A method for measuring a sealing surface of a triple offset butterfly valve

Abstract

The application discloses a kind of three eccentric butterfly valve sealing surface measurement methods, it is related to high-precision industrial measurement technical field, the application is by constructing a virtual reference torus identical with design, and using coordinate transformation, the point cloud data of valve plate sealing surface obtained by actual scanning is accurately mapped to the coordinate system of the reference torus, accurately reproduces the cooperation relationship of theoretical valve plate and valve seat, by calculating the normal distance of each actual data point relative to virtual reference torus, generate clearance distribution dataset, the negative value area in this clearance field represents the theoretical interference contact area, by analyzing the clearance field, the application does not need to carry out physical dynamic assembly and pressure test, can in computer inside pre-quantification the potential state of valve plate and valve seat contact, the dynamic wedging process in physical world is converted into static clearance calculation in digital space, to realize the prior, non-destructive prediction of sealing performance.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of high-precision industrial measurement, in particular to a kind of three eccentric butterfly valve sealing surface measurement method. BACKGROUND

[0002] Three eccentric butterfly valve as the core component in modern fluid control field, its core technical advantage is through the unique geometric design of axial, radial and conical angle eccentric, realize the zero friction separation of valve plate and valve seat in the process of opening and closing, and in the closed final state through wedge tight effect form metal to metal forced sealing, this design shows excellent sealing performance and long life in harsh conditions such as high temperature and high pressure, however, it is this complex spatial geometric relationship, the machining precision and matching quality of its valve plate and valve body sealing surface, become the most key factor to determine the performance and reliability of valve.

[0003] In the prior art, the measurement of the sealing surface of the three eccentric butterfly valve mainly relies on three coordinate measuring machines or special templates to detect the size and geometric tolerance of discrete points. These methods measure the valve plate or valve body separately in a static state, and cannot simulate and reflect the dynamic sealing state of the valve plate in the real closing process along its complex spatial trajectory and finally wedging with the valve seat. Moreover, they cannot accurately capture and quantify the micro-gap distribution on the entire sealing ring. It is these micro-gaps that determine the effectiveness of the seal, ultimately making the correspondence between the test results and the final performance ambiguous.

[0004] Therefore, it is of great significance to develop a comprehensive measurement method that can accurately represent the actual contact state of the sealing surface of the three eccentric butterfly valve under simulated conditions and quantify it into intuitive and reliable performance indicators for realizing quality control, process optimization and reliability guarantee of such valve manufacturing. SUMMARY

[0005] The purpose of the present application is to overcome the shortcomings of the prior art and provide a three eccentric butterfly valve sealing surface measurement method. It can construct a virtual reference ring surface that is identical to the design, and accurately map the point cloud data of the valve plate sealing surface obtained by actual scanning to the coordinate system of the reference ring surface using coordinate transformation. It can accurately reproduce the theoretical matching relationship between the valve plate and the valve seat. It can generate a gap distribution dataset by calculating the normal distance of each actual data point relative to the virtual reference ring surface. The negative value area in this gap field represents the theoretical interference contact area. Through analysis of the gap field, the present application can pre-quantify the potential state of valve plate and valve seat contact in the computer without physical dynamic assembly and pressure test. It can convert the dynamic wedging process in the physical world into static gap calculation based on accurate geometric model in digital space, thereby realizing the prior and non-destructive prediction of sealing performance.

[0006] The application provides the following technical scheme to solve the above technical problems: a kind of three eccentric butterfly valve sealing surface measurement method, the specific steps of this method are as follows:

[0007] S100, according to the design parameters of three eccentric butterfly valve, a virtual reference torus conforming to the theoretical valve plate sealing surface is constructed in computer as a reference for subsequent data comparison;

[0008] S200, the actual valve plate sealing surface is scanned using a non-contact three-dimensional measuring device, and a point cloud data set representing its three-dimensional topography is obtained;

[0009] S300, the point cloud data set is mapped to the coordinate system of the virtual reference torus through coordinate transformation algorithm, and the normal distance of each data point to the reference torus is calculated , the set of normal distances is taken as the gap distribution data set;

[0010] S400, based on the preset effective sealing threshold , all data points with normal distance are selected from the sealing gap distribution data set, and the three-dimensional space region represented by these data points is fitted as an actual contact sealing ring belt;

[0011] S500, based on the fitted actual contact sealing ring belt, the quantitative parameters for evaluating its sealing performance are calculated, and the quantitative parameters include the continuity of the actual contact sealing ring belt and the maximum local gap value.

