CN-121637701-B - Automatic blade selecting method and system for blade disc flow channel

CN121637701BCN 121637701 BCN121637701 BCN 121637701BCN-121637701-B

Abstract

The disclosure provides an automatic blade selecting method and system for a blade disc runner, and relates to the technical field of computer-aided manufacturing. The method comprises the steps of determining a hub spline curve and a receiver spline curve corresponding to a runner based on a three-dimensional geometric model corresponding to a leaf disc, carrying out parameterization treatment on the hub spline curve and the receiver spline curve to obtain initial parameters, carrying out iterative calculation on each hub feature point based on the initial parameters to obtain a depth range corresponding to the runner, determining a suction surface curve and a pressure surface curve corresponding to the runner based on the three-dimensional geometric model, traversing each feature point in the suction surface curve, determining nearest feature points corresponding to each feature point from the pressure surface curve based on an iterative search algorithm, determining a width range corresponding to the runner based on each feature point and the corresponding nearest feature point, and determining a target cutter corresponding to the runner based on the depth range and the width range. By the method, the processing precision and efficiency corresponding to the flow channel are improved.

Inventors

CHEN ZUQING
SU FAN
CHEN GUOLIN

Assignees

陕西空天信息技术有限公司

Dates

Publication Date: 20260508
Application Date: 20260130

Claims (9)

