Workpiece automatic detection system based on data analysis

Abstract

The invention relates to the field of machining detection, and discloses a data analysis-based machined part automatic detection system, which comprises a detection module used for acquiring detection data; the detection data processing and analyzing module is used for judging whether the outer surface of the machined part is qualified or unqualified; the secondary verification module is used for carrying out secondary verification on the machined part of which the outer surface quality is judged to be unqualified, if the outer surface quality of the machined part is judged to be qualified for the second time, alarming is not carried out, and otherwise, the outer surface quality of the machined part is judged to be unqualified; the alarm module is used for sending an alarm signal to the machined part of which the outer surface quality is judged to be unqualified through the secondary verification module; the detection data processing and analyzing module is used for preliminarily judging the detection data, and then the secondary verification module is used for rechecking, so that the detection error caused by impurities on the surface of the machined part is prevented, and finally, the alarm module is used for giving an alarm to put the machined part into an unqualified area.

Description

Technical Field

[0001] The invention relates to the field of processing detection, and in particular to an automatic detection system for processed parts based on data analysis. Background Art

[0002] Existing machined parts need to be inspected during and after the processing. The inspection is divided into internal inspection and appearance inspection. The purpose of internal inspection is to detect whether there are hidden scratches or cracks inside the machined parts, while the appearance inspection is basically divided into cracks, surface quality, and size. In general, both internal inspection and appearance inspection determine the factory quality of the machined parts.

[0003] For rod, shaft or disk workpieces with a circular shape, whether the shape of the outer surface is regular is an important factor affecting the quality of the workpiece. However, in the actual inspection process, the outer cylindrical surface is generally inspected by placing it in a gauge for measurement. However, the measurement result of the gauge will be affected by impurities attached to the surface of the workpiece, resulting in detection errors, which in turn leads to inaccurate overall inspection results. Summary of the invention

[0004] The purpose of the present invention is to provide an automatic detection system for workpieces based on data analysis to solve the above technical problems.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A workpiece automatic detection system based on data analysis, comprising:

[0007] The detection module is used to detect the outer surface of the workpiece and obtain detection data;

[0008] The detection data processing and analysis module is used to process the detection data to obtain the outer surface quality coefficient of the workpiece, and compare the outer surface quality coefficient with the preset outer surface quality interval. If the outer surface quality coefficient is within the outer surface quality interval, the outer surface quality of the workpiece is judged to be qualified, otherwise, the outer surface quality of the workpiece is judged to be unqualified;

[0009] The secondary verification module performs secondary verification on the workpieces whose outer surface quality is judged to be unqualified. The process of the secondary verification is as follows:

[0010] The outer surface of the current workpiece is cleaned by the pre-installed cleaning module, and then a secondary inspection is performed by the inspection module to obtain secondary inspection data;

[0011] After processing the secondary test data through the test data processing and analysis module, the secondary outer surface quality coefficient is obtained;

[0012] If the secondary outer surface quality coefficient is within the outer surface quality range, the outer surface quality of the workpiece is secondarily judged to be qualified, otherwise the outer surface quality of the workpiece is secondarily judged to be unqualified;

[0013] The alarm module sends an alarm signal to the processed parts whose outer surface quality is judged to be unqualified by the secondary verification module.

[0014] As a further technical solution, the detection module includes:

[0015] A laser emitter, wherein a plurality of laser emitters are provided and are evenly spaced and distributed on the periphery of one end of the workpiece being processed;

[0016] A rotating disk, the laser emitter is mounted on the rotating disk, and a display panel is provided at the other end of the workpiece, the display panel is used to display the laser trajectory obtained by the laser emitter rotating along the periphery of the workpiece;

[0017] A driving member, the driving member is drivingly connected to the rotating disk and is used to drive the rotating disk and the laser emitter to rotate;

[0018] The camera unit is used to collect images formed by the laser track and use them as detection data.

