CN115507803A - Method, device and equipment for machining and detecting turbine blade - Google Patents
Method, device and equipment for machining and detecting turbine blade Download PDFInfo
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- CN115507803A CN115507803A CN202211288889.9A CN202211288889A CN115507803A CN 115507803 A CN115507803 A CN 115507803A CN 202211288889 A CN202211288889 A CN 202211288889A CN 115507803 A CN115507803 A CN 115507803A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/20—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/4097—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using design data to control NC machines, e.g. CAD/CAM
- G05B19/4099—Surface or curve machining, making 3D objects, e.g. desktop manufacturing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The application provides a method, a device and equipment for machining and detecting a turbine blade. When the method is executed, firstly, scanning a blade entity to obtain the actual size and the actual spatial pose of the blade; integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the blade; calculating to obtain a blade deviation model according to the space optimization pose; calculating and acquiring theoretical characteristic point positions of the blades according to the space optimization pose; acquiring actual characteristic point positions of the blades at the actual positions of the blades according to the blade deviation model; and finally, adjusting the actual position of the blade until the theoretical characteristic point position coincides with the actual characteristic point position so as to adjust the actual pose of the space. So, can reduce the many-sided error at the in-process of making turbine blade, realize carrying out the self-adaptation processing to turbine blade and detect on the machine to it, improved turbine blade's production efficiency greatly.
Description
Technical Field
The application relates to the field of aeroengine manufacturing, in particular to a method, a device and equipment for machining and detecting turbine blades.
Background
The turbine blade is one of important parts of an aircraft engine, and as a representative part of a high-complexity and high-precision part, the manufacturing precision of the turbine blade has a crucial influence on the service performance of the aircraft engine. The key point of the processing production is to ensure the processing quality and the production efficiency of parts. In the machining production of the blade, the detection and machining precision is the key for ensuring the machining quality of the blade, and the efficiency of the detection and machining process integrally controls the efficiency of the blade production, so the detection and machining are the key links in the blade production.
At present, in the traditional blade processing process, six-point positioning of a blade body is used for limiting the degrees of freedom of the blade in six directions. In the process of casting the blade blank, casting errors can be generated due to various complex factors, the machining process still depends on the theoretical blade model to perform machining, the conditions of poor consistency, machining step difference and even out-of-tolerance can be generated, and the machining quality of the blade is reduced. The processing and the detection are two mutually independent processes, one blade may need to be clamped and positioned for many times, and clamping errors are introduced. In addition, a coordinate system of a workpiece measured by three coordinates may have a certain deviation from a coordinate system of a numerical control machine tool, and the detection and processing standards are not consistent, so that the processing precision is difficult to guarantee. Therefore, how to automatically and accurately carry out self-adaptive machining on the turbine blade and carry out on-machine detection on the turbine blade is a problem to be solved urgently.
Disclosure of Invention
In view of the above problems, the present application provides a method, an apparatus and a device for machining and detecting a turbine blade, which can perform adaptive machining on the turbine blade and perform on-machine detection on the turbine blade.
In a first aspect, embodiments of the present application provide a method for machining and inspecting a turbine blade, the method including:
scanning the blade entity to obtain the actual size and the actual spatial pose of the blade;
integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the blade;
calculating to obtain a blade deviation model according to the space optimization pose;
calculating and acquiring theoretical characteristic points of the blades according to the space optimization pose;
acquiring actual characteristic point positions of the blades at the actual positions of the blades according to the blade deviation model;
adjusting the actual position of the blade until the theoretical characteristic point position is coincident with the actual characteristic point position so as to adjust the actual spatial pose;
and selecting a machining reference surface according to the adjusted space actual pose, thereby designing a machining tool and machining.
Optionally, the step of integrating the actual size of the blade with the theoretical model to obtain the space optimization pose of the blade includes:
generating actual point cloud according to the actual size of the blade;
designing and obtaining a theoretical model point cloud according to a theoretical model;
carrying out initial registration on the actual point cloud and the theoretical model point cloud, and adjusting a coordinate system of the actual point cloud and a coordinate system of the theoretical model point cloud to be coincident;
selecting a characteristic point cloud data set from the theoretical model point cloud according to local characteristics of the blade to be protected;
and registering the actual point cloud according to the characteristic point cloud data set to obtain a target point cloud which is overlapped with the characteristic point cloud data set, wherein the target point cloud is the space optimization pose of the blade obtained after integration.
Optionally, the calculating to obtain a blade deviation model according to the spatial optimization pose includes:
calculating difference values between all points of the actual point cloud and the theoretical model point cloud according to the space optimization pose of the blade, and integrating the difference values to obtain a blade deviation model;
when the actual point cloud is larger than the theoretical model point cloud, the deviation value is positive, and when the actual point cloud is larger than the theoretical model point cloud, the deviation value is negative.
