset data and the noise data is a three-dimensional curve. The relative movement of the inner and outer rings of most bearings basically does not involve deflection. Therefore, this embodiment only collects the offsets in three directions, and incorporates the axial movement and radial movement into the factors affecting the noise data, making the results more accurate.

[0066] Embodiment 7: In order to reduce data processing while ensuring the accuracy of the detection results, an improvement is made on the basis of Embodiment 6. In this embodiment, in the third working state, the variables of the relationship curve between the offset data and the noise data are f, k and p, where f 2 =m 2 +n 2 , p is the noise intensity.

[0067] During the specific implementation, when the offset data in the third working state involves three directions, x, y, and z, there are four variables in the relationship curve, which increases the difficulty of data processing. Therefore, this embodiment processes the data in the x and y directions so that f can be the offset of the overall standard bearing radial direction, thereby reducing the curve variables and the difficulty of data processing. In addition, f is essentially the actual offset of the bearing center, so the accuracy of the data processing result can be guaranteed. The offset direction of the bearing center may not be parallel to a certain coordinate axis of the coordinate system in B100. If the offset of the inner and outer rings is calculated separately and then the offset data is processed, it is possible that the offset directions of the two rings are not on a straight line. Therefore, this embodiment first uses m= m 1 -m 2 , n = n 1 -n 2 The relative displacement of the two circles in the x and y directions is obtained, and then data processing is performed to improve the reliability of the final detection results after data processing. If it is necessary to analyze the direction of the relative displacement of the two circles, such as when it is necessary to determine the detection strategy based on the influence of the displacement on the vibration, the direction angle α can be calculated by α=arctan(m / n).

[0068] When the offset of the bearing also involves the three directions of x, y, and z in the first working state and the second working state, the data processing can be performed with reference to the above. In the first working state, the offset of the outer ring of the bearing can be directly set to 0. In the second working state, the offset of the outer ring of the bearing can also be directly set to 0.

[0069] Embodiment 8: This embodiment provides a bearing quality detection system, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the bearing quality detection method.

[0070] Embodiment 9: This embodiment provides a computer-readable storage medium, in which a computer program is stored. The computer program is used to be programmed or configured by a microprocessor to execute the bearing quality detection method.

[0071] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A bearing quality detection method, characterized in that: include: S100, respectively collecting displacement data and noise data when the bearing is in a first working state, a second working state, and a third working state; When the bearing is in the first working state, the outer ring of the bearing is fixed and the inner ring rotates; when the bearing is in the second working state, the outer ring of the bearing rotates and the inner ring is fixed; when the bearing is in the third working state, both the inner and outer rings of the bearing rotate; S200, obtaining the relationship curve between the offset data and the noise data under each working state, obtaining the influence weight μ1 of the outer ring offset data on the noise data and the influence weight μ2 of the inner ring offset data on the noise data, and obtaining the quality detection threshold I0; S300, obtaining a difference △I between the quality detection values ​​I and I0, if △I>0, the quality of the bearing is unqualified, if △I≤0, the quality of the bearing is qualified.

2. The bearing quality detection method according to claim 1, characterized in that: The S200 includes: A100, obtain the relationship curve between the offset data and the noise data under each working state; A200, obtaining a first noise correlation curve, where the first noise correlation curve is a relationship curve of noise data in the first working state and the third working state when the inner circle offset data in the two working states are the same; Obtaining a second noise correlation curve, wherein the second noise correlation curve is a relationship curve of noise data in the second working state and the third working state when the outer ring offset data of the second working state and the third working state are the same; A300, obtaining the influence weight μ1 of the outer ring offset data on the noise data according to the first noise correlation curve; obtaining the influence weight μ2 of the inner ring offset data on the noise data according to the second noise correlation curve; In the S200, I0=μ1D 1+ μ2D2, wherein D1 is the outer circle offset data threshold, and D2 is the inner circle offset data threshold; in S300, I=a1M1+ a2M2, wherein M1 is the measured value of the outer circle offset data, and a1 is the influence weight corresponding to M1; M2 is the measured value of the inner circle offset data, and a2 is the influence weight corresponding to M2.

3. The bearing quality detection method according to claim 2, characterized in that: The specific operations of A300 include: Obtain a first weight curve, where the first weight curve is a relationship curve between the third outer ring offset data and the first slope; the first slope is the slope of a line between a corresponding point of the third outer ring offset data on the first noise correlation curve and the origin; the third outer ring offset data is the offset data of the outer ring under the third working state; Obtain a second weight curve, where the second weight curve is a relationship curve between the third inner circle offset data and the second slope; the second slope is the slope of a line between a corresponding point of the third inner circle offset data on the second noise correlation curve and the origin; the third inner circle offset data is the offset data of the inner circle under the third working state; In the S200, μ1 is a first slope corresponding to D1 on the first weight curve, and μ2 is a second slope corresponding to D2 on the second weight curve; In S300, a1 is a first slope corresponding to M1 on the first weight curve, and a2 is a second slope corresponding to M2 on the second weight curve.

4. The bearing quality detection method according to claim 1, characterized in that: The offset data includes at least one of axial offset data and radial offset data.

5. The bearing quality detection method according to claim 1, characterized in that: The method for collecting the offset data of the third working state includes: B100, establish a coordinate system with the bearing center as the center of the circle; B200, collect the offset array (m1, n1, ...) of the center of the outer circle in the coordinate system in the third working state, where m1 is the offset of the center of the outer circle in the x direction, and n1 is the offset of the center of the outer circle in the y direction; collect the offset array (m2, n2, ...) of the center of the inner circle in the coordinate system in the third working state, where m2 is the offset of the center of the inner circle in the x direction, and n2 is the offset of the center of the inner circle in the y direction; B300, obtaining the offset data (m, n, ...) of the third working state; wherein m = m1 - m2, n = n1 - n2; In the third working state, the relationship curve between the offset data and the noise data is a three-dimensional curve.

6. The bearing quality detection method according to claim 5, characterized in that: The coordinate system in B100 is a three-dimensional coordinate system; in B200, the offset array of the outer circle center in the coordinate system is (m1, n1, k1), and the offset array of the inner circle center in the coordinate system is (m2, n2, k2); k1 is the offset of the outer circle center in the z direction, and k2 is the offset of the inner circle center in the z direction; the offset data of the third working state in B300 is (m, n, k), k= k1- k2.

7. The bearing quality detection method according to claim 6, characterized in that: In the third working state, the variables of the relationship curve between the offset data and the noise data are f, k and p, where f 2 =m 2 +n 2 , p is the noise intensity.

8. A bearing quality detection system, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the bearing quality detection method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: The computer program is used to be programmed or configured by a microprocessor to execute the bearing quality detection method according to any one of claims 1 to 7.