1. An automatic knife selecting method for a leaf disc runner is characterized by comprising the following steps: constructing a three-dimensional geometric model corresponding to the leaf disc, and determining a hub spline curve and a receiver spline curve corresponding to the flow channel based on the three-dimensional geometric model; performing parameterization on the hub spline curve and the receiver spline curve to obtain initial parameters, and performing iterative computation on each hub characteristic point based on the initial parameters to obtain a depth range corresponding to the flow channel; Determining a suction surface curve and a pressure surface curve corresponding to the flow channel based on the three-dimensional geometric model, traversing each characteristic point in the suction surface curve, determining nearest characteristic points corresponding to each characteristic point respectively from the pressure surface curve based on an iterative search algorithm, and determining a width range corresponding to the flow channel based on each characteristic point and the corresponding nearest characteristic point; determining a target cutter corresponding to the flow channel based on the depth range and the width range; the parameterizing the hub spline curve and the receiver spline curve to obtain initial parameters comprises the following steps: Traversing each hub characteristic point on the hub spline curve, and aiming at each hub characteristic point, performing the following operation: Connecting adjacent casing characteristic points in the casing spline curve to obtain a plurality of straight line segments; Determining the vertical distance from the hub characteristic point to each straight line segment, and determining the minimum vertical distance, and a target straight line segment and a drop foot corresponding to the minimum vertical distance; determining hub feature point coordinates of the hub feature points, foot drop coordinates of the foot drops and endpoint coordinates corresponding to the target straight line segment; constructing a two-dimensional linear equation set based on the hub characteristic point coordinates, the foot drop coordinates and the end point coordinates, and solving to obtain a receiver curve parameter and a minimum distance corresponding to the hub characteristic point; And determining the curve parameters of the case and the minimum distance as the initial parameters corresponding to the hub characteristic points.
2. The method of claim 1, wherein determining a hub spline and a receiver spline corresponding to a runner based on the three-dimensional geometric model comprises: Extracting a discrete data point set of a hub curved surface and a casing curved surface from the three-dimensional geometric model; Extracting a hub characteristic point set corresponding to the hub curved surface from the discrete data point set along the flow channel direction, and performing cubic spline interpolation processing on the hub characteristic point set to generate the hub spline curve; and extracting a receiver characteristic point set corresponding to the receiver curved surface from the discrete data point set, and performing cubic spline interpolation processing on the receiver characteristic point set to generate the receiver spline curve.
3. The method according to claim 1, wherein the performing iterative computation on each hub feature point based on the initial parameters to obtain the depth range corresponding to the flow channel includes: Determining each hub characteristic point from the hub spline curve and each receiver characteristic point from the receiver spline curve by taking the initial parameters as iteration starting points; determining effective intervals between each hub characteristic point and the corresponding receiver characteristic point, and determining the position of the receiver characteristic point corresponding to the minimum effective interval by iteratively adjusting the parameter positions of the receiver characteristic points; And determining the depth range corresponding to the flow channel based on the positions of the receiver characteristic points corresponding to the characteristic points of each hub.
4. A method according to claim 3, wherein determining the effective distance between each hub feature point and the corresponding receiver feature point, and determining the receiver feature point position corresponding to the minimum effective distance by iteratively adjusting the parameter positions of the receiver feature points, comprises: constructing an axial objective function and a radial objective function based on the current receiver characteristic point coordinates, the unit normal vector and the current hub characteristic coordinate points; Solving the axial objective function based on the current receiver characteristic points and the unit normal vector to obtain an axial function value, and solving the radial objective function to obtain a radial function value; if the absolute value of the axial function value is smaller than the axial tolerance threshold value and the absolute value of the radial function value is smaller than the radial tolerance threshold value, determining the position of the feature point of the casing corresponding to the minimum effective distance; if the absolute value of the axial function value is not smaller than the axial tolerance threshold, or the absolute value of the radial function value is not smaller than the radial tolerance threshold, updating the initial parameter to obtain an iteration parameter, and adjusting the parameter position of the receiver characteristic point based on the iteration parameter until the receiver characteristic point position corresponding to the minimum effective distance is determined.
5. The method of claim 4, wherein updating the initial parameters to obtain iteration parameters comprises: extracting a casing curve parameter and a minimum distance from the initial parameter; calculating the partial derivative of the axial objective function on the curve parameter of the casing to obtain a first partial derivative, and calculating the partial derivative of the axial objective function on the minimum distance to obtain a second partial derivative; calculating the partial derivative of the radial objective function on the curve parameter of the casing to obtain a third partial derivative, and calculating the partial derivative of the radial objective function on the minimum distance to obtain a fourth partial derivative; constructing a linear equation set based on the first partial derivative, the second partial derivative, the third partial derivative, the fourth partial derivative, the axial function value and the radial function value, and solving to obtain a receiver parameter compensation value corresponding to the receiver curve parameter and a distance compensation value corresponding to the minimum distance; and adding the receiver curve parameter and the receiver parameter compensation value to obtain an updated receiver curve parameter, adding the minimum distance and the distance compensation value to obtain an updated minimum distance, and determining the updated receiver curve parameter and the updated minimum distance as the iteration parameter.
6. The method according to claim 1, wherein determining the nearest feature point corresponding to each feature point from the pressure surface curve based on the iterative search algorithm comprises: the characteristic points are set with angle values along the circumferential direction in an offset mode, and a virtual target point is obtained; constructing a target error function based on the virtual target point, the circumferential angle of the characteristic point and the set angle value, wherein the virtual target point is determined by iterative search based on a golden section algorithm; performing iterative search updating on the set angle value based on a linear interpolation algorithm, and determining a target angle value when the target error function is a set value; and determining the nearest characteristic point corresponding to the characteristic point on the pressure surface curve based on the target angle value.
7. The method of claim 1, wherein determining the corresponding width range of the flow channel based on the each feature point and the corresponding nearest feature point comprises: Determining the arc length distance between each characteristic point in the suction surface curve and the corresponding nearest characteristic point; and determining a minimum arc length distance and a maximum arc length distance from all the arc length distances, and determining a width range corresponding to the flow channel based on the minimum arc length distance and the maximum arc length distance.
8. An automatic knife selection system for a leaf disc flow channel, the system comprising: the curve acquisition module is used for constructing a three-dimensional geometric model corresponding to the leaf disc, and determining a hub spline curve and a casing spline curve corresponding to the flow channel based on the three-dimensional geometric model; The depth determining module is used for carrying out parameterization on the hub spline curve and the receiver spline curve to obtain initial parameters, and carrying out iterative computation on each hub characteristic point based on the initial parameters to obtain a depth range corresponding to the flow channel; the width determining module is used for determining a suction surface curve and a pressure surface curve corresponding to the flow channel based on the three-dimensional geometric model, traversing each characteristic point in the suction surface curve, determining nearest characteristic points corresponding to each characteristic point respectively from the pressure surface curve based on an iterative search algorithm, and determining a width range corresponding to the flow channel based on each characteristic point and the corresponding nearest characteristic point; the automatic knife selecting module is used for determining a target knife corresponding to the flow channel based on the depth range and the width range; the parameterizing the hub spline curve and the receiver spline curve to obtain initial parameters comprises the following steps: Traversing each hub characteristic point on the hub spline curve, and aiming at each hub characteristic point, performing the following operation: Connecting adjacent casing characteristic points in the casing spline curve to obtain a plurality of straight line segments; Determining the vertical distance from the hub characteristic point to each straight line segment, and determining the minimum vertical distance, and a target straight line segment and a drop foot corresponding to the minimum vertical distance; determining hub feature point coordinates of the hub feature points, foot drop coordinates of the foot drops and endpoint coordinates corresponding to the target straight line segment; constructing a two-dimensional linear equation set based on the hub characteristic point coordinates, the foot drop coordinates and the end point coordinates, and solving to obtain a receiver curve parameter and a minimum distance corresponding to the hub characteristic point; And determining the curve parameters of the case and the minimum distance as the initial parameters corresponding to the hub characteristic points.
9. A computer device, comprising: A memory and a processor, wherein the memory has stored therein a computer program which, when executed by the processor, implements the automatic knife selection method of the blisk flow channel of any one of claims 1-7.