[0012] Further, in S100, the design parameters include the axial eccentricity, the radial eccentricity, the angular eccentricity, the nominal diameter of the sealing surface and the sealing ring belt width of the three eccentric butterfly valve;

[0013] The geometric parameters of the virtual reference torus correspond one by one to the design parameters.

[0014] Further, the specific steps of obtaining the point cloud data set in S200 include:

[0015] Scan planning and system calibration: according to the size of the valve plate and the spatial posture of the sealing surface, the moving path of the three-dimensional scanner is planned to ensure that the entire sealing surface area can be covered without collision and dead angle, and the precision of the three-dimensional scanner is calibrated using standard blocks to ensure that the measurement error within the calibration period is less than the allowable tolerance;

[0016] Control the three-dimensional scanner to scan the valve plate sealing surface along the planned path, multiple views to fully cover the sealing surface, emit measurement beams and receive reflected signals, directly obtain the three-dimensional coordinates on the sealing surface, and form multi-view point clouds;

[0017] By identifying common localization target points in point clouds from different perspectives, calculating coordinate transformation matrices, and aligning and merging all multi-view point clouds into a point cloud dataset under a unified coordinate system;

[0018] The point cloud dataset is filtered to identify and remove abnormal noise points caused by measurement noise.

[0019] Furthermore, in S300, the coordinate transformation algorithm includes rigid transformation and eccentricity compensation transformation:

[0020] Rigid transformations are used to translate and rotate the coordinate system of a point cloud dataset to align it with the coordinate system of a virtual reference toroidal surface.

[0021] Eccentricity compensation transformation is used to correct spatial position deviations caused by triple eccentricity structures. A transformation matrix is ​​established based on the axial eccentricity, radial eccentricity, and angular eccentricity angle in the design parameters, and the point cloud data after rigid transformation is calibrated a second time.

[0022] Furthermore, in S300, the calculation process for the normal distance is as follows:

[0023] S301. In a computer, the virtual reference torus is represented as a parametric surface: ,in For parameters on the surface The three-dimensional coordinate vector of the point. The circumferential parameter of the toroidal surface characterizes the position of the sealing surface along the circumferential direction. The radial parameter of the toroidal surface characterizes the radial position of the sealing surface. , , Points The X, Y, and Z coordinates in a three-dimensional coordinate system;

[0024] S302. For any point in the point cloud dataset To find its position on the virtual reference toroidal surface Projection point on The parameters corresponding to this projection point are Minimize the point through numerical optimization algorithm To the surface Square distance to any point on Solving for the parameters that minimize the squared distance yields the solution. This parameter corresponds to the projection point. ;

[0025] S303, Calculate the virtual reference torus at the projection point Normal vector at point ,in:

[0026] along Tangent vector of parameter direction , indicating the tangent direction of the curved surface at along the ring direction;

[0027] Along Tangent vector of parameter direction , indicating the tangent direction of the curved surface at along the radial direction;

[0028] Normal vector is calculated by the cross product of two tangent vectors, that is: , the direction of which is perpendicular to the tangent plane of the virtual reference torus at , and the unitization processing is performed on to obtain the unit normal vector ;

[0029] S304, the normal distance of point to the virtual reference torus is obtained by performing dot product operation between the vector pointing from to and the unit normal vector at the projection point: , the distance is a scalar, and its positive or negative indicates that the point is located on the positive side or the negative side of the normal vector;

[0030] S305, traverse all points in the point cloud data set, repeat S302 to S304 to obtain the normal distance of each point, and form a gap distribution data set.

[0031] Further, in S400, the specific process of fitting the actual contact sealing ring band from the gap distribution data set includes:

[0032] Traverse the gap distribution data set, compare the normal distance of each data point with , when , mark the point as an effective sealing point, and when , mark it as a non-sealing point;

[0033] Perform three-dimensional spatial clustering analysis on all the obtained effective sealing points, and merge the effective sealing points densely distributed in the space into the same cluster, and each cluster represents an effective sealing area;

[0034] Among the multiple clusters obtained by clustering, select the cluster containing the largest number of data points as the main sealing ring band candidate cluster;

[0035] For all the effective sealing points in the screened main sealing ring band candidate cluster, a continuous spatial curved surface is fitted by using a moving least square method, and the curved surface is an actual contact sealing ring band.

