CN118838285B - A method for the tool to quickly find the model coordinates during CNC 3-axis processing - Google Patents
A method for the tool to quickly find the model coordinates during CNC 3-axis processing Download PDFInfo
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- 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
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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Abstract
The invention discloses a method for quickly finding model coordinates of a cutter in a numerical control 3-axis process machining process, which relates to the relevant technical field of computer-aided machining, and comprises the steps of setting initial coordinate values and machining paths, carrying out initial positioning by using preset parameters, accurately positioning the cutter to the initial position of a workpiece, carrying out path planning by using CAD software in a path planning stage, determining the machining path of the cutter according to the geometric shape and machining requirements of the workpiece, carrying out path planning by using CAD software, and predicting coordinate points of the next cutter positioning by using preloaded workpiece model data and a prediction algorithm in a cutter motion control and prediction stage, thereby improving the precision and efficiency of cutter positioning; the process builds a prediction model, inputs the workpiece surface model and the current cutter position characteristics, outputs the predicted value of the next cutter position, dynamically adjusts the prediction model according to the real-time sensor data, and adapts to the actual condition change of the workpiece surface.
Description
Technical Field
The invention relates to the technical field of computer-aided machining, in particular to a method for quickly finding model coordinates by a cutter in a numerical control 3-axis technological machining process.
Background
Numerical control machining processes include most commonly milling and turning, and secondarily grinding, electric discharge machining, etc., where a rotating tool is used for the surface of a workpiece, and moving along 3,4, or 5 axes, and milling essentially cuts or trims the workpiece, and can rapidly machine complex geometries and precision parts from metal or thermoplastic, and turning is the use of lathes to manufacture parts that contain cylindrical features.
For example, patent publication No. CN110096034B discloses a reconstruction method of three-axis tool path curved surface transverse information based on a projection algorithm, which comprises the following steps of (1) recording indexes of each tool position point according to a tool position file and storing the indexes according to a KD-Tree structure, (2) searching adjacent track projection points of each tool position point based on the data stored in the step (1), and pairing and storing the adjacent track projection points with corresponding tool position points, so that transverse information of a tool path curved surface formed by pairing all the tool position points with the corresponding adjacent track projection points is obtained, wherein the adjacent track projection points are closest points to seed points on adjacent tool paths, the tool path curved surface is the curved surface containing all the tool position points in the tool path, the invention does not need to reconstruct the curved surface, reduces calculation load, considers the transverse information of the tool path, and has good optimization effect and strong applicability.
Although the above-mentioned solution has the advantages as described above, the conventional method for quickly finding the model coordinates by the tool during the machining process of the numerical control 3-axis process is limited in manual adjustment accuracy and low in efficiency, and once the positioning of the tool is completed, when the path adjustment is required during the machining stage, the real-time monitoring and adjustment mechanism is often lacking, and the change of the workpiece surface cannot be timely dealt with, so that a method for quickly finding the model coordinates by the tool during the machining process of the numerical control 3-axis process is needed to solve the problems.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for quickly finding the model coordinates by a cutter in the machining process of a numerical control 3-axis process, which solves the problems that the traditional method for quickly finding the model coordinates by the cutter in the machining process of the numerical control 3-axis process in the prior art is limited in manual adjustment precision and low in efficiency, and once the positioning of the cutter is finished, when path adjustment is needed in the machining stage, a real-time monitoring and adjusting mechanism is often lacking, and the change of the surface of a workpiece cannot be timely dealt with.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
The invention provides a method for quickly finding model coordinates by a cutter in a numerical control 3-axis technical processing process, which comprises the following steps:
Step 1, initial positioning, namely setting an initial coordinate value and a machining path of a cutter, and utilizing preset parameters to perform initial positioning to position the cutter to an initial position of a workpiece;
step 2, path planning, namely pre-designing and generating a cutter path in CAD software, and determining a machining path of the cutter according to the geometric shape and machining requirements of a workpiece, wherein the machining path comprises a cutting path, a cutting direction and cutting depth parameters;
Step 3, initial tool motion control and prediction, namely controlling the motion trail and speed of a tool, including control of X, Y, Z axis coordinates of the tool, preloading a workpiece model into a numerical control system before machining;
step 4, monitoring and positioning and adjusting the workpiece in real time in the processing stage, deploying a displacement sensor and a camera, monitoring the surface condition of the workpiece in real time, collecting sensor data, dynamically adjusting a prediction model according to the real-time data, and adjusting the position and the posture of a cutter in real time according to the actual condition of the surface of the workpiece and the sensor data so as to accurately align the cutter with the surface of the workpiece;
and 5, redundancy control, deploying a system architecture with high redundancy and fault tolerance, and providing multiple backup and redundancy control mechanisms, and automatically switching to a standby mode under abnormal conditions.
The invention is further arranged that the initial positioning step in step 1 comprises:
Setting an initial coordinate value and a processing path of a tool, wherein the initial coordinate value of the tool is set in a numerical control system and comprises X, Y, Z axis coordinates;
setting a machining path of a cutter, wherein the machining path comprises a cutting path, a cutting direction and cutting depth parameters;
initial positioning is carried out by using preset parameters, and a cutter is positioned in a numerical control system according to preset initial coordinate values;
Moving the cutter to a preset initial position by using a motion control function provided by a numerical control system;
Determining an initial machining position according to the CAD model of the workpiece, converting a coordinate system by using a numerical control system, and positioning the cutter to the initial position of the workpiece;
simultaneously recording a cutter coordinate value and a machining path parameter used for initial positioning;
the invention further provides that the path planning mode in the step 2 is as follows:
Importing a CAD model file of the workpiece by using CAD software;
determining basic requirements of a processing path, including surface smoothness and dimensional accuracy, according to the geometric shape and the processing requirements of a workpiece;
according to the workpiece material, the processing requirement and the cutter performance, adopting a corresponding processing technology, and drawing a cutting path in CAD software by using a corresponding technology function;
Determining the trend, shape and spacing of a cutting path according to the machining requirements and the geometric shape of a workpiece;
setting a cutting direction, including a feed direction and a cutting direction, based on the determined trend, shape, and pitch of the cutting path;
the invention is further arranged that the work piece model construction step comprises:
Scanning the surface of the workpiece by using a three-dimensional laser scanner to obtain three-dimensional point cloud data of the surface;
Processing the scanned point cloud data, including filtering and point cloud registration, to obtain a three-dimensional model of the surface of the workpiece;
generating a three-dimensional surface model of the workpiece by using point cloud data and adopting a grid-based reconstruction algorithm;
constructing a predictive model, the input parameters including 、And,
Wherein, Representing three-dimensional grid data for a three-dimensional model of the surface of the workpiece,Is the characteristic vector of the current position of the cutter, comprising position coordinates, cutting speed and acceleration,A predicted value indicating a next tool position;
The input of the prediction model is AndOutput as a value;
Training the prediction model and the processing data, learning the relation between the workpiece surface and the tool motion, and adopting back propagationThe algorithm and the optimizer optimize model parameters and reduce prediction errors;
The invention further provides that in the step 3, the construction mode of the prediction algorithm is as follows:
preparing training set and verification set, constructing prediction model based on long-short-term memory network LSTM, defining input parameters including ,AndWherein, the method comprises the steps of, wherein,Representing three-dimensional grid data for a three-dimensional model of the surface of the workpiece,Is the characteristic vector of the current position of the cutter, comprising position coordinates, cutting speed and acceleration,A predicted value indicating a next tool position;
Training the neural network model by using a back propagation algorithm and a gradient descent optimization algorithm, wherein an optimization loss function formula is as follows: Wherein For the actual tool position,For the number of samples to be taken,Representing a time step;
verifying the trained neural network model by using a verification set, and adjusting the model structure and the super parameters;
before machining, the characteristic vector of the current position of the cutter is calculated And a three-dimensional model of the surface of the workpieceInputting a trained neural network model;
The model outputs the predicted value of the next cutter position ;
The invention further provides that the real-time monitoring and positioning adjustment steps of the workpiece in the step 4 comprise the following steps:
the displacement sensor and the camera are arranged on processing equipment to monitor the condition of the surface of the workpiece in real time, and continuously monitor the condition of the surface of the workpiece, including the surface shape, the roughness and the temperature;
the method comprises the steps of collecting sensor data, processing and analyzing, dynamically adjusting a prediction model according to the real-time sensor data to predict the position of a cutter at the next step;
the invention is further provided that the step of real-time monitoring, positioning and adjusting the workpiece in the step 4 further comprises the following steps:
updating model parameters according to new data by adopting a self-adaptive algorithm, and adapting to actual condition changes of the surface of the workpiece;
according to the cutter position predicted value output by the prediction model and the real-time sensor data, the position and the posture of the cutter are adjusted in real time;
the control function provided by the numerical control system is used for adjusting the processing path and the movement track of the cutter, so that the cutter is accurately aligned with the surface of the workpiece;
According to the position and the gesture of the cutter after the real-time adjustment, the cutter is accurately aligned with the surface of the workpiece, and the position and the gesture of the cutter are adjusted to be completely attached to the surface of the workpiece;
The invention is further arranged that in the step 4, the mode of predicting the position of the cutter in the next step is as follows:
Continuously monitoring the surface condition of a workpiece by using a displacement sensor and a camera, collecting related sensor data, and preprocessing the collected data, wherein the preprocessing comprises noise filtering, data alignment and calibration;
Using a neural network model based on deep learning, taking real-time sensor data as input characteristics of the model, and predicting an output value of a next cutter position;
Updating model parameters according to actual prediction errors by using a gradient descent method;
Defining a difference between a predicted value and an actual value of a loss function measurement model;
According to the cutter position predicted value output by the updated prediction model, the position and the posture of the cutter are adjusted by combining with real-time sensor data;
the invention is further arranged that the redundant control system architecture comprises:
the main control module is responsible for monitoring the running state of the processing equipment, controlling the processing process and processing various instructions;
The redundant main control module is used for performing main-standby switching and fault-tolerant control;
The backup control module is used as a backup of the main control module, keeps synchronous with the main control module, prepares to take over control right at any time, and communicates with the main control module in real time through a redundant communication link;
The power supply module is used for providing power supply required by equipment, is provided with a redundant power supply module and can be automatically switched to a standby power supply when the main power supply fails;
the invention is further arranged that the redundant control system architecture further comprises:
The sensor module is responsible for monitoring parameters of workpieces and equipment, including temperature, pressure and speed, is provided with a redundant sensor module, and can continuously acquire data when the sensor fails;
The execution module is used for controlling the movement and the gesture of the cutter;
The communication module is responsible for communicating with external equipment and systems, and comprises an industrial personal computer and a monitoring system;
And the fault detection and automatic switching module is used for implementing abnormality detection and automatic switching logic, monitoring the running states of all modules of the system and automatically switching to a standby mode when a fault is detected.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, through preloading the workpiece model and utilizing a prediction algorithm, accurate prediction of the cutter position is realized, and the positioning precision and efficiency are improved;
According to the invention, by arranging the displacement sensor and the camera, the surface condition of the workpiece is monitored in real time, sensor data are collected, and the real-time adjustment of the position and the posture of the cutter is realized according to the dynamic adjustment of the real-time data, so that the accurate alignment of the cutter and the surface of the workpiece is ensured;
The invention is provided with multiple backup and redundancy control mechanisms, so that the system is ensured to be automatically switched to a standby mode under abnormal conditions, and the stability and the safety of the processing process are improved;
The invention sets an initial coordinate value and a processing path and utilizes preset parameters to perform initial positioning, a cutter is accurately positioned to an initial position of a workpiece, a path planning stage utilizes CAD software to predesign and generate a cutter path, the processing path of the cutter is determined according to the geometric shape and the processing requirement of the workpiece, path planning is performed through the CAD software, and a coordinate point of the next cutter positioning is predicted by utilizing preloaded workpiece model data and a prediction algorithm in a cutter motion control and prediction stage, so that the precision and efficiency of cutter positioning are improved;
In the real-time monitoring and adjusting stage, a displacement sensor and a camera are deployed, the surface condition of a workpiece is monitored in real time, sensor data are collected, a prediction model is dynamically adjusted according to the real-time data, a cutter is accurately aligned with the surface of the workpiece, and the position and the gesture of the cutter are dynamically adjusted according to a cutter position prediction value output by the prediction model and combined with the real-time sensor data, so that the accurate alignment of the cutter with the surface of the workpiece is realized;
And finally, in the redundancy control and safety guarantee stage, deploying a system architecture with strong redundancy and high fault tolerance, and providing a multiple backup and redundancy control mechanism, wherein the system architecture can be automatically switched to a standby mode or a safety state under an abnormal condition, so that the stability and safety of the processing process are ensured.
Drawings
FIG. 1 is a flow chart of a method for quickly finding model coordinates by a cutter in the numerical control 3-axis technical processing process.
Detailed Description
In order that those skilled in the art will better understand the present invention, a detailed description of embodiments of the present invention will be provided below, with reference to the accompanying drawings, wherein it is apparent that the described embodiments are only some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above-described drawings are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the attached drawing figures:
Example 1
Referring to fig. 1, the invention provides a method for quickly finding model coordinates by a cutter in a numerical control 3-axis technical processing process, which comprises the following steps:
Step 1, initial positioning, namely setting an initial coordinate value and a machining path of a cutter, and utilizing preset parameters to perform initial positioning to position the cutter to an initial position of a workpiece;
the initial positioning step in the step 1 comprises the following steps:
Setting an initial coordinate value and a processing path of a tool, wherein the initial coordinate value of the tool is set in a numerical control system and comprises X, Y, Z axis coordinates;
setting a machining path of a cutter, wherein the machining path comprises a cutting path, a cutting direction and cutting depth parameters;
initial positioning is carried out by using preset parameters, and a cutter is positioned in a numerical control system according to preset initial coordinate values;
Moving the cutter to a preset initial position by using a motion control function provided by a numerical control system;
Determining an initial machining position according to the CAD model of the workpiece, converting a coordinate system by using a numerical control system, and positioning the cutter to the initial position of the workpiece;
simultaneously recording a cutter coordinate value and a machining path parameter used for initial positioning;
The initial positioning is implemented through the step 1, so that the cutter is accurately positioned to the initial position of the workpiece;
step 2, path planning, namely pre-designing and generating a cutter path in CAD software, and determining a machining path of the cutter according to the geometric shape and machining requirements of a workpiece, wherein the machining path comprises a cutting path, a cutting direction and cutting depth parameters;
the path planning method in the step 2 is as follows:
Importing a CAD model file of the workpiece by using CAD software;
determining basic requirements of a processing path, including surface smoothness and dimensional accuracy, according to the geometric shape and the processing requirements of a workpiece;
according to the workpiece material, the processing requirement and the cutter performance, adopting a corresponding processing technology, and drawing a cutting path in CAD software by using a corresponding technology function;
Determining the trend, shape and spacing of a cutting path according to the machining requirements and the geometric shape of a workpiece;
setting a cutting direction, including a feed direction and a cutting direction, based on the determined trend, shape, and pitch of the cutting path;
Path planning is carried out in CAD software so as to determine the machining path of the tool;
Step 3, initial tool motion control and prediction, namely controlling the motion trail and speed of a tool, including control of X, Y, Z axis coordinates of the tool, preloading a workpiece model into a numerical control system before machining;
the work piece model construction step includes:
Scanning the surface of the workpiece by using a three-dimensional laser scanner to obtain three-dimensional point cloud data of the surface;
Processing the scanned point cloud data, including filtering and point cloud registration, to obtain a three-dimensional model of the surface of the workpiece;
generating a three-dimensional surface model of the workpiece by using point cloud data and adopting a grid-based reconstruction algorithm;
constructing a predictive model, the input parameters including ,And,
Wherein, Representing three-dimensional grid data for a three-dimensional model of the surface of the workpiece,Is the characteristic vector of the current position of the cutter, comprising position coordinates, cutting speed and acceleration,A predicted value indicating a next tool position;
The input of the prediction model is AndThe output is a value, and the output is a value,;
Training a prediction model and processing data, learning the relation between the surface of a workpiece and the movement of a cutter, and optimizing model parameters by adopting a back propagation algorithm and an optimizer;
In step 3, the prediction algorithm is constructed in the following manner:
preparing training set and verification set, constructing prediction model based on long-short-term memory network LSTM, defining input parameters including ,AndWherein, the method comprises the steps of, wherein,Representing three-dimensional grid data for a three-dimensional model of the surface of the workpiece,Is the characteristic vector of the current position of the cutter, comprising position coordinates, cutting speed and acceleration,A predicted value indicating a next tool position;
Training the neural network model by using a back propagation algorithm and a gradient descent optimization algorithm, wherein an optimization loss function formula is as follows: Wherein For the actual tool position,For the number of samples to be taken,Representing a time step;
verifying the trained neural network model by using a verification set, and adjusting the model structure and the super parameters;
before machining, the characteristic vector of the current position of the cutter is calculated And a three-dimensional model of the surface of the workpieceInputting a trained neural network model;
The model outputs the predicted value of the next cutter position ;
Constructing a prediction model by using a deep learning technology, and realizing accurate prediction of the next cutter positioning;
step 4, monitoring and positioning and adjusting the workpiece in real time in the processing stage, deploying a displacement sensor and a camera, monitoring the surface condition of the workpiece in real time, collecting sensor data, dynamically adjusting a prediction model according to the real-time data, and adjusting the position and the posture of a cutter in real time according to the actual condition of the surface of the workpiece and the sensor data so as to accurately align the cutter with the surface of the workpiece;
The method comprises installing displacement sensor and camera on processing equipment, monitoring the surface condition of workpiece in real time, continuously monitoring the surface condition of workpiece, including surface shape, roughness, and temperature,
The method comprises the steps of collecting sensor data, processing and analyzing, dynamically adjusting a prediction model according to the real-time sensor data to predict the position of a cutter at the next step;
Updating model parameters according to new data by adopting a self-adaptive algorithm, adapting to the actual condition change of the surface of a workpiece, adjusting the position and the gesture of a cutter in real time according to a cutter position predicted value output by a predicted model and real-time sensor data, adjusting the processing path and the motion track of the cutter by using a control function provided by a numerical control system to enable the cutter to be accurately aligned with the surface of the workpiece, and accurately aligning the cutter with the surface of the workpiece according to the position and the gesture of the cutter after the real-time adjustment, and adjusting the position and the gesture of the cutter to enable the cutter to be completely attached with the surface of the workpiece;
the mode of predicting the position of the cutter in the next step is as follows:
Continuously monitoring the surface condition of a workpiece by using a displacement sensor and a camera, collecting related sensor data, and preprocessing the collected data, wherein the preprocessing comprises noise filtering, data alignment and calibration;
Using a neural network model based on deep learning, taking real-time sensor data as input characteristics of the model, and predicting an output value of a next cutter position;
Updating model parameters according to actual prediction errors by using a gradient descent method;
Defining a difference between a predicted value and an actual value of a loss function measurement model;
According to the cutter position predicted value output by the updated prediction model, the position and the posture of the cutter are adjusted by combining with real-time sensor data;
step 5, redundancy control, deploying a system architecture with high redundancy and fault tolerance, and providing multiple backup and redundancy control mechanisms, and automatically switching to a standby mode under abnormal conditions;
The redundant control system architecture includes:
the main control module is responsible for monitoring the running state of the processing equipment, controlling the processing process and processing various instructions;
The redundant main control module is used for performing main-standby switching and fault-tolerant control;
The backup control module is used as a backup of the main control module, keeps synchronous with the main control module, prepares to take over control right at any time, and communicates with the main control module in real time through a redundant communication link;
The power supply module is used for providing power supply required by equipment, is provided with a redundant power supply module and can be automatically switched to a standby power supply when the main power supply fails;
The redundant control system architecture further includes:
The sensor module is responsible for monitoring parameters of workpieces and equipment, including temperature, pressure and speed, is provided with a redundant sensor module, and can continuously acquire data when the sensor fails;
The execution module is used for controlling the movement and the gesture of the cutter;
The communication module is responsible for communicating with external equipment and systems, and comprises an industrial personal computer and a monitoring system;
And the fault detection and automatic switching module is used for implementing abnormality detection and automatic switching logic, monitoring the running states of all modules of the system and automatically switching to a standby mode when a fault is detected.
The invention sets an initial coordinate value and a processing path and utilizes preset parameters to perform initial positioning, a cutter is accurately positioned to an initial position of a workpiece, a path planning stage utilizes CAD software to predesign and generate a cutter path, the processing path of the cutter is determined according to the geometric shape and the processing requirement of the workpiece, path planning is performed through the CAD software, and a coordinate point of the next cutter positioning is predicted by utilizing preloaded workpiece model data and a prediction algorithm in a cutter motion control and prediction stage, so that the precision and efficiency of cutter positioning are improved;
In the real-time monitoring and adjusting stage, a displacement sensor and a camera are deployed, the surface condition of a workpiece is monitored in real time, sensor data are collected, a prediction model is dynamically adjusted according to the real-time data, a cutter is accurately aligned with the surface of the workpiece, and the position and the gesture of the cutter are dynamically adjusted according to a cutter position prediction value output by the prediction model and combined with the real-time sensor data, so that the accurate alignment of the cutter with the surface of the workpiece is realized;
And finally, in the redundancy control and safety guarantee stage, deploying a system architecture with strong redundancy and high fault tolerance, and providing a multiple backup and redundancy control mechanism, wherein the system architecture can be automatically switched to a standby mode or a safety state under an abnormal condition, so that the stability and safety of the processing process are ensured.
The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.
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| CN109318051A (en) * | 2018-10-17 | 2019-02-12 | 芜湖常瑞汽车部件有限公司 | A kind of curved surface part numerical control processing localization method |
| CN117718831A (en) * | 2024-01-16 | 2024-03-19 | 浙江万丰科技开发股份有限公司 | Off-line programming method of full six-axis CNC rough machining polishing equipment |
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| CN109318051A (en) * | 2018-10-17 | 2019-02-12 | 芜湖常瑞汽车部件有限公司 | A kind of curved surface part numerical control processing localization method |
| CN117718831A (en) * | 2024-01-16 | 2024-03-19 | 浙江万丰科技开发股份有限公司 | Off-line programming method of full six-axis CNC rough machining polishing equipment |
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