[0019] As a further technical solution, the process of processing the detection data is as follows:

[0020] After processing the image into a standard format, an actual image is obtained, and the actual image is compared with a preset standard image;

[0021] Obtain the ratio K of the area of ​​the overlapped part of the actual image and the standard image to the total area and the arc length L of the missing part in the actual image;

[0022] Input K and L into the quality inspection model to obtain the outer surface quality coefficient F of the current workpiece.

[0023] As a further technical solution, the expression of the quality detection model is:

[0024]

[0025] Among them, x(L) is the judgment function of the arc length L of the missing part in the actual image. When L>0, x(L)=1+L*δ b , when L = 0, x(L) = 1, δ a ,δ b is the preset proportional coefficient, K0 is the standard value, and F is the outer surface quality coefficient.

[0026] As a further technical solution, the system further includes a marking module for marking the processed parts judged to be unqualified. The markings include red markings and yellow markings. Among them, the objects of the red markings are the processed parts whose outer surface quality is judged to be unqualified by the secondary verification module, and the objects of the yellow markings are the processed parts whose outer surface quality is judged to be unqualified by the detection data processing and analysis module.

[0027] As a further technical solution, the system further includes a processed part quality prediction module for performing quality prediction and analysis of the processed parts based on the historical data of the marking module, and comparing the quality prediction value Q calculated according to the quality prediction and analysis with the quality prediction threshold Q0;

[0028] If Q≥Q0, judge the quality trend difference of the processed parts in the next unit time. If Q<Q0, judge the quality trend of the processed parts in the next unit time is good.

[0029] As a further technical solution, the process of performing quality prediction and analysis of the processed parts based on the historical data of the marking module is as follows:

[0030] Obtain the number M of red markings of the marking module in m consecutive unit times traced back from the current moment i , the number M of yellow markings j ;

[0031] Obtain the number M of the total detected processed parts in each unit time z ;

[0032] Draw the curve M of the number of red markings changing with time in each unit time i (t), the curve M of the number of yellow markings changing with time j (t) and the curve M of the number of the total detected processed parts changing with time z (t);

[0033] Through the formula:

[0034]

[0035] Calculate the quality prediction value Q;

[0036] Among them, A r is the change amount of the red markings, B r is the change amount of the yellow markings, C r is the change amount of the total detected processed parts; θ, μ, σ are weight coefficients, and r is the rth unit time.

[0037] As a further technical solution, the expression of the A r is:

[0038] B r The expression is:

[0039] The C r The expression is:

[0040] Among them, t0 and t1 are the starting time and ending time of the unit time respectively.

[0041] Beneficial effects of the present invention:

[0042] The present invention first makes a preliminary judgment on the detection data through the detection data processing and analysis module, and then verifies it through the secondary verification module, so as to prevent the detection error caused by impurities on the surface of the workpiece, and selectively starts the cleaning module according to the judgment result of the detection data processing and analysis module, the purpose of which is to avoid the detection error caused by the possible attachment of impurities on the outer surface. On this basis, detection and analysis are performed again. If the quality is still judged to be unqualified, it means that the workpiece is indeed unqualified. Finally, an alarm is issued through the alarm module, and the workpiece is placed in the unqualified area. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 It is a system logic schematic diagram of the present invention;

[0045] Figure 2 This is a working diagram of the detection module. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] See also Figure 1-Figure 2 As shown, the present invention is an automatic detection system for workpieces based on data analysis, comprising:

[0048] The detection module is used to detect the outer surface of the workpiece and obtain detection data;

[0049] The detection data processing and analysis module is used to process the detection data to obtain the outer surface quality coefficient of the workpiece, and compare the outer surface quality coefficient with the preset outer surface quality interval. If the outer surface quality coefficient is within the outer surface quality interval, the outer surface quality of the workpiece is judged to be qualified, otherwise, the outer surface quality of the workpiece is judged to be unqualified;

[0050] The secondary verification module performs secondary verification on the workpieces whose outer surface quality is judged to be unqualified. The process of the secondary verification is as follows:

[0051] The outer surface of the current workpiece is cleaned by the pre-installed cleaning module, and then a secondary inspection is performed by the inspection module to obtain secondary inspection data;

[0052] After processing the secondary test data through the test data processing and analysis module, the secondary outer surface quality coefficient is obtained;

[0053] If the secondary outer surface quality coefficient is within the outer surface quality range, the outer surface quality of the workpiece is secondarily judged to be qualified, otherwise the outer surface quality of the workpiece is secondarily judged to be unqualified;

[0054] The alarm module sends an alarm signal to the processed parts whose outer surface quality is judged to be unqualified by the secondary verification module.

[0055] In this embodiment, the detection data is first preliminarily judged by the detection data processing and analysis module, and then reviewed by the secondary verification module, so as to prevent detection errors caused by impurities on the surface of the workpiece, and selectively start the cleaning module according to the judgment result of the detection data processing and analysis module. The cleaning module can use a high-pressure air pump to blow out airflow for cleaning or use other similar cleaning effects, which are not limited here; there should be no impurities on the surface of the workpiece after cleaning by the cleaning module. Compared with the method of cleaning before detection, the cleaning module is a newly added module on the original processing production line to prevent detection errors. In actual use, if each time Cleaning all parts may slow down the detection efficiency, so only the workpieces that are initially judged to be unqualified are cleaned, with the aim of avoiding detection errors caused by impurities that may be attached to the outer surface. On this basis, inspection and analysis are performed again. If the quality is still judged to be unqualified, it means that the workpiece is indeed unqualified. Finally, an alarm is issued through the alarm module, and the workpiece is placed in the unqualified area. Through the above technical scheme, dual detection of the detection data processing and analysis module and the secondary verification module is utilized, so that on the one hand, detection errors caused by non-processing problems on the outer surface of the workpiece can be avoided as much as possible, and on the other hand, the alarm accuracy can be improved through double inspection to prevent misjudgment.

[0056] The detection module comprises:

[0057] A laser emitter, wherein a plurality of laser emitters are provided and are evenly spaced and distributed on the periphery of one end of the workpiece being processed;

[0058] A rotating disk, the laser emitter is mounted on the rotating disk, and a display panel is provided at the other end of the workpiece, the display panel is used to display the laser trajectory obtained by the laser emitter rotating along the periphery of the workpiece;

[0059] A driving member, the driving member is drivingly connected to the rotating disk and is used to drive the rotating disk and the laser emitter to rotate;

[0060] The camera unit is used to collect images formed by the laser track and use them as detection data.

[0061] In this embodiment, a specific working method of the detection module is provided. The outer cylindrical surface of the workpiece is detected by driving a rotating disk with a driving member to drive multiple laser emitters on the rotating disk, preferably 1-2. The laser beam emitted by the laser emitter is close to the outer cylindrical surface of the workpiece and rotates one circle or half a circle from the starting point. According to the moving trajectory of the laser beam, it can be judged whether the outer cylindrical surface of the workpiece is regular. Because when there is a local protrusion on the outer surface of the workpiece, the laser beam will be blocked, causing the moving trajectory of the laser beam to be broken at that location, thereby achieving the purpose of detection. The moving trajectory of the laser beam is compared with the standard trajectory. The moving trajectory of the laser beam tends to be circular. The higher the degree of overlap with the standard circle, the more standard it is.

[0062] The process of processing the detection data is as follows:

[0063] After processing the image into a standard format, an actual image is obtained, and the actual image is compared with a preset standard image;

[0064] Obtain the ratio K of the area of ​​the overlapped part of the actual image and the standard image to the total area and the arc length L of the missing part in the actual image;

[0065] Input K and L into the quality inspection model to obtain the outer surface quality coefficient F of the current workpiece.

[0066] The expression of the quality detection model is:

[0067]

[0068] Among them, x(L) is the judgment function of the arc length L of the missing part in the actual image. When L>0, x(L)=1+L*δ b , when L = 0, x(L) = 1, δ a , δ b is the preset proportional coefficient, K0 is the standard value, and F is the outer surface quality coefficient.