[0036] Further, in S500, the continuity of the actual contact sealing ring band is quantified by a ring direction continuity rate The sealing surface is equally divided into 360 sampling segments along the ring direction of the virtual reference ring surface, each sampling segment corresponds to 1 degree of central angle, the effective coverage length of the actual contact sealing ring band in each sampling segment is counted The effective coverage length is the continuous arc length of the normal distance in the sampling segment, and the ring direction continuity rate is calculated as follows: Wherein, is the total length of the ring direction of the virtual reference ring surface.

[0037] Further, in S500, the maximum local gap value of the actual contact sealing ring band is represented by a maximum local gap, from the gap distribution data set corresponding to the actual contact sealing ring band, the absolute value of the normal distance is extracted, 3 rules are used to eliminate outliers, the average value mu and the standard deviation sigma of all are calculated, the data points are eliminated , and the maximum value in the remaining data points is the maximum local gap value .

[0038] Compared with the prior art, the three eccentric butterfly valve sealing surface measurement method has the following beneficial effects:

[0039] The present application constructs a virtual reference ring surface completely consistent with the design, and accurately maps the valve plate sealing surface point cloud data obtained by actual scanning to the coordinate system of the reference ring surface by using coordinate transformation, accurately reproduces the theoretical cooperation relationship between the valve plate and the valve seat, generates a gap distribution data set by calculating the normal distance of each actual data point relative to the virtual reference ring surface, and the negative value area in the gap field represents the theoretical interference contact area. Through the analysis of the gap field, the present application can pre-quantify the potential state of the valve plate and the valve seat contact in the computer without physical dynamic assembly and pressure test, and converts the dynamic wedging process in the physical world into static gap calculation based on the accurate geometric model in the digital space, thereby realizing the prior and non-destructive prediction of the sealing performance.

[0040] Other advantages, objects, and features of the present application will be in part apparent and in part pointed out hereinafter in the specification, and it is to be understood that various changes can be made therein without departing from the scope of the present application, and that it can adapt to various working conditions and environments. BRIEF DESCRIPTION OF DRAWINGS

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0042] Figure 1 A flowchart illustrating a method for measuring the sealing surface of a triple eccentric butterfly valve;

[0043] Figure 2 This is a flowchart illustrating the steps of a method for measuring the sealing surface of a triple eccentric butterfly valve. Detailed Implementation

[0044] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0045] Example 1: This example provides a method for measuring the sealing surface of a triple eccentric butterfly valve, such as... Figure 2 As shown, this method achieves accurate characterization of the contact state of the sealing surface of a triple-eccentric butterfly valve and quantitative evaluation of its sealing performance through the following steps: S100 constructing a virtual reference toroidal surface, S200 scanning to obtain point cloud data of the actual valve plate sealing surface, S300 coordinate transformation and gap calculation, S400 fitting the actual contact sealing ring, and S500 quantifying the sealing performance parameters. This method eliminates the need for physical dynamic assembly and pressure testing, transforming the dynamic wedging process into static gap calculation in digital space. It can predict sealing performance a priori and non-destructively, solving the problem that existing technologies cannot reflect the dynamic sealing state and quantify the microscopic gap distribution. This provides reliable technical support for valve manufacturing quality control and process optimization.

[0046] Virtual reference toroidal construction phase (S100)

[0047] Before measuring the sealing surface of the triple eccentric butterfly valve, a virtual reference torus completely conforming to the theoretical valve plate sealing surface is established as a reference standard for subsequent comparison of actual measurement data. This process is based on the design parameters of the triple eccentric butterfly valve, and the geometric shape of the theoretical sealing surface is accurately reproduced in the computer three-dimensional modeling environment. The design parameters of the triple eccentric butterfly valve are the key basis for constructing the virtual reference torus, including the axial eccentricity, the radial eccentricity, the angular eccentricity, the nominal diameter of the sealing surface, and the sealing ring width. The axial eccentricity refers to the offset distance of the valve plate rotation axis and the valve body center line in the axial direction. The radial eccentricity is the offset distance of the valve plate rotation axis and the valve body center line in the radial direction. The angular eccentricity is the angle between the valve plate sealing surface conical generatrix and the valve plate rotation axis. These three eccentric parameters together constitute the core structural characteristics of the triple eccentric butterfly valve, which determines the spatial motion trajectory of the valve plate during opening and closing. The nominal diameter of the sealing surface defines the overall size range of the sealing surface, and the sealing ring width determines the effective area width of the sealing function. The geometric parameters of the virtual reference torus correspond one-to-one with the above design parameters. When constructing the torus in the computer, a virtual reference torus completely consistent with the theoretical valve plate sealing surface is generated through three-dimensional modeling, laying a precise geometric reference foundation for subsequent comparison of actual measurement data.

