Method, device and system for detecting radial runout anomaly of facing cutter

Abstract

The invention relates to a facing cutter radial runout anomaly detection method, device, system and equipment and a medium, and the method comprises the steps: enabling a line laser sensor to orthogonally align to the outer side surface of a facing cutter, enabling the facing cutter to rotate for at least one circle at a constant speed, and obtaining a point cloud data set P {Pi (x, y, z), i = 0-n-1} of the outer side surface of the facing cutter; wherein x, y and z are coordinate values of the ith point relative to the X axis, the Y axis and the Z axis of the line laser sensor respectively; determining the deviation between the point cloud data and the standard point cloud data; when the deviation exceeds a preset deviation, determining that the facing cutter has radial run-out abnormity and abnormal point cloud coordinates; and according to the abnormal point cloud coordinates, the specific position of the milling cutter with abnormal jumping is positioned. Thus, the limitation of the complex shape of the facing cutter can be overcome, and the anomaly detection of the facing cutter is realized, so that the radial run-out anomaly can be found and processed in time, and the cutting effect of a milling and grinding vehicle and the safety of a steel rail are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of abnormal detection of milling cutter discs, and in particular to a method, device and system for detecting abnormal radial runout of a milling cutter disc. Background Art

[0002] With the rapid development of rail transit, rail maintenance has become an important part of ensuring train operation safety and improving operation efficiency. Rail milling and grinding vehicles, as a new type of rail transit maintenance equipment, have been widely used in the field of rail disease repair due to their advantages such as high repair accuracy, large milling volume at one time, clean and environmentally friendly. Its core component, the milling cutter disc, is the key to achieving rail shaping repair, and its performance directly determines the operation effect of the milling and grinding vehicle.

[0003] The milling cutter disc usually adopts a "profiling" design, that is, multiple groups of profiling blades are evenly installed on the circumference, and each group of blades envelops a profile consistent with the rail. During the operation, the milling and grinding vehicle moves along the direction of the rail, driving the high-speed rotating cutter disc and the rail to form a relative feed motion, removing the surface material of the rail by circular milling, thereby eliminating rail defects. However, factors such as the design tolerance of the milling cutter disc, structural deformation, blade installation error, and abnormal blade breakage may all cause abnormal radial circumferential runout of the cutter disc. These abnormal runouts not only exist alone, but may also overlap with each other, resulting in an increase in the total runout. When the radial runout of the milling cutter disc exceeds the normal threshold, it will leave obvious abnormal cutter marks on the surface of the rail, seriously reducing the operating effect of the milling and grinding vehicle, and even causing damage to the rail. Therefore, the detection of abnormal radial runout of the milling and grinding vehicle has become an important means to ensure cutting effect and rail safety.

[0004] However, the current detection of radial runout anomalies of milling cutter discs mainly relies on manual operation. The specific process includes moving the milling cutter disc to the inspection table, rotating the cutter disc and using a micrometer to detect and count the blades at each tool position. This method has many shortcomings: first, there are usually hundreds of blades on the milling cutter disc, and due to the need for profiling design, the blade size, shape and installation height of different tool positions are different, resulting in a large amount of labor and low efficiency in the detection process; second, manual detection is greatly affected by subjective factors and has poor data consistency; in addition, due to the limitation of operating space, this method is difficult to perform real-time detection on the work vehicle, resulting in poor real-time detection data, and the radial runout anomaly of the cutter disc at the work site cannot be effectively monitored.

[0005] In addition, the outer surface of the milling cutter disc is complex in design and has the characteristics of "unevenness", such as the grooves between different groups of blades, the differences in blade types and installation heights within the same group, etc. This complex structure makes the outer surface almost without a continuous arc surface. During the rotation of the cutter disc, the radius of the outer surface fluctuates, which brings great difficulties to the radial runout detection.

[0006] Therefore, in this context, the present invention aims to provide an efficient and accurate method for detecting abnormal radial runout of the milling cutter disc of a milling and grinding machine to solve the problems existing in the prior art, overcome the limitations of the complex shape of the milling cutter disc, improve detection efficiency and data accuracy, and ensure the cutting effect of the milling and grinding machine and the safety of the rails. Summary of the invention

[0007] In view of the above problems in the prior art, the present application provides a method, device, system, equipment and medium for detecting abnormal radial runout of a milling cutter disc. The present application can overcome the limitations of the complex shape of the milling cutter disc and realize abnormal detection of the milling cutter disc, so as to timely discover and deal with abnormal radial runout, thereby ensuring the cutting effect of the milling machine and the safety of the rails.

[0008] To achieve the above-mentioned purpose, the first aspect of the present application provides a method for detecting abnormal radial runout of a milling cutter disc, comprising:

[0009] A line laser sensor is used to orthogonally aim at the outer side of the milling cutter disk, so that the milling cutter disk rotates at a constant speed for at least one circle, and a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disk is obtained; wherein x, y, and z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disk and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disk axis, and the Y-axis direction matches the tangent direction of the milling cutter disk rotation direction;

[0010] Determine the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle;

[0011] When the deviation exceeds the preset deviation, it is determined that the milling cutter disc has abnormal radial runout and abnormal point cloud coordinates;

[0012] The specific position of the milling cutter disc where the abnormal vibration occurs is located according to the abnormal point cloud coordinates.

