3D printing equipment safety management system and method based on dynamic analysis

Abstract

The present invention discloses a 3D printing equipment safety management system and method based on dynamic analysis, which relates to the technical field of data analysis. In the 3D printing equipment, the present invention obtains slice data of the printing model and determines each printing difficulty level; summarizes historical printing records of the same printing difficulty level, determines feature records, and determines a first operation behavior and a second operation behavior; obtains slice data of the model to be printed, calculates the printing difficulty score of the model to be printed, determines the printing difficulty level of the model to be printed, obtains a first operation behavior set of the printing difficulty level, calculates the first operation behavior score, and judges the execution step; when printing is completed, calculates the operator's operation score, calculates the operator's next training time interval, and determines the training behavior based on the next training time interval, thereby improving equipment safety in the 3D printing process and reducing potential risks of human operation.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a 3D printing equipment security management system and method based on dynamic analysis. Background Art

[0002] With the rapid development and widespread application of 3D printing technology, equipment safety management has become a critical issue in ensuring the safety of production and operators. However, traditional 3D printing equipment safety management methods mostly focus on monitoring the status of the equipment itself. For example, sensors collect parameters such as temperature, motor load, and printing platform displacement, and determine whether to trigger an alarm based on preset thresholds. Although these methods can ensure equipment safety to a certain extent, they still have some significant shortcomings in practical applications.

[0003] Traditional methods often overlook the risks posed by human operation. During the 3D printing process, the operator's operating behavior, such as the startup sequence, pause timing, and fault recovery process, may directly affect the safety of the equipment. However, too frequent training will affect the efficiency of equipment use. Therefore, it is necessary to find the right time to train operators to improve equipment safety during the 3D printing process and reduce the potential risks of human operation. Summary of the Invention

[0004] The purpose of the present invention is to provide a 3D printing equipment safety management system and method based on dynamic analysis to solve the problems raised in the prior art.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: a 3D printing equipment security management method based on dynamic analysis, the method comprising:

[0006] Step S100: In the 3D printing device, slice data of the printed model is obtained, the operation instructions of each slice layer are collected, the total operation distance of the printed model is calculated, the number of material types and colors, and the weight of the materials used in the printed model are obtained, the printing difficulty score is calculated, and each printing difficulty level is determined;

[0007] Step S200: Summarize historical printing records of the same printing difficulty level, determine characteristic records, classify the characteristic records based on the event time points corresponding to the abnormal events in the characteristic records and the operation time points at which the operators performed the operation behaviors, calculate characteristic scores of the operation behaviors, and determine the first operation behavior and the second operation behavior;

[0008] Step S300: Acquire slice data of the model to be printed, calculate the printing difficulty score of the model to be printed, determine the printing difficulty level of the model to be printed, obtain a first operation behavior set of the printing difficulty level, calculate the first operation behavior score based on real-time monitoring of the operator's operation behavior, and determine the execution step based on the first operation behavior score;

[0009] Step S400: When printing is completed, the number of times the operator performs the second operation behavior is collected, the operator's operation score is calculated, the operator's next training time interval is calculated, and the training behavior is determined based on the next training time interval.

[0010] Furthermore, step S100 includes:

[0011] Step S101: obtaining slice data of a model to be printed by a 3D printing device, collecting operation instructions for printing each slice layer, and monitoring device operation parameters during the printing process through a sensor device of the 3D printing device. When a device operation parameter exceeds a device operation parameter threshold, the device operation parameter is set as an abnormal parameter and an abnormal event is generated;

[0012] Step S102: Obtain the running distances of the nozzle on the X, Y, and Z axes respectively when executing the running instruction as AX, AY, and ZY, calculate the total running distance of executing the running instruction as A=AX+AY+ZY, and add the total running distances of all running instructions to obtain the total running distance of the printed model;

[0013] Step S103: Obtain historical printing records, collect the material type, number, color, and weight used in a certain historical printing record when printing the model, summarize the material type, number, color, and weight of all historical printing records, and perform normalization calculations to obtain the normalized material type, color, and weight;

[0014] Step S104: Obtain the total running distance of a certain historical printing record, and calculate the printing difficulty score according to the following formula:

[0015] ;

[0016] Where W represents the printing difficulty score, A represents the total running distance, B represents the normalized number of material types, C represents the normalized number of colors, D represents the normalized weight of used materials, and UA, UB, UC, and UD represent the weights of the total running distance, number of material types, number of colors, and weight of used materials, respectively.