[0048] Actual valve plate sealing surface point cloud data acquisition stage (S200)

[0049] After completing the construction of the virtual reference torus, a non-contact three-dimensional measurement device is used to scan the actual valve plate sealing surface to obtain a point cloud dataset that can represent its three-dimensional topography. This process involves four key steps: scanning planning and system calibration, multi-angle scanning, point cloud alignment and merging, and filtering processing, to ensure the integrity, accuracy, and effectiveness of the point cloud data.

[0050] According to the size of the actual valve plate and the spatial pose of the sealing surface, the movement path of the three-dimensional scanner is planned.

[0051] After completing the scanning planning, the three-dimensional scanner is controlled to scan the valve plate sealing surface along the preset planning path. During the scanning process, the scanner emits a measurement beam, which reflects after being incident on the sealing surface. The scanner receives the reflected signal and calculates the three-dimensional coordinates of each point on the sealing surface based on the propagation time and phase change of the beam. Each view of the scanning generates corresponding point cloud data, i.e., multi-angle point cloud.

[0052] In order to integrate the point cloud data obtained from multiple perspectives into a unified coordinate system, the point cloud alignment is realized by identifying the common positioning target points in the point clouds of different perspectives, the coordinate transformation matrix capable of converting the point clouds of each perspective into the same coordinate system is calculated by extracting the three-dimensional coordinates of the positioning target points in the point clouds of different perspectives, the point cloud data of each perspective is transformed according to the corresponding coordinate transformation matrix, so that all the point cloud data is in a unified coordinate system, then the transformed multi-perspective point clouds are merged to form a complete point cloud data set covering the entire sealing surface.

[0053] According to the spatial distribution characteristics of the point cloud data, the distance between adjacent points and other information, abnormal noise points with large differences from normal point cloud data are identified and removed, and finally a pure and effective point cloud data set is obtained, which provides a reliable data basis for subsequent coordinate transformation and gap calculation.

[0054] Coordinate transformation and gap calculation stage (S300)

[0055] After obtaining the effective point cloud data set, it is mapped to the coordinate system of the virtual reference ring surface through a coordinate transformation algorithm, so that they are in the same spatial reference system, and then the normal distance of each data point to the reference ring surface is calculated to form a gap distribution data set. The coordinate transformation algorithm includes rigid transformation and eccentricity compensation transformation, which work together to realize the accurate alignment of the point cloud data set and the virtual reference ring surface coordinate system. The rigid transformation is to align the coordinate system of the point cloud data set and the coordinate system of the virtual reference ring surface through translation and rotation. Since the point cloud data is obtained in the actual measurement coordinate system, while the virtual reference ring surface exists in the computer preset coordinate system, the coordinate system origins and coordinate axis directions of the two may be different. Through the rigid transformation, the translation vector and the rotation matrix are calculated according to the positional relationship between the two coordinate systems. The point cloud data is translated along the translation vector, so that the coordinate system origin of the point cloud data set coincides with the coordinate system origin of the virtual reference ring surface. Then, the point cloud data is rotated according to the rotation matrix, so that the coordinate axis of the point cloud data set is consistent with the direction of the coordinate axis of the virtual reference ring surface, preliminarily realizing the alignment of the coordinate systems of the two. The eccentricity compensation transformation is because the three-eccentric butterfly valve has the structural characteristics of axial, radial and angular eccentricity. Therefore, it is difficult to completely eliminate the spatial position deviation between the actual point cloud data and the virtual reference ring surface caused by the eccentric structure only through the rigid transformation. Therefore, a special transformation matrix is established based on the axial eccentricity, radial eccentricity and angular eccentricity in the design parameters to perform secondary calibration on the point cloud data after rigid transformation. The transformation matrix can simulate the influence of the three-eccentric structure on the spatial position of the valve plate sealing surface. Through the corresponding coordinate adjustment of the point cloud data after rigid transformation, the positional deviation caused by the eccentric structure is accurately compensated, so that the point cloud data and the virtual reference ring surface are highly matched in spatial position, laying a foundation for the accurate calculation of the normal distance. After completing the coordinate transformation, the normal distance of each point in the point cloud data set to the virtual reference ring surface is calculated, and the specific process is as follows:

[0056] Parametric representation of virtual reference ring surface (S301): In the computer, the virtual reference ring surface is represented as a parametric surface form: , wherein is the three-dimensional coordinate vector of the point on the surface with the parameter is the circumferential parameter of the ring surface, representing the position of the sealing surface along the circumference, is the radial parameter of the ring surface, representing the position of the sealing surface along the radial direction, , , , are the X, Y and Z axis coordinates of the point in the three-dimensional coordinate system, respectively.

[0057] Finding the projection point (S302): for any point in the point cloud data set , it is necessary to find its projection point on the virtual reference ring surface the projection point on the virtual reference torus , which is the foot point of point P in the normal direction of the virtual reference torus, for determining the projection point the corresponding parameters , a numerical optimization algorithm is adopted to take the square of the distance of point P to any point on the surface as the objective function, and the values of parameters and are constantly adjusted through iterative calculation, so that the objective function reaches a minimum value, at which time the corresponding parameters are the parameters of the projection point on the virtual reference torus, and further, the three-dimensional coordinates of the projection point can be obtained according to the expression of .

[0058] Calculating the normal vector (S303): To calculate the normal distance of point P to the virtual reference torus, the normal vector of the virtual reference torus at the projection point needs to be determined first. First, the tangent vector in the direction of parameter is calculated, which represents the tangent direction of the surface in the circumferential direction at and reflects the circumferential variation trend of the torus; then the tangent vector in the direction of parameter is calculated, which represents the tangent direction of the surface in the radial direction at and reflects the radial variation trend of the torus. The normal vector N of the virtual reference torus at is calculated by the cross product of the two tangent vectors, i.e. , which is perpendicular to the tangent plane of the virtual reference torus at . For the convenience of subsequent calculation, the normal vector N needs to be unitized to obtain the unit normal vector , whose module length is 1 and only represents the direction.

[0059] Calculating the normal distance (S304): The normal distance of point P to the virtual reference torus is obtained by the dot product operation of the vector from the projection point S0 to point P and the unit normal vector n at the projection point, and the calculation formula is . The distance d is a scalar, and its positive and negative have specific physical meanings. If d is positive, it means that point P is located on the positive side of the unit normal vector n; if d is negative, it means that point P is located on the negative side of the unit normal vector n, and the negative value area usually corresponds to the theoretical interference contact area.

[0060] ​Data aggregation (S305): According to the above steps, all points in the point cloud dataset are traversed, and the operations of S302 to S304 are repeated to calculate the normal distance of each point. All normal distances are aggregated to form a gap distribution dataset.

[0061] Actual contact sealing ring band fitting stage (S400)

[0062] Based on the preset effective sealing threshold From the gap distribution dataset, data points that meet the effective sealing condition are selected, and through clustering analysis and surface fitting, the actual contact sealing ring band is obtained. The ring band can truly reflect the actual contact area of the valve plate sealing surface in the theoretical matching state. When the normal distance of the point cloud data point to the virtual reference ring surface is , the point can theoretically participate in the sealing effect and is marked as an effective sealing point; when , the point cannot meet the sealing requirement and is marked as a non-sealing point. By comparing the normal distance of each data point in the gap distribution dataset with , the classification and marking of effective sealing points and non-sealing points are completed, and data points with sealing potential are preliminarily selected. Due to local defects, processing errors, etc. in the actual processing process, the effective sealing points selected may not be continuous and integral in spatial distribution, but may present scattered areas. Therefore, three-dimensional spatial clustering analysis is performed on all effective sealing points, and according to the spatial distance and distribution density between effective sealing points, the effective sealing points that are densely distributed and adjacent to each other in space are merged into the same cluster. Each cluster represents a potential effective sealing area. Through clustering analysis, different sealing areas can be clearly distinguished, and the interference of isolated and scattered invalid sealing points on subsequent analysis is excluded. In the multiple clusters obtained by clustering, the number of effective sealing points contained in different clusters differs. The cluster containing the most data points is usually the main sealing area of the sealing surface, which plays a leading role in the overall sealing performance of the valve. Therefore, the cluster containing the most data points is selected as the main sealing ring band candidate cluster. The candidate cluster can concentrate the main sealing characteristics of the sealing surface. For all effective sealing points in the selected main sealing ring band candidate cluster, a moving least squares method is used for surface fitting. The moving least squares method establishes a local approximation function around each data point, and according to the size of the weight of the data point, the data points in the local area are fitted and calculated. The method can effectively handle the discreteness and local fluctuations of the data points. A continuous and smooth spatial surface is fitted, which is the actual contact sealing ring band, accurately reflecting the actual contact area form of the valve plate sealing surface in the theoretical matching state.