[0013] Thus, in this application, the method can obtain high-precision point cloud data by using a line laser sensor for non-contact measurement. By comparing the real-time point cloud data with the standard point cloud data, the tiny radial runout anomaly of the milling cutter disc can be accurately identified. When the radial runout anomaly is detected, the abnormal point cloud coordinates can be quickly used to locate the specific blade or cutter disc body structure abnormal position, which provides a strong basis for subsequent maintenance and repair work and reduces troubleshooting time. In addition, the milling cutter disc can be inspected during operation without stopping or disassembling, and without manual handling, disassembly and installation of the cutter disc, which greatly saves manpower and time and improves detection efficiency.

[0014] As a possible implementation of the first aspect, the point cloud data collection includes a plurality of point cloud coordinates;

[0015] The point cloud coordinates are determined by the following formula:

[0016]

[0017] Among them, x t ,y t 、z t is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time t. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t;

[0018] The standard point cloud coordinates are determined by the following formula:

[0019]

[0020] Among them, x ts ,y ts 、z ts is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time ts. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t.

[0021] In this way, by using an accurate mathematical model to calculate the position of each point, the accuracy of the point cloud data is improved. When compared with the standard point cloud data later, the specific location of the abnormal vibration of the milling cutter disc can be effectively identified, thereby improving the accuracy of the abnormal detection of the milling cutter disc.

[0022] As a possible implementation manner of the first aspect, determining the deviation between the point cloud data and standard point cloud data includes:

[0023] Slice and frame the point cloud data to obtain point cloud data with a length of L in the Y-axis direction as a test frame;

[0024] The test frame is aligned with a data frame of the same length in the standard point cloud data;

[0025] The coordinates of the point cloud data corresponding to the standard point cloud data are determined by the following formula:

[0026]

[0027] Determine the same (x t ,y t ) The difference in the coordinate value of the Z axis between the point cloud data and the standard point cloud data at the position;

[0028] The difference in the coordinate value of the Z axis is determined as the deviation between the point cloud data and the standard point cloud data.

[0029] In this way, the collected point cloud data is matched and aligned with the standard point cloud data to ensure that the two are in the same coordinate system, and then the same (x t ,y t ) can clearly determine which positions on the milling cutter disc have abnormal vibrations, so that targeted maintenance can be carried out to avoid unnecessary comprehensive inspections, reduce unplanned downtime, and thus reduce maintenance costs.

[0030] As a possible implementation manner of the first aspect, the abnormal point cloud coordinates are determined by the following formula:

[0031]

[0032] Among them, z′ t The point cloud data is the same as the standard point cloud data (x t ,y t ) position, and z′ t Greater than the preset deviation, a total of n points in the X-axis direction, ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter disk, and β is the sampling spacing.

[0033] In this way, by determining the coordinates of the abnormal point cloud, it is convenient to subsequently locate the specific location of the abnormal jump on the milling cutter disc, which helps maintenance personnel to quickly find the problem and reduce the time and effort of inspecting the entire milling cutter disc.

[0034] In some implementations, the method further includes: utilizing the object point coordinate information acquired by the line laser sensor;

[0035] As a possible implementation of the first aspect, the method further includes: obtaining object point coordinate information using the line laser sensor;

[0036] The object point coordinate information is determined by the following formula:

[0037]

[0038] Among them, P obj (i,θ t ,r it ) is a point in the i-th row on the outer surface of the cutter disc at time t. There are n points in the X-axis direction. i is any point among the n points. θ t P is the time point t obj (i,θ t ,r it ) angle, θ 0 is the angle between the object point and the 0° mark of the milling cutter at time t=0, ω 0 is the angular velocity of the milling cutter, r it is the radius of the i-th row detection at time t;

[0039] The method of locating the specific position of the milling cutter disc where abnormal vibration occurs according to the abnormal point cloud coordinates includes:

[0040] According to the abnormal point cloud coordinates Determine the time when the radial runout of the milling cutter occurs; where the time is determined by the following formula:

[0041]

[0042] According to the determined time of radial runout of the milling cutter, the coordinate information of the object point is used Determine the specific location P of the abnormal point obj (i,θ t ,r it ).

[0043] In this way, the abnormal time is determined by using the abnormal point cloud coordinates, and the specific position of the abnormal object point is located in combination with the object point coordinate information. After the specific position of the abnormal object point is determined, resources can be deployed more specifically for maintenance and processing, avoiding a comprehensive inspection of the milling cutter disc, saving time and resources.

[0044] As a possible implementation of the first aspect, the maximum value of the uniform rotation of the milling cutter disc is:

[0045]

[0046] Among them, ω max is the maximum speed of the milling cutter, β maxis the maximum sampling interval, α is the sampling frequency, r 0 is the radius of the milling cutter disc.

[0047] In this way, by controlling the maximum speed of the milling cutter, it is possible to ensure that the sampling interval is not too large, thereby reducing the circumferential positioning error, helping to improve the positioning accuracy of the abnormal point cloud coordinates and ensure the accuracy of abnormality detection. When the sampling interval is too large, some small abnormal jumps may be missed, or normal fluctuations may be misjudged as abnormalities. Therefore, controlling the maximum speed of the milling cutter can also reduce such misjudgments.

[0048] In order to achieve the above-mentioned object, the second aspect of the present application provides a device for detecting abnormal radial runout of a milling cutter disc, comprising:

[0049] An acquisition unit is used to use a line laser sensor to orthogonally align the outer side of the milling cutter disc, so that the milling cutter disc rotates at a constant speed for at least one circle, and obtain a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disc; wherein x, y, and z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disc and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disc axis, and the Y-axis direction matches the tangent direction of the milling cutter disc rotation direction;

[0050] The first determination unit is used to determine the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc by using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle;

[0051] A second determination unit is used to determine that the milling cutter disc has radial runout anomaly and abnormal point cloud coordinates when the deviation exceeds a preset deviation;

[0052] The positioning unit is used to locate the specific position of the milling cutter disc where abnormal vibration occurs according to the abnormal point cloud coordinates.

