Integrated machining workpiece positioning method of turning and milling composite machine tool

Abstract

The invention relates to the technical field of machine tool positioning, in particular to an integrated machining workpiece positioning method of a turning-milling composite machine tool, which comprises the following steps of: really capturing geometrical characteristics of a workpiece through a high-resolution image acquisition and deep learning algorithm, and establishing an accurate point cloud model and a mathematical model, so that the workpiece is positioned more accurately in the subsequent machining process; machining defects caused by positioning errors are obviously reduced; on the basis of the machining requirement of a current workpiece, proper clamping force and a proper clamping mode are designed, so that the workpiece can be kept stable in the machining process, workpiece displacement or damage caused by improper clamping is reduced, and then the machining quality is improved; and meanwhile, a dynamic monitoring and feedback mechanism is introduced, the deviation between the actual clamping position and the target position of the workpiece can be judged in real time, corresponding adjustment is made to adapt to displacement or deformation possibly occurring in the machining process, and continuous and accurate positioning of the workpiece is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of machine tool positioning, and more specifically, to an integrated machining workpiece positioning method of a turning-milling compound machine tool. Background Art

[0002] Turning-milling compound machine tools integrate turning and milling functions, and can perform multiple optimized processing on the same equipment to meet the processing needs of complex parts; however, traditional workpiece positioning methods only judge whether the workpiece has been clamped in place based on the data fed back by the sensor set on the machine tool. For example, patent publication number CN109909811B discloses a workpiece positioning method and its material removal processing method. This positioning method often has problems such as insufficient positioning accuracy, poor adaptability to complex workpiece shapes and long adjustment time. When the clamping position of the clamped workpiece is adjusted multiple times and the workpiece clamping fixture is replaced, these problems may lead to low processing efficiency and unstable product quality; therefore, there is an urgent need for a novel, creative and integrated workpiece positioning method to improve the processing performance of turning-milling compound machine tools. Summary of the invention

[0003] In view of the deficiencies in the prior art, an object of the present invention is to provide an integrated workpiece positioning method for a turning-milling compound machine tool to solve the problems existing in the above-mentioned background technology.

[0004] The above technical objectives of the present invention are achieved through the following technical solutions: an integrated machining workpiece positioning method of a turning-milling compound machine tool, comprising: Step A, image acquisition of the processed workpiece: during the processing of the workpiece, a number of image acquisition time points are set, and then the image parameters and geometric feature parameters of the workpiece are acquired at each image acquisition time point, and the standard model that is most similar to the workpiece is screened and matched by the geometric feature parameters acquired at any of the acquisition time points, and then the image parameters at the corresponding acquisition time point are compared and matched with the standard model to obtain the workpiece feature points; the image parameters include workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters; the workpiece feature points are distinguishing feature coordinate parameters between the workpiece and the screened and matched standard model; Step B, constructing a point cloud model of the workpiece: three-dimensional reconstruction is performed through the collected feature points of the workpiece to construct a feature point cloud model of the workpiece for positioning and processing tracking in subsequent processing; Step C, constructing a mathematical model of the workpiece: obtaining the standard model in step A, matching a general mathematical model through the standard model, and then fitting the general mathematical model through a feature point cloud model of the workpiece to establish a mathematical model of the workpiece; Step D, matching the clamping tool and the corresponding clamping method: Based on the constructed workpiece mathematical model, use the feature matching algorithm to match it with the clamping tools in the preset clamping tool library, and then obtain the corresponding clamping tool; Match the corresponding clamping method: Based on the matched clamping tool, calculate the clamping force required to clamp the workpiece, and design the motion trajectory of the fixture when clamping or releasing the workpiece; Step E, executing clamping of the workpiece: the execution module clamps and processes the workpiece through a matching clamping tool and a corresponding clamping method; Step F, dynamically adjust the clamping position: according to the error optimization model, the data deviation between the actual clamping position and the target position is analyzed to obtain the analysis result. The control module will automatically adjust the position of the fixture holding the workpiece according to the analysis result, so that the positioning of the workpiece in the fixture is more accurate.

[0005] Optionally, the specific implementation process of step A is as follows: A1. Use a high-resolution camera to perform 360-degree all-round image acquisition of the workpiece to obtain complete appearance information of the workpiece, effectively capture the geometric features of the workpiece, and then obtain the geometric feature parameters; A2, performing image preprocessing on the acquired image information, and then collecting and extracting the workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters through the image preprocessed; A3. Screen and match the most similar standard model through the workpiece geometric feature parameters; compare the collected image parameters with the standard model through a feature point matching algorithm to obtain specific workpiece feature points.

[0006] Optionally, the three-dimensional reconstruction is performed by collecting the workpiece feature points in step B to construct a point cloud model. The specific implementation process is as follows: B1. The three-dimensional workpiece feature points obtained by image processing and feature extraction algorithm are converted into three-dimensional point clouds, and the point cloud model construction formula ,in is the coordinate of the workpiece in three-dimensional space.

[0007] Optionally, the standard model in step A is obtained in step C, a general mathematical model is matched by the standard model, and then the general mathematical model is fitted by the feature point cloud model of the workpiece to establish the workpiece mathematical model. The specific implementation process is as follows: C1. Obtain the standard model matched in step A, and then match the corresponding universal mathematical model; C2, define the error measure between the point cloud model and the mathematical model by minimizing the error using the least squares method; C3, use the fitting algorithm to adjust the parameters of the general mathematical model so that the general mathematical model fits the point cloud data as closely as possible, and then establish the workpiece mathematical model; the objective function is expressed as ,in represents the point cloud distance calculated for the model, Represented as the actual measured point cloud distance.

[0008] Optionally, based on the constructed workpiece mathematical model, a feature matching algorithm is used to perform feature matching with the clamping tools in the preset clamping tool library to match the corresponding clamping tools. The specific implementation process is as follows: By using the characteristics of the part to be clamped in the mathematical model of the workpiece and the characteristics of the clamping part of the clamping tool, a feature matching algorithm is used to screen and match in a preset clamping tool library, and then select a suitable clamping tool; the preset clamping tool library is a collection of fixtures installed and used on the machine tool.

[0009] Optionally, the step D is based on the matched clamping tool, the clamping force required to clamp the workpiece is calculated, and the motion trajectory of the clamp when clamping or releasing the workpiece is designed. The specific implementation process is as follows: D1. Based on the type of processing required, calculate and confirm the cutting force on the workpiece during the processing ,in It is expressed as the cutting strength of the current processing. It is expressed as the contact area between the tool and the workpiece during the current machining; D2. Calculate the required clamping force based on the stability requirements of the workpiece and the actual contact conditions of the clamping surface ,in is the friction coefficient between the workpiece and the fixture during the current processing, is the normal force applied by the fixture on the workpiece, g is the acceleration due to gravity; D3. Calculate the normal force applied by the fixture on the workpiece ,in The quality of the workpiece processed at that time; D4. Model the motion trajectory of the fixture and set the linear motion trajectory equation in the Cartesian coordinate system ,in Represented as the initial position parameter of the fixture, Represented as the final position parameter of the fixture, It is expressed as a time progress parameter in the current processing process with a value between 0 and 1; D5. During the movement of the fixture, an S-shaped curve is used for acceleration and deceleration control to ensure that the movement of the fixture during clamping and releasing does not produce impact.

[0010] Optionally, in step F, the data deviation between the actual holding position and the target position is analyzed according to the error optimization model to obtain an analysis result, and the control module automatically adjusts the position of the fixture holding the workpiece according to the analysis result. The specific implementation process is as follows: F1. Dynamically monitor the position of the workpiece being processed, use sensors to check the current actual position of the workpiece, and compare the current actual position with the predetermined position to obtain the position deviation. ,in It is expressed as the actual clamping position parameter of the workpiece being processed. It is expressed as a predetermined clamping position parameter; F2, according to the obtained position deviation ,in To adjust the amplitude coefficient, is the clamping position parameter after adjustment.

[0011] In summary, the present invention has the following beneficial effects: 1. The present invention uses high-resolution image acquisition and deep learning algorithms to truly capture the geometric features of the workpiece and establish accurate point cloud models and mathematical models, so that the positioning of the workpiece in subsequent processing is more precise, significantly reducing processing defects caused by positioning errors.

[0012] 2. Based on the processing requirements of the workpiece at that time, design appropriate clamping force and clamping method to ensure that the workpiece can remain stable during the processing, reduce the displacement or damage of the workpiece caused by improper clamping, and thus improve the processing quality; at the same time, introduce a dynamic monitoring and feedback mechanism to judge the deviation between the actual clamping position and the target position of the workpiece in real time, and make corresponding adjustments to adapt to the displacement or deformation that may occur during the processing process, ensuring the continuous and accurate positioning of the workpiece. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the method steps of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. Several embodiments of the present invention are shown in the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0015] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0016] In the present invention, unless otherwise clearly specified and limited, the first feature being "above" or "below" the second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, the first feature being "above", "above" and "above" the second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature includes the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature. The terms "vertical", "horizontal", "left", "right", "above", "below" and similar expressions are for illustrative purposes only, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0017] The present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0018] The present invention provides an integrated machining workpiece positioning method for a turning-milling compound machine tool, such as Figure 1 As shown, including: The method comprises: step A, acquiring an image of a processed workpiece: in the process of processing the workpiece, setting a plurality of image acquisition time points, and then acquiring image parameters and geometric feature parameters of the workpiece at each image acquisition time point, screening and matching the standard model that is most similar to the workpiece by the geometric feature parameters collected at any of the acquisition time points, and then comparing and matching the image parameters at the corresponding acquisition time point with the standard model to obtain feature points of the workpiece; the image parameters include edge parameters of the workpiece, corner point parameters of the workpiece, and arc parameters of the workpiece; the feature points of the workpiece are distinguishing feature coordinate parameters between the workpiece and the screened and matched standard model; Step B, constructing a point cloud model of the workpiece: three-dimensional reconstruction is performed through the collected feature points of the workpiece to construct a feature point cloud model of the workpiece for positioning and processing tracking in subsequent processing; Step C, constructing a mathematical model of the workpiece: obtaining the standard model in step A, matching a general mathematical model through the standard model, and then fitting the general mathematical model through a feature point cloud model of the workpiece to establish a mathematical model of the workpiece; Step D, matching the clamping tool and the corresponding clamping method: Based on the constructed workpiece mathematical model, use the feature matching algorithm to match it with the clamping tools in the preset clamping tool library, and then obtain the corresponding clamping tool; Match the corresponding clamping method: Based on the matched clamping tool, calculate the clamping force required to clamp the workpiece, and design the motion trajectory of the fixture when clamping or releasing the workpiece; Step E, executing clamping of the workpiece: the execution module clamps and processes the workpiece through a matching clamping tool and a corresponding clamping method; Step F, dynamically adjust the clamping position: according to the error optimization model, the data deviation between the actual clamping position and the target position is analyzed to obtain the analysis result. The control module will automatically adjust the position of the fixture holding the workpiece according to the analysis result, so that the positioning of the workpiece in the fixture is more accurate.

[0019] In a specific embodiment, the several image acquisition points set are specifically the time points when the workpiece is waiting to be clamped in the placement area and needs to be re-clamped after the workpiece is processed. The image acquisition points can be set manually or by the system according to the processing stage time to adapt to the need to adjust the clamping position of the workpiece during the processing process.

[0020] Furthermore, the specific implementation process of step A is as follows: A1. Use a high-resolution camera to perform 360-degree all-round image acquisition of the workpiece to obtain complete appearance information of the workpiece, effectively capture the geometric features of the workpiece, and then obtain the geometric feature parameters; A2, performing image preprocessing on the acquired image information, and then collecting and extracting the workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters through the image preprocessed; A3. Screen and match the most similar standard model through the workpiece geometric feature parameters; compare the collected image parameters with the standard model through a feature point matching algorithm to obtain specific workpiece feature points.

[0021] In a specific embodiment, the geometric features in the collected image parameters are used to match the standard model of the corresponding shape that is most similar to it. For example, when the geometric features of the workpiece being processed are identified as a cylinder or a quasi-cylindrical shape, the parameterization formula of the cylindrical standard model is substituted into the formula. , where r is the radius of the cylinder base, It is expressed as the angle parameter of the cylinder, and the parameter z is the height coordinate of the cylinder. The above parameters can be adjusted through the workpiece geometric parameters in the image parameters. The workpiece geometric feature parameters include length, width, height, corner shape and other data, so as to obtain the most approximate standard model; then the workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters are adapted to the model to obtain specific workpiece feature points.

[0022] Furthermore, in step B, three-dimensional reconstruction is performed through the collected workpiece feature points to construct a point cloud model. The specific implementation process is as follows: B1. The three-dimensional workpiece feature points obtained by image processing and feature extraction algorithm are converted into three-dimensional point clouds, and the point cloud model construction formula ,in is the coordinate of the workpiece in three-dimensional space.

[0023] Furthermore, the step C obtains the standard model in step A, matches the general mathematical model through the standard model, and then fits the general mathematical model through the feature point cloud model of the workpiece to establish the workpiece mathematical model. The specific implementation process is as follows: C1. Obtain the standard model matched in step A, and then match the corresponding universal mathematical model; C2, define the error measure between the point cloud model and the mathematical model by minimizing the error using the least squares method; C3, use the fitting algorithm to adjust the parameters of the general mathematical model so that the general mathematical model fits the point cloud data as closely as possible, and then establish the workpiece mathematical model; the objective function is expressed as ,in represents the point cloud distance calculated for the model, Represented as the actual measured point cloud distance.

[0024] In a specific embodiment, the error metric is defined by the least square method of C2, and then The function is fitted to minimize the error of the generated point cloud model.

[0025] In a specific embodiment, geometric features of the workpiece are extracted according to geometric feature parameters, including planes, curves, curved surfaces, cylinders, cones, spheres, etc., and an applicable mathematical model is selected according to the extracted geometric features to restore the shape features of the workpiece; the mathematical model used can be a linear equation group for describing a straight line or a plane; a polynomial model for describing a more complex shape of a curve or a surface; or a parametric equation for circular features such as a circle or an ellipse; or an implicit function for describing a more complex geometric shape; in the process of construction, one or more mathematical models can be integrated to restore and construct a mathematical model of the workpiece; The optimization error algorithm can be the least squares method, which minimizes the sum of squares between the model prediction value and the actual observation value by optimizing the parameters of the curve or surface; it can also be the gradient descent method, which reduces the error by iteratively adjusting the model parameters; it can also be a genetic algorithm or simulated annealing. For complex nonlinear models, these specific optimization techniques can effectively find approximate optimal solutions; Using the fitting algorithm to adjust the parameters of the mathematical model specifically also includes: using the optimization algorithm to iteratively update the model parameters, ,in Represents the model parameters after iterative update, Represents the model parameters after iterative update, Denoted as the learning rate, It is expressed as the partial derivative of the error function with respect to the parameter. At the same time, when iteratively reducing the error, a convergence threshold is set. When the error of the optimization algorithm is reduced to below the threshold or after a certain number of iterations, it stops. The change in the objective function value is monitored to determine whether it has converged or stopped. ,in and It is expressed as the error value after two consecutive iterations. is the set convergence threshold; to verify the fitting effect of the constructed mathematical model, a visual comparison can be made between the mathematical model and the point cloud data, the fitting accuracy can be analyzed, and the accuracy of the model can be verified.

[0026] Furthermore, based on the constructed workpiece mathematical model, a feature matching algorithm is used to perform feature matching with the clamping tools in the preset clamping tool library to match the corresponding clamping tools. The specific implementation process is as follows: By using the characteristics of the part to be clamped in the mathematical model of the workpiece and the characteristics of the clamping part of the clamping tool, a feature matching algorithm is used to screen and match in a preset clamping tool library, and then select a suitable clamping tool; the preset clamping tool library is a collection of fixtures installed and used on the machine tool.

[0027] In the specific implementation process, based on the key features of the constructed workpiece mathematical model, including shape features, such as contour, curvature, etc.; dimensional parameters, such as length, width, height, diameter, angle and other dimensional information; the extracted feature data are combined into feature vectors ,in is the shape feature vector, is the size information vector; The preset clamping tool library contains summary data of the clamping tools installed and used on the machine tool, wherein each clamp includes a unique identifier, a clamp type (such as gripping, fixing, etc.), a clamp size parameter (such as clamping range, clamping force, etc.) and a clamp shape feature (such as a descriptor of a geometric shape); a suitable feature matching algorithm is selected according to the geometric features of the part to be clamped of the workpiece. In this embodiment, the nearest neighbor algorithm is used to match by calculating the Euclidean distance between feature vectors; the similarity is calculated based on the feature vector of the part to be clamped of the mathematical model of the workpiece and the feature vector of the clamping part of the clamping tool in the clamping tool library, and the Euclidean distance is used. ,in It is expressed as the characteristic vector of the part to be clamped in the mathematical model of the workpiece. It is represented as the feature vector of the clamping part of the clamping tool. The smaller the similarity, the higher the matching degree. The appropriate fixture is selected according to the calculated similarity. The matching threshold can be set manually or by the system. When the similarity is less than the threshold, it is regarded as a matching fixture, and then a matched fixture is obtained. If there are several matching results for subsequent selection, all matching fixtures and their similarity rankings are recorded, and the best fixture is selected according to the ranking.

[0028] Furthermore, in step D, based on the matched clamping tool, the clamping force required to clamp the workpiece is calculated, and the motion trajectory of the clamp when clamping or releasing the workpiece is designed. The specific implementation process is as follows: D1. Based on the type of processing required, calculate and confirm the cutting force on the workpiece during the processing ,in It is expressed as the cutting strength of the current processing. It is expressed as the contact area between the tool and the workpiece during the current machining; D2. Calculate the required clamping force based on the stability requirements of the workpiece and the actual contact conditions of the clamping surface ,in is the friction coefficient between the workpiece and the fixture during the current processing, is the normal force applied by the fixture on the workpiece; D3. Calculate the normal force applied by the fixture on the workpiece ,in is the mass of the workpiece being processed, and g is the acceleration due to gravity; D4. Model the motion trajectory of the fixture and set the linear motion trajectory equation in the Cartesian coordinate system ,in Represented as the initial position parameter of the fixture, Represented as the final position parameter of the fixture, It is expressed as a time progress parameter in the current processing process with a value between 0 and 1; D5. During the movement of the fixture, an S-shaped curve is used for acceleration and deceleration control to ensure that the movement of the fixture during clamping and releasing does not produce impact.

[0029] In the specific implementation process, the cutting cross-sectional area is calculated according to the current processing type and processing requirements. The cutting cross-sectional area is the contact area between the cutting tool and the workpiece during the current processing. It can be manually input or automatically calculated by the system, and then the cutting force exerted on the workpiece during the processing is calculated; for example, in the cutting and drilling operation, through the known workpiece parameters and environmental data, the cutting strength k=100N / cm², the cutting cross-sectional area =50cm², workpiece friction coefficient =0.5, the mass of the workpiece being processed is m=10kg, and the cutting force of the processing is calculated based on the above data =5000N, the required clamping force is =10000N, the normal force of the fixture is 98.1N, set the initial position = (0,0,0), final position =(10,10,5),then the motion trajectory equation is (10t, 10t, 5t), an S-shaped curve is designed through an S-shaped curve model to promote smooth movement during the clamping process, wherein the S-shaped curve model is an S-shaped curve model well known to personnel in this field to ensure smooth acceleration and deceleration of the clamp during the entire clamping and releasing process; the above values ​​are all reference values.

[0030] Furthermore, in step F, the data deviation between the actual holding position and the target position is determined according to the error optimization model, and the control module automatically adjusts the position of the fixture holding the workpiece according to the detection result. The specific implementation process is as follows: F1. Dynamically monitor the position of the workpiece being processed, use sensors to check the current actual position of the workpiece, and compare the current actual position with the predetermined position to obtain the position deviation. ,in It is expressed as the actual clamping position parameter of the workpiece being processed. It is expressed as a predetermined clamping position parameter; F2, according to the obtained position deviation ,in To adjust the amplitude coefficient, is the clamping position parameter after adjustment.

[0031] In the specific implementation process, the control module receives the new clamping position The motion controller is used to adjust the motion of the fixture and the new position coordinates are transmitted through the bus system (such as CAN, Ethernet). The motion controller receives the position information and controls the servo motor or stepper motor to adjust the position of the fixture according to the new coordinates to adjust the position of the workpiece held by the fixture. At the same time, the control module calculates the position from to and The optimal motion trajectory ensures that the fixture moves smoothly and without impact; after adjustment, the sensor will measure the position of the workpiece again to ensure that the clamping position has reached the expected value, and provide feedback to adjust the structure; if the deviation is still within the allowable range, processing can continue; if the deviation exceeds the preset tolerance, the system will repeat steps F1 and F2 for adjustment. The preset tolerance can be set manually or the system can be dynamically adjusted according to the current processing requirements.

[0032] The integrated machining workpiece positioning method of a turning-milling compound machine tool of the present invention truly captures the geometric features of the workpiece through high-resolution image acquisition and deep learning algorithms, and establishes accurate point cloud models and mathematical models, so that the positioning of the workpiece in the subsequent machining process is more precise, and the machining defects caused by positioning errors are significantly reduced; based on the machining requirements of the workpiece at that time, appropriate clamping force and clamping method are designed, so that the workpiece can remain stable during the machining process, and the displacement or damage of the workpiece caused by improper clamping is reduced, thereby improving the machining quality; at the same time, a dynamic monitoring and feedback mechanism is introduced, which can judge the deviation between the actual clamping position and the target position of the workpiece in real time, and make corresponding adjustments to adapt to the displacement or deformation that may occur during the machining process, so as to ensure the continuous and accurate positioning of the workpiece.

[0033] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for positioning a workpiece during integrated machining of a turning-milling compound machine tool, characterized in that: include: Step A, image acquisition of the processed workpiece: during the processing of the workpiece, a number of image acquisition time points are set, and then the image parameters and geometric feature parameters of the workpiece are acquired at each image acquisition time point, and the standard model that is most similar to the workpiece is screened and matched by the geometric feature parameters acquired at any of the acquisition time points, and then the image parameters at the corresponding acquisition time point are compared and matched with the standard model to obtain the workpiece feature points; the image parameters include workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters; the workpiece feature points are distinguishing feature coordinate parameters between the workpiece and the screened and matched standard model; Step B, constructing a point cloud model of the workpiece: three-dimensional reconstruction is performed through the collected feature points of the workpiece to construct a feature point cloud model of the workpiece for positioning and processing tracking in subsequent processing; Step C, constructing a mathematical model of the workpiece: obtaining the standard model in step A, matching a general mathematical model through the standard model, and then fitting the general mathematical model through a feature point cloud model of the workpiece to establish a mathematical model of the workpiece; Step D, matching the clamping tool and the corresponding clamping method: Based on the constructed workpiece mathematical model, use the feature matching algorithm to match it with the clamping tools in the preset clamping tool library, and then obtain the corresponding clamping tool; Match the corresponding clamping method: Based on the matched clamping tool, calculate the clamping force required to clamp the workpiece, and design the motion trajectory of the fixture when clamping or releasing the workpiece; Step E, clamping the workpiece: the execution module clamps the workpiece through a matching clamping tool and a corresponding clamping method; Step F, dynamically adjust the clamping position: according to the error optimization model, the data deviation between the actual clamping position and the target position is analyzed to obtain the analysis result. The control module will automatically adjust the position of the fixture holding the workpiece according to the analysis result, so that the positioning of the workpiece in the fixture is more accurate.

2. The integrated machining workpiece positioning method of a turning-milling compound machine tool according to claim 1 is characterized in that: The specific implementation process of step A is as follows: A1. Use a high-resolution camera to perform 360-degree all-round image acquisition of the workpiece to obtain complete appearance information of the workpiece, effectively capture the geometric features of the workpiece, and then obtain the geometric feature parameters; A2, performing image preprocessing on the acquired image information, and then collecting and extracting the workpiece edge parameters, workpiece corner point parameters and workpiece arc parameters through the image preprocessed; A3. Screen and match the most similar standard model through the workpiece geometric feature parameters; compare the collected image parameters with the standard model through a feature point matching algorithm to obtain specific workpiece feature points.

3. The integrated machining workpiece positioning method of a turning-milling compound machine tool according to claim 1 is characterized in that: The three-dimensional reconstruction of the workpiece feature points collected in step B is performed to construct a point cloud model. The specific implementation process is as follows: B1. The three-dimensional workpiece feature points obtained by image processing and feature extraction algorithm are converted into three-dimensional point clouds, and the point cloud model construction formula ,in is the coordinate of the workpiece in three-dimensional space.

4. The integrated machining workpiece positioning method of a turning-milling compound machine tool according to claim 1 is characterized in that: The step C of obtaining the standard model in step A, matching the general mathematical model through the standard model, and then fitting the general mathematical model through the feature point cloud model of the workpiece to establish the workpiece mathematical model, the specific implementation process is as follows: C1. Obtain the standard model matched in step A, and then match the corresponding universal mathematical model; C2, define the error measure between the point cloud model and the mathematical model by minimizing the error using the least squares method; C3, use the fitting algorithm to adjust the parameters of the general mathematical model so that the general mathematical model fits the point cloud data as closely as possible, and then establish the workpiece mathematical model; the objective function is expressed as ,in represents the point cloud distance calculated for the model, Represented as the actual measured point cloud distance.

5. The integrated machining workpiece positioning method of a turning-milling compound machine tool according to claim 1 is characterized in that: Based on the constructed workpiece mathematical model, the feature matching algorithm is used to match the features of the workpiece with the clamping tools in the preset clamping tool library to match the corresponding clamping tools. The specific implementation process is as follows: By using the characteristics of the part to be clamped in the mathematical model of the workpiece and the characteristics of the clamping part of the clamping tool, a feature matching algorithm is used to screen and match in a preset clamping tool library, and then select a suitable clamping tool; the preset clamping tool library is a collection of fixtures installed and used on the machine tool.

6. The integrated machining workpiece positioning method of a turning-milling compound machine tool according to claim 1, characterized in that: The specific implementation process of step D is as follows: D1. Based on the type of processing required, calculate and confirm the cutting force on the workpiece during the processing ,in It is expressed as the cutting strength of the current processing. It is expressed as the contact area between the tool and the workpiece during the current machining; D2. Calculate the required clamping force based on the stability requirements of the workpiece and the actual contact conditions of the clamping surface ,in is the friction coefficient between the workpiece and the fixture during the current processing, is the normal force applied by the fixture on the workpiece; D3. Calculate the normal force applied by the fixture on the workpiece ,in is the mass of the workpiece being processed, and g is the acceleration due to gravity; D4. Model the motion trajectory of the fixture and set the linear motion trajectory equation in the Cartesian coordinate system ,in Represented as the initial position parameter of the fixture, Represented as the final position parameter of the fixture, It is expressed as a time progress parameter in the current processing process with a value between 0 and 1; D5. During the movement of the fixture, an S-shaped curve is used for acceleration and deceleration control to ensure that the movement of the fixture during clamping and releasing does not produce impact.

7. The integrated workpiece positioning method for a turning-milling compound machine tool according to claim 1 is characterized in that: In step F, the data deviation between the actual holding position and the target position is determined according to the error optimization model to analyze the analysis result, and the control module automatically adjusts the position of the fixture holding the workpiece according to the analysis result. The specific implementation process is as follows: F1. Dynamically monitor the position of the workpiece being processed, use sensors to check the current actual position of the workpiece, and compare the current actual position with the predetermined position to obtain the position deviation. ,in It is expressed as the actual clamping position parameter of the workpiece being processed. It is expressed as a predetermined clamping position parameter; F2, according to the obtained position deviation ,in To adjust the amplitude coefficient, is the clamping position parameter after adjustment.

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