[0017] Step S105: Preset a number of printing difficulty levels, obtain the printing difficulty score corresponding to each printing difficulty level, and determine the printing difficulty level corresponding to the historical printing record;

[0018] By collecting and monitoring equipment operating parameters in real time, abnormal parameters such as temperature, speed, and current can be discovered in a timely manner and abnormal events can be generated, thereby achieving dynamic monitoring and fault warning during the printing process, avoiding printing failures or quality defects caused by equipment abnormalities;

[0019] Printing tasks are comprehensively evaluated based on multiple dimensions, including running distance, material type, number of colors, and material weight. Weights are then introduced to assign scores and calculate a printing difficulty score, which objectively reflects the complexity of the printing task and facilitates task classification, resource scheduling, and printing strategy optimization.

[0020] By normalizing historical printing records, the order of magnitude differences between different printing tasks can be eliminated, and a unified measurement standard can be achieved, which is helpful for model learning and printing strategy adjustment, and improves the system's adaptability to different printing tasks and intelligent decision-making capabilities.

[0021] Furthermore, step S200 includes:

[0022] Step S201: Summarize historical printing records of the same printing difficulty level, and in the historical printing record set of each printing difficulty level, collect historical printing records with abnormal events and set them as feature records;

[0023] Step S202: In a feature record set of a certain printing difficulty level, abnormal events of the same type are aggregated to obtain a feature record set of a certain abnormal event. The event time point corresponding to a certain abnormal event in a certain feature record is collected, the operation behavior of the operator in the certain feature record is obtained, and the operation time point corresponding to the execution of the operation behavior is obtained. The operation behavior whose operation time point is less than the event time point is set as the first feature record, and the operation behavior whose operation time point is greater than or equal to the event time point is set as the second feature record.

[0024] Step S203: Summarize the first feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a first feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all first feature records, calculate the average slope change value of the operation behavior, and count the number of first feature records of the operation behavior. The average slope change value and the number of first feature records are used as the first feature data group of the operation behavior;

[0025] Step S204: Summarize the second feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a second feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all second feature records, calculate the average slope change value of the operation behavior, and count the number of second feature records of the operation behavior. The average slope change value and the number of second feature records are used as the second feature data set of the operation behavior;

[0026] Step S205: Establish an operation behavior formula to calculate the characteristic score of the operation behavior:

[0027] ;

[0028] Where P represents the feature score of the operation behavior, K represents the average slope change value, H represents the number of feature records of the operation behavior, H represents the total number of feature records, Lk and Lh represent the weights of the average slope change value and the number of feature records, respectively. The first feature data group and the second feature data group of a certain operation behavior are input into the operation behavior formula respectively to calculate the first feature score and the second feature score of the certain operation behavior;

[0029] Step S206: Preset a feature score threshold, set the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and set the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain a first operation behavior set and a second operation behavior set;

[0030] By comparing operational behavior with the time of abnormal events, the operational behavior before and after the abnormality can be distinguished. This helps determine whether the operational behavior may be the cause or response to the abnormal event, thereby improving the pertinence and accuracy of fault analysis.

[0031] By plotting the change curve of abnormal parameters and calculating its slope change value, the impact of operating behavior on the equipment status before and after the abnormality occurs can be effectively quantified. Combined with statistical data, a characteristic data set of operating behavior can be further formed to achieve the goal of discovering patterns and extracting features from the data.

[0032] By setting an operation behavior scoring formula, the impact of operation behavior on abnormal parameters and its frequency of occurrence are integrated to scientifically measure the "abnormal correlation" or "response effectiveness" of various operation behaviors;

[0033] The first and second operation behaviors are distinguished by setting thresholds, which can be used for:

[0034] The first set of operational behaviors: used to analyze potential improper operations, guide the optimization of operating procedures, and update training content;

[0035] The second set of operational behaviors: used to analyze effective emergency response actions, extract best practices, and enhance operational standardization.

[0036] Furthermore, step S300 includes:

[0037] Step S301: obtaining slice data of the model to be printed, calculating the printing difficulty score of the model to be printed, and determining the printing difficulty level of the model to be printed;

[0038] Step S302: Obtain a first set of operation behaviors and a second set of operation behaviors corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if the first operation behavior exists, record and count the number of the first operation behavior, and calculate the first operation behavior score according to the following formula:

[0039] ;

[0040] Among them, Q represents the first operation behavior score, S i Expressed as the number of the first operation behavior of type i, g i It is represented as the characteristic score of the i-th first operation behavior, and r is represented as the number of types of first operation behaviors;

[0041] Step S303: Preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed.

[0042] Combined with the dynamic identification and recording of the first set of operating behaviors, it can track in real time whether the operator has performed any behaviors that may cause abnormalities during the printing process. Through the behavior identification + statistical scoring mechanism, it can achieve continuous supervision and evaluation of high-risk behaviors.

[0043] The first operation behavior scoring formula is introduced. This mechanism realizes the quantitative assessment of behavior risk, which can fully reflect the contribution of the operator's current behavior to printing risk and provide a data basis for the system to make control decisions.