[0053] To achieve the above-mentioned object, the third aspect of the present application provides a milling cutter disc radial runout abnormality detection system, characterized in that it comprises: a drive control module, a network device, a host computer, a line laser sensor and a milling cutter disc;

[0054] The host computer is connected to the line laser sensor and the drive control module respectively through the network device, and the drive control module is connected to the milling cutter disc;

[0055] The drive control module controls the milling disc to rotate at a constant speed for at least one circle, and the line laser sensor is aimed directly at the outer side of the milling disc to obtain a point cloud data collection of the outer side of the milling disc, and sends it to the host computer. The host computer is used to implement the method described in any one of the first aspects above.

[0056] To achieve the above-mentioned object, the fourth aspect of the present application provides a computing device, including:

[0057] processor,

[0058] and a memory having program instructions stored thereon, wherein the program instructions, when executed by the processor, cause the processor to execute any of the methods described in the first aspect above.

[0059] To achieve the above-mentioned purpose, the fifth aspect of the present application provides a computer-readable storage medium having program instructions stored thereon, and when the program instructions are executed by a computer, the computer implements any of the methods described in the first aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flow chart of a method for detecting abnormal radial runout of a milling cutter disc provided in the present application;

[0061] Figure 2 It is a schematic diagram of the principle of the embodiment provided by this application;

[0062] Figure 3 It is a structural schematic diagram of a device for detecting abnormal radial runout of a milling cutter disc provided in the present application;

[0063] Figure 4 It is a structural schematic diagram of a milling cutter disc radial runout abnormality detection system provided by the present application;

[0064] Figure 5 It is a structural schematic diagram of a computing device provided in an embodiment of the present application.

[0065] It should be understood that the size and shape of each block diagram in the above structural diagram are for reference only and should not constitute an exclusive interpretation of the embodiment of the present invention. The relative position and inclusion relationship between the blocks presented in the structural diagram are only schematic representations of the structural association between the blocks, and do not limit the physical connection method of the embodiment of the present invention. DETAILED DESCRIPTION

[0066] The technical solution provided by the present application is further described below with reference to the accompanying drawings and examples. It should be understood that the system structure and business scenarios provided in the examples of the present application are mainly to illustrate the possible implementation methods of the technical solution of the present application and should not be interpreted as the only limitation on the technical solution of the present application. It is known to those of ordinary skill in the art that with the evolution of the system structure and the emergence of new business scenarios, the technical solution provided by the present application is also applicable to similar technical problems.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present application. In case of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0068] The present application embodiment provides a method for detecting abnormal radial runout of a milling cutter disc, such as Figure 1 As shown, including:

[0069] S101, use a line laser sensor to orthogonally aim at the outer side of the milling cutter disk, make the milling cutter disk rotate at a constant speed for at least one circle, and obtain a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disk; wherein x, y, z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disk and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disk axis, and the Y-axis direction matches the tangent direction of the milling cutter disk rotation direction;

[0070] Among them, the line laser sensor can select a 3D line laser sensor, which can generate a laser line and measure the distance information between the laser line and the contact point of the milling cutter disc surface, thereby constructing a three-dimensional profile of the milling cutter disc.

[0071] S102, determining the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle;

[0072] Among them, although the standard point cloud data represents the standard form of the milling cutter under normal working conditions, in actual applications, it may face different working conditions and loading conditions. These different working conditions and loading conditions will affect the running stability and radial runout of the milling cutter, so the standard point cloud data also needs to be adjusted or corrected according to the actual working state of the milling cutter.

[0073] Furthermore, standard point cloud data is pre-stored and used as a reference standard for later detection of whether the cutter disc has abnormal radial runout.

[0074] S103, when the deviation exceeds the preset deviation, determining that the milling cutter disc has radial runout abnormality and abnormal point cloud coordinates;

[0075] S104: Locate the specific position of the milling cutter disc where the abnormal vibration occurs according to the abnormal point cloud coordinates.

[0076] Thus, in this application, the method can obtain high-precision point cloud data by using a line laser sensor for non-contact measurement. By comparing the real-time point cloud data with the standard point cloud data, the tiny radial runout anomaly of the milling cutter disc can be accurately identified. When the radial runout anomaly is detected, the abnormal point cloud coordinates can be quickly used to locate the specific blade or cutter disc body structure abnormal position, which provides a strong basis for subsequent maintenance and repair work and reduces troubleshooting time. In addition, the milling cutter disc can be inspected during operation without stopping or disassembling, and without manual handling, disassembly and installation of the cutter disc, which greatly saves manpower and time and improves detection efficiency.

[0077] It is worth mentioning that when selecting and using line laser sensors, the following should be noted:

[0078] Z-axis direction: The measurement accuracy of the line laser sensor in the Z-axis direction must be high enough to meet the detection requirements at the micron level. In other words, the line laser sensor needs to have extremely high resolution and sensitivity in order to accurately capture the slightest changes in the radial runout of the cutter head.

[0079] X-axis direction: The X-axis field of view of the line laser sensor should be parallel to the rotation axis of the cutter disc. In other words, the measurement direction of the line laser sensor is along the thickness direction of the cutter disc. In order to ensure that all parts of the cutter disc can be fully detected, the X-axis measurement range of the line laser sensor must not be less than the thickness of the outer side of the cutter disc.