Description

Automatic blade selecting method and system for blade disc flow channel Technical Field The disclosure relates to the technical field of computer-aided manufacturing, in particular to an automatic blade selecting method and system for a blade disc runner. Background With the development of computer-aided manufacturing technology, the application of the method in the field of processing and manufacturing is more and more widespread. The vane disk of the core component of the aero-engine and the gas turbine has complex flow passage structure and changeable curved surface, and has extremely high requirements on processing precision and surface quality. The computer-aided manufacturing technology can more scientifically select the most suitable cutter and accurately adjust cutting parameters by introducing an algorithm and an intelligent decision system, thereby improving the production efficiency of the runner, ensuring the product quality and reducing the cost. At present, by extracting key molded lines of the flow channel, iterative calculation is performed on the maximum applicable cutter radius by adopting a dichotomy method, the flow channel is divided into a plurality of areas, and cutters with different sizes are respectively selected for carrying out distributed rough machining. However, the multi-tool partition processing mode has obvious defects that the processing quality of a runner is affected due to residual allowance at the joint of areas due to the fact that tools with different sizes are used in different areas, meanwhile, the searching area can be reduced by half each time by the dichotomy solution, the maximum tool radius is required to be determined, repeated iteration is needed for many times, the solving time is prolonged, the multi-tool partition processing efficiency is low, in addition, the processing time and the machine tool load are increased due to frequent tool changing, and the overall production efficiency is affected. In summary, how to improve the processing precision and efficiency corresponding to the flow channel becomes a major problem to be solved at present. Disclosure of Invention In order to overcome the problems in the related art, the present disclosure provides an automatic blade selecting method and system for a blade disc flow channel. According to a first aspect of embodiments of the present disclosure, there is provided an automatic blade selecting method for a blade disc flow channel, the method including: constructing a three-dimensional geometric model corresponding to the leaf disc, and determining a hub spline curve and a receiver spline curve corresponding to the flow channel based on the three-dimensional geometric model; performing parameterization on the hub spline curve and the receiver spline curve to obtain initial parameters, and performing iterative computation on each hub characteristic point based on the initial parameters to obtain a depth range corresponding to the flow channel; Determining a suction surface curve and a pressure surface curve corresponding to the flow channel based on the three-dimensional geometric model, traversing each characteristic point in the suction surface curve, determining nearest characteristic points corresponding to each characteristic point respectively from the pressure surface curve based on an iterative search algorithm, and determining a width range corresponding to the flow channel based on each characteristic point and the corresponding nearest characteristic point; and determining a target cutter corresponding to the flow channel based on the depth range and the width range. In one possible design, the determining, based on the three-dimensional geometric model, a hub spline curve and a receiver spline curve corresponding to the runner includes: Extracting a discrete data point set of a hub curved surface and a casing curved surface from the three-dimensional geometric model; Extracting a hub characteristic point set corresponding to the hub curved surface from the discrete data point set along the flow channel direction, and performing cubic spline interpolation processing on the hub characteristic point set to generate the hub spline curve; and extracting a receiver characteristic point set corresponding to the receiver curved surface from the discrete data point set, and performing cubic spline interpolation processing on the receiver characteristic point set to generate the receiver spline curve. In one possible design, the parameterizing the hub spline curve and the receiver spline curve to obtain initial parameters includes: Traversing each hub characteristic point on the hub spline curve, and aiming at each hub characteristic point, performing the following operation: Connecting adjacent casing characteristic points in the casing spline curve to obtain a plurality of straight line segments; Determining the vertical distance from the hub characteristic point to each straight line segment, and determi