[0044] By setting a reasonable first-operation score threshold, once the cumulative score of the operator's high-risk behaviors exceeds the threshold, the system will automatically interrupt printing and trigger a training or guidance mechanism to curb printing failures or quality problems caused by human operational errors at the source.

[0045] Furthermore, step S400 includes:

[0046] Step S401: When printing is completed, the number of times the operator performs the second operation is collected, and the operator's operation score is calculated according to the following formula:

[0047] ;

[0048] Among them, G represents the operator's operation score, R n Expressed as the number of the nth second operation behavior, q n It is expressed as the characteristic score of the nth second operational behavior;

[0049] Step S402: Obtain the date of the last safety operation training for the operator, calculate the time interval from the last training to the completion of the current printing job, and calculate the next training time interval according to the following formula:

[0050] ;

[0051] T1 represents the time interval for the next training, and T2 represents the time interval from the last training to the completion of this printing job;

[0052] Step S403: Preset the operator's regular training time interval. If the next training time interval is less than the regular training time interval, the operator needs to be trained in safe operation in advance.

[0053] By collecting the operator's secondary operation behaviors during the printing process and introducing a scoring formula to score the characteristics of these behaviors, the operator's exception handling capabilities and emergency response effects can be objectively reflected, helping to build a data-based performance evaluation system.

[0054] A formula for operator training intervals has been introduced to provide the recommended time interval for the next training session. Through this mechanism, the system can dynamically determine the frequency of training based on the operator's actual performance, enabling the transition from "periodic training" to "on-demand training."

[0055] Introduce the concept of regular training time intervals to improve the accuracy and timeliness of training, avoid the waste of ineffective training resources, and strengthen attention and guidance for operators with potential risks.

[0056] In order to better implement the above method, a 3D printing equipment safety management system based on dynamic analysis is proposed. The system includes a printing difficulty level module, an operation behavior module, an execution step module, and a management training module.

[0057] Printing difficulty level module: In the 3D printing device, it obtains the slice data of the printed model, collects the running instructions of each slice layer, calculates the total running distance of the printed model, obtains the number of material types, colors, and weight of the printed model, calculates the printing difficulty score, and determines the difficulty level of each printing;

[0058] Operation behavior module: This module aggregates historical printing records of the same printing difficulty level, identifies characteristic records, categorizes characteristic records based on the event time points corresponding to abnormal events in the characteristic records and the operation time points at which the operator performs the operation behavior, calculates characteristic scores for the operation behavior, and determines the first and second operation behaviors;

[0059] Execution step module: obtains slice data of the model to be printed, calculates the printing difficulty score of the model to be printed, determines the printing difficulty level of the model to be printed, obtains a first operation behavior set of the printing difficulty level, calculates the first operation behavior score based on real-time monitoring of the operator's operation behavior, and determines the execution step based on the first operation behavior score;

[0060] Management training module: When printing is completed, the number of second operation behaviors performed by the operator is collected, the operator's operation score is calculated, the operator's next training time interval is calculated, and the training behavior is determined based on the next training time interval.

[0061] Furthermore, the printing difficulty level module includes a unit for calculating the total running distance and a unit for determining the printing difficulty level:

[0062] A total running distance calculation unit: obtains slice data of a model to be printed by a 3D printing device, collects running instructions for printing each slice layer, monitors the device operating parameters during the printing process through the sensor device of the 3D printing device, and when a device operating parameter exceeds the device operating parameter threshold, the device operating parameter is set as an abnormal parameter, an abnormal event is generated, and the running distance of the nozzle on the X, Y, and Z axes when executing the running instruction is obtained. The total running distance of the running instruction is calculated, and the total running distance of all running instructions is added to obtain the total running distance of the printed model;

[0063] Printing difficulty level determination unit: obtains historical printing records, collects the number of material types, number of colors, and weight of materials used in a certain historical printing record when printing a model, summarizes the number of material types, number of colors, and weight of materials used for all historical printing records, and performs normalization calculations to obtain the normalized number of material types, number of colors, and weight of materials used, obtains the total running distance of a certain historical printing record, calculates the printing difficulty score, presets several printing difficulty levels, obtains the printing difficulty score corresponding to each printing difficulty level, and determines the printing difficulty level corresponding to the historical printing record.