[0069] In this embodiment, a method for processing detection data is provided. By detecting the acquired picture and the standard picture, the difference between the two pictures can be compared, and the ratio K of the area of the overlapping part to the total area and the arc length L of the missing part in the actual picture can be extracted from the comparison process. The above two features can directly reflect the quality of the outer circular surface of the workpiece. Then, through the quality detection model the outer surface quality coefficient of the workpiece can be obtained. If it is within the interval, it means that the quality of the workpiece is qualified; otherwise, it means that the quality of the workpiece is unqualified. l i is the arc length occupied by each break in the trajectory image, and i is the i-th one. Obviously, the larger the total arc length L, the worse the outer surface quality; the larger the |K - K0|, the better the outer surface quality.

[0070] The system further includes a marking module for marking the workpieces judged to be unqualified. The markings include red markings and yellow markings. Among them, the objects of the red markings are the workpieces whose outer surface quality is judged to be unqualified by the secondary verification module, and the objects of the yellow markings are the workpieces whose outer surface quality is judged to be unqualified by the detection data processing and analysis module.

[0071] The system further includes a workpiece quality prediction module for performing quality prediction and analysis of the workpiece based on the historical data of the marking module, and comparing the quality prediction value Q calculated according to the quality prediction and analysis with the quality prediction threshold Q0;

[0072] If Q ≥ Q0, it is judged that the quality trend of the workpiece in the next unit time is poor; if Q < Q0, it is judged that the quality trend of the workpiece in the next unit time is good.

[0073] The process of performing quality prediction and analysis of the workpiece based on the historical data of the marking module is as follows:

[0074] Obtain the number M of red markings of the marking module continuously traced back m unit times backward from the current moment i and the number M of yellow markings j ;

[0075] Obtain the number M of the total detected workpieces per unit time z ;

[0076] Draw the curve M of the number of red markings changing with time per unit time i (t), the curve M of the number of yellow markings changing with time j (t) and the curve M of the number of the total detected workpieces changing with time z (t);

[0077] Through the formula:

[0078]

[0079] The quality prediction value Q is calculated;

[0080] Among them, A r is the change in red, B r is the change in yellow mark, C r is the total change of the inspected workpiece; θ, μ, σ are weight coefficients, and r is the rth unit time.

[0081] The A r The expression is:

[0082] B r The expression is:

[0083] The C r The expression is:

[0084] Among them, t0 and t1 are the starting time and ending time of the unit time respectively.

[0085] In this embodiment, the marking module is used to mark the workpieces that are initially judged to be unqualified and the workpieces that are secondarily judged to be unqualified, so as to evaluate the cleanliness of the workpieces before subsequent inspection, and to facilitate the regional processing of the workpieces for easy distinction; at the same time, according to the changes in the number of two marks in the historical data, the overall change amount is obtained comprehensively, so as to predict the condition of the workpiece according to the size of the change amount, and the formula is used to The quality prediction value Q is calculated. Obviously, the larger the quality prediction value Q is, the worse the quality trend of the processed parts will be in the next unit time. Therefore, it is necessary to check the problems in the processing equipment to prevent quality problems of batch processed parts and avoid the expansion of losses.

