Accurate control method and system for 3D printing based on Internet of Things

Abstract

The invention relates to the technical field of 3D printing of the Internet of Things, and particularly discloses an accurate control method and system for 3D printing based on the Internet of Things, and the method comprises the steps: obtaining 3D printing data, calculating the number of printing layers, sending the printing size data of each layer to a printer, measuring the actual printing size of each layer through an optical sensor, comparing the actual printing size with the design size, and obtaining a size error; and processing the printing error parameter, comparing the printing error parameter with a specified range, outputting a printer working signal, analyzing an error layer number proportion, and predicting a printing error trend and the remaining available printing layer number after receiving a printing prediction analysis signal. If the printing error changes regularly, the number of layers reaching an error threshold value is determined by fitting intersection of a trend prediction line and an early warning line, and if the printing error changes irregularly, curve segments are divided to obtain the maximum slope value to judge the error change trend and the number of the remaining layers. The 3D printing precision can be improved, and real-time monitoring and early warning, intelligent analysis and prediction and remote control and management are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things in 3D printing, and in particular to a precise control method and system for 3D printing based on Internet of Things. Background Art

[0002] With the development of Internet of Things technology, its application in various fields is becoming more and more extensive. As an emerging manufacturing technology, the application field of 3D printing technology is also expanding. However, the existing 3D printing technology still has certain limitations in precise control, and printing accuracy and quality control have become key issues. The existing 3D printing technology is difficult to monitor and control the printing quality in real time during the printing process, resulting in the accumulation of printing errors and affecting the quality of the final product. It is an urgent problem to achieve precise control of the 3D printing process through Internet of Things devices.

[0003] A Chinese patent application with publication number CN113977949B discloses a 3D printer and a control method thereof, including: a printing platform, a projection device, an adjustment device and a control device, wherein the projection device and the adjustment device are electrically connected to the control device respectively, the control device controls the projection device to emit light and form an initial picture on the printing platform, the adjustment device is arranged on the optical path of the light emitted by the projection device, and the control device controls the adjustment device to adjust the size of the initial picture.

[0004] In the prior art, the analysis of printing errors is not comprehensive enough. For example, there is a lack of analysis of the error of each layer and the error change trend. In the prior art, the 3D printing is usually stopped by checking whether the printing error exceeds the error range. The disadvantage is that when the printing error exceeds the specified range during 3D printing, the printing control is stopped, the timeliness of the printing control is poor, and it will have a damaging effect on the 3D printing. The quality protection of 3D printing cannot be achieved through the analysis of printing error data.

[0005] To this end, the present invention provides a 3D printing precision control method and system based on the Internet of Things. Summary of the invention

[0006] The purpose of the present invention is to provide a precise control method for 3D printing based on the Internet of Things to solve the above-mentioned problems.

[0007] The purpose of the present invention can be achieved by the following technical solution: A precise control method for 3D printing based on the Internet of Things, comprising:

[0008] Acquire printing data for 3D printing, wherein the printing data includes: the total printing thickness of the physical object and the printing thickness of each layer when the printer prints, and obtain the number of 3D printing layers N based on the printing data;

[0009] Use an optical sensor to measure the actual printing size and design size of each layer, and mark the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through the formula E d =|D i -S i |Get the printing error parameter E of each printing layer d ;

[0010] The error parameter E will be printed d Perform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal;

[0011] Based on the analysis signal, according to the recorded printing layer number, the error layer ratio Z is obtained. b , the error layer accounts for Z b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal;

[0012] Based on the type analysis signal, the change type of the printing error parameter is identified, and according to the change type of the printing error parameter, the target number of printing layers is obtained through processing and analysis, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing;

[0013] The change types of the printing error parameters include regular changes and irregular changes.

[0014] As a further technical solution of the present invention, the target error value is obtained in the following manner:

[0015] The error parameter E will be printed d The difference is processed with the two end points of the specified range of printing error respectively, and the absolute value of the difference is taken to obtain the upper limit value and the lower limit value of the error respectively;

[0016] Compare the upper error limit value with the lower error limit value. The specific comparison process is:

[0017] If the upper error limit is greater than the lower error limit, the lower error limit is used as the target error value, and its target error value is marked as L;

[0018] If the upper error limit is less than the lower error limit, the upper error limit is used as the target error value, and its target error value is marked as L.

[0019] As a further technical solution of the present invention, a precise control method of 3D printing based on the Internet of Things is characterized in that the working signal is obtained in the following manner:

[0020] Determine the target error value L and the error threshold H;

[0021] If L≤H, it means that the printing error is close to the upper limit of the error threshold requirement, and an analysis signal is generated;

[0022] If L>H, it means that the printing error is not close to the upper limit of the error threshold requirement, and a normal operation signal is generated, and the current printing layer number is recorded at the same time.

[0023] As a further technical solution of the present invention, the error layer number accounts for Z b The way to obtain is:

[0024] When the statistical analysis signal is generated, the number of printed layer numbers that have been recorded is compared with the number of 3D printed layers N to obtain the error layer ratio Z. b .

[0025] As a further technical solution of the present invention, the process of identifying the change type of the printing error parameter is as follows:

[0026] The proportion of the number of growth curve segments obtained is Z e Data processing is performed with the variance f of the slope set K, using the formula: Obtain a linear reference X, where α and β are preset proportional coefficients;

[0027] Compare the linear reference X with the linear reference threshold. The specific comparison process is as follows:

[0028] The preset linear reference threshold is Y;

[0029] If the linear reference X ≥ the linear reference threshold Y, it means that the change type of the printing error parameter is a regular change;

[0030] If the linear reference X<linear reference threshold Y, it means that the change type of the printing error parameter is irregular change.

[0031] As a further technical solution of the present invention, the number of growth curve segments accounts for Z e The method of obtaining is:

[0032] Construct a printing error variation curve in a two-dimensional coordinate system. The specific construction method is as follows:

[0033] The number of printed layers is the X-axis, and the printing error parameter E dAs the Y axis, a rectangular two-dimensional coordinate system is constructed, and the numbers of the printed layers and the printing error parameters corresponding to the printed layers are recorded and marked in the rectangular two-dimensional coordinate system, and the marked printing error parameter data points are connected to obtain a printing error change curve;

[0034] Divide the print error curve into multiple curve segments, measure the slope of each curve segment, and compare it with 0:

[0035] If the slope of the curve segment is greater than 0, the curve segment is marked as a growth curve segment;

[0036] If the slope of the curve segment is less than or equal to 0, the curve segment is marked as a non-increasing curve segment;

[0037] The ratio of the number of growth curve segments to the total number of curve segments is calculated to obtain the ratio of the number of growth curve segments, which is marked as Z. e .

[0038] As a further technical solution of the present invention, the variance f of the slope set K is obtained as follows:

[0039] The slopes of all curve segments are integrated into a slope set K, specifically: K = {k 1 , k 2 , k 3 ,......,k j}, j represents the number of the curve segment, calculate the variance of the elements in the set K and mark it as f.

[0040] As a further technical solution of the present invention, the target number of printing layers is obtained as follows:

[0041] If the printing error parameter E d The change type is a regular change, which will be related to the printing error parameter E d The endpoint value of the nearest error specified range is used as the reference parameter, and the reference parameter is marked on the Y axis of the coordinate system where the printing error change curve is located. The marked data point is used as the reference point, and a parallel line parallel to the X axis is drawn through the reference point and marked as the printing error warning line;

[0042] Obtain all printing error parameter data points used to construct the printing error change curve, and fit all the printing error parameter data points by the least square method to obtain a fitting straight line, extend the fitting straight line and intersect it with the printing error warning line to obtain the intersection of the two lines, obtain the X-axis coordinate of the intersection, and obtain the target number of printing layers n based on the X-axis coordinate of the intersection;

[0043] If the printing error parameter E dThe change type of is irregular change, the curve segment with the largest slope among all growth curve segments is obtained as the target curve segment, the printing error parameters corresponding to the end points of the target curve segment are obtained, and the difference processing is performed to obtain the maximum value of the printing error parameter change;

[0044] The target error value when the analysis signal is generated is processed by ratio with the maximum value of the change of the printing error parameter to obtain the number of remaining printing layers;

[0045] Add the remaining number of printing layers to the number of printed layers to get the target number of printing layers n.

[0046] As a further technical solution of the present invention, the process of determining whether to continue 3D printing is as follows:

[0047] Compare the target number of printing layers n with the number of 3D printing layers N;

[0048] If n ≥ the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer will not exceed the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will not exceed the specified range of the printing error, and the printing will continue;

[0049] If n<the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer exceeds the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will exceed the specified range of the printing error, and the printing will be stopped.

[0050] As a further technical solution of the present invention, a precise control system for 3D printing based on the Internet of Things includes:

[0051] Layering module: obtains the printing data of 3D printing, wherein the printing data includes: the total printing thickness of the physical object and the printing thickness of each layer when the printer prints, and processes the printing data to obtain the number of 3D printing layers N;

[0052] Error acquisition module: Use optical sensors to measure the actual printing size and design size of each layer, and mark the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through the formula E d =|D i -S i |Get the printing error parameter E of each printing layer d ;

[0053] Error proximity analysis module: print error parameter E dPerform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal;

[0054] Error change analysis module: Based on the analysis signal, according to the recorded printing layer number, the error layer ratio Z is processed b , the error layer accounts for Z b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal;

[0055] Control analysis module: Based on the type analysis signal, the change type of the printing error parameter is identified, and according to the change type of the printing error parameter, the target number of printing layers is obtained through processing and analysis, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing;

[0056] The change types of the printing error parameters include regular changes and irregular changes.

[0057] Beneficial effects of the present invention:

[0058] 1. Based on the 3D printing data, the number of 3D printing layers N is obtained, the actual printing size of each layer is measured and compared with the design size, and the printing error parameter E of each printing layer is obtained. d , print the error parameter E d The error ratio is compared with the specified range of printing error and the working signal is output. Based on the recorded printing layer number, the error layer ratio Z is obtained. b The error is compared with the error layer ratio threshold K, and the speed of change of the printing error parameters is identified according to the comparison result. The present invention analyzes the change type of the error generated during 3D printing, identifies whether the change type of the printing error is a rapid change, and stops the 3D printing in time based on the rapid change, which is conducive to protecting 3D printing and improving the quality of 3D printing.

[0059] 2. The stratification module obtains the printing layer data, the error acquisition module measures the printing error parameters, the error approaching change analysis module analyzes the target error value to obtain the normal working signal and the analysis signal, the error change analysis module processes the error layer ratio based on the analysis signal, judges the parameter change type, stops the printing work for rapid changes, generates the type analysis signal for slow changes, and the control analysis module predicts the remaining printing error layers based on the type analysis signal, sums the remaining printing layers and the printed layers, compares with the maximum number of printing layers, and determines whether to terminate the printing work. The present invention can predict the remaining printing error layers and find out in advance whether the printing error will exceed the specified error range, which is conducive to early intervention when the printing error has a trend of exceeding the specified error range, and further protects the quality of its 3D printing. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The present invention will be further described below in conjunction with the accompanying drawings.

[0061] Figure 1 It is a flowchart of the steps of a precise control method of 3D printing based on the Internet of Things according to an embodiment of the present invention;

[0062] Figure 2 This is a module diagram of a precise control system for 3D printing based on the Internet of Things described in Example 3 of the present invention. DETAILED DESCRIPTION

[0063] 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.

[0064] Example 1

[0065] See also Figure 1 As shown, the present invention is a precise control method for 3D printing based on the Internet of Things, comprising:

[0066] Step 1: Obtain the printing data for 3D printing, wherein the printing data includes: the total printing thickness H of the physical object, the printing thickness h of each layer when the printer prints, and based on the printing data, obtain the number of 3D printing layers N;

[0067] It should be noted that the total thickness of the physical print is obtained through the physical design drawings, and the printing thickness of each layer when the printer is printing is obtained by the thickness of the number of printing layers set when the printer is printing; specifically, through the formula Obtain the total number of printing layers N, and send the printing size data of each layer to the printer through the IoT device so that the printer can use the optical sensor to measure the actual printing size information;

[0068] It should be noted that the printing size data includes but is not limited to the printing area of ​​each layer;

[0069] Step 2: Use an optical sensor to measure the actual printing size and design size of each layer, and mark the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through the formula E d =|D i -S i |Get the printing error parameter E of each printing layer d ;

[0070] Step 3: Print error parameter E d Perform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal;

[0071] It should be noted that the specified range of printing error represents the dimensional deviation range required to meet the requirements of 3D printing;

[0072] The error parameter E will be printed d The difference is processed with the two end points of the specified range of printing error respectively, and the absolute value of the difference is taken to obtain the upper limit value and the lower limit value of the error respectively;

[0073] Compare the upper error limit value with the lower error limit value. The specific comparison process is:

[0074] If the upper error limit is greater than the lower error limit, the lower error limit is used as the target error value, and its target error value is marked as L;

[0075] If the upper error limit is less than the lower error limit, the upper error limit is used as the target error value, and its target error value is marked as L;

[0076] Determine the target error value L and the error threshold H;

[0077] If L≤H, it means that the printing error is close to the upper limit of the error threshold requirement, and an analysis signal is generated;

[0078] If L>H, it means that the printing error is not close to the upper limit of the error threshold requirement, and a normal operation signal is generated, and the current printing layer number is recorded at the same time;

[0079] It should be noted that the significance of the analysis signal generation is: when L≤H, the printing error is close to the upper limit of the error threshold requirement, and analysis is required to prevent the printing error parameter from exceeding the specified range of the printing error, thereby causing damage or adverse effects on 3D printing;

[0080] It should also be noted that the normal working signal means: L>H, the printing error is not close to the upper limit of the error threshold requirement, and the printer can continue to print normally;

[0081] Step 4: Based on the analysis signal, according to the recorded printing layer number, the error layer ratio is processed and the error layer ratio Z is calculated. b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal;

[0082] Specifically, the number of printed layer numbers recorded when the statistical analysis signal is generated is compared with the number of 3D printed layers N to obtain the error layer ratio Z. b ;

[0083] It should be noted that the error layer accounts for Z b It reflects the number of printing layers that have produced printing errors when the analysis signal is generated, and the proportion of error layers is Z. b The smaller it is, the faster the change of printing error parameters is. On the contrary, the error layer accounts for Z b The larger it is, the slower the change of the printing error parameter is;

[0084] If Z b ≤K, it means that the printing error parameter changes quickly. The change of the printing error parameter is rapid, and a stop printing signal is generated.

[0085] If Z b >K, it indicates the speed of change of the printing error parameter. The change of the printing error parameter is non-rapid change, and a type analysis signal is generated;

[0086] Based on the fact that the change type of the printing error parameter is a rapid change, a stop printing signal is sent to the printer to prevent the printer from continuing to print, so that the printing error parameter exceeds the specified range of the printing error, thereby having an adverse effect on its 3D printing;

[0087] The technical solution of the embodiment of the present invention is: based on the 3D printing data, the number of 3D printing layers N is obtained by processing, the actual printing size of each layer is measured and compared with the design size, and the printing error parameter E of each printing layer is obtained. d , print the error parameter E dThe error ratio is compared with the specified range of printing error and the working signal is output. Based on the recorded printing layer number, the error layer ratio Z is obtained. b The error is compared with the error layer ratio threshold K, and the speed of change of the printing error parameters is identified according to the comparison result. The present invention analyzes the change type of the error generated during 3D printing, identifies whether the change type of the printing error is a rapid change, and stops the 3D printing in time based on the rapid change, which is conducive to protecting 3D printing and improving the quality of 3D printing.

[0088] Example 2

[0089] like Figure 1 As shown, based on Example 1, a precise control method for 3D printing based on the Internet of Things described in an embodiment of the present invention includes:

[0090] Step 5: Based on the type analysis signal, identify the change type of the printing error parameter, and process and analyze the target number of printing layers according to the change type of the printing error parameter, and compare the target number of printing layers with the 3D printing layer number N to determine whether to continue 3D printing;

[0091] Among them, the change types of printing error parameters include regular changes and irregular changes;

[0092] Construct a printing error variation curve in a two-dimensional coordinate system. The specific construction method is as follows:

[0093] The number of printed layers is the X-axis, and the printing error parameter E d As the Y axis, a rectangular two-dimensional coordinate system is constructed, and the numbers of the printed layers and the printing error parameters corresponding to the printed layers are recorded and marked in the rectangular two-dimensional coordinate system, and the marked printing error parameter data points are connected to obtain a printing error change curve;

[0094] Divide the print error curve into multiple curve segments, measure the slope of each curve segment, and compare it with 0:

[0095] If the slope of the curve segment is greater than 0, the curve segment is marked as a growth curve segment;

[0096] If the slope of the curve segment is less than or equal to 0, the curve segment is marked as a non-increasing curve segment;

[0097] The ratio of the number of growth curve segments to the total number of curve segments is calculated to obtain the ratio of the number of growth curve segments, which is marked as Z. e ;

[0098] It should be noted that the curve segment is a line segment between two printing error parameter data points, and the slope of the curve segment is obtained as follows:

[0099] A number of sampling points are selected on the curve segment, the tangent slope of the curve segment at each sampling point is measured, and all the measured tangent slope values ​​are summed and averaged to obtain the slope value of the curve segment;

[0100] The slopes of all curve segments are integrated into a slope set K, specifically: K = {k 1 , k 2 , k 3 ,......,k j}, j represents the number of the curve segment, calculate the variance of the elements in the set K and mark it as f;

[0101] The proportion of the number of growth curve segments obtained is Z e Data processing is performed with the variance f of the slope set K, using the formula: Obtain a linear reference X, where α and β are preset proportional coefficients;

[0102] It should be noted that the linear reference X means: the linear reference X is a combination of the growth curve segment number proportion Z e The variance f of the slope set K is calculated, where the number of growth curve segments accounts for Z e It reflects the persistence of the growth change of the printing error parameters. The variance f of the slope set K reflects the volatility of the growth change of the printing error parameters. The number of growth curve segments accounts for Z e The larger the value is, the stronger the persistence of the growth change of the printing error parameter is. The smaller the variance f of the slope set K is, the smaller the volatility of the growth change of the printing error parameter is. The overall indication is that the change of the printing error parameter presents a regular change.

[0103] Compare the linear reference X with the linear reference threshold. The specific comparison process is as follows:

[0104] The preset linear reference threshold is Y;

[0105] If the linear reference X ≥ the linear reference threshold Y, it means that the change type of the printing error parameter is a regular change;

[0106] If the linear reference X<linear reference threshold Y, it means that the change type of the printing error parameter is irregular;

[0107] Specifically, if the printing error parameter E d The change type is a regular change, which will be related to the printing error parameter E dThe endpoint value of the nearest error specified range is used as the reference parameter, and the reference parameter is marked on the Y axis of the coordinate system where the printing error change curve is located. The marked data point is used as the reference point, and a parallel line parallel to the X axis is drawn through the reference point and marked as the printing error warning line;

[0108] Obtain all printing error parameter data points used to construct the printing error change curve, and fit all the printing error parameter data points by the least square method to obtain a fitting straight line, extend the fitting straight line and intersect it with the printing error warning line to obtain the intersection of the two lines, obtain the X-axis coordinate of the intersection, and obtain the target number of printing layers n based on the X-axis coordinate of the intersection;

[0109] It should be noted that when the least squares method is used to predict the number of layers that reach the printing threshold, if the result is not an integer, in order to ensure that it meets the actual printing requirements, we adopt the strategy of rounding up and adding one to determine the final number of data layers used. This processing method can provide more adequate protection for the printing process to a certain extent, and avoid affecting the printing quality and effect due to insufficient layers.

[0110] An exemplary description is given below:

[0111] For example, the target number of printing layers predicted by the least squares method is 7.3, which is rounded up to 8, and the 8th layer is used as the target number of printing layers to reach the printing error threshold;

[0112] Compare the target number of printing layers n with the number of 3D printing layers N;

[0113] If n ≥ the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer will not exceed the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will not exceed the specified range of the printing error, and the printing will continue;

[0114] If n<the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer exceeds the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will exceed the specified range of the printing error, and the printing will be stopped;

[0115] If the printing error parameter E d The change type of is irregular change, the curve segment with the largest slope among all growth curve segments is obtained as the target curve segment, the printing error parameters corresponding to the end points of the target curve segment are obtained, and the difference processing is performed to obtain the maximum value of the printing error parameter change;

[0116] The target error value when the analysis signal is generated is processed by ratio with the maximum value of the change of the printing error parameter to obtain the number of remaining printing layers;

[0117] It should be noted that in order to ensure that the actual printing requirements are met, we adopt the strategy of rounding up and adding one to determine the remaining number of printing layers. This processing method can provide more adequate protection for the printing process to a certain extent, and avoid affecting the printing quality and effect due to insufficient layers;

[0118] Add the remaining number of printing layers to the number of printed layers to get the target number of printing layers n;

[0119] Compare the target number of printing layers n with the number of 3D printing layers N;

[0120] If n ≥ the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer will not exceed the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will not exceed the specified range of the printing error, and the printing will continue;

[0121] If n<the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer exceeds the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will exceed the specified range of the printing error, and the printing will be stopped;

[0122] The technical solution of the embodiment of the present invention is: based on the type analysis signal, the change type of its printing error parameters is identified, and according to the change type of the printing error parameters, the target number of printing layers is processed and analyzed, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing. The present invention deeply explores the error change characteristics by constructing a curve, calculates the linear reference degree to comprehensively evaluate the error trend to accurately determine the error type, and overall improves the accuracy, versatility, stability and reliability of the 3D printing precision control method.

[0123] Example 3

[0124] See also Figure 2 As shown, a precise control system for 3D printing based on the Internet of Things according to an embodiment of the present invention includes:

[0125] Layering module: obtains the printing data of 3D printing, wherein the printing data includes: the total printing thickness H of the physical object and the printing thickness h of each layer when the printer prints, and processes the printing data to obtain the number of 3D printing layers N;

[0126] Error acquisition module: Use optical sensors to measure the actual printing size of each layer and compare it with the designed size, marking the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through the formula E d =|D i -S i|Get the printing error parameter E of each printing layer d ;

[0127] Error proximity analysis module: print error parameter E d Perform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal;

[0128] Error change analysis module: Based on the analysis signal, according to the recorded printing layer number, the error layer ratio is processed and the error layer ratio Z is calculated. b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal;

[0129] Control analysis module: Based on the type analysis signal, the change type of the printing error parameters is identified, and according to the change type of the printing error parameters, the target number of printing layers is processed and analyzed, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing.

[0130] The technical solution of the embodiment of the present invention is: based on the precise control of 3D printing of the Internet of Things, the printing data of the total thickness H of the physical printing and the printing thickness h of each layer are obtained through the layering module, and the number of 3D printing layers is calculated. Through the error acquisition module, the actual printing size and design size of each layer are measured by using an optical sensor, and the printing error parameters of each printing layer are calculated according to the formula to realize the quantification of the printing error of each layer. Through the error proximity analysis module, the printing error parameter is analyzed with the specified range for difference analysis to determine whether the printing error is close to the specified upper limit. Through the error change analysis module, based on the analysis signal, the error layer ratio is calculated according to the recorded printing layer number, and compared with the threshold K to identify whether the change of the printing error parameter is a rapid change, and then a stop printing signal or a type analysis signal is generated to preliminarily determine whether the change speed of the printing error is too fast. The control analysis module identifies the change type of the printing error parameter based on the type analysis signal, and further predicts the number of printing layers according to the change type, and then compares it with the 3D printing layer number N to decide whether to continue printing. Through the orderly collaboration between the various modules, the device can maintain a stable operating state, reliably and accurately control the printing process, and improve the reliability of the entire 3D printing system.

[0131] 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. A precise control method for 3D printing based on the Internet of Things, characterized in that: include: Acquire printing data for 3D printing, wherein the printing data includes: the total printing thickness of the physical object and the printing thickness of each layer when the printer prints, and obtain the number of 3D printing layers N based on the printing data; Use an optical sensor to measure the actual printing size and design size of each layer, and mark the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through formula E d =|D i -S i |Get the printing error parameter E of each printing layer d ; The error parameter E will be printed d Perform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal; Based on the analysis signal, according to the recorded printing layer number, the error layer ratio Z is obtained. b , the error layer ratio Z b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal; Based on the type analysis signal, the change type of the printing error parameter is identified, and according to the change type of the printing error parameter, the target number of printing layers is obtained through processing and analysis, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing; The change types of the printing error parameters include regular changes and irregular changes.

2. According to the method for precise control of 3D printing based on the Internet of Things in claim 1, it is characterized in that: The target error value is obtained as follows: The error parameter E will be printed d The difference is processed with the two end points of the specified range of printing error respectively, and the absolute value of the difference is taken to obtain the upper limit value and the lower limit value of the error respectively; Compare the upper error limit value with the lower error limit value. The specific comparison process is: If the upper error limit is greater than the lower error limit, the lower error limit is used as the target error value, and its target error value is marked as L; If the upper error limit is less than the lower error limit, the upper error limit is used as the target error value, and its target error value is marked as L.

3. The precise control method of 3D printing based on the Internet of Things according to claim 1, characterized in that: The working signal is obtained in the following manner: Determine the target error value L and the error threshold H; If L≤H, it means that the printing error is close to the upper limit of the error threshold requirement, and an analysis signal is generated; If L>H, it means that the printing error is not close to the upper limit of the error threshold requirement, and a normal operation signal is generated, and the current printing layer number is recorded at the same time.

4. According to the method for precise control of 3D printing based on the Internet of Things in claim 1, it is characterized in that: The error layer number accounts for Z b The way to obtain is: When the statistical analysis signal is generated, the number of printed layer numbers that have been recorded is compared with the number of 3D printed layers N to obtain the error layer ratio Z. b .

5. The precise control method of 3D printing based on the Internet of Things according to claim 4 is characterized in that: The process of identifying the change type of its printing error parameter is as follows: The proportion of the number of growth curve segments obtained is Z e Data processing is performed with the variance f of the slope set K, using the formula: Obtain a linear reference X, where α and β are preset proportional coefficients; Compare the linear reference X with the linear reference threshold. The specific comparison process is as follows: The preset linear reference threshold is Y; If the linear reference X ≥ the linear reference threshold Y, it means that the change type of the printing error parameter is a regular change; If the linear reference X<linear reference threshold Y, it means that the change type of the printing error parameter is irregular change.

6. The precise control method of 3D printing based on the Internet of Things according to claim 5, characterized in that: The proportion of the growth curve segments is Z e The method of obtaining is: Construct a printing error variation curve in a two-dimensional coordinate system. The specific construction method is as follows: The number of printed layers is the X-axis, and the printing error parameter E d As the Y axis, a rectangular two-dimensional coordinate system is constructed, and the numbers of the printed layers and the printing error parameters corresponding to the printed layers are recorded and marked in the rectangular two-dimensional coordinate system, and the marked printing error parameter data points are connected to obtain a printing error change curve; Divide the print error curve into multiple curve segments, measure the slope of each curve segment, and compare it with 0: If the slope of the curve segment is greater than 0, the curve segment is marked as a growth curve segment; If the slope of the curve segment is less than or equal to 0, the curve segment is marked as a non-increasing curve segment; The ratio of the number of growth curve segments to the total number of curve segments is calculated to obtain the ratio of the number of growth curve segments, which is marked as Z. e .

7. The precise control method of 3D printing based on the Internet of Things according to claim 5, characterized in that: The variance f of the slope set K is obtained as follows: The slopes of all curve segments are integrated into a slope set K, specifically: K = {k1, k2, k3, ..., k j }, j represents the number of the curve segment, calculate the variance of the elements in the set K and mark it as f.

8. The precise control method for 3D printing based on the Internet of Things according to claim 1, characterized in that: The target number of printing layers is obtained as follows: If the printing error parameter E d The change type is a regular change, which will be related to the printing error parameter E d The endpoint value of the nearest error specified range is used as the reference parameter, and the reference parameter is marked on the Y axis of the coordinate system where the printing error change curve is located. The marked data point is used as the reference point, and a parallel line parallel to the X axis is drawn through the reference point and marked as the printing error warning line; Obtain all printing error parameter data points used to construct the printing error change curve, and fit all the printing error parameter data points by the least square method to obtain a fitting straight line, extend the fitting straight line and intersect it with the printing error warning line to obtain the intersection of the two lines, obtain the X-axis coordinate of the intersection, and obtain the target number of printing layers n based on the X-axis coordinate of the intersection; If the printing error parameter E d The change type of is irregular change, the curve segment with the largest slope among all growth curve segments is obtained as the target curve segment, the printing error parameters corresponding to the end points of the target curve segment are obtained, and the difference processing is performed to obtain the maximum value of the printing error parameter change; The target error value when the analysis signal is generated is processed by ratio with the maximum value of the change of the printing error parameter to obtain the number of remaining printing layers; Add the remaining number of printing layers to the number of printed layers to get the target number of printing layers n.

9. The precise control method for 3D printing based on the Internet of Things according to claim 1, characterized in that: The process of determining whether to continue 3D printing is as follows: Compare the target number of printing layers n with the number of 3D printing layers N; If n ≥ the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer will not exceed the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will not exceed the specified range of the printing error, and the printing will continue; If n<the maximum number of layers N, it means that under the change type of the printing error parameter, the nth layer exceeds the 3D printing layer number N, which means that before the printing is completed, the printing error parameter will exceed the specified range of the printing error, and the printing will be stopped.

10. A precise control system for 3D printing based on the Internet of Things, characterized by: The system is used to implement the control method according to any one of claims 1 to 9, comprising: Layering module: obtains the printing data of 3D printing, wherein the printing data includes: the total printing thickness of the physical object and the printing thickness of each layer when the printer prints, and processes the printing data to obtain the number of 3D printing layers N; Error acquisition module: Use optical sensors to measure the actual printing size and design size of each layer, and mark the actual printing size of each layer as D i , mark the design size of each layer as S i , i = 1, 2, 3.....i represents the layer number; through formula E d =|D i -S i |Get the printing error parameter E of each printing layer d ; Error proximity analysis module: print error parameter E d Perform difference processing and analysis with the specified range of printing error to obtain a target error value, perform comparison processing on the target error value to obtain a working signal, wherein the working signal includes a normal working signal and an analysis signal; Error change analysis module: Based on the analysis signal, according to the recorded printing layer number, the error layer ratio Z is processed b , the error layer ratio Z b Compare it with the error layer ratio threshold K, and identify whether the change of its printing error parameter is a rapid change according to the comparison result. If so, generate a stop printing signal, if not, generate a type analysis signal; Control analysis module: Based on the type analysis signal, the change type of the printing error parameter is identified, and according to the change type of the printing error parameter, the target number of printing layers is obtained through processing and analysis, and the target number of printing layers is compared with the 3D printing layer number N to determine whether to continue 3D printing; The change types of the printing error parameters include regular changes and irregular changes.

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