[0064] Furthermore, the operation behavior module includes a feature recording unit and an operation behavior determination unit:

[0065] Determine the feature record unit: summarize the historical printing records of the same printing difficulty level, collect the historical printing records with abnormal events in the historical printing record set of each printing difficulty level and set them as feature records, summarize the same abnormal events in the feature record set of a certain printing difficulty level to obtain a feature record set of a certain abnormal event, collect the event time point corresponding to a certain abnormal event in a certain feature record, obtain the operation behavior of the operator in the said certain feature record, and obtain the operation time point corresponding to the execution of the operation behavior, set the operation behavior with an operation time point less than the event time point as the first feature record, set the operation behavior with an operation time point greater than or equal to the event time point as the second feature record, summarize the first feature records of the same operation behavior, and collect the abnormal parameters of a certain first feature record between the operation time point and the event time point. The value between the first and second feature records is collected, and a quality change curve of the abnormal parameter is drawn to obtain the slope change value of the abnormal parameter, and all first feature records are summarized to calculate the average slope change value of the operation behavior, and the number of first feature records of the operation behavior is counted, and the average slope change value and the number of first feature records are used as the first feature data group of the operation behavior, and the second feature records of the same operation behavior are summarized, and the value of the abnormal parameter of a second feature record between the operation time point and the event time point is collected, and a quality change curve of the abnormal parameter is drawn to obtain the slope change value of the abnormal parameter, and all second feature records are summarized to calculate the average slope change value of the operation behavior, and the number of second feature records of the operation behavior is counted, and the average slope change value and the number of second feature records are used as the second feature data group of the operation behavior;

[0066] Determine the operation behavior unit: establish an operation behavior formula to calculate the feature score of the operation behavior, input the first feature data group and the second feature data group of a certain operation behavior into the operation behavior formula respectively, calculate the first feature score and the second feature score of the certain operation behavior, preset the feature score threshold, set the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and set the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain the first operation behavior set and the second operation behavior set.

[0067] Furthermore, the execution step module includes a first operation behavior scoring unit and an execution step determination unit:

[0068] A first operation behavior scoring calculation unit is configured to obtain slice data of a model to be printed, calculate a printing difficulty score of the model to be printed, determine a printing difficulty level of the model to be printed, obtain a first operation behavior set and a second operation behavior set corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if a first operation behavior exists, record and count the number of the first operation behaviors, and calculate a first operation behavior score;

[0069] Determine execution step unit: preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed.

[0070] Furthermore, the management training module includes a calculation operation scoring unit and an analysis training unit:

[0071] An operation score calculation unit: when printing is completed, collecting the number of second operation behaviors performed by the operator and calculating the operation score of the operator;

[0072] Analysis and training unit: obtain the date of the last safety operation training for the operator, calculate the time interval from the last training to the completion of this printing job, calculate the next training time interval, and preset the operator's regular training time interval. When the next training time interval is less than the regular training time interval, the operator needs to be trained in safety operation in advance.

[0073] Compared with the existing technology, the present invention has the beneficial effect of monitoring and evaluating the entire printing process by starting from multiple dimensions such as pre-printing slice data, equipment operating parameters, historical data normalization, and printing difficulty score. The real-time identification of abnormal parameters and the event generation mechanism enhance the system's self-diagnosis capability, effectively preventing printing failures or quality defects caused by equipment out of control or misoperation.

[0074] The printing difficulty scoring formula can quantify the complexity of printing tasks, providing a scientific basis for scheduling task allocation, equipment resource selection, and operator arrangement, thereby optimizing overall production efficiency and risk management.

[0075] Match operational behaviors with abnormal events at specific time points, calculate slope change values ​​and behavior frequencies, and establish an operational behavior scoring model to effectively distinguish between behaviors that potentially cause abnormalities and behaviors that respond to abnormalities, enabling quantitative correlation analysis of operational behaviors and system state changes.

[0076] The next recommended training time is calculated based on the actual training interval, realizing a mechanism for dynamically adjusting the training cycle based on operational performance, which not only improves the timeliness of training but also avoids waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 Schematic diagram of the process of the 3D printing equipment security management method based on dynamic analysis of the present invention;

[0078] Figure 2 This is a schematic diagram of the structure of the 3D printing equipment safety management system based on dynamic analysis of the present invention. DETAILED DESCRIPTION

[0079] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0080] See also Figure 1 The present invention provides a technical solution: a 3D printing equipment security management method based on dynamic analysis, the method comprising:

[0081] Step S100: In the 3D printing device, slice data of the printed model is obtained, the operation instructions of each slice layer are collected, the total operation distance of the printed model is calculated, the number of material types and colors, and the weight of the materials used in the printed model are obtained, the printing difficulty score is calculated, and each printing difficulty level is determined;

[0082] Wherein, step S100 includes:

[0083] Step S101: obtaining slice data of a model to be printed by a 3D printing device, collecting operation instructions for printing each slice layer, and monitoring device operation parameters during the printing process through a sensor device of the 3D printing device. When a device operation parameter exceeds a device operation parameter threshold, the device operation parameter is set as an abnormal parameter and an abnormal event is generated;

[0084] Step S102: Obtain the running distances of the nozzle on the X, Y, and Z axes respectively when executing the running instruction as AX, AY, and ZY, calculate the total running distance of executing the running instruction as A=AX+AY+ZY, and add the total running distances of all running instructions to obtain the total running distance of the printed model;