[0080] Y-axis direction: In the process of collecting point cloud data, it is necessary to control the cutter head to rotate at a uniform speed to ensure that the point cloud data obtained by the line laser sensor is evenly distributed in the Y-axis direction.

[0081] And, when installing the line laser sensor, you should pay attention to the following three aspects:

[0082] Orthophoto or near-orthophoto alignment: Ensure that the line laser sensor is aligned with the outer side of the milling tool disc at the best angle to reduce measurement errors caused by angle deviation.

[0083] Maintain an appropriate distance: The distance between the line laser sensor and the cutterhead needs to be precisely controlled to ensure that sufficient details can be captured while avoiding inaccurate measurements caused by being too close or too far away.

[0084] Fixed installation: Line laser sensors need to be mounted securely to prevent vibration or movement during the detection process from affecting the accuracy of the measurement results.

[0085] In some implementations, after obtaining the point cloud data collection of the outer side of the milling cutter disc in step S101, the method further includes: performing noise reduction processing on the point cloud data collection.

[0086] Among them, a point cloud filtering method can be used to remove or reduce noise and outliers in the point cloud data to improve the quality and accuracy of the point cloud data.

[0087] However, in addition to the above-mentioned point cloud filtering method (filtering each point cloud data set separately), it is also possible to perform comprehensive analysis and processing on the point cloud data of multiple consecutive cycles to further reduce the impact of noise. Specifically, the joint filtering method is used to process the point cloud data of multiple cycles as a whole. If a point appears as an outlier in the point cloud data of multiple cycles, it is more likely to be noise, and the point can be removed.

[0088] Of course, in practical applications, the above two methods are only examples, and any method known to those skilled in the art for removing noise may also be used, which is not specifically limited here, so as to improve the flexibility of design.

[0089] In some implementations, the point cloud data collection includes a number of point cloud coordinates;

[0090] The point cloud coordinates are determined by the following formula:

[0091]

[0092] Among them, x t ,y t 、z t is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time t. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t;

[0093] The standard point cloud coordinates are determined by the following formula:

[0094]

[0095] Among them, x ts ,yts 、z ts is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time ts. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t.

[0096] Explain one thing, y t The coordinate value of y is calculated based on the sampling frequency α and time t t =y 0 +αt,y 0 is the sampling count value of the line laser sensor at time t = 0, usually y 0 =0, that is, y t =αt, where the sampling frequency α and the sampling interval β have the following relationship: For details, please refer to the formula (2) mentioned below. I will not repeat it here. Based on formula (2), we can deduce that y t The coordinate value of

[0097] Moreover, in the present application, the z-axis zero point of the line laser sensor is calibrated to the center of the milling cutter shaft, and the z-axis coordinates in the point cloud data collected by the line laser sensor and the object point coordinate information (see the following content for details) are r it That is to say, the z-axis coordinate z of any point cloud data collected by the line laser sensor is t , which is actually equal to r it .

[0098] In addition, usually, point cloud data and standard point cloud data have different time reference starting points, which means that the two sets of data are not strictly synchronized in time. In order to facilitate calculation and ensure data consistency, the milling cutter head can be rotated to a predetermined initial angle θ during detection. 0 , and then start timing at this angle. This ensures that all subsequent data collection starts from the same angle, eliminating the problem of different time reference starting points. 0 In the case of β and sampling interval, at the same time t, the coordinate values ​​of the point cloud data collected by the line laser sensor in the y-axis direction are the same.

[0099] In this way, by using an accurate mathematical model to calculate the position of each point, the accuracy of the point cloud data is improved. When compared with the standard point cloud data later, the specific location of the abnormal vibration of the milling cutter disc can be effectively identified, thereby improving the accuracy of the abnormal detection of the milling cutter disc.

[0100] In some implementations, determining the deviation between the point cloud data and standard point cloud data includes:

[0101] Slice and frame the point cloud data to obtain point cloud data with a length of L in the Y-axis direction as a test frame;

[0102] The test frame is aligned with a data frame of the same length in the standard point cloud data;

[0103] The coordinates of the point cloud data corresponding to the standard point cloud data are determined by the following formula:

[0104]

[0105] Determine the same (x t ,y t ) The difference in the coordinate value of the Z axis between the point cloud data and the standard point cloud data at the position;

[0106] The difference in the coordinate value of the Z axis is determined as the deviation between the point cloud data and the standard point cloud data.

[0107] One thing to note is that since the milling cutter is rotating, the point cloud data collected by the line laser sensor will show periodic changes in the y-axis direction. Therefore, it can be assumed that after each complete rotation of a cycle T, the coordinate change length of the point cloud data on the y-axis is L. Among them, T = 60 / w 0 , L = 2πr 0 ×10 3 / β.

[0108] Moreover, in the actual test process, due to the influence of noise or the accuracy of the rotary encoder, there may be a certain deviation between the coordinates of the point cloud data and the standard point cloud data. In order to improve the effect of point cloud alignment and ensure that the subsequent milling cutter diameter jump anomaly detection is more accurate, it is necessary to perform pre-processing such as filtering and denoising on the point cloud data, and use point cloud alignment algorithms such as ICP (Iterative Closest Point) to accurately align the point cloud data with the standard point cloud data.

[0109] The following example will illustrate how to determine the same (x t ,y t ) position and the difference in the Z-axis coordinate value between the point cloud data and the standard point cloud data.

[0110] For example, if the acquired point cloud data is (1, 1, 1.2) and the standard point cloud data is (1, 1, 1), then the deviation between the point cloud data and the standard point cloud data at the same position (1, 1) is: 1.2-1=0.2.

