An automated production system for smart door lock panels

Abstract

The present invention belongs to the field of intelligent door lock panel production, and specifically is an intelligent door lock panel automatic production system, including an electronic component assembly module, an assembly module, a vertical alloy die-casting machine, a detection module, a conveyor belt, and a transfer module; the detection module includes: an optical capture unit, a processing unit, and a fixed-point fill light unit. The optical capture unit is used to observe the outer surface of the intelligent door lock panel during transportation, and record the distortion fluctuation values ​​of two side lines formed by the parallel light beams by irradiating the surface of the intelligent door lock panel with parallel light beams. The distortion fluctuation values ​​are used to indicate the fluctuation of the side lines. When the intelligent door lock panel is concave or convex, diffuse reflection will occur at the edge of the reflective area irradiated on the surface, resulting in distortion of the side lines. The greater the distortion, the lower the surface flatness of the intelligent door lock panel, and the lower the quality. It is necessary to screen out low-quality products, thereby achieving the effect of effectively judging the quality of the intelligent door lock panel.

Description

Technical Field

[0001] The invention belongs to the field of intelligent door lock panel production, and specifically relates to an intelligent door lock panel automatic production system. Background Art

[0002] Smart door locks are improved upon traditional mechanical locks and are more intelligent and simple in terms of user security, identification, and manageability. They use mature technologies such as non-mechanical keys as user identification IDs, such as fingerprint locks, iris recognition access control, and TM cards. For large-scale production, smart door lock panel automated production systems are required to assist in the production of smart door lock panels.

[0003] A patent application with publication number CN114044351B discloses an automated production system and method for smart door lock panels, which relates to the field of smart door lock technology and solves the problems of high labor intensity, high labor cost, low automation and low production efficiency in the existing production mode of smart door lock panels. The system includes a zinc alloy die-casting machine, a cooling and air-drying unit, an automatic punching unit, an automatic drilling and tapping unit, an automatic bottom grinding unit, an automatic punching unit, an automatic milling burr unit and a connecting robot. The system can save labor, reduce the labor intensity of workers, improve the degree of automation and improve production efficiency.

[0004] In the quality inspection part of the traditional production system, it is difficult to directly distinguish the quality of smart door lock panels. However, the production and sale of smart door lock panels need to maintain product quality standards, which leads to the need to waste man-hours for separate production quality inspection of smart door lock panels in the later stage.

[0005] To this end, the present invention provides an automated production system for an intelligent door lock panel. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: an automatic production system for intelligent door lock panels described in the present invention comprises:

[0008] A vertical alloy die-casting machine, which is used to die-cast the metal housing of the door lock;

[0009] An electronic component assembly module, which is used to assemble the electronic components required for the smart door lock and output the assembled electronic components to the outside;

[0010] The final assembly module is used to receive the electronic parts and the electroplated metal shell, assemble the two, and output the assembled smart door lock panel to the outside;

[0011] A detection module, which is used to perform quality inspection on the assembled smart door lock panel;

[0012] Conveyor belts, where multiple conveyor belts are arranged at the output ends and input ports of multiple modules for transporting various parts;

[0013] A transfer module, which is used to transfer parts on different conveyor belts;

[0014] The detection module includes: an optical capture unit, a processing unit, and a fixed-point fill light unit;

[0015] The optical capture unit is used to observe the outer surface of the smart door lock panel during transportation, and generate image information to be transmitted to the processing unit; it should be noted that the image information is controlled according to the transportation speed of the conveyor belt and the required detection accuracy. The slower the conveyor belt transportation speed, the slower the image recording speed. When high-precision detection is required, the speed of acquiring images is increased, such as acquiring an image every 0.1s. In this way, the number of images used for judgment is increased, thereby improving the detection accuracy;

[0016] The fixed-point fill light unit is used to irradiate a parallel light beam to the surface of the smart door lock panel; the length of the light beam is greater than the width of the smart door lock panel; it should be noted that the parallel light beam irradiated on the smart door lock panel needs to cross both sides of the smart door lock panel;