[0085] Step S103: Obtain historical printing records, collect the material type, number, color, and weight used in a certain historical printing record when printing the model, summarize the material type, number, color, and weight of all historical printing records, and perform normalization calculations to obtain the normalized material type, color, and weight;

[0086] Step S104: Obtain the total running distance of a certain historical printing record, and calculate the printing difficulty score according to the following formula:

[0087] ;

[0088] where, W represents the printing difficulty score, A represents the total running distance, B represents the number of normalized material types, C represents the number of normalized colors, D represents the normalized weight of the used material, and UA, UB, UC, UD respectively represent the weights of the total running distance, the number of material types, the number of colors, and the weight of the used material;

[0089] Step S105: Preset several printing difficulty levels, obtain the printing difficulty scores corresponding to each printing difficulty level, and determine the printing difficulty level corresponding to the historical printing record;

[0090] For example, the system reads the G-code slicing data of a gear model and monitors key running parameters during printing, such as temperature, nozzle pressure, motor current, etc.; when the nozzle pressure instantaneously rises above the critical threshold, the system records this as an abnormal event and sets this running parameter as an "abnormal parameter";

[0091] In the G-code instruction, the system extracts the cumulative movement distances of the nozzle in the three-axis directions as follows: AX = 2500mm, AY = 1800mm, AZ = 600mm, then the total running distance for executing the printing of this model is 4900mm;

[0092] The current model uses the following printing material information: number of material types: 3 types (ABS, PLA, TPU), number of colors: 4 types (red, yellow, blue, black), total weight of the used material: 350g. From 100 historical printing records, the following standardized parameter examples are obtained after normalization: B = 0.75, C = 0.80, D = 0.60;

[0093] Set the weights as follows: UA = 0.4, UB = 0.2, UC = 0.2, UD = 0.2, and the calculated printing difficulty score is 0.798;

[0094] Assume that for printing difficulty level one, W ≤ 0.4; for printing difficulty level two, 0.4 < W ≤ 0.7; for printing difficulty level three, 0.7 < W ≤ 0.9; for printing difficulty level four, W > 0.9. Then the gear model belongs to printing difficulty level three.

[0095] Step S200: Summarize historical printing records of the same printing difficulty level, determine characteristic records, classify the characteristic records based on the event time points corresponding to the abnormal events in the characteristic records and the operation time points at which the operators performed the operation behaviors, calculate characteristic scores of the operation behaviors, and determine the first operation behavior and the second operation behavior;

[0096] Wherein, step S200 includes:

[0097] Step S201: Summarize historical printing records of the same printing difficulty level, and in the historical printing record set of each printing difficulty level, collect historical printing records with abnormal events and set them as feature records;

[0098] Step S202: In a feature record set of a certain printing difficulty level, abnormal events of the same type are aggregated to obtain a feature record set of a certain abnormal event. The event time point corresponding to a certain abnormal event in a certain feature record is collected, the operation behavior of the operator in the certain feature record is obtained, and the operation time point corresponding to the execution of the operation behavior is obtained. The operation behavior whose operation time point is less than the event time point is set as the first feature record, and the operation behavior whose operation time point is greater than or equal to the event time point is set as the second feature record.

[0099] Step S203: Summarize the first feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a first feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all first feature records, calculate the average slope change value of the operation behavior, and count the number of first feature records of the operation behavior. The average slope change value and the number of first feature records are used as the first feature data group of the operation behavior;

[0100] Step S204: Summarize the second feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a second feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all second feature records, calculate the average slope change value of the operation behavior, and count the number of second feature records of the operation behavior. The average slope change value and the number of second feature records are used as the second feature data set of the operation behavior;

[0101] Step S205: Establish an operation behavior formula to calculate the characteristic score of the operation behavior:

[0102] ;

[0103] Where P represents the feature score of the operation behavior, K represents the average slope change value, H represents the number of feature records of the operation behavior, H represents the total number of feature records, Lk and Lh represent the weights of the average slope change value and the number of feature records, respectively. The first feature data group and the second feature data group of a certain operation behavior are input into the operation behavior formula respectively to calculate the first feature score and the second feature score of the certain operation behavior;

[0104] Step S206: Preset a feature score threshold, set the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and set the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain a first operation behavior set and a second operation behavior set;

[0105] For example, the system screened all historical printing records with difficulty level three, totaling 120 records, of which 24 records contained "abnormal nozzle temperature" events and were marked as feature record sets by the system;

[0106] In the 24 characteristic records of "nozzle temperature anomaly," the system traces the operator's actions back to the time point. For example, some operators performed "temporary manual adjustment of heater power" before the abnormal event occurred. Such actions were classified as the first characteristic record. However, those who performed operations such as "pausing printing" and "adjusting the temperature control threshold" after the abnormal event occurred were classified as the second characteristic record.