[0086] It should be noted that the calculation formulas and various parameters involved in the calculation in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0087] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An automatic inspection system for workpieces based on data analysis, characterized in that: Including: A detection module, which is used to detect the outer surface of the workpiece and obtain detection data; A detection data processing and analysis module, which is used to process the detection data, obtain the outer surface quality coefficient of the workpiece, and compare the outer surface quality coefficient with a preset outer surface quality range. If the outer surface quality coefficient is within the outer surface quality range, it is determined that the outer surface quality of the workpiece is qualified; otherwise, it is determined that the outer surface quality of the workpiece is unqualified; A secondary verification module, which conducts secondary verification on the workpiece determined to have unqualified outer surface quality. The process of the secondary verification is as follows: Clean the outer surface of the current workpiece through a pre-installed cleaning module, and then conduct secondary detection through the detection module to obtain secondary detection data; After processing the secondary detection data through the detection data processing and analysis module, obtain the secondary outer surface quality coefficient; If the secondary outer surface quality coefficient is within the outer surface quality range, it is secondarily determined that the outer surface quality of the workpiece is qualified; otherwise, it is secondarily determined that the outer surface quality of the workpiece is unqualified; An alarm module, which emits an alarm signal for the workpiece determined to have unqualified outer surface quality by the secondary verification module.

2. The automatic workpiece detection system based on data analysis according to claim 1 is characterized in that: The detection module includes: Laser emitters, multiple laser emitters are provided and evenly distributed on the outer periphery of one end of the current workpiece; A rotating disk, the laser emitters are installed on the rotating disk, and a display board is provided at the other end of the workpiece. The display board is used to display the laser trajectory obtained by the rotation of the laser emitters along the outer periphery of the workpiece; A driving member, the driving member is in transmission connection with the rotating disk and is used to drive the rotating disk and the laser emitters to rotate; A camera unit, which is used to collect the image formed by the laser trajectory and use it as detection data.

3. The automatic workpiece detection system based on data analysis according to claim 2 is characterized in that: The process of processing the detection data is as follows: Process the image into a standard format to obtain an actual picture, and compare the actual picture with a preset standard picture; Obtain the ratio K of the area of the overlapping part of the actual picture and the standard picture to the total area and the arc length L of the missing part in the actual picture; Input K and L into the quality detection model to obtain the outer surface quality coefficient F of the current workpiece.

4. The automatic workpiece detection system based on data analysis according to claim 3 is characterized in that: The expression of the quality detection model is: Among them, x(L) is the judgment function of the arc length L of the missing part in the actual image. When L>0, x(L)=1+L*δ b , when L = 0, x(L) = 1, δ a ,δ b is the preset proportional coefficient, K0 is the standard value, and F is the outer surface quality coefficient.

5. The automatic workpiece detection system based on data analysis according to claim 1 is characterized in that: The system further includes a marking module, which is used to mark the unqualified workpieces. The markings include red markings and yellow markings. Among them, the objects of the red markings are the workpieces determined to have unqualified outer surface quality by the secondary verification module, and the objects of the yellow markings are the workpieces determined to have unqualified outer surface quality by the detection data processing and analysis module.

6. The automatic workpiece detection system based on data analysis according to claim 5 is characterized in that: The system further includes a workpiece quality prediction module, which conducts quality prediction and analysis of the workpiece based on the historical data of the marking module, and compares the quality prediction value Q calculated according to the quality prediction and analysis with the quality prediction threshold Q0; If Q≥Q0, it is determined that the quality trend of the workpiece in the next unit time is poor; if Q<Q0, it is determined that the quality trend of the workpiece in the next unit time is good.

7. The automatic workpiece detection system based on data analysis according to claim 1 is characterized in that: The process of conducting quality prediction and analysis of the workpiece based on the historical data of the marking module is as follows: Get the number of red marks M in the marking module traced back from the current moment in m consecutive unit time i 、The number of yellow marks M j ; Get the total number of inspected workpieces per unit time M z ; Draw a curve M showing the number of red marks per unit time as a function of time i (t), the curve of the number of yellow marks changing with time M j (t) and the total number of inspected workpieces changing with time M z (t); Through the formula: Calculate to obtain the quality prediction value Q; Among them, A r is the change in red, B r is the change in yellow mark, C r is the total change of the inspected workpiece; θ, μ, σ are weight coefficients, and r is the rth unit time.

8. The automatic workpiece detection system based on data analysis according to claim 7 is characterized in that: The A r The expression is: B r The expression is: The C r The expression is: Where t0 and t1 are the starting time and ending time of the unit time respectively.

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