Optionally, the method further includes:
and judging whether the difference value between the machining position and the space actual pose meets the upper limit value of a deviation model or not according to the space optimization pose, and if not, adjusting the space actual pose.
Optionally, the adjusting the actual pose of the space includes:
recording the coordinates of the actual feature point location as (x) according to the actual feature point location i ，y i ，z i ) I =1, 2.. 6 and its vector direction cosine (a) xi ，a yi ，a zi ) I =1, 2.. 6, wherein x i Is the abscissa value, y, of the ith feature point i Is the ordinate value of the i-th feature point, z i Is the vertical axis coordinate value of the ith feature point; a is xi Is the abscissa value of the i-th vector direction cosine, a yi Is the ordinate value of the i-th vector direction cosine, a zi Is the vertical axis coordinate value of the ith vector direction cosine;
according to the space optimization pose obtained by the integration, marking the deviation value of the actual characteristic point position and the theoretical characteristic point position as b;
calculating a theoretical point location compensation value according to the theoretical characteristic point location compensation formula, wherein the theoretical characteristic point location compensation formula is as follows:
wherein, x 'is the abscissa value of the compensation value, y' is the ordinate value of the compensation value, z 'is the ordinate value of the value, (x', y ', z') is the value obtained after compensation;
and inputting the compensated value into a numerical control program of the five-axis machine tool, and adjusting the actual spatial pose to enable the actual characteristic point to coincide with the theoretical characteristic point.
Optionally, according to the actual position and posture in space, a machining reference surface is selected, so that a machining tool is designed and machined, and the machining tool comprises:
and selecting a machining plane which ensures that the subsequent repeated machining positioning error is within a preset range according to the actual spatial pose, and selecting a machining plane opposite to the machining reference plane to ensure the subsequent machining of the machining reference plane for machining.
In a second aspect, embodiments of the present application provide a turbine blade machining and inspection apparatus, the apparatus including:
the pose acquisition module is used for scanning the blade entity and acquiring the actual size and the actual spatial pose of the blade;
the integration module is used for integrating the actual size of the blade with a theoretical model and acquiring the space optimization pose of the blade;
the deviation model calculation module is used for calculating to obtain a blade deviation model according to the space optimization pose;
the theoretical characteristic point location obtaining module is used for calculating and obtaining blade theoretical characteristic point locations according to the space optimization pose;
the actual point location obtaining module is used for collecting actual characteristic point locations of the blades at the actual positions of the blades according to the blade deviation model;
the position and pose adjusting module is used for adjusting the actual position of the blade until the theoretical characteristic point coincides with the actual characteristic point so as to adjust the actual position and pose of the space;
and the design module is used for selecting a machining reference surface according to the actual spatial pose so as to design a machining tool and carry out machining.
Optionally, the integration module includes:
the actual point cloud generating unit is used for generating actual point cloud according to the actual size of the blade;
the theoretical model point cloud obtaining unit is used for obtaining a theoretical model point cloud according to the theoretical model design;
the adjusting unit is used for carrying out initial registration on the actual point cloud and the theoretical model point cloud and adjusting the coordinate system of the actual point cloud and the coordinate system of the theoretical model point cloud to be overlapped;
the theoretical model point cloud set acquisition unit is used for selecting a characteristic point cloud data set from the theoretical model point cloud according to local characteristics of blades needing to be protected;
and the space optimization pose acquisition unit is used for registering the actual point cloud according to the characteristic point cloud data set to acquire a target point cloud which is overlapped with the characteristic point cloud data set, and the target point cloud is the space optimization pose of the blade acquired after integration.
Optionally, the deviation model calculating module is specifically configured to:
calculating difference values between all points of the actual point cloud and the theoretical model point cloud according to the space optimization pose of the blade, and integrating the difference values to obtain a blade deviation model;
and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a positive deviation value, and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a negative deviation value.
In a third aspect, an embodiment of the present application provides an apparatus for machining and detecting a turbine blade, including:
a memory, a processor, and a computer program stored on the memory and executable on the processor, when executing the computer program, implementing the method of turbine blade machining and inspection of the first aspect.