[0111] In this way, the collected point cloud data is matched and aligned with the standard point cloud data to ensure that the two are in the same coordinate system, and then the same (x t ,y t ) can clearly determine which positions on the milling cutter disc have abnormal vibrations, so that targeted maintenance can be carried out to avoid unnecessary comprehensive inspections, reduce unplanned downtime, and thus reduce maintenance costs.

[0112] In some implementations, the coordinates of the abnormal point cloud are determined by the following formula:

[0113]

[0114] Among them, z′ t The point cloud data is the same as the standard point cloud data (x t ,y t ) position, and z′ t Greater than the preset deviation, a total of n points in the X-axis direction, ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter disk, and β is the sampling spacing.

[0115] In this way, by determining the coordinates of the abnormal point cloud, it is convenient to subsequently locate the specific location of the abnormal jump on the milling cutter disc, which helps maintenance personnel to quickly find the problem and reduce the time and effort of inspecting the entire milling cutter disc.

[0116] In some implementations, the method further includes: utilizing the object point coordinate information acquired by the line laser sensor;

[0117] The object point coordinate information is determined by the following formula:

[0118]

[0119] Among them, P obj (i,θ t ,r it ) is a point in the i-th row on the outer surface of the cutter disc at time t. There are n points in the X-axis direction. i is any point among the n points. θ t P is the time point t obj (i,θ t ,r it ) angle, θ 0 is the angle between the object point and the 0° mark of the milling cutter at time t=0, ω 0 is the angular velocity of the milling cutter, r it is the radius of the i-th row detection at time t;

[0120] The method of locating the specific position of the milling cutter disc where abnormal vibration occurs according to the abnormal point cloud coordinates includes:

[0121] According to the abnormal point cloud coordinates Determine the time when the radial runout of the milling cutter occurs; where the time is determined by the following formula:

[0122]

[0123] According to the determined time of radial runout of the milling cutter, the coordinate information of the object point is used Determine the specific location P of the abnormal point obj (i,θ t ,r it ).

[0124] In this way, the abnormal time is determined by using the abnormal point cloud coordinates, and the specific position of the abnormal object point is located in combination with the object point coordinate information. After the specific position of the abnormal object point is determined, resources can be deployed more specifically for maintenance and processing, avoiding a comprehensive inspection of the milling cutter disc, saving time and resources.

[0125] In some implementations, the maximum value of the uniform rotation speed of the milling cutter disc is:

[0126]

[0127] Among them, ω max is the maximum speed of the milling cutter, β max is the maximum sampling interval, α is the sampling frequency, r 0 is the radius of the milling cutter disc.

[0128] The following will explain in detail how to determine the maximum value of the uniform rotation speed of the milling cutter disc.

[0129] Since the line laser sensor is fixedly installed near the milling cutter disc, there is no other relative movement between the line laser sensor and the cutter disc except the rotation of the cutter disc itself. The sampling frequency of the line laser sensor is α Hz, that is, α data are collected per second. At the midpoint of the outer side of the cutter disc, equidistant sampling with a spacing of β mm is generated along the tangent direction. Therefore, the following formula (1) Established.

[0130] The specific meaning of formula (1) is:

[0131] On the left side of the equal sign: The total distance (in meters) that a point on the milling cutter head moves due to rotation in a given time is calculated. This is calculated by converting the rotation speed to radians per second (using 2π / 60), multiplying by the time (in seconds), and then multiplying by the radius (in meters). This distance can be understood as the distance a point on the outer surface of the milling cutter head moves along the circumference.

[0132] On the right side of the equal sign: The total distance (in meters) that the line laser sensor can cover in the same amount of time if it moves continuously in the tangential direction is calculated. This is calculated by multiplying the sampling frequency (number of sampling points per second) by the time (seconds) to get the total number of sampling points, and then multiplying it by the sampling interval (converted to meters, use 10 -3 ), obtained. This distance can be understood as the distance that the line laser sensor can scan along the tangent direction within a given time.

[0133] According to formula (1), formula (2) can be derived

[0134] It can be seen from formula (2) that when the sampling frequency α of the line laser sensor and the radius r of the milling cutter are given 0 When the sampling interval β is related to the angular velocity ω of the cutter head 0 In other words, the sampling interval β depends only on the angular velocity ω of the cutter head. 0 Specifically, when the angular velocity of the cutter head ω 0 When increases, the sampling interval β will also increase accordingly. A larger sampling interval may cause the distance between adjacent sampling points to increase, and some small abnormal jumps may be missed, or normal fluctuations may be misjudged as abnormalities, thereby causing a large positioning error in the circumferential direction. The circular positioning error refers to the inability to accurately locate the specific position of the abnormal point in the circumferential direction.

[0135] Therefore, in order to avoid the above-mentioned problem, it is necessary to control the rotation angular velocity ω of the cutter head. 0 Do not exceed the maximum speed of the milling cutter max , according to formula (2), formula (3) can be derived

[0136] In this way, by controlling the maximum speed of the milling cutter, it is possible to ensure that the sampling interval is not too large, thereby reducing the circumferential positioning error, helping to improve the positioning accuracy of the abnormal point cloud coordinates and ensure the accuracy of abnormality detection. When the sampling interval is too large, some small abnormal jumps may be missed, or normal fluctuations may be misjudged as abnormalities. Therefore, controlling the maximum speed of the milling cutter can also reduce such misjudgments.

[0137] In order to more clearly illustrate the above method, the present application provides a specific embodiment.

[0138] In this embodiment, if Figure 2 As shown, the sampling interval of the 3D line laser sensor is β and the rotation angular velocity is ω 0 , with a radius of r 0Here, reference numeral 1 represents a milling cutter disc, reference numeral 2 represents a 3D line laser sensor of the milling cutter disc, reference numeral 3 represents point cloud data, and reference numeral 4 represents a schematic diagram of abnormality detection analysis.

[0139] Step 1: Align the 3D line laser sensor orthogonally or approximately orthogonally to the outer side of the milling cutter disc, calibrate the z-axis zero point of the 3D line laser sensor to the center of the milling cutter disc shaft, and fix the 3D line laser sensor;

[0140] Step 2: Control the milling cutter disc to rotate at a constant speed for at least one circle, and use the 3D line laser sensor to continuously scan the outer side of the cutter disc to obtain a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disc; wherein x, y, and z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively. The X-axis direction matches the axial direction of the milling cutter disc and also matches the line scan distribution direction of the line laser sensor. One line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disc axis, and the Y-axis direction matches the tangent direction of the milling cutter disc rotation direction.

[0141] In addition, the coordinates of any point cloud in the point cloud data collection are determined by the following formula:

[0142]

[0143] Among them, x t ,y t 、z t is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time t. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t.

[0144] Step 3, obtaining the pre-stored standard point cloud data, which is obtained by periodically and repeatedly scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in normal working condition, after debugging and installation, and rotates at a constant speed for at least one circle;

[0145] The standard point cloud coordinates are determined by the following formula:

[0146]

[0147] Among them, x ts ,y ts 、z ts is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time ts. There are n points in the X-axis direction. ω 0 is the angular velocity of the milling cutter, r 0is the radius of the milling cutter, β is the sampling spacing, r it is the radius of the i-th row detection at time t.

[0148] Step 4: Slice and frame the point cloud data, obtain point cloud data with a length of L in the Y-axis direction as a test frame, and align it with the data frame of the same length in the standard point cloud data to determine the same (x t ,y t ) at a position of the point cloud data and the standard point cloud data, the difference being determined as a deviation between the point cloud data and the standard point cloud data;

[0149] Step 5: When the deviation exceeds the preset deviation, it is determined that the milling cutter disc has abnormal radial runout and abnormal point cloud coordinates.

[0150] The coordinates of the abnormal point cloud are determined by the following formula:

[0151]

[0152] Among them, z′ t The point cloud data is the same as the standard point cloud data (x t ,y t ) position, and z′ t Greater than the preset deviation, a total of n points in the X-axis direction, ω 0 is the angular velocity of the milling cutter, r 0 is the radius of the milling cutter disk, and β is the sampling spacing.

[0153] Step 6: abnormal point cloud coordinates; determine the time when the radial runout of the milling cutter occurs;

[0154] The time is determined by the following formula:

[0155]

[0156] Specifically, the y in the abnormal point cloud coordinates can be t The coordinate value of is used to deduce the time t, which is the above formula.

[0157] Step seven: using the line laser sensor to obtain object point coordinate information.

[0158] The object point coordinate information is determined by the following formula:

[0159]

[0160] Among them, P obj (i,θ t ,r it) is a point in the i-th row on the outer surface of the cutter disc at time t. There are n points in the X-axis direction. i is any point among the n points. θ t P is the time point t obj (i,θ t ,r it ) angle, θ 0 is the angle between the object point and the 0° mark of the milling cutter at time t=0, ω 0 is the angular velocity of the milling cutter, r it is the radius of the i-th row detection at time t.

[0161] Step 8: According to the time t obtained in step 5 and the object point coordinate information in step 6, determine the specific position P of the abnormal object point obj (i,θ t ,r it ).

[0162] Figure 3 : is a structural schematic diagram of a milling cutter disc radial runout abnormality detection device provided in an embodiment of the present application. The present application embodiment provides a milling cutter disc radial runout abnormality detection device 300, the device comprising:

[0163] The acquisition unit 301 is used to use the line laser sensor to orthogonally align the outer side of the milling cutter disc, so that the milling cutter disc rotates at a constant speed for at least one circle, and obtain the point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disc; wherein x, y, z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disc and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disc axis, and the Y-axis direction matches the tangent direction of the milling cutter disc rotation direction;

[0164] The first determining unit 302 is used to determine the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle;

[0165] The second determination unit 303 is used to determine that the milling cutter disc has radial runout anomaly and abnormal point cloud coordinates when the deviation exceeds a preset deviation;

[0166] The positioning unit 304 is used to locate the specific position of the milling cutter disc where the abnormal jump occurs according to the abnormal point cloud coordinates.

[0167] Figure 44 is a structural schematic diagram of a milling cutter disc radial runout abnormality detection system provided in an embodiment of the present application. The present application embodiment provides a milling cutter disc radial runout abnormality detection system 400, the system comprising: a drive control module 401, a network device 402, a host computer 403, a line laser sensor 404 and a milling cutter disc 405;

[0168] The host computer is connected to the line laser sensor 404 and the drive control module 401 respectively through the network device 402, and the drive control module 401 is connected to the milling cutter disc 405;

[0169] The drive control module 401 controls the milling disc 405 to rotate at a constant speed for at least one circle, and the line laser sensor 404 is aimed directly at the outer side of the milling disc 405 to obtain a point cloud data collection of the outer side of the milling disc 405, and sends it to the host computer. The host computer is used to implement the above-mentioned method for detecting radial runout anomalies of the milling disc 405.

[0170] In some embodiments, the system also includes a power supply device 406, which is used to provide a stable power supply to the drive control module 401, the network device 402, the host computer 403, and the line laser sensor 404 to ensure that the system can operate continuously and stably and avoid system failures or data loss caused by power fluctuations or interruptions.

[0171] Specifically, the power supply device 406 may include power supply equipment such as a DC power supply and a voltage conversion module:

[0172] DC power supply: Provides stable DC voltage and current to meet the DC power requirements of different devices in the system. DC power supply usually has high voltage and current stability, which can reduce the impact of power fluctuations on device performance.

[0173] Voltage conversion module: responsible for converting the voltage output by the DC power supply into the specific voltage required by different devices in the system. Since different devices in the system may have different voltage requirements, the voltage conversion module can flexibly adjust the output voltage to meet these requirements.

[0174] In some embodiments, the drive control module 401 is responsible for driving and controlling various actuators, which may include a motor drive controller, a servo motor, a reduction transmission mechanism, etc.

[0175] In some embodiments, the network device 402 is responsible for implementing communication and data exchange between various devices within the system, and may include switches and routing devices.

[0176] It is worth noting that in the present application, the power supply system on the milling and grinding vehicle (such as a battery pack, a generator, etc.) can also be used to power the line laser sensor 404, the drive control module 401, etc., and the on-board network system on the milling and grinding vehicle, such as WIFI, Ethernet, etc., can also be used to provide the needs for instructions and data transmission between devices. Therefore, making full use of existing resources is conducive to reducing the cost of the radial runout abnormality detection system of the milling cutter disc 405.

[0177] In addition, the host computer 403 and the line laser sensor 404 are packaged into an independent, detachable module, and a special electrical interface is reserved on the body of the milling and grinding vehicle, so that when the module needs to be installed or removed, it is only necessary to simply connect or disconnect these electrical interfaces without complicated wiring or wiring work. Through the above design, a set of host computers 403 and line laser sensors 404 can be shared in multiple milling cutter disc radial runout anomaly detection systems. In other words, when different milling cutter discs need to be detected, it is only necessary to remove the module from the current position and then install it at another position that needs to be detected. In this way, there is no need to equip each milling cutter disc with a complete set of detection systems, thereby greatly reducing the system application cost.

[0178] Figure 5 900 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application. The computing device can be used as a device for detecting the abnormal radial runout of a milling cutter disc, and executes each optional embodiment of the above-mentioned abnormal radial runout detection method of the milling cutter disc. The computing device can be a terminal, or a chip or chip system inside the terminal. Figure 5 As shown, the computing device 900 includes: a processor 910 , a memory 920 , and a communication interface 930 .

[0179] It should be understood that Figure 5 The communication interface 930 in the computing device 900 shown may be used to communicate with other devices, and may specifically include one or more transceiver circuits or interface circuits.

[0180] The processor 910 may be connected to a memory 920. The memory 920 may be used to store the program code and data. Therefore, the memory 920 may be a storage unit inside the processor 910, or an external storage unit independent of the processor 910, or a component including a storage unit inside the processor 910 and an external storage unit independent of the processor 910.

[0181] Optionally, the computing device 900 may further include a bus. The memory 920 and the communication interface 930 may be connected to the processor 910 via the bus. The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 A line without an arrow is used to represent the bus, but this does not mean that there is only one bus or one type of bus.

[0182] It should be understood that in the embodiment of the present application, the processor 910 may adopt a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Alternatively, the processor 910 may adopt one or more integrated circuits to execute relevant programs to implement the technical solutions provided in the embodiment of the present application.

[0183] The memory 920 may include a read-only memory and a random access memory, and provides instructions and data to the processor 910. A portion of the processor 910 may also include a nonvolatile random access memory. For example, the processor 910 may also store information on the device type.

[0184] When the computing device 900 is running, the processor 910 executes the computer-executable instructions in the memory 920 to perform any operation step of the above method and any optional embodiment thereof.

[0185] It should be understood that the computing device 900 according to the embodiment of the present application can correspond to the corresponding subjects in the methods according to the embodiments of the present application, and the above-mentioned and other operations and / or functions of each module in the computing device 900 are respectively for implementing the corresponding processes of each method of the present embodiment. For the sake of brevity, they will not be repeated here.

[0186] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0187] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0188] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0189] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0190] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0191] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0192] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it is used to execute the above method, which includes at least one of the solutions described in the above embodiments.

[0193] The computer storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0194] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0195] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0196] Computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0197] In addition, the words "first, second, third, etc." or module A, module B, module C and other similar terms in the specification and claims are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that the specific order or sequence can be interchanged where permitted so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0198] In the above description, the numbers representing the steps, such as S110, S120, etc., do not necessarily mean that the steps will be executed accordingly. If permitted, the order of the steps can be interchanged or they can be executed simultaneously.

[0199] The term "comprising" as used in the description and claims should not be interpreted as being limited to what is listed thereafter; it does not exclude other elements or steps. Therefore, it should be interpreted as specifying the presence of the features, integers, steps or components mentioned, but does not exclude the presence or addition of one or more other features, integers, steps or components and groups thereof. Therefore, the expression "a device comprising means A and B" should not be limited to a device consisting of components A and B only.

[0200] References to "one embodiment" or "an embodiment" in this specification mean that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present application. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing in various places in this specification do not necessarily refer to the same embodiment, but may refer to the same embodiment. In addition, in one or more embodiments, the particular features, structures, or characteristics can be combined in any appropriate manner, as would be apparent to one of ordinary skill in the art from this disclosure.

[0201] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present application, all of which belong to the scope of protection of the present application.

Claims

1. A method for detecting abnormal radial runout of a milling cutter disc, characterized in that: include: A line laser sensor is used to orthogonally aim at the outer side of the milling cutter disk, so that the milling cutter disk rotates at a constant speed for at least one circle, and a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disk is obtained; wherein x, y, and z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disk and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disk axis, and the Y-axis direction matches the tangent direction of the milling cutter disk rotation direction; Determine the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle; When the deviation exceeds the preset deviation, it is determined that the milling cutter disc has abnormal radial runout and abnormal point cloud coordinates; The specific position of the milling cutter disc where the abnormal vibration occurs is located according to the abnormal point cloud coordinates.

2. The method according to claim 1, characterized in that: The point cloud data collection includes a plurality of point cloud coordinates; The point cloud coordinates are determined by the following formula: Among them, x t ,y t 、z t is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time t. There are n points in the X-axis direction. ω0 is the angular velocity of the milling cutter disk. r0 is the radius of the milling cutter disk. β is the sampling interval. it is the radius of the i-th row detection at time t; The standard point cloud coordinates are determined by the following formula: Among them, x ts ,y ts 、z ts is the coordinate value of the i-th point on the X-axis, Y-axis, and Z-axis at time ts. There are n points in the X-axis direction. ω0 is the angular velocity of the milling cutter disk. r0 is the radius of the milling cutter disk. β is the sampling interval. it is the radius of the i-th row detection at time t.

3. The method according to claim 1, characterized in that Determining the deviation between the point cloud data and standard point cloud data includes: Slice and frame the point cloud data to obtain point cloud data with a length of L in the Y-axis direction as a test frame; The test frame is aligned with a data frame of the same length in the standard point cloud data; The coordinates of the point cloud data corresponding to the standard point cloud data are determined by the following formula: Determine the same (x t ,y t ) The difference in the coordinate value of the Z axis between the point cloud data and the standard point cloud data at the position; The difference in the coordinate value of the Z axis is determined as the deviation between the point cloud data and the standard point cloud data.

4. The method according to claim 1, characterized in that The coordinates of the abnormal point cloud are determined by the following formula: Among them, z′ t The point cloud data is the same as the standard point cloud data (x t ,y t ) position, and z′ t Greater than the preset deviation, there are n points in the X-axis direction, ω0 is the angular velocity of the milling cutter disk, r0 is the radius of the milling cutter disk, and β is the sampling interval.

5. The method according to claim 1, characterized in that It also includes: object point coordinate information obtained by using the line laser sensor; The object point coordinate information is determined by the following formula: Among them, P obj (i,θ t ,r it ) is a point in the i-th row on the outer surface of the cutter disc at time t. There are n points in the X-axis direction. i is any point among the n points. θ t P is the time point t obj (i,θ t ,r it ), θ0 is the angle of the object point relative to the 0° mark of the milling cutter at time t = 0, ω0 is the angular velocity of the milling cutter, r it is the radius of the i-th row detection at time t; The method of locating the specific position of the milling cutter disc where abnormal vibration occurs according to the abnormal point cloud coordinates includes: According to the abnormal point cloud coordinates Determine the time when the radial runout of the milling cutter occurs; where the time is determined by the following formula: According to the determined time of radial runout of the milling cutter, the coordinate information of the object point is used Determine the specific location P of the abnormal point obj (i,θ t ,r it ).

6. The method according to claim 1, characterized in that The maximum value of the uniform rotation speed of the milling cutter disc is: Among them, ω max is the maximum speed of the milling cutter, β max is the maximum sampling interval, α is the sampling frequency, and r0 is the radius of the milling cutter.

7. A device for detecting abnormal radial runout of a milling cutter disc, characterized in that: include: An acquisition unit is used to use a line laser sensor to orthogonally align the outer side of the milling cutter disc, so that the milling cutter disc rotates at a constant speed for at least one circle, and obtain a point cloud data collection P{Pi(x, y, z), i=0~n-1} of the outer side of the milling cutter disc; wherein x, y, and z are the coordinate values ​​of the i-th point relative to the X-axis, Y-axis, and Z-axis of the line laser sensor, respectively, wherein the X-axis direction matches the axial direction of the milling cutter disc and also matches the line scan distribution direction of the line laser sensor, and a line scan collects n points, the Z-axis direction is opposite to and perpendicular to the milling cutter disc axis, and the Y-axis direction matches the tangent direction of the milling cutter disc rotation direction; The first determination unit is used to determine the deviation between the point cloud data and the standard point cloud data; the standard point cloud data is point cloud data with periodic repetition characteristics obtained by scanning the outer side of the milling cutter disc using a line laser sensor when the milling cutter disc is in a normal working state and rotates at a constant speed for at least one circle; A second determination unit is used to determine that the milling cutter disc has radial runout anomaly and abnormal point cloud coordinates when the deviation exceeds a preset deviation; The positioning unit is used to locate the specific position of the milling cutter disc where abnormal vibration occurs according to the abnormal point cloud coordinates.

8. A milling cutter disc radial runout abnormality detection system, characterized in that: include: Drive control module, network equipment, host computer, line laser sensor and milling cutter head; The host computer is connected to the line laser sensor and the drive control module respectively through the network device, and the drive control module is connected to the milling cutter disc; The drive control module controls the milling cutter disc to rotate at a constant speed for at least one circle, and the line laser sensor is aimed directly at the outer side of the milling cutter disc to obtain a point cloud data collection of the outer side of the milling cutter disc, and sends it to the host computer. The host computer is used to implement the method described in any one of claims 1 to 6 above.

9. A computing device, characterized in that include: processor, and a memory having program instructions stored thereon, wherein when the program instructions are executed by the processor, the processor is caused to execute the method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: Program instructions are stored thereon, and when the program instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 6.

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