[0017] The processing unit is used to process the image information, obtain the image of the surface of the smart door lock panel, obtain the reflected image of the parallel light beam in the image, and record the distortion fluctuation values ​​of the two edge lines formed by the parallel light beam. ; Set multiple threshold intervals , determine the distortion fluctuation value The threshold interval to which it belongs, the judgment result is input to the transfer module behind the detection module, and the smart door lock panels located in different intervals are transported to different conveyor belts; and The value is obtained through historical evaluation of staff; distorted fluctuation value It is used to indicate the fluctuation of the edge line. When the smart door lock panel is concave or convex, diffuse reflection will occur on the edge of the reflective area on the surface, causing the edge line to be distorted. The greater the distortion, the lower the surface flatness of the smart door lock panel and the lower the quality. It is necessary to screen out low-quality products.

[0018] Preferably, the method of obtaining the two edge lines of the reflective image in the image is specifically:

[0019] The output end of the fixed-point fill light unit faces downward, and when the smart door lock panel passes by, the tilted optical capture unit captures images on the smart door lock panel multiple times;

[0020] The image information contains two color blocks, namely, a reflective color block and a dark color block without reflective light. There is an intersection line at the intersection of the two color blocks;

[0021] Through the method of color difference tracing, the reflective color block is color framed, the frame shape is recorded and stored, the four corners of the frame are cut to obtain four side lines, the two side lines that are in line with the edge of the smart door lock panel are removed, and the data of the two side lines are stored to obtain two side lines.

[0022] Preferably, a blank two-dimensional plane is generated in the processing unit, a rectangular coordinate system is established in the plane, all recorded edge lines are placed in the rectangular coordinate system, one end of the edge line is aligned with the origin, and the other end is located on the X-axis, a standard unit is set, and a detection point on the edge line is obtained at every standard unit interval, and a Y-axis value of each detection point is obtained;

[0023] Distortion Fluctuation Value The specific calculation method is based on the formula:

[0024] Where: y represents the Y-axis value of each detection point; represents the average value of all collected y values; N represents the total number of y values ​​collected;

[0025] Distorted volatility calculated by variance , a statistic that reflects the size of data fluctuations. The data comes from the detection points of the edge line, and the fluctuation of the edge line can be obtained. When the panel is flat, the edge line should be in a state of no fluctuation. The value of the error range is set to ; The value of is obtained by shining a light beam on the display screen, pressing down the display screen, and making the center of the display screen sink. The line generated by the light beam in the sunken area is bent, and the variance value of the line is measured. The sinking distance is the boundary between not affecting the normal display of the display screen and affecting the normal display of the display screen. The variance value is recorded and marked as , thus obtaining the required and ,conform to The distortion fluctuation value in this range The products corresponding to the edge of are defined as high-quality products, which meet the requirements of The products in this range are classified as medium quality and meet the The products in the interval are defined as defective and are transported on different conveyor belts.

[0026] Preferably, the detection point of the edge line placed on the X-axis is obtained by the equal division method, the contact point between the end of the edge line away from the origin and the X-axis is obtained, and the X-axis value of the contact point is obtained, the value is accurate to one decimal place, and the value is rounded off; the obtained data is divided equally; the value after equal division is the standard unit, and from the zero point of the X-axis, a plurality of straight lines L perpendicular to the X-axis are established every other standard unit, and the intersection of the edge line placed on the X-axis and the straight line L is the obtained detection point;

[0027] Since the lines are curved, it is rather troublesome to obtain the coordinates of points on the lines of equal length. Obtaining data directly from the vertical line corresponding to the standard unit can obtain suitable data more quickly.

[0028] Preferably, The boundary of the interval is re-judged;

[0029] Get the partition line generated by the edge line placed on the X axis between adjacent straight lines L , obtain multiple partition lines, and aggregate all the obtained multiple partition line data to form a data set, and for all the partition lines in the data set To process, the specific processing method is: The row is enlarged proportionally, and the enlargement multiple is the same as the value of the equal division. One end is aligned with the origin of the rectangular coordinate system to obtain The ordinate values ​​of the intersection points with multiple straight lines L , according to the formula:

[0030] in Indicates all collected The average value of the value; W represents the total number of The numerical value of the quantity; Indicates breakline The distortion fluctuation value of

[0031] Calculated Used to determine the break line The fluctuation of Again with the set threshold interval Perform adaptation and determine the quality of the smart door lock panel based on the judgment result;

[0032] Since defects on the panel surface are generally concentrated in a small area, simply measuring the distortion fluctuation value of the entire edge line will find that the distortion fluctuation value of the entire edge line is close to 0, and it is impossible to accurately determine whether there are defects on the panel surface. The distortion fluctuation value can detect the defects of the panel more accurately, so that the smart door lock panels that have been screened as high-quality products can be screened again, and the best products among the high-quality products and the defective products among the high-quality products can be screened out, and different conveyor belts 15 can be used for transportation.

[0033] Preferably, the edge distortion fluctuation value After the detection is completed, the dichotomy method is used for the edge line. The distance length value B between the two ends of the edge line is obtained according to the rectangular coordinate system. A straight line perpendicular to the X axis is established on the rectangular coordinate system. The X axis coordinate of the straight line is , split the edge into two segments, the edge before the split is called the original edge, and the edge after the split is called the split edge. The two split edges are measured for distortion fluctuation values ​​respectively. The calculation method is the same as the distortion fluctuation value measurement method of the original edge, and the binary distortion fluctuation value is obtained. , the binary distortion fluctuation value obtained by splitting the two segments of the edge line is compared with the original edge line distortion fluctuation value Subtract them respectively and convert them into absolute values ​​to get ;Set the deviation value;

[0034] when When the value of is less than the deviation value, the original edge line to be split is discarded and no subsequent detection is performed on this original edge line;

[0035] when When the value is greater than the deviation value, the split edge is divided into two parts again, and the distortion fluctuation value of the two split edge parts after the division is measured again. ,Will Compare and get ,in , where n represents the number of times the line segment is divided into two halves, and the above comparison process is repeated; through this dichotomy, the amount of calculation of the system can be reduced without reducing the detection accuracy, because after the edge line is divided into two halves, the distortion fluctuation value of the two separated edge lines is calculated. If the difference between the distortion fluctuation value and the distortion fluctuation value of the original line segment is small, it means that the edge line after the dichotomy is in a flat state as a whole, and no further detection is required. If the difference is large, it means that the curved part of the edge line is on this edge line. Compared with the method of directly dividing the edge line into equal parts and performing all detections, the amount of calculation can be reduced, and at the same time, the curved part of the smart door lock panel can be found.

[0036] Preferably, the deviation peak value is set to Constantly compare with the deviation peak value, when it appears When the value of is greater than the deviation peak, the dichotomy is stopped;

[0037] The smart door lock panels with detected deviation peaks are identified as defective products among good products, and different conveyor belts are used to transport the defective products among good products.

[0038] Preferably, the image acquired by the optical capture unit is processed; by adjusting the shadows and highlights in the image, the bright side is made brighter and the dark side is made darker;

[0039] Use sharpening technology to process the image to assist in obtaining the edges of color blocks.

[0040] Preferably, the image acquired by the optical capture unit is reprocessed to obtain light spots other than the reflective color blocks;

[0041] Augmented reality technology is used to determine the connection between light spots outside the reflective color block and the acquired edge line. When detecting the corresponding edge line, the influence of the light spots outside the reflective color block on the edge line distortion fluctuation value is weakened.

[0042] Preferably, the specific method of reducing the influence is, when obtaining the light point outside the reflective color block, taking the light point outside the reflective color block as the origin, establishing a straight line K parallel to the edge line of the color block, and using augmented reality technology;

[0043] The specific augmented reality technology is: using optoelectronic display technology, interactive technology, sensor technology, and computer graphics and multimedia technology to integrate the computer-generated virtual environment with the display environment around the user, so that the user can be convinced from the sensory effect that the virtual environment is a part of the real environment around him;

[0044] The straight line K is kept at a predetermined position on the smart door lock panel. When the edge of the reflective color block coincides with the straight line K, the origin position of the straight line K is determined. When the distortion fluctuation value is detected, the area corresponding to the origin position of the straight line K is not detected for the distortion fluctuation value.

[0045] This setting can reduce the reflection of dust and debris on the surface of the smart door lock panel, which affects the quality inspection of the smart door lock panel.

[0046] The beneficial effects of the present invention are as follows:

[0047] 1. The present invention discloses an automated production system for smart door lock panels, which irradiates the surface of the smart door lock panel with a parallel light beam and records the distortion fluctuation values ​​of two side lines formed by the parallel light beams. The distortion fluctuation values ​​are used to indicate the fluctuation of the side lines. When the smart door lock panel is concave or convex, diffuse reflection will occur at the edge of the reflective area irradiated on the surface, causing distortion of the side lines. The greater the distortion, the lower the surface flatness of the smart door lock panel and the lower the quality. It is necessary to screen out low-quality products, thereby effectively judging the quality of the smart door lock panel.

[0048] 2. The present invention describes an automated production system for smart door lock panels, which obtains multiple partition lines by cutting the acquired edge lines, and aggregates all the acquired data of the multiple partition lines to form a data set, and processes all the partition lines in the data set. Since the defects on the panel surface are generally concentrated in a small area, simply measuring the distortion fluctuation value of the entire edge line will find that the distortion fluctuation value of the entire edge line tends to 0, and it is impossible to accurately determine whether there are defects on the panel surface. By dividing the collected edge lines into equal parts and then detecting the distortion fluctuation value, the defects of the panel can be detected more accurately, so that the smart door lock panels that have been screened as excellent products can be screened again to screen out the best of the best and the inferior of the best. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Figure 1 It is a schematic diagram of the intelligent door lock panel production line of the present invention;

[0051] In the figure: 10. Vertical alloy die-casting machine; 11. Electronic component assembly module; 12. Final assembly module; 13. Transfer module; 14. Inspection module; 15. Conveyor belt. DETAILED DESCRIPTION

[0052] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0053] like Figure 1 As shown, an automatic production system for smart door lock panels according to an embodiment of the present invention includes:

[0054] A vertical alloy die-casting machine 10, which is used to die-cast a metal housing of a door lock;

[0055] An electronic component assembly module 11, which is used to assemble the electronic components required for the smart door lock and output the assembled electronic components to the outside;

[0056] The final assembly module 12 is used to receive the electronic components and the electroplated metal housing, assemble the two, and output the assembled smart door lock panel to the outside;

[0057] A detection module 14, which is used to perform quality detection on the assembled smart door lock panel;

[0058] Conveyor belts 15, multiple conveyor belts 15 are arranged at the output ends and input ports of multiple modules for transporting various parts;

[0059] A transfer module 13, wherein the transfer module 13 is used to transfer parts on different conveyor belts 15;

[0060] The detection module includes: an optical capture unit, a processing unit, and a fixed-point fill light unit;

[0061] The optical capture unit is used to observe the outer surface of the smart door lock panel during transportation, and generate image information to be transmitted to the processing unit; it should be noted that the image information is controlled according to the transportation speed of the conveyor belt 15 and the required detection accuracy. The slower the transportation speed of the conveyor belt 15, the slower the image recording speed. When high-precision detection is required, the speed of acquiring images is increased, such as acquiring an image every 0.1s. In this way, the number of images used for judgment is increased, thereby improving the detection accuracy;

[0062] The fixed-point fill light unit is used to irradiate a parallel light beam to the surface of the smart door lock panel; the length of the light beam is greater than the width of the smart door lock panel; it should be noted that the parallel light beam irradiated on the smart door lock panel needs to cross both sides of the smart door lock panel;

[0063] The processing unit is used to process the image information, obtain the image of the surface of the smart door lock panel, obtain the reflected image of the parallel light beam in the image, and record the distortion fluctuation values ​​of the two edge lines formed by the parallel light beam. ; Set multiple threshold intervals , determine the distortion fluctuation value The threshold interval to which it belongs, the judgment result is input to the transfer module behind the detection module, and the smart door lock panels located in different intervals are transported to different conveyor belts 15; The value is obtained through historical evaluation of staff; distorted fluctuation value It is used to indicate the fluctuation of the edge line. When the smart door lock panel is concave or convex, diffuse reflection will occur on the edge of the reflective area on the surface, causing the edge line to be distorted. The greater the distortion, the lower the surface flatness of the smart door lock panel and the lower the quality. It is necessary to screen out low-quality products.

[0064] The method of obtaining the two edge lines of the reflective image in the image is specifically as follows:

[0065] The output end of the fixed-point fill light unit faces downward, and when the smart door lock panel passes by, the tilted optical capture unit captures images on the smart door lock panel multiple times;

[0066] The image information contains two color blocks, namely, a reflective color block and a dark color block without reflective light. There is an intersection line at the intersection of the two color blocks;

[0067] Through the method of color difference tracing, the reflective color block is color framed, the frame shape is recorded and stored, the four corners of the frame are cut to obtain four side lines, the two side lines that are in line with the edge of the smart door lock panel are removed, and the data of the two side lines are stored to obtain two side lines.

[0068] A blank two-dimensional plane is generated in the processing unit, a rectangular coordinate system is established in the plane, all recorded edge lines are placed in the rectangular coordinate system, one end of the edge line is aligned with the origin, and the other end is located on the X-axis, a standard unit is set, and a detection point on the edge line is obtained at every standard unit interval, and the Y-axis value of each detection point is obtained;

[0069] Distortion Fluctuation Value The specific calculation method is based on the formula:

[0070] Where: y represents the Y-axis value of each detection point; represents the average value of all collected y values; N represents the total number of y values ​​collected;

[0071] Distorted volatility calculated by variance , a statistic that reflects the size of data fluctuations. The data comes from the detection points of the edge line, and the fluctuation of the edge line can be obtained. When the panel is flat, the edge line should be in a state of no fluctuation. The value of the error range is set to ; The value of is obtained by shining a light beam on the display screen, pressing down the display screen, and making the center of the display screen sink. The line generated by the light beam in the sunken area is bent, and the variance value of the line is measured. The sinking distance is the boundary between not affecting the normal display of the display screen and affecting the normal display of the display screen. The variance value is recorded and marked as , thus obtaining the required and ,conform to The distortion fluctuation value in this range The products corresponding to the edge of are defined as high-quality products, which meet the requirements of The products in this range are classified as medium quality and meet the The products in the interval are defined as defective products and are transported by different conveyor belts 15 .

[0072] The detection point of the edge line placed on the X-axis is obtained by the equal division method, the contact point between the end of the edge line away from the origin and the X-axis is obtained, and the X-axis value of the contact point is obtained. The value is accurate to one decimal place and is rounded off; the obtained data is divided equally; the value after equal division is the standard unit, and from the zero point of the X-axis, multiple straight lines L perpendicular to the X-axis are established every standard unit, and the intersection of the edge line placed on the X-axis and the straight line L is the obtained detection point;

[0073] Since the lines are curved, it is rather troublesome to obtain the coordinates of points on the lines of equal length. Obtaining data directly from the vertical line corresponding to the standard unit can obtain suitable data more quickly.

[0074] For The edge of the threshold interval is judged again;

[0075] Get the partition line generated by the edge line placed on the X axis between adjacent straight lines L , obtain multiple partition lines, and aggregate all the obtained multiple partition line data to form a data set, and for all the partition lines in the data set To deal with it, the specific method is: Perform geometric expansion, the expansion multiple is the same as the value of the equal division, and the geometric partition line Align one end with the origin of the rectangular coordinate system to obtain the partition line The ordinate values ​​of the intersection points with multiple straight lines L , according to the formula:

[0076] in Indicates all collected The average value of the value; W represents the total number of The numerical value of the quantity; Indicates breakline The distortion fluctuation value of

[0077] Calculated Used to determine the break line The fluctuation of Again with the set threshold interval Adaptation is performed, and according to the judgment results, the smart door lock panels that have been confirmed as high-quality products are further subdivided into high-quality products, medium-quality products and sub-quality products;

[0078] Since defects on the panel surface are generally concentrated in a small area, simply measuring the distortion fluctuation value of the entire edge line will find that the distortion fluctuation value of the entire edge line is close to 0, and it is impossible to accurately determine whether there are defects on the panel surface. The distortion fluctuation value can detect the defects of the panel more accurately, so that the smart door lock panels that have been screened as high-quality products can be screened again, and the best products among the high-quality products and the defective products among the high-quality products can be screened out, and different conveyor belts 15 can be used for transportation.

[0079] The distortion fluctuation value of the edge After the detection is completed, the dichotomy method is used for the edge line. The distance length value B between the two ends of the edge line is obtained according to the rectangular coordinate system. A straight line perpendicular to the X axis is established on the rectangular coordinate system. The X axis coordinate of the straight line is , split the edge into two segments, the edge before the split is called the original edge, and the edge after the split is called the split edge. The two split edges are measured for distortion fluctuation values ​​respectively. The calculation method is the same as the distortion fluctuation value measurement method of the original edge, and the binary distortion fluctuation value is obtained. , the binary distortion fluctuation value obtained by splitting the two segments of the edge line is compared with the original edge line distortion fluctuation value Subtract them respectively and convert them into absolute values ​​to get ;Set the deviation value;

[0080] when When the value of is less than the deviation value, the original edge line to be split is discarded and no subsequent detection is performed on this original edge line;

[0081] when When the value is greater than the deviation value, the split edge is divided into two parts again, and the distortion fluctuation value of the two split edge parts after the division is measured again. , will be compared and get ,in , where n represents the number of times the line segment is divided into two halves, and the above comparison process is repeated; through this dichotomy, the amount of calculation of the system can be reduced without reducing the detection accuracy, because after the edge line is divided into two halves, the distortion fluctuation value of the two separated edge lines is calculated. If the difference between the distortion fluctuation value and the distortion fluctuation value of the original line segment is small, it means that the edge line after the dichotomy is in a flat state as a whole, and no further detection is required. If the difference is large, it means that the curved part of the edge line is on this edge line. Compared with the method of directly dividing the edge line into equal parts and performing all detections, the amount of calculation can be reduced, and at the same time, the curved part of the smart door lock panel can be found.

[0082] Set the deviation peak value. Constantly compare with the deviation peak value, when it appears When the value of is greater than the deviation peak, the dichotomy is stopped;

[0083] The smart door lock panel with the detected deviation peak is determined as a defective product among the good products, and a different conveyor belt 15 is used to transport the defective products among the good products.

[0084] Process the image acquired by the optical capture unit; adjust the shadows and highlights in the image to make the bright side brighter and the dark side darker;

[0085] Use sharpening technology to process the image to assist in obtaining the edges of color blocks.

[0086] Reprocessing the image acquired by the optical capture unit to obtain light spots other than the reflective color blocks;

[0087] Augmented reality technology is used to determine the connection between light spots outside the reflective color block and the acquired edge line. When detecting the corresponding edge line, the influence of the light spots outside the reflective color block on the edge line distortion fluctuation value is weakened.

[0088] The specific method of reducing the influence is to obtain the light points outside the reflective color block, take the light points outside the reflective color block as the origin, establish a straight line K parallel to the edge of the color block, and use augmented reality technology;

[0089] The specific augmented reality technology is: using optoelectronic display technology, interactive technology, sensor technology, and computer graphics and multimedia technology to integrate the computer-generated virtual environment with the display environment around the user, so that the user can be convinced from the sensory effect that the virtual environment is a part of the real environment around him;

[0090] The straight line K is kept at a predetermined position on the smart door lock panel. When the edge of the reflective color block coincides with the straight line K, the origin position of the straight line K is determined. When the distortion fluctuation value is detected, the area corresponding to the origin position of the straight line K is not detected for the distortion fluctuation value.

[0091] Through this setting, the reflection of dust and debris on the surface of the smart door lock panel can be reduced, and the impact on the quality inspection of the smart door lock panel can be reduced.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An automated production system for smart door lock panels, characterized in that: include: A vertical alloy die-casting machine (10), the vertical alloy die-casting machine (10) being used for die-casting a portion of a metal housing of a door lock; An electronic component assembly module (11), the electronic component assembly module (11) being used to assemble the electronic components required for the smart door lock and output the assembled electronic components externally; An assembly module (12), the assembly module (12) being used to receive the electronic components and the electroplated metal housing, assemble the two, and output the assembled smart door lock panel to the outside; A detection module (14), the detection module (14) being used to perform quality detection on the assembled smart door lock panel; Conveyor belts (15), where a plurality of conveyor belts (15) are arranged at output ends and input ports of a plurality of modules and are used to transport various parts; A transfer module (13), wherein the transfer module (13) is used to transfer parts on different conveyor belts (15); The detection module includes: an optical capture unit, a processing unit, and a fixed-point fill light unit; The optical capture unit is used to observe the outer surface of the smart door lock panel during transportation and generate image information to be transmitted to the processing unit; The fixed-point fill light unit is used to irradiate a parallel light beam to the surface of the smart door lock panel; the length of the light beam is greater than the width of the smart door lock panel; The processing unit is used to process the image information, obtain the image of the surface of the smart door lock panel, obtain the reflected image of the parallel light beam in the image, and record the distortion fluctuation values ​​of the two edge lines formed by the parallel light beam. ; Set multiple threshold intervals , determine the distortion fluctuation value The threshold interval to which the detection module belongs is inputted, and the judgment result is inputted into the transfer module behind the detection module, so that the smart door lock panels located in different intervals are transported to different conveyor belts (15); The method of obtaining the two edge lines of the reflective image in the image is specifically as follows: The output end of the fixed-point fill light unit faces downward, and when the smart door lock panel passes by, the tilted optical capture unit captures images on the smart door lock panel multiple times; The image information contains two color blocks, namely, a reflective color block and a dark color block without reflective light. There is an intersection line at the intersection of the two color blocks; By using the color difference tracing method, the reflective color block is framed, the frame shape is recorded and stored, the four corners of the frame are cut to obtain four side lines, the two side lines that are in contact with the edge of the smart door lock panel are removed, the two side lines are stored, and two side lines are obtained; A blank two-dimensional plane is generated in the processing unit, a rectangular coordinate system is established in the plane, all recorded edge lines are placed in the rectangular coordinate system, one end of the edge line is aligned with the origin, and the other end is located on the X-axis, a standard unit is set, and a detection point on the edge line is obtained at every standard unit interval, and the Y-axis value of each detection point is obtained; Distortion Fluctuation Value The specific calculation method is based on the formula: Where: y represents the Y-axis value of each detection point; represents the average value of all collected y values; N represents the total number of y values ​​collected; conform to The distortion fluctuation value in this range The products corresponding to the edge of are defined as high-quality products, which meet the requirements of The products in this range are classified as medium quality and meet the requirements The products in the interval are defined as defective products and are transported by different conveyor belts (15); The detection point of the edge line placed on the X-axis is obtained by the equal division method, the contact point between the end of the edge line away from the origin and the X-axis is obtained, and the X-axis value of the contact point is obtained. The value is accurate to one decimal place and is rounded off; the obtained data is divided equally; the value after equal division is the standard unit, and from the zero point of the X-axis, multiple straight lines L perpendicular to the X-axis are established every standard unit, and the intersection of the edge line placed on the X-axis and the straight line L is the obtained detection point; For The boundary of the interval is re-judged; Get the partition line generated by the edge line placed on the X axis between adjacent straight lines L , obtain multiple partition lines, and aggregate all the obtained multiple partition line data to form a data set, and for all the partition lines in the data set To deal with it, the specific method is: The row is enlarged proportionally. The enlargement multiple is the same as the value of the equal division. Align one end with the origin of the rectangular coordinate system to obtain the partition line The ordinate values ​​of the intersection points with multiple straight lines L , according to the formula: in Indicates all collected The average value of the value; W represents the total number of The numerical value of the quantity; Indicates breakline The distortion fluctuation value of Calculated Used to determine the break line The fluctuation of Again with the set threshold interval Perform adaptation and determine the quality of the smart door lock panel based on the judgment results.

2. The intelligent door lock panel automatic production system according to claim 1, characterized in that: The distortion fluctuation value of the edge After the detection is completed, the dichotomy method is used for the edge line. The distance length value B between the two ends of the edge line is obtained according to the rectangular coordinate system. A straight line perpendicular to the X axis is established on the rectangular coordinate system. The X axis coordinate of the straight line is , split the edge into two segments, the edge before the split is called the original edge, and the edge after the split is called the split edge. The two split edges are measured for distortion fluctuation values ​​respectively. The calculation method is the same as the distortion fluctuation value measurement method of the original edge, and the binary distortion fluctuation value is obtained. , the binary distortion fluctuation value obtained by splitting the two segments of the edge line is compared with the original edge line distortion fluctuation value Subtract them respectively and convert them into absolute values ​​to get ; Set the deviation value; when When the value of is less than the deviation value, the original edge line for splitting is discarded and no subsequent detection is performed on this original edge line; when When the value is greater than the deviation value, the split edge is divided into two parts again, and the distortion fluctuation value of the two split edge parts after the division is measured again. ,Will Compare and get ,in , where n represents the number of times the line segment is divided into two halves, and the above comparison process is repeated.

3. The intelligent door lock panel automatic production system according to claim 2, characterized in that: Set the deviation peak value. ,in Constantly compare with the deviation peak value, when it appears When the value is greater than the deviation peak, the binary division is stopped.

4. The intelligent door lock panel automatic production system according to claim 3, characterized in that: Process the image acquired by the optical capture unit; adjust the shadows and highlights in the image to make the bright side brighter and the dark side darker; Use sharpening technology to process the image to assist in obtaining the edges of color blocks.

5. The intelligent door lock panel automatic production system according to claim 4, characterized in that: Reprocessing the image acquired by the optical capture unit to obtain light spots other than the reflective color blocks; Augmented reality technology is used to determine the connection between light spots outside the reflective color block and the acquired edge line. When detecting the corresponding edge line, the influence of the light spots outside the reflective color block on the edge line distortion fluctuation value is weakened.

6. The intelligent door lock panel automatic production system according to claim 5, characterized in that: The specific method of reducing the influence is to obtain the light points outside the reflective color block, take the light points outside the reflective color block as the origin, establish a straight line K parallel to the edge of the color block, and use augmented reality technology; The specific augmented reality technology is: using optoelectronic display technology, interactive technology, sensor technology, and computer graphics and multimedia technology to integrate the computer-generated virtual environment with the display environment around the user, so that the user can be convinced from the sensory effect that the virtual environment is a part of the real environment around him; Keep the straight line K at the predetermined position of the smart door lock panel. When the edge of the reflective color block coincides with the straight line K, determine the origin position of the straight line K. During the distortion fluctuation value detection, the area corresponding to the origin position of the straight line K is not subjected to the distortion fluctuation value detection.

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