The embodiment of the application provides a method, a device and equipment for machining and detecting a turbine blade. When the method is executed, firstly, scanning a blade entity to obtain the actual size and the actual spatial pose of the blade; integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the blade; calculating to obtain a blade deviation model according to the space optimization pose; calculating and acquiring theoretical characteristic points of the blades according to the space optimization pose; acquiring actual characteristic point positions of the blades at the actual positions of the blades according to the blade deviation model; and finally, adjusting the actual position of the blade until the theoretical characteristic point position coincides with the actual characteristic point position so as to adjust the actual pose of the space. So, can reduce the many-sided error at the in-process of making turbine blade, realize carrying out the self-adaptation processing to turbine blade and detect on the machine to it, improved turbine blade's production efficiency greatly.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, and obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for machining and inspecting a turbine blade according to an exemplary embodiment of the present disclosure;
FIG. 2 is a flow chart of a method for turbine blade machining and inspection in accordance with an embodiment of the present disclosure;
FIG. 3 is a schematic view of an apparatus for machining and inspecting a turbine blade according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a corresponding apparatus and a computer storage medium according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without any creative effort belong to the protection scope of the present application.
The method, the device and the equipment for machining and detecting the turbine blade are used in the field of aircraft engine manufacturing. The foregoing is merely an example, and does not limit the application fields of the names of the methods and apparatuses provided in the present application.
Referring to fig. 1, which is a flowchart of a method for machining and inspecting a turbine blade according to an embodiment of the present application, it should be noted that, in the embodiment, only a turbine guide blade is taken as an example, local features of the turbine guide blade need to be preferentially ensured as a cavity and an inner edge plate, but the present application is not limited to the turbine guide blade.
The turbine guide vane is one of key parts of an aircraft engine, and is subjected to higher working temperature and higher thermal stress during operation. Therefore, in order to make the engine work stably under the above conditions, the structural design of the turbine guide vane is very complicated, which involves multiple operations such as vane body shaping, vane strength calculation, material selection and the like, and is decisive for the influence of the inside and outside air flows, and can directly influence the excellent performance of the whole engine, such as starting performance, weight, cost, reliability and the like. Therefore, the shape of the turbine guide vane, including the shape, the inner shape, the position and the number of the guide vanes, of the aircraft engine are very strict. In the machining process of the turbine guide vane, the design of a machining tool needs to be tighter, and the error of a vane part obtained by machining needs to be smaller.
S101: and scanning the turbine guide blade entity to obtain the actual size and the actual spatial pose of the turbine guide blade.
In this embodiment, the pose is the position and the posture of the blade on the clamp.
One possible way is to obtain the physical three-dimensional profile dimensions of the turbine guide vane by means of a non-contact blue light scan.
The non-contact blue light scanning device is a method for acquiring three-dimensional coordinate information of the surface of the turbine guide blade by utilizing certain physical phenomena, such as light, sound, electromagnetism and the like, which are bionically interacted with the surface of an object.
The actual pose in space comprises: three-dimensional profile dimensions of the turbine guide vane and local features to be guaranteed, etc.
S102: and integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the turbine guide blade.
In the embodiment of the application, after the turbine guide vane is scanned, the actual size of the vane is compared and integrated with a theoretical model for manufacturing the turbine guide vane, so that the space optimization pose of the turbine guide vane is obtained.
One possible way is as follows, comprising the steps of:
and generating a turbine guide blade entity point cloud Q according to the actual size of the turbine guide blade obtained after scanning.
And (2) importing the theoretical model of the turbine guide blade into GOM software (processing software supporting simple or complex detection tasks in the whole detection process, from recording a part to be detected, grid processing, importing CAD, necessary shape and position calculation to trend analysis, digital assembly or special detection) to generate a turbine guide blade theoretical model point cloud X.
And initially registering the scanned turbine guide blade entity point cloud Q and the theoretical model point cloud X by utilizing PCA (Principal Component Analysis), so that the reference coordinate systems of the two point clouds are adjusted to be consistent.
The registration refers to automatic registration, and the point cloud automatic registration technology calculates the dislocation between two pieces of point clouds by using a computer through a certain algorithm or statistical rule, so that the effect of automatically registering the two pieces of point clouds is achieved.
And selecting a characteristic dimension point cloud data set E of the cavity opening and the inner edge plate from the theoretical model point cloud X of the turbine guide vane.
And registering the theoretical model characteristic dimension Point cloud data set E of the turbine guide blade with the physical Point cloud of the turbine guide blade part by utilizing an ICP (Iterative Closest Point) algorithm, wherein the registered theoretical model E of the turbine guide blade and the physical model characteristic dimension Point cloud are overlapped to complete the local characteristic integration of the turbine guide blade, so that the optimized spatial pose of a certain turbine guide blade is obtained.
The point cloud and the point cloud data set refer to a massive point set of the surface characteristics of the target, and comprise three-dimensional coordinates, laser reflection intensity, color information and the like.
S103: and calculating to obtain a turbine guide blade deviation model according to the space optimization pose.
In this embodiment, according to the above-mentioned spatial optimization pose, a deviation model of the turbine guide blade is obtained by calculating a difference between the solid point cloud and the theoretical model point cloud.
And the deviation model is the difference between the actual point location and the theoretical model point location.
One possible way is as follows:
and calculating the difference value of all point positions of the integrated turbine guide blade part solid point cloud and the turbine guide blade theoretical model point cloud according to the space optimization pose to obtain a deviation model under the space pose optimized by the turbine guide blade, wherein when the actual point cloud is larger than the theoretical model point cloud, the deviation value is a positive deviation value, and when the actual point cloud is larger than the theoretical model point cloud, the deviation value is a negative deviation value.
S104: and calculating and acquiring theoretical characteristic point positions of the turbine guide blades according to the space optimization pose.
In this embodiment, theoretical feature point locations of the turbine guide blade, including but not limited to feature point locations such as six reference points, are calculated and obtained by using a deviation model according to the spatial optimization pose obtained in the above steps.
The six reference points are six support points which are reasonably distributed and limit six degrees of freedom of the blade, wherein the six support points have six degrees of freedom in a space rectangular coordinate system, namely three degrees of freedom moving along X, Y and Z axes and three degrees of freedom rotating around the three axes, so that the blade occupies a correct position in the clamp.
The theoretical characteristic point location is the location of each characteristic point of the blade in an ideal state, and includes, but is not limited to, a six-point-of-reference isopoint location.
S105: and acquiring actual characteristic point positions of the blades under the actual positions of the blades according to the deviation model of the turbine guide blades.
The actual feature point position is the position of each feature point in the actual state of the blade, and includes, but is not limited to, a six-point datum equivalent position.
In this embodiment, according to the turbine guide blade deviation model obtained in step S103, actual feature point positions in an actual pose are collected on the turbine guide blade.
One possible way is as follows:
and according to the optimized pose, registering the turbine guide blade entity point cloud Q and the theoretical model point cloud model X, wherein the turbine guide blade entity point cloud Q protrudes out of the theoretical model point cloud model X at each machining position, and the machining allowance is sufficient.
And the machining allowance is that when the actual point cloud Q is larger than the theoretical model point cloud X and is a positive deviation value, and when the actual point cloud Q is larger than the theoretical model point cloud X and is a negative deviation value, whether the difference value between the machining position and the space actual pose meets the upper limit value of a deviation model needs to be judged, and if not, the space actual pose needs to be adjusted in the subsequent steps.
Finding six positioning reference points G and E in the deviation model 1 、E 2 、K 1 、K 2 Obtaining the deviation value T of the six positioning reference points G 、T E 、T E2 、T K1 、T K2 、T JB 。
S106: and adjusting the actual position of the turbine guide blade until the theoretical characteristic point position is coincident with the actual characteristic point position so as to adjust the actual spatial pose.
In this embodiment, if the machining allowance is not sufficient, the actual position of the turbine guide blade is adjusted, so that the theoretical characteristic point coincides with the actual characteristic point in the space actual pose.
One possible way is as follows:
the guide vane of the turbine is clamped and installed by a toolOn a five-axis milling machine of a machine contact type measuring head, the spatial position of six points is recorded as (x) through acquisition and positioning of the machine measuring head i ，y i ，z i )，i＝1，2，...6。
In the numerical control program of the five-axis machine tool, six positioning points are positioned according to the deviation value T G 、T E 、T E2 、T K1 、T K2 、T JB And compensating according to a positioning point compensation formula:
then according to the compensated positioning six-point coordinate (x) i ，y i ，z i ) And i =1, 2.. 6, iteratively establishing a coordinate system, and regulating and controlling the spatial pose of the turbine guide blade to be basically consistent with the acquired optimized spatial pose obtained in the non-contact detection process of the process 1.
Wherein x is i Is the abscissa value, y, of the ith feature point i Is the ordinate value of the i-th feature point, z i Is the vertical axis coordinate value of the ith feature point, a xi Is the abscissa value of the i-th vector direction cosine, a yi Is the ordinate value of the i-th vector direction cosine, a zi And (4) recording the deviation value of the actual feature point position and the theoretical feature point position as T according to the space optimization pose obtained by integrating the vertical axis coordinate value of the i-th vector direction cosine.
S107: and selecting a machining reference surface according to the adjusted space actual pose, so as to design a machining tool and carry out machining.
In the embodiment, the reference plane of the machining is selected by utilizing the actual spatial pose, the structural shape, the machining characteristics and the like of the turbine guide blade, so that the error of the subsequent machining is reduced.
One possible way is as follows:
according to the actual spatial pose, the structural shape and the machining characteristics of a certain turbine guide blade, two machining planes of a back side wedge-shaped surface and a gas inlet edge plate are selected as medium conversion reference surfaces.
And (6) milling the wedge-shaped surface at the back side and the air inlet edge plate under the spatial pose regulated and controlled by the five-axis milling machine in the step S106, and reserving a machining allowance of 0.08 mm.
In the embodiments of the present application, the machining allowance is merely an example, and may be set according to a required machining allowance in practical applications, and is within the scope of the present application.
And designing a machining and positioning tool by taking the back side wedge-shaped surface and the air inlet edge plate as references, installing the turbine guide blade on a five-axis numerical control machining grinding machine, and grinding the two machining reference surfaces of the basin side wedge-shaped surface and the air outlet edge plate according to machining allowance obtained by an optimized deviation model under the space pose in the non-contact detection process in the steps S101-S105.
And (3) detecting the position degrees of the cavity opening and the inner edge plate by using a three-coordinate measuring machine by taking the wedge-shaped surface of the basin side and the exhaust edge plate as references, and confirming the manufacturing conformity of the turbine guide blade entity and the cavity opening and the inner edge plate in the simulation optimization pose state, so that the machining tool is designed and machined.
Based on the above content, in the embodiment of the application, the actual size of the turbine guide blade is obtained through on-machine contact detection and the theoretical model is integrated, so that the space optimization pose of the turbine guide blade is obtained, the space actual pose is further adjusted, and the reference surface is selected according to the space optimization pose to perform machining tool design and perform machining. Under the condition of the machining tool designed after the reference surface is selected, the turbine guide vane is not required to be differentially adjusted, only the subsequent fixed machining process flow is required to be completed, the error rate in the machining process of the turbine guide vane can be greatly reduced through the steps, and the machining quality is improved.
The turbine blade machining and detecting method provided by the embodiment of the present application is described above, and the following description is made by way of example in conjunction with a specific application scenario.
Referring to fig. 2, a flowchart of a method for machining and detecting a turbine blade according to an embodiment of the present disclosure includes:
s201: and carrying out blue light scanning on the blade to obtain the actual size and the actual spatial pose of the blade.
The actual size includes the three-dimensional size of the blade, the size of each feature point to be protected by the blade, and the like.
S202: and integrating the actual size of the blade obtained in the step S201 with the theoretical model of the blade and obtaining the spatial pose of the blade.
Wherein the integration comprises the steps of:
and generating a turbine blade entity point cloud Q according to the actual size of the turbine blade acquired after scanning.
And (2) importing the theoretical model of the turbine blade into GOM software (processing software supporting simple or complex detection tasks in the whole detection process, from recording of a part to be detected, grid processing, importing of CAD, necessary shape and position calculation to trend analysis, digital assembly or special detection), and generating a turbine blade theoretical model point cloud X.
And (3) initially registering the turbine blade entity point cloud Q obtained by scanning with the theoretical model point cloud X by using PCA (Principal Component Analysis), so that the reference coordinate systems of the two point clouds are adjusted to be consistent.
And selecting a characteristic dimension point cloud data set E of the cavity opening and the inner flange plate from the theoretical turbine blade model point cloud X.
And registering the turbine blade theoretical model characteristic dimension Point cloud data set E with the turbine blade part entity Point cloud by utilizing an ICP (Iterative Closest Point) algorithm, overlapping the registered turbine blade theoretical model E and the entity model characteristic dimension Point cloud to complete local characteristic integration of the turbine blade and obtain the optimized spatial pose of a certain turbine blade.
The point cloud and point cloud data set refer to a massive point set of target surface characteristics, including three-dimensional coordinates, laser reflection intensity, color information, and the like.
S203: and calculating and acquiring a deviation model of the turbine blade according to the space optimization pose.
In the step, the difference value of all point positions of the integrated turbine blade part solid point cloud and the turbine blade theoretical model point cloud needs to be calculated, wherein when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a positive deviation value, and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a negative deviation value, and a deviation model of the turbine blade is obtained according to the deviation value.
S204: and (5) installing the blades, and carrying out on-machine detection.
In the step, the tool is firstly clamped on a five-axis milling machine provided with an on-machine contact type measuring head, and on-machine detection is carried out.
Wherein the on-machine detection comprises:
six-point spatial position (x) is collected and positioned by a machine measuring head i ，y i ，z i )，i＝1，2，...6。
Wherein x is i Is the abscissa value, y, of the ith feature point i Is the ordinate value of the i-th feature point, z i Is the vertical axis coordinate value of the ith feature point.
In this step, the coordinates of the six-point position are located by on-machine inspection acquisition.
S205: and judging whether the on-machine attitude of the blade needs to be adjusted.
And comparing the coordinates of the six positioning points acquired in the step S204 with the actual size and the actual spatial pose of the blade acquired after the blue light scanning in the step S201 to judge whether the on-machine attitude of the blade needs to be adjusted.
In this step, if it is determined that the on-machine attitude needs to be adjusted, the on-machine attitude of the blade is adjusted, and if it is determined that the on-machine attitude is not needed, the process proceeds to step S206.
Wherein, the on-machine attitude of the blade is adjusted according to the following steps:
according to the optimized pose, the registered turbine guide blade entity point cloud Q and the theoretical model point cloud model X are protruded outside the theoretical model point cloud model X at each machining position, and the machining allowance is sufficient.
And the machining allowance is that when the actual point cloud Q is larger than the theoretical model point cloud X and is a positive deviation value, and when the actual point cloud Q is larger than the theoretical model point cloud X and is a negative deviation value, whether the difference value between the machining position and the space actual pose meets the upper limit value of a deviation model needs to be judged, and if not, the space actual pose needs to be adjusted in the subsequent steps.
Finding six positioning reference points G and E in the deviation model 1 、E 2 、K 1 、K 2 Obtaining the deviation value T of the six positioning reference points G 、T E 、T E2 、T K1 、T K2 、T JB 。
In the numerical control program of the five-axis milling machine in the step S204, six positioning points are positioned according to the deviation value T G 、T E 、T E2 、T K1 、T K2 、T JB And compensating according to a positioning point compensation formula, wherein the positioning point compensation formula is as follows:
then according to the compensated positioning six-point coordinate (x) i ，y i ，z i ) And i =1, 2.. 6, iteratively establishing a coordinate system, and regulating and controlling the spatial pose of the turbine blade to be basically consistent with the optimized spatial pose.
Wherein, a xi Is the abscissa value of the i-th vector direction cosine, a yi Is the ordinate value of the i-th vector direction cosine, a zi And (4) recording the deviation value of the actual feature point position and the theoretical feature point position as T according to the space optimization pose obtained by integrating the vertical axis coordinate value of the i-th vector direction cosine.
S206: and designing a machining tool and machining.
In this step, the design of the machining tool includes:
firstly, coarse reference processing such as milling, grinding and the like is carried out, a coarse reference processing tool is designed, and finally, a subsequent grinding process is completed.
During the rough reference machining, the principle of ensuring mutual position requirement, the principle of ensuring reasonable distribution of machining allowance of a machined surface, the principle of facilitating workpiece clamping, the principle that the rough reference cannot be reused generally and the like are followed.
Based on the above, the processing tool is further designed through non-contact detection and machine-contact detection, so that the problems of poor leaf shape position, poor step and the like in the machining process caused by the size error of a leaf blank in the traditional leaf processing process are solved, and the design and manufacturing conformance of the leaf is further improved.
Referring to fig. 3, the schematic diagram of a turbine blade machining and detecting apparatus according to an embodiment of the present application includes: the system comprises a pose acquisition module 301, an integration module 302, a deviation model calculation module 303, a theoretical characteristic point location acquisition module 304, an actual point location acquisition module 305, a pose adjustment module 306 and a design module 307.
The pose acquisition module 301 is specifically configured to scan a blade entity and acquire an actual size and an actual spatial pose of the blade.
The integration module 302 is specifically configured to integrate the actual size of the blade with the theoretical model, and obtain a spatial optimization pose of the blade.
And the deviation model calculation module 303 is specifically configured to calculate and obtain a blade deviation model according to the space optimization pose.
And the theoretical characteristic point location obtaining module 304 is specifically configured to calculate and obtain a blade theoretical characteristic point location according to the spatial optimization pose.
The actual point location obtaining module 305 is specifically configured to collect, according to the blade deviation model, actual feature point locations of the blade at the actual position of the blade.
And a pose adjusting module 306, configured to adjust the actual position of the blade until the theoretical feature point coincides with the actual feature point, so as to adjust the actual pose of the space.
And a design module 307, specifically configured to select a machining reference surface according to the actual spatial pose, so as to design a machining tool and perform machining.
In one implementable manner, the integration module 302 includes:
and the actual point cloud generating unit is used for generating actual point cloud according to the actual size of the blade.
And the theoretical model point cloud obtaining unit is used for obtaining the theoretical model point cloud according to the theoretical model design.
And the adjusting unit is used for carrying out initial registration on the actual point cloud and the theoretical model point cloud and adjusting the coordinate system of the actual point cloud and the coordinate system of the theoretical model point cloud to be coincident.
And the theoretical model point cloud set acquisition unit is used for selecting a characteristic point cloud data set from the theoretical model point cloud according to the local characteristics of the blade to be protected.
And the space optimization pose acquisition unit is used for registering the actual point cloud according to the characteristic point cloud data set, acquiring a target point cloud which is overlapped with the characteristic point cloud data set, and acquiring the space optimization pose of the blade after integration.
In one implementation, the bias model calculation module 303 includes:
and the first calculation unit is used for calculating the difference values between all points of the actual point cloud and the theoretical model point cloud according to the space optimization pose of the blade, and integrating the difference values to obtain a blade deviation model.
When the actual point cloud is larger than the theoretical model point cloud, the deviation value is positive, and when the actual point cloud is larger than the theoretical model point cloud, the deviation value is negative.
In one possible implementation, the apparatus further includes:
and the second adjusting unit is used for judging whether the difference value between the machining position and the space actual pose meets the upper limit value of a deviation model or not according to the space optimization pose, and if not, adjusting the space actual pose.
In one possible implementation, the pose adjustment module 306 includes:
a second calculating unit, configured to record, according to the actual feature point location, a coordinate of the actual feature point location as (x) i ，y i ，z i ) I =1, 2.. 6 and its vector direction cosine is noted as (a) xi ，a yi ，a zi ) I =1, 2.. 6, where xi is the abscissa value of the i-th feature point, y i Is the ordinate value of the i-th feature point, z i Is the vertical axis coordinate value of the ith feature point; a is a xi Is the abscissa value of the i-th vector direction cosine, a yi Is the ordinate value of the i-th vector direction cosine, a zi Is the vertical axis coordinate value of the i-th vector direction cosine.
And the third calculation unit is used for recording the deviation value of the actual characteristic point position and the theoretical characteristic point position as b according to the space optimization pose obtained by integration.
A fourth calculating unit, configured to calculate a theoretical point location compensation value according to the theoretical characteristic point location compensation formula, where the theoretical characteristic point location compensation formula is:
wherein x 'is an abscissa value of the compensation value, y' is an ordinate value of the compensation value, z 'is a vertical value of the value, and (x', y ', z') is a value obtained after the compensation.
And the fifth calculation unit is used for inputting the compensated value into a numerical control program of the five-axis machine tool and adjusting the actual spatial pose so that the actual characteristic point coincides with the theoretical characteristic point.
In one possible implementation, the design module 307 includes:
and designing a processing unit, selecting a machining plane which ensures that the subsequent repeated machining positioning error is within a preset range according to the actual spatial pose, and selecting a machining plane opposite to the machining reference plane to ensure the subsequent machining of the machining reference plane for machining.
Referring to fig. 4, a schematic diagram of a corresponding apparatus and a computer storage medium provided for an embodiment of the present application includes:
the device comprises a memory 401 and a processor 402, wherein the memory 401 is used for storing instructions or codes, and the processor 402 is used for executing the instructions or codes so as to enable the device to execute the method for machining and detecting the turbine blade according to any embodiment of the application.
In the embodiments of the present application, the names "first" and "second" (if present) in the names "first" and "second" are used for name identification, and do not represent the first and second in sequence.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the above embodiment methods can be implemented by software plus a general hardware platform. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a read-only memory (ROM)/RAM, a magnetic disk, an optical disk, or the like, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the method according to the embodiments or some parts of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only an exemplary embodiment of the present application, and is not intended to limit the scope of the present application.
Claims (10)
1. A method of turbine blade machining and inspection, the method comprising:
scanning the blade entity to obtain the actual size and the actual spatial pose of the blade;
integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the blade;
calculating to obtain a blade deviation model according to the space optimization pose;
calculating and acquiring theoretical characteristic point positions of the blades according to the space optimization pose;
acquiring actual characteristic point positions of the blades at the actual positions of the blades according to the blade deviation model;
adjusting the actual position of the blade until the theoretical characteristic point position coincides with the actual characteristic point position so as to adjust the actual pose of the space;
and selecting a machining reference surface according to the adjusted space actual pose, thereby designing a machining tool and machining.
2. The method according to claim 1, wherein the integrating the actual size of the blade with the theoretical model to obtain the spatial optimization pose of the blade comprises:
generating actual point cloud according to the actual size of the blade;
designing and obtaining a theoretical model point cloud according to a theoretical model;
carrying out initial registration on the actual point cloud and the theoretical model point cloud, and adjusting a coordinate system of the actual point cloud and a coordinate system of the theoretical model point cloud to be coincident;
selecting a characteristic point cloud data set from the theoretical model point cloud according to local characteristics of the blade to be protected;
and registering the actual point cloud according to the feature point cloud data set to obtain a target point cloud which is overlapped with the feature point cloud data set, wherein the target point cloud is the space optimization pose of the blade obtained after integration.
3. The method according to claim 2, wherein the calculating and obtaining a blade deviation model according to the space optimization pose comprises:
calculating difference values between all points of the actual point cloud and the theoretical model point cloud according to the space optimization pose of the blade, and integrating the difference values to obtain a blade deviation model;
and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a positive deviation value, and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a negative deviation value.
4. The method of claim 1, further comprising:
and judging whether the difference value between the machining position and the space actual pose meets the upper limit value of a deviation model or not according to the space optimization pose, and if not, adjusting the space actual pose.
5. The method according to claim 4, wherein the adjusting the actual pose in space comprises:
recording the coordinates of the actual feature point location as (x) according to the actual feature point location i ，y i ，z i ) I =1, 2.. 6 and its vector direction cosine is noted as (a) xi ，a yi ，a zi ) I =1, 2.. 6, wherein x i Is the abscissa value, y, of the ith feature point i Is the ordinate value of the i-th feature point, z i Is the vertical axis coordinate value of the ith feature point; a is xi Is the abscissa value of the i-th vector direction cosine, a yi Is the ordinate value of the i-th vector direction cosine, a zi Is the vertical axis coordinate value of the i-th vector direction cosine;
recording the deviation value of the actual characteristic point location and the theoretical characteristic point location as b according to the space optimization pose obtained by the integration;
calculating a theoretical point location compensation value according to the theoretical characteristic point location compensation formula, wherein the theoretical characteristic point location compensation formula is as follows:
wherein x 'is an abscissa value of the compensation value, y' is an ordinate value of the compensation value, z 'is a vertical value of the value, and (x', y ', z') is a value obtained after compensation;
and inputting the compensated value into a numerical control program of the five-axis machine tool, and adjusting the actual pose of the space to enable the actual characteristic point to coincide with the theoretical characteristic point.
6. The method according to claim 1, wherein the step of selecting a machining reference surface according to the actual spatial pose so as to design a machining tool and perform machining comprises the following steps:
and selecting a machining plane which ensures that the subsequent repeated machining positioning error is within a preset range according to the actual spatial pose, and then selecting a machining plane opposite to the machining reference plane to ensure the machining of the subsequent machining reference plane for machining.
7. An apparatus for turbine blade machining and inspection, the apparatus comprising:
the pose acquisition module is used for scanning the blade entity and acquiring the actual size and the actual spatial pose of the blade;
the integration module is used for integrating the actual size of the blade with a theoretical model to obtain the space optimization pose of the blade;
the deviation model calculation module is used for calculating to obtain a blade deviation model according to the space optimization pose;
the theoretical characteristic point location obtaining module is used for calculating and obtaining blade theoretical characteristic point locations according to the space optimization pose;
the actual point location obtaining module is used for collecting actual characteristic point locations of the blades at the actual positions of the blades according to the blade deviation model;
the pose adjusting module is used for adjusting the actual positions of the blades until the theoretical characteristic point positions coincide with the actual characteristic point positions so as to adjust the actual poses of the space;
and the design module is used for selecting a machining reference surface according to the actual spatial pose so as to design a machining tool and carry out machining.
8. The apparatus of claim 7, wherein the integration module comprises:
the actual point cloud generating unit is used for generating actual point cloud according to the actual size of the blade;
the theoretical model point cloud obtaining unit is used for obtaining a theoretical model point cloud according to the theoretical model design;
the adjusting unit is used for carrying out initial registration on the actual point cloud and the theoretical model point cloud and adjusting the coordinate system of the actual point cloud and the coordinate system of the theoretical model point cloud to be coincident;
a theoretical model point cloud set acquisition unit used for selecting a characteristic point cloud data set from the theoretical model point cloud according to the local characteristics of the blade to be protected;
and the space optimization pose acquisition unit is used for registering the actual point cloud according to the characteristic point cloud data set to acquire a target point cloud which is overlapped with the characteristic point cloud data set, and the target point cloud is the space optimization pose of the blade acquired after integration.
9. The apparatus of claim 6, wherein the bias model calculation module is specifically configured to:
calculating difference values between all points of the actual point cloud and the theoretical model point cloud according to the space optimization pose of the blade, and integrating the difference values to obtain a blade deviation model;
and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a positive deviation value, and when the actual point cloud is larger than the theoretical model point cloud, the actual point cloud is a negative deviation value.
10. An apparatus for turbine blade machining and inspection, comprising:
a memory, a processor, and a computer program stored on the memory and executable on the processor, when executing the computer program, implementing a method of turbine blade machining and inspection as claimed in any one of claims 1 to 6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115890537A (en) * | 2023-03-07 | 2023-04-04 | 北京汉飞航空科技有限公司 | Posture adjusting method for turbine blade based on six-point positioning |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115890537A (en) * | 2023-03-07 | 2023-04-04 | 北京汉飞航空科技有限公司 | Posture adjusting method for turbine blade based on six-point positioning |
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