[0107] The system counted the performance of the behavior of "temporarily adjusting the heater power" in the first feature record: the average slope change value K1 = +3.8℃ / min, the number of behavior samples is H1 = 18, the total number of feature records HT = 24, and the first feature data group is: K = 3.8, H = 18, HT = 24

[0108] For the "Pause Printing" behavior, analysis of the second feature record revealed an average slope change of K2 = −2.4°C / min. The number of behavior samples, H2 = 14, yielding the second feature data set: K = −2.4, H = 14, HT = 24.

[0109] Assume that the weight is set to L k =0.7, L h =0.3, the first characteristic score is 2.885, and the second characteristic score is -1.505.

[0110] Step S300: Acquire slice data of a model to be printed, calculate a printing difficulty score of the model to be printed, determine a printing difficulty level of the model to be printed, obtain a first operation behavior set of the printing difficulty level, calculate a first operation behavior score based on real-time monitoring of the operator's operation behavior, and determine an execution step based on the first operation behavior score;

[0111] Wherein, step S300 includes:

[0112] Step S301: obtaining slice data of the model to be printed, calculating the printing difficulty score of the model to be printed, and determining the printing difficulty level of the model to be printed;

[0113] Step S302: Obtain a first set of operation behaviors and a second set of operation behaviors corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if the first operation behavior exists, record and count the number of the first operation behavior, and calculate the first operation behavior score according to the following formula:

[0114] ;

[0115] Among them, Q represents the first operation behavior score, S i Expressed as the number of the first operation behavior of type i, g i It is represented as the characteristic score of the i-th first operation behavior, and r is represented as the number of types of first operation behaviors;

[0116] Step S303: Preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed.

[0117] For example, the system extracts the G-code slice data of the model and calculates the following parameters: A=0.91 after normalization of the total print run distance, B=0.80 after normalization of the material type, C=0.10 after normalization of the color type, and D=0.75 after normalization of the material weight. The calculated printing difficulty is 0.694, which is the second level of printing difficulty.

[0118] The second level of printing difficulty established the following first set of operational behaviors: manually adjusting the platform temperature setting during printing was scored as 1.6, turning off the auxiliary fan during printing was scored as 2.1, and starting printing without confirming the consumables number according to the process was scored as 1.2;

[0119] The number of times the platform temperature was manually adjusted was 1, the number of times the auxiliary fan was turned off was 2, and the number of times printing was started without confirming the consumables number according to the process was 0. The calculated score for the first operation behavior was 5.8;

[0120] If the first operation behavior score threshold is set to 6.0, printing continues.

[0121] Step S400: When printing is completed, the number of times the operator performs the second operation behavior is collected, the operation score of the operator is calculated, the next training time interval of the operator is calculated, and the training behavior is determined based on the next training time interval;

[0122] Wherein, step S400 includes:

[0123] Step S401: When printing is completed, the number of times the operator performs the second operation is collected, and the operator's operation score is calculated according to the following formula:

[0124] ;

[0125] Among them, G represents the operator's operation score, R n Expressed as the number of the nth second operation behavior, q n It is expressed as the characteristic score of the nth second operational behavior;

[0126] Step S402: Obtain the date of the last safety operation training for the operator, calculate the time interval from the last training to the completion of the current printing job, and calculate the next training time interval according to the following formula:

[0127] ;

[0128] T1 represents the time interval for the next training, and T2 represents the time interval from the last training to the completion of this printing job;

[0129] Step S403: Preset the operator's regular training time interval. If the next training time interval is less than the regular training time interval, the operator needs to be trained in safe operation in advance.

[0130] For example, the system identifies the following second operation behaviors in a print task: Delayed processing after an exception leading to print interruption has a feature score of 2.2 and is executed 1 times; repeatedly adjusting the fan speed to interfere with cooling efficiency has a feature score of 1.5 and is executed 2 times, resulting in a calculated operation score of 5.2;

[0131] Assuming that the time interval from the last training to the completion of this printing job is 140 days, the calculated time interval for the next training is 26.92 days. The system sets a regular training cycle of 60 days. 26.92 days < 60 days, so the judgment result is: training is required in advance.

[0132] In order to better implement the above method, a 3D printing equipment safety management system based on dynamic analysis is proposed. The system includes a printing difficulty level module, an operation behavior module, an execution step module, and a management training module.