[0063] Sealing performance quantitative evaluation stage (S500)

[0064] Based on the fitted actual contact sealing ring belt, quantitative parameters for evaluating the sealing performance thereof are calculated, mainly including continuity of the actual contact sealing ring belt and maximum local gap value, and through the two parameters, the sealing performance of the sealing surface can be intuitively and accurately judged, wherein the continuity of the sealing ring belt is quantified by calculating a ring-wise continuity rate C, the sealing surface is equally divided into 360 sampling segments along a ring-wise direction of the virtual reference ring surface, each sampling segment corresponds to a 1° central angle, so as to ensure that the circumferential range of the sealing surface can be fully covered, for each sampling segment, the effective coverage length of the actual contact sealing ring belt in the sampling segment is counted , the effective coverage length is a continuous arc length of the normal distance in the sampling segment, if there is no actual contact sealing ring belt coverage in the sampling segment, then =0. According to a formula , a ring-wise continuity rate C is calculated, wherein is a total ring-wise length of the virtual reference ring surface, i.e. the development length of the virtual reference ring surface along the circumference, the larger the value of the ring-wise continuity rate C is, the better the continuity of the actual contact sealing ring belt in the circumferential direction is, and the more stable the sealing performance is; on the contrary, the smaller C is, the more discontinuous regions exist in the sealing ring belt, and the sealing performance has hidden dangers; for the maximum local gap value, it directly reflects the gap size of the local region in the actual contact sealing ring belt, if the local gap is too large, it may lead to medium leakage through the gap, affecting the sealing effect, from the gap distribution data set corresponding to the actual contact sealing ring belt, the absolute value of the normal distance of all effective sealing points is extracted , since there may be abnormal values in the data set due to measurement errors and other factors, these abnormal values will affect the accuracy of the calculation of the maximum local gap value, therefore, the 3σ rule is adopted to eliminate abnormal values, first, the average value μ and the standard deviation σ of all are calculated, the average value μ reflects the average level of the absolute value of the normal distance of all effective sealing points, and the standard deviation σ reflects the dispersion degree of the data, according to the 3σ rule, the data points with > μ+3σ are eliminated, these data points are considered as abnormal values and do not participate in the subsequent calculation of the maximum local gap value, among the remaining data points, the maximum value of the absolute value of the normal distance is selected, i.e. the maximum local gap value , the smaller the maximum local gap value G is, the smaller the local gap in the actual contact sealing ring belt is, and the better the sealing performance is; if G exceeds the allowable gap range, it indicates that there is a risk of local sealing failure of the sealing surface.

[0065] In summary, through the complete process of S100 to S500, the embodiment realizes the precise measurement and sealing performance evaluation of the sealing surface of the triple-eccentric butterfly valve. The entire method does not require physical dynamic assembly and pressure testing, converts the dynamic sealing process of the triple-eccentric butterfly valve into a static calculation in the digital space, can predict the sealing performance a priori and non-destructively, effectively solves the deficiencies of the prior art, and provides a feasible technical solution for manufacturing quality control, process optimization and reliability guarantee of the triple-eccentric butterfly valve.

[0066] Embodiment Two: Based on Embodiment One, the embodiment provides a specific step of a measuring method for a sealing surface of a triple-eccentric butterfly valve, as shown in the following table: Figure 1

[0067] (1) Construct a virtual reference torus

[0068] Obtain the design parameters of the triple-eccentric butterfly valve, including the axial eccentricity, the radial eccentricity, the angular eccentricity, the nominal diameter of the sealing surface, and the sealing ring width;

[0069] Construct a virtual reference torus in the computer based on the above parameters, which is completely consistent with the theoretical valve plate sealing surface;

[0070] Take the virtual reference torus as the reference model for subsequent data comparison and analysis.

[0071] (2) Obtain the point cloud data set of the actual valve plate sealing surface

[0072] According to the size of the valve plate and the spatial posture of the sealing surface, plan the scanning path of the three-dimensional scanner;

[0073] Calibrate the accuracy of the three-dimensional scanner using standard blocks;

[0074] Control the scanner to scan the valve plate sealing surface from multiple angles along the planned path;

[0075] Obtain point cloud data from multiple angles, and perform coordinate alignment and merging through positioning target points;

[0076] Filter the merged point cloud data set to remove abnormal noise points.

[0077] (3) Calculate the normal distance from the point cloud to the virtual reference torus

[0078] Preliminarily align the point cloud data set with the virtual reference torus coordinate system through rigid transformation;

[0079] Perform eccentricity compensation transformation based on the triple-eccentric parameters to further calibrate the position of the point cloud;

[0080] For each point in the point cloud, find its nearest projection point on the virtual reference torus;​

[0081] Calculate the distance of each point to the normal direction at the projection point to form a gap distribution dataset;

[0082] Record the normal distance value of each point and its positive and negative direction.

[0083] (4) Fit the actual contact sealing ring belt

[0084] Set the effective sealing threshold value;

[0085] Traverse the gap distribution dataset and filter out all points with normal distance less than or equal to the threshold value;

[0086] Perform three-dimensional spatial clustering analysis on the filtered points to identify the main sealing area;

[0087] Select the cluster with the most data points as the main sealing ring belt;

[0088] Use the moving least squares method to fit the main sealing ring belt into a continuous spatial surface.

[0089] (5) Calculate the sealing performance quantification parameter

[0090] Continuity analysis:

[0091] Divide the sealing ring belt into 360 sampling segments along the circumferential direction;

[0092] Statistical arc length of the effective sealing area in each sampling segment;

[0093] Calculate the ring-wise continuity rate to evaluate the completeness of the sealing ring belt.

[0094] Maximum local gap analysis:

[0095] Extract the absolute value of the normal distance from the gap data corresponding to the actual contact sealing ring belt;

[0096] Use the 3σ criterion to remove outliers;

[0097] Determine the maximum value in the remaining data as the maximum local gap value.

[0098] The above is only the preferred embodiment of the present application, not any form of limitation on the present application, although the present application has been disclosed as above with the preferred embodiment, however, it is not intended to limit the present application, any person skilled in the art, without departing from the scope of the present application technical solution, can make some changes or modifications to the above disclosed technical content as equivalent embodiments, but as long as it does not deviate from the technical solution content of the present application, according to the technical essence of the present application, any modification, equivalent change and modification of the above embodiments, all still belong to the scope of the present application technical solution.

Claims

1. A method of measuring a sealing surface of a triple offset butterfly valve, characterized in that, The specific steps of the method are: S100, according to the design parameters of the triple eccentric butterfly valve, a virtual reference torus conforming to the theoretical valve plate sealing surface is constructed in the computer as a reference for subsequent data comparison; S200, using a non-contact three-dimensional measurement device to scan the actual valve plate sealing surface to obtain a point cloud data set representing its three-dimensional topography; S300, mapping the point cloud dataset to the coordinate system of the virtual reference annulus by a coordinate transformation algorithm, calculating the normal distance of each data point to the reference annulus , the set of normal distances as a gap distribution dataset; In S300, the calculation process of the normal distance is: S301、In the computer, the virtual reference torus is expressed as a parameter surface form: wherein is a three-dimensional coordinate vector of a point on the surface with parameters , is a circumferential parameter of the torus, representing the position of the sealing surface along the circumference, is a radial parameter of the torus, representing the position of the sealing surface along the radial direction, , , are X, Y, Z axis coordinates of the point in the three-dimensional coordinate system; S302、For any point in the point cloud dataset , find its projection point on the virtual reference torus , the parameter corresponding to the projection point , minimize the square of the distance from the point to any point on the curved surface by numerical optimization algorithm , solve the parameter that makes the distance square minimum , which corresponds to the projection point ;​ S303、Calculate the normal vector of the virtual reference ring surface at the projection point wherein:​ along a tangent vector of the parameter direction , indicating the tangent direction of the surface at along the ring direction; along a tangent vector of the parameter direction , indicating the tangent direction of the surface at along the radial direction; Normal vector The normal vector is calculated by the cross product of two tangent vectors, i.e. The direction of the normal vector is perpendicular to the tangent plane of the virtual reference annulus at The unit normal vector is obtained by unitizing ; S304, point normal distance to the virtual reference ring surface , by vector pointing to P unit normal vector at the projection point dot product operation is performed to obtain: ; S305, traverse all points in the point cloud data set, repeat S302 to S304 to obtain the normal distance of each point, and form the gap distribution data set S400, based on a preset effective sealing threshold Normal distances are filtered from the gap distribution dataset. All data points are used to fit the three-dimensional spatial region represented by these data points into the actual contact sealing ring. S500, based on the fitted actual contact sealing ring, calculate the quantitative parameters for evaluating its sealing performance, including the continuity of the actual contact sealing ring and the maximum local gap value.

2. The method of measuring a seal face of a triple offset butterfly valve of claim 1, wherein, In S100, the design parameters include the axial eccentricity, radial eccentricity, angular eccentricity, nominal diameter of the sealing surface and sealing ring width of the triple eccentric butterfly valve. The geometric parameters of the virtual reference torus correspond one by one to the design parameters.

3. The method of claim 1, wherein the method further comprises: The specific steps of obtaining the point cloud data set in S200 include: Scan planning and system calibration: according to the size of the valve plate and the spatial pose of the sealing surface, plan the moving path of the three-dimensional scanner; Control the three-dimensional scanner to scan the valve plate sealing surface along the planned path, fully cover the sealing surface from multiple perspectives, emit measurement light beams and receive reflected signals, directly obtain three-dimensional coordinates on the sealing surface, and form multi-perspective point clouds; By identifying the positioning target points common in different perspective point clouds, calculate the coordinate transformation matrix, align and merge all multi-perspective point clouds into a point cloud data set in a unified coordinate system; Filter the point cloud data set to identify and remove abnormal noise points caused by measurement noise.

4. The method of claim 1, wherein the method further comprises: In S300, the coordinate transformation algorithm includes rigid transformation and eccentric compensation transformation: The rigid transformation is used to align the coordinate system of the point cloud data set with the coordinate system of the virtual reference torus through translation and rotation; The eccentric compensation transformation is used to correct the spatial position deviation caused by the triple eccentric structure, and a transformation matrix is established based on the axial eccentricity, radial eccentricity and angular eccentricity in the design parameters to perform secondary calibration on the point cloud data after rigid transformation.

5. The method of measuring a seal face of a triple offset butterfly valve of claim 1, wherein, In S400, the specific process of fitting the actual contact sealing ring from the gap distribution data set includes: traversing the gap distribution dataset, the normal distance of each data point is compared to the maximum normal distance of the dataset with when the point is marked as a valid seal point, when it is marked as a non-seal point; Perform three-dimensional spatial clustering analysis on all valid sealing points obtained, merge the valid sealing points densely distributed in space into the same cluster, and each cluster represents an effective sealing area; Among the multiple clusters obtained by clustering, select the cluster containing the most data points as the main sealing ring candidate cluster; For all valid sealing points in the selected main sealing ring candidate cluster, use the moving least squares method to fit a continuous spatial surface, which is the actual contact sealing ring.

6. The method of measuring a seal face of a triple offset butterfly valve of claim 1, wherein, The continuity of the actual contact sealing ring belt in the S500 is quantified by the ring continuity rate The sealing surface is equally divided into 360 sampling segments along the ring direction of the virtual reference ring surface, each sampling segment corresponds to a 1° central angle, and the effective coverage length of the actual contact sealing ring belt in each sampling segment is counted The effective coverage length is the continuous arc length of the normal distance The ring continuity rate is calculated as follows: Wherein, The total length of the ring surface of the virtual reference ring surface.

7. The method of measuring a seal face of a triple offset butterfly valve of claim 1, wherein, In the S500, the maximum local gap value of the actual contact sealing ring belt is represented by the maximum local gap, and the absolute value of all normal distances is extracted from the gap distribution data set corresponding to the actual contact sealing ring belt , and the abnormal values are removed by adopting three criteria, the average value and the standard deviation of all are calculated, the data points of are removed, and the maximum value in the remaining data points is the maximum local gap value .

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