Frozen sand mold precision manufacturing surface quality on-line detection system and method

Abstract

According to the frozen sand mold precise manufacturing surface quality online detection system and method, numerical control machining frozen sand molds serve as research objects, the numerical control machining process is divided into different machining stages, machining and detection are carried out in stages, the detection result is used for assisting machining of the next stage, and the machining efficiency is improved. Full-flow online detection and process regulation and control of numerical control machining of the frozen sand mold are realized, multi-index automatic and intelligent surface quality detection can be performed on the frozen sand mold by building an intelligent detection device, a judgment basis is provided for quality monitoring and process parameter adjustment in the machining process, the automation level of the manufacturing process is improved, and the production efficiency is improved. And the method has obvious engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of sand mold detection, and in particular relates to an online detection system and method for the surface quality of frozen sand mold precision manufacturing. Background Art

[0002] Digital frozen sand mold green casting forming technology is a new casting manufacturing technology that integrates digital manufacturing and green manufacturing. It uses water as a binder to make frozen sand blanks at low temperature, obtains castings through digital model design and manufacturing, and obtains the required castings through direct pouring or negative pressure pouring. There is no waste gas and waste sand pollution in the pouring process. After the pouring is completed, the molding sand naturally collapses, and the molding sand material can be directly recycled, which has a high green manufacturing application value.

[0003] During the frozen sand mold processing, the temperature of the processing area is usually constant between -20℃ and 0℃. In order to ensure the quality of frozen sand mold CNC processing, workers are required to enter the processing area for quality inspection during the processing. When the temperature difference between the ambient temperature and the processing area is large, the operators' long-term travel back and forth between the processing area is easy to affect their health and significantly affect the thermal balance of the processing environment. At the same time, manual inspection efficiency is low. At present, there is no relevant automated inspection method that can meet the quality inspection requirements of the frozen sand mold processing process. Summary of the invention

[0004] To solve the above problems, the present invention discloses an online detection system for the surface quality of frozen sand mold precision manufacturing, which can realize the online detection requirements of quality indicators during the frozen sand mold processing process and solve the problems of low efficiency of manual detection and inability to achieve automated detection.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: an online detection system for the surface quality of frozen sand mold precision manufacturing, characterized in that it includes a CNC machine tool, a frozen sand mold, a robotic arm, a data collector and an intelligent control system; the data collector is fixedly installed on the robotic arm, and the robotic arm is installed on one side of the CNC machine tool processing area; the intelligent control system is installed on the side of the CNC machine tool away from the processing area.

[0006] Preferably, the robotic arm is installed on one side of the processing area, and is used to move the data collector to above the frozen sand mold to collect surface morphology data during the processing.

[0007] Preferably, the intelligent control system is used to realize the processing and analysis of data collected from the surface of frozen sand molds and the equipment operation control.

[0008] Preferably, the data collector can be any one or more of a 2D industrial camera, a stereo vision camera, a 3D camera, a line laser scanner and a grating scanner, and is used to collect the surface morphology of frozen sand molds of different sizes and accuracy ranges.

[0009] Preferably, the CNC machine tool may be a three-axis milling device or a five-axis machining center.

[0010] At the same time, a method for online detection of surface quality of frozen sand mold precision manufacturing is provided, comprising the following steps:

[0011] Step 1: Input the frozen sand mold milling model, divide the milling process into different processing stages according to the frozen sand mold model, set the tool to automatically pause processing at the end of each stage, move it to the specified position, output the processing program, and import it into the intelligent control system.

[0012] Step 2: Place the prepared frozen sand blank into the processing position of the CNC machine tool, perform milling according to the input program, automatically pause the processing according to the program at different stages of the processing, and move the spindle out of the frozen sand mold processing area.

[0013] Step 3: Plan the data collection path. The intelligent control system controls the robotic arm and the data collector to move to the top of the frozen sand mold, and collects point cloud data on the surface of the frozen sand mold according to the planned path. After the collection is completed, the robotic arm and the data collector return to their initial position.

[0014] Step 4: The intelligent control system determines the surface roughness, sand removal rate and dimensional accuracy information of the frozen sand mold CNC machining based on the collected surface point cloud data through data processing and analysis, and adjusts the machining parameters.

[0015] Step 5: The spindle of the CNC machine tool moves to the end position of the previous processing stage of the frozen sand mold according to the program settings, and continues to the next stage of processing. After the processing is completed, the spindle is automatically moved out of the frozen sand mold processing area, and the inspection tasks of steps 3 and 4 are repeated until the last stage of the CNC processing program is completed and the processing task is ended.

[0016] Step 6: After the processing and inspection tasks at each stage are completed accurately, the finished frozen sand mold with good surface quality can be obtained.

[0017] Preferably, the processing is divided into several stages, and data sampling is performed after the processing of different stages is completed.

[0018] Preferably, the CNC machining surface roughness detection method in step 4 specifically includes: Step 1: Select the point cloud of the specified machining surface measurement area, perform Gaussian filtering on the selected point cloud, and remove outlier noise points. Step 2: Fit the selected point cloud using the least squares method to obtain the reference plane of the point cloud. Step 3: Traverse all selected sampling points, calculate the absolute distance value from each point to the reference plane point by point, calculate the average value of the absolute distance value from each point to the reference plane according to the roughness calculation formula (1), and obtain the CNC machining surface roughness information.

[0019]

[0020] Where m is the number of point clouds in the measurement area, P m is any point inside the point cloud, P m Projection point on the reference plane. Preferably, the step 4 CNC machining sand removal rate detection method specifically includes: Step 1: Segment the collected frozen sand mold point cloud data and remove the point cloud outside the processing area. Step 2: Perform noise reduction processing on the three-dimensional point cloud of the remaining cutting area, remove the outlier point cloud, grid the remaining point cloud, and create an approximate three-dimensional model of the cutting cavity. Step 3: Divide the approximate three-dimensional model into a collection of many vertical slices, calculate the volume of each slice respectively, and use the numerical integration method to obtain the volume of the complete three-dimensional model according to the slice volume, and obtain the model volume of the CNC machined frozen sand mold with cutting sand particles. Step 4: According to the designed casting shape, calculate the complete volume V of the cavity when there are no sand particles, and calculate the sand removal rate value according to formula (2).

[0021]

[0022] Among them, V1 is the volume of the model with cutting sand particles, and V is the complete volume of the cavity when there are no sand particles.

[0023] Preferably, the step 4 CNC machining dimensional accuracy detection method specifically includes: Step 1: preprocessing the collected frozen sand mold three-dimensional point cloud, removing noise, performing point cloud cutting, and retaining the cutting area point cloud. Step 2: Using the cutting model as the reference model for three-dimensional size alignment, performing corner point detection on the cutting area point cloud, using the model corner points as feature descriptors, performing model coarse alignment between the cutting model and the point cloud data, and determining the pose relationship between the model and the point cloud. Step 3: After the coarse alignment is completed, the ICP algorithm is used to perform precise alignment between the model and the point cloud. After the alignment is completed, the size deviation between the point cloud and the model is calculated, and the three-dimensional size accuracy detection of the frozen sand mold is realized by comparing the point cloud with the cutting model.

[0024] Preferably, the frozen sand mold is a sand mold composed of one or more materials selected from silica sand, zircon sand, chromite sand, olivine sand, corundum sand and water glass sand.

[0025] Preferably, the operating temperature of the data collector is above -20°C.

[0026] Compared with the prior art, the present invention has the following advantages:

[0027] 1. The present invention can realize automatic detection of the frozen sand mold processing process under low temperature conditions, avoiding the errors of manual detection and the damage to the health of workers.

[0028] 2. The present invention can meet the detection requirements of different technical indicators such as surface defects, surface roughness, sand removal rate and dimensional accuracy of frozen sand molds, improve the integrated analysis and detection capabilities of the processing process, save detection time, and reduce the scrap rate of casting processing.

[0029] 3. The present invention can realize a data acquisition mode that integrates multiple data acquisition methods such as two-dimensional sampling, three-dimensional spatial sampling and mixed sampling of the frozen sand mold surface morphology, quickly acquire the sand mold processing surface morphology according to different detection characteristics, and realize accurate detection of multiple quality targets.

[0030] 4. The present invention divides the CNC machining process into different stages to achieve quality detection of the frozen sand mold machining process, laying a technical foundation for online process control of frozen sand mold CNC machining. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the system device of the present invention.

[0032] Figure 2 It is a process flow chart of the present invention.

[0033] List of reference numerals:

[0034] 1-CNC machine tool; 2-frozen sand mold; 3-robotic arm; 4-data collector; 5-intelligent control system. DETAILED DESCRIPTION

[0035] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. It should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to directions in the accompanying drawings, and the words "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0036] like Figure 1 As shown, the present invention provides an online detection system for the surface quality of precise manufacturing of frozen sand molds, including a CNC machine tool, a frozen sand mold, a robotic arm, a data collector and an intelligent control system; the data collector is fixedly installed on the robotic arm, and the robotic arm is installed on one side of the CNC machine tool processing area; the intelligent control system is installed on the side of the CNC machine tool away from the processing area.

[0037] The intelligent control system of this embodiment mainly includes four modules: the first is the robot arm movement control module, which is responsible for moving the camera to realize point cloud data collection. The second, third and fourth modules correspond to the three detection content modules of roughness detection, sand removal rate detection and size accuracy detection respectively.

[0038] In this embodiment, the robotic arm is installed on one side of the processing area, and is used to move the data collector to the top of the frozen sand mold to collect surface morphology data during the processing.

[0039] In this embodiment, the intelligent control system is used to realize the processing and analysis of the data collected from the surface of the frozen sand mold and the equipment operation control.

[0040] In this embodiment, the data collector is a combination of a 2D industrial camera and a 3D camera, wherein the 2D industrial camera is used for two-dimensional cutting profile size detection, and the 3D camera is used for frozen sand mold surface roughness, sand removal conditions and three-dimensional dimensional accuracy detection.

[0041] In this embodiment, the CNC machine tool may be a three-axis milling forming device or a five-axis machining center, which can realize rapid data collection and analysis under different machining forms.

[0042] Example 2

[0043] This embodiment provides a digital frozen sand mold surface roughness online detection method, comprising the following steps:

[0044] Step 1: Input the frozen sand mold milling model, divide the milling process into different processing stages according to the frozen sand mold model, set the tool to automatically pause processing at the end of each stage, move it to the specified position, output the processing program, and import it into the intelligent control system.

[0045] Step 2: Place the prepared frozen sand blank into the processing position of the CNC machine tool. The temperature of the processing area is -8°C. The spindle of the CNC machine tool performs milling processing according to the input program. At different stages of processing, the processing is automatically paused according to the program, and the spindle is moved out of the frozen sand mold processing area.

[0046] Step 3: The data collector selects the 3D camera, and the intelligent control system controls the robotic arm and the 3D camera to move above the frozen sand mold. After reaching the specified position, the point cloud data of the frozen sand mold surface is collected. After the collection is completed, the robotic arm and 3D return to the initial position.

[0047] Step 4: The intelligent control system fits the point cloud reference surface according to the collected frozen sand mold point cloud data, calculates the surface roughness by traversing the average distance from all points in the point cloud to the reference surface, and compares it with the CNC machining roughness reference to determine whether to adjust the machining process and adjust the machining parameters.

[0048] Step 5: The spindle of the CNC machine tool moves to the end position of the previous processing stage of the frozen sand mold according to the program settings, and continues to the next stage of processing. After the processing is completed, the spindle is automatically moved out of the frozen sand mold processing area, and the inspection tasks of steps 3 and 4 are repeated.

[0049] Step 6: After the processing and inspection tasks at each stage are completed accurately, the finished frozen sand mold with good surface quality can be obtained.

[0050] In this embodiment, the processing process is divided into several stages according to the complexity of the shape of the cut sand mold. For simple shapes, the test is performed once halfway through the processing. For complex shapes, the key positions of the cutting process can be divided into multiple stages for testing. The purpose is to find quality problems in time during the processing process to avoid finding problems after the processing is completed, which reduces efficiency; data sampling is performed after the processing of different stages is completed.

[0051] In this embodiment, the method for detecting the roughness of a CNC machining surface in step 4 includes: Step 1: Selecting a point cloud of a specified machining surface measurement area, performing Gaussian filtering on the selected point cloud, and removing outlier noise points. Step 2: Fitting the selected point cloud using the least squares method to obtain the reference plane of the point cloud. Step 3: Traversing all selected sampling points, calculating the absolute distance value from each point to the reference plane point by point, and calculating the average value of the absolute distance value from each point to the reference plane according to the roughness calculation formula (1) to obtain the roughness information of the CNC machining surface.

[0052]

[0053] Where m is the number of point clouds in the measurement area, P m is any point inside the point cloud, P dm P m Projected point on the datum plane.

[0054] In this embodiment, the operating temperature of the data collector is above -20°C.

[0055] The technical means disclosed in the scheme of the present invention are not limited to the technical means disclosed in the above-mentioned implementation mode, but also include technical schemes composed of any combination of the above technical features.

Claims

1. An online detection system for surface quality of frozen sand mold precision manufacturing, characterized in that: The invention comprises a numerical control machine tool (1), a frozen sand mold (2), a mechanical arm (3), a data collector (4) and an intelligent control system (5); the data collector (4) is fixedly mounted on the mechanical arm (3), the mechanical arm (3) is mounted on one side of a processing area of ​​the numerical control machine tool (1), and is used to move the data collector (4) to the top of the frozen sand mold to collect surface morphology data during the processing; the intelligent control system (5) is mounted on the side of the numerical control machine tool away from the processing area.

2. According to claim 1, a frozen sand mold precision manufacturing surface quality online detection system is characterized in that: The intelligent control system (5) is used to realize processing and analysis of data collected from the surface of frozen sand molds and equipment operation control.

3. The online detection system for surface quality of frozen sand mold precision manufacturing according to claim 1 is characterized in that: The data collector (4) is used in combination with any one or more of a 2D industrial camera, a stereo vision camera, a 3D camera, a line laser scanner and a grating scanner to collect the surface morphology of frozen sand molds of different sizes and accuracy ranges.

4. The online detection system for surface quality of frozen sand mold precision manufacturing according to claim 1 is characterized in that: The numerically controlled machine tool (1) adopts a three-axis milling forming device or a five-axis machining center.

5. A method for online detection of surface quality of frozen sand mold precision manufacturing, characterized in that: The following steps are involved: Step 1: Input the milling model of the frozen sand mold (2), divide the milling process into different processing stages according to the frozen sand mold model, set the tool to automatically pause processing at the end of each stage, move it out to a specified position, output the processing program, and import it into the intelligent control system (5); Step 2: placing the prepared frozen sand blank into the processing position of the CNC machine tool (1), performing milling processing according to the input program, pausing the processing automatically according to the program at different stages of the processing, and moving the spindle out of the processing area of ​​the frozen sand mold (1); Step 3: Perform data collection and path planning. The intelligent control system (5) controls the robot arm (3) and the data collector (4) to move to the top of the frozen sand mold (2), and collects the three-dimensional point cloud data of the frozen sand mold (2) according to the planned path. After the collection is completed, the robot arm (3) and the data collector (4) return to the initial position; Step 4: The intelligent control system (5) determines the surface roughness, sand removal rate and dimensional accuracy information of the frozen sand mold (2) through data processing and analysis based on the collected surface point cloud data, and adjusts the processing parameters; Step 5: The spindle of the CNC machine tool (1) moves to the end position of the previous processing stage of the frozen sand mold according to the program setting, and continues the next stage of processing. After the processing is completed, the spindle is automatically moved out of the processing area of ​​the frozen sand mold (2), and the detection tasks of steps 3 and 4 are repeated until the last stage of the CNC processing program is completed and the processing task is ended; Step 6: After the processing and inspection tasks at each stage are accurately completed, a finished frozen sand mold (2) with good surface quality can be obtained.

6. A method for online detection of surface quality of frozen sand mold precision manufacturing according to claim 5, characterized in that: The processing process is divided into several stages, and data sampling is performed after the processing of different stages is completed.

7. A method for online detection of surface quality of frozen sand mold precision manufacturing according to claim 5, characterized in that: The method for detecting surface roughness of CNC machining in step 4 specifically comprises: Step 1: Select the point cloud of the specified machining surface measurement area, perform Gaussian filtering on the selected point cloud, and remove outlier noise points; Step 2: Use the least squares method to fit the selected point cloud and obtain the reference plane of the point cloud; Step 3: Traverse all selected sampling points, calculate the absolute distance value from each point to the reference surface point by point, calculate the average value of the absolute distance value from each point to the reference surface according to the roughness calculation formula (1), and obtain the roughness information of the CNC machining surface. Where m is the number of point clouds in the measurement area, P m is any point inside the point cloud, P m Projected point on the datum plane.

8. The method for online detection of surface quality of frozen sand mold precision manufacturing according to claim 5, characterized in that: The method for detecting the sand removal rate of CNC machining in step 4 specifically comprises: Step 1: Segment the collected frozen sand mold point cloud data and remove the point cloud outside the processing area. Step 2: De-noise the remaining cutting area 3D point cloud, remove outlier point clouds, mesh the remaining point clouds, and create an approximate 3D model of the cutting cavity; Step 3: Divide the approximate three-dimensional model into a set of many vertical slices, calculate the volume of each slice, and use the numerical integration method to obtain the volume of the complete three-dimensional model according to the slice volume, and obtain the model volume V1 of the CNC machined frozen sand mold with cutting sand particles; Step 4: According to the designed casting shape, calculate the complete volume V of the cavity when there is no sand. The sand removal rate can be obtained by calculation according to formula (2); Among them, V1 is the volume of the model with cutting sand particles, and V is the complete volume of the cavity when there are no sand particles.

9. The method for online detection of surface quality of frozen sand mold precision manufacturing according to claim 5, characterized in that: The method for detecting dimensional accuracy of numerical control machining in step 4 specifically comprises: Step 1: Preprocess the collected frozen sand mold 3D point cloud, remove noise, perform point cloud cutting, and retain the point cloud of the cutting area. Step 2: Use the cutting model as the reference model for 3D size registration, perform corner detection on the cutting area point cloud, use the model corner points as feature descriptors, perform rough model registration on the cutting model and point cloud data, and determine the pose relationship between the model and the point cloud. Step 3: After the rough registration is completed, the ICP algorithm is used to accurately align the model and the point cloud. After the registration is completed, the size deviation between the point cloud and the model is calculated, and the three-dimensional size accuracy of the frozen sand mold is detected by comparing the point cloud with the cutting model.

10. The method for online detection of surface quality of frozen sand mold precision manufacturing according to claim 5, characterized in that: The frozen sand mold is a combination of one or more materials selected from silica sand, zircon sand, chromite sand, olivine sand, corundum sand and water glass sand; The operating temperature of the data collector (4) is above -20°C.

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