[0133] Printing difficulty level module: In the 3D printing device, it obtains the slice data of the printed model, collects the running instructions of each slice layer, calculates the total running distance of the printed model, obtains the number of material types, colors, and weight of the printed model, calculates the printing difficulty score, and determines the difficulty level of each printing;

[0134] The printing difficulty level module includes a unit for calculating the total running distance and a unit for determining the printing difficulty level:

[0135] A total running distance calculation unit: obtains slice data of a model to be printed by a 3D printing device, collects running instructions for printing each slice layer, monitors the device operating parameters during the printing process through the sensor device of the 3D printing device, and when a device operating parameter exceeds the device operating parameter threshold, the device operating parameter is set as an abnormal parameter, an abnormal event is generated, and the running distance of the nozzle on the X, Y, and Z axes when executing the running instruction is obtained. The total running distance of the running instruction is calculated, and the total running distance of all running instructions is added to obtain the total running distance of the printed model;

[0136] Printing difficulty level determination unit: obtains historical printing records, collects the number of material types, number of colors, and weight of materials used in a certain historical printing record when printing a model, summarizes the number of material types, number of colors, and weight of materials used for all historical printing records, and performs normalization calculations to obtain the normalized number of material types, number of colors, and weight of materials used, obtains the total running distance of a certain historical printing record, calculates the printing difficulty score, presets several printing difficulty levels, obtains the printing difficulty score corresponding to each printing difficulty level, and determines the printing difficulty level corresponding to the historical printing record.

[0137] Operation behavior module: This module aggregates historical printing records of the same printing difficulty level, identifies characteristic records, categorizes characteristic records based on the event time points corresponding to abnormal events in the characteristic records and the operation time points at which the operator performs the operation behavior, calculates characteristic scores for the operation behavior, and determines the first and second operation behaviors;

[0138] The operation behavior module includes a feature recording unit and an operation behavior determination unit:

[0139] Determine the feature record unit: summarize the historical printing records of the same printing difficulty level, collect the historical printing records with abnormal events in the historical printing record set of each printing difficulty level and set them as feature records, summarize the same abnormal events in the feature record set of a certain printing difficulty level to obtain a feature record set of a certain abnormal event, collect the event time point corresponding to a certain abnormal event in a certain feature record, obtain the operation behavior of the operator in the said certain feature record, and obtain the operation time point corresponding to the execution of the operation behavior, set the operation behavior with an operation time point less than the event time point as the first feature record, set the operation behavior with an operation time point greater than or equal to the event time point as the second feature record, summarize the first feature records of the same operation behavior, and collect the abnormal parameters of a certain first feature record between the operation time point and the event time point. The value between the first and second feature records is collected, and a quality change curve of the abnormal parameter is drawn to obtain the slope change value of the abnormal parameter, and all first feature records are summarized to calculate the average slope change value of the operation behavior, and the number of first feature records of the operation behavior is counted, and the average slope change value and the number of first feature records are used as the first feature data group of the operation behavior, and the second feature records of the same operation behavior are summarized, and the value of the abnormal parameter of a second feature record between the operation time point and the event time point is collected, and a quality change curve of the abnormal parameter is drawn to obtain the slope change value of the abnormal parameter, and all second feature records are summarized to calculate the average slope change value of the operation behavior, and the number of second feature records of the operation behavior is counted, and the average slope change value and the number of second feature records are used as the second feature data group of the operation behavior;

[0140] Determine the operation behavior unit: establish an operation behavior formula to calculate the feature score of the operation behavior, input the first feature data group and the second feature data group of a certain operation behavior into the operation behavior formula respectively, calculate the first feature score and the second feature score of the certain operation behavior, preset the feature score threshold, set the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and set the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain the first operation behavior set and the second operation behavior set.

[0141] Execution step module: obtains slice data of the model to be printed, calculates the printing difficulty score of the model to be printed, determines the printing difficulty level of the model to be printed, obtains a first operation behavior set of the printing difficulty level, calculates the first operation behavior score based on real-time monitoring of the operator's operation behavior, and determines the execution step based on the first operation behavior score;

[0142] The execution step module includes a first operation behavior scoring unit and an execution step determination unit:

[0143] A first operation behavior scoring calculation unit is configured to obtain slice data of a model to be printed, calculate a printing difficulty score of the model to be printed, determine a printing difficulty level of the model to be printed, obtain a first operation behavior set and a second operation behavior set corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if a first operation behavior exists, record and count the number of the first operation behaviors, and calculate a first operation behavior score;

[0144] Determine execution step unit: preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed.

[0145] Management training module: when printing is completed, collect the number of second operation behaviors performed by the operator, calculate the operator's operation score, calculate the operator's next training time interval, and determine the training behavior based on the next training time interval;

[0146] The execution step module includes a first operation behavior scoring unit and an execution step determination unit:

[0147] A first operation behavior scoring calculation unit is configured to obtain slice data of a model to be printed, calculate a printing difficulty score of the model to be printed, determine a printing difficulty level of the model to be printed, obtain a first operation behavior set and a second operation behavior set corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if a first operation behavior exists, record and count the number of the first operation behaviors, and calculate a first operation behavior score;

[0148] Determine execution step unit: preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed.

[0149] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A 3D printing equipment safety management method based on dynamic analysis, characterized in that: Methods include: Step S100: In the 3D printing device, slice data of the printed model is obtained, the operation instructions of each slice layer are collected, the total operation distance of the printed model is calculated, the number of material types and colors, and the weight of the materials used in the printed model are obtained, the printing difficulty score is calculated, and each printing difficulty level is determined; Step S200: Summarize historical printing records of the same printing difficulty level, determine characteristic records, classify the characteristic records based on the event time points corresponding to the abnormal events in the characteristic records and the operation time points at which the operators performed the operation behaviors, calculate characteristic scores of the operation behaviors, and determine the first operation behavior and the second operation behavior; Step S201: Summarize historical printing records of the same printing difficulty level, and in the historical printing record set of each printing difficulty level, collect historical printing records with abnormal events and set them as feature records; Step S202: In a feature record set of a certain printing difficulty level, abnormal events of the same type are aggregated to obtain a feature record set of a certain abnormal event. The event time point corresponding to a certain abnormal event in a certain feature record is collected, the operation behavior of the operator in the certain feature record is obtained, and the operation time point corresponding to the execution of the operation behavior is obtained. The operation behavior whose operation time point is less than the event time point is set as the first feature record, and the operation behavior whose operation time point is greater than or equal to the event time point is set as the second feature record. Step S203: Summarize the first feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a first feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all first feature records, calculate the average slope change value of the operation behavior, and count the number of first feature records of the operation behavior. The average slope change value and the number of first feature records are used as the first feature data group of the operation behavior; Step S204: Summarize the second feature records of the same operation behavior, collect the values ​​of the abnormal parameters of a second feature record between the operation time point and the event time point, draw a quality change curve of the abnormal parameters, calculate the slope change value of the abnormal parameters, summarize all second feature records, calculate the average slope change value of the operation behavior, and count the number of second feature records of the operation behavior. The average slope change value and the number of second feature records are used as the second feature data set of the operation behavior; Step S205: Establish an operation behavior formula to calculate the characteristic score of the operation behavior: ； Where P represents the feature score of the operation behavior, K represents the average slope change value, H represents the number of feature records of the operation behavior, H represents the total number of feature records, Lk and Lh represent the weights of the average slope change value and the number of feature records, respectively. The first feature data group and the second feature data group of a certain operation behavior are input into the operation behavior formula respectively to calculate the first feature score and the second feature score of the certain operation behavior; Step S206: Preset a feature score threshold, set the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and set the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain a first operation behavior set and a second operation behavior set; Step S300: Acquire slice data of the model to be printed, calculate the printing difficulty score of the model to be printed, determine the printing difficulty level of the model to be printed, obtain a first operation behavior set of the printing difficulty level, calculate the first operation behavior score based on real-time monitoring of the operator's operation behavior, and determine the execution step based on the first operation behavior score; Step S301: obtaining slice data of the model to be printed, calculating the printing difficulty score of the model to be printed, and determining the printing difficulty level of the model to be printed; Step S302: Obtain a first set of operation behaviors and a second set of operation behaviors corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if the first operation behavior exists, record and count the number of the first operation behavior, and calculate the first operation behavior score according to the following formula: ； Among them, Q represents the first operation behavior score, S i Expressed as the number of the first operation behavior of type i, g i It is represented as the characteristic score of the i-th first operation behavior, and r is represented as the number of types of first operation behaviors; Step S303: Preset a first operation score threshold. If the operator's first operation score exceeds the operation score threshold, stop printing and immediately train the operator. If the operator's first operation score does not exceed the operation score threshold, execute step S302 until printing is completed. Step S400: When printing is completed, the number of times the operator performs the second operation behavior is collected, the operator's operation score is calculated, the operator's next training time interval is calculated, and the training behavior is determined based on the next training time interval.

2. The 3D printing equipment security management method based on dynamic analysis according to claim 1 is characterized in that: The step S100 includes the following steps: Step S101: obtaining slice data of a model to be printed by a 3D printing device, collecting operation instructions for printing each slice layer, and monitoring device operation parameters during the printing process through a sensor device of the 3D printing device. When a device operation parameter exceeds a device operation parameter threshold, the device operation parameter is set as an abnormal parameter and an abnormal event is generated; Step S102: Obtain the running distances of the nozzle on the X, Y, and Z axes respectively when executing the running instruction as AX, AY, and ZY, calculate the total running distance of executing the running instruction as A=AX+AY+ZY, and add the total running distances of all running instructions to obtain the total running distance of the printed model; Step S103: Obtain historical printing records, collect the material type, number, color, and weight used in a certain historical printing record when printing the model, summarize the material type, number, color, and weight of all historical printing records, and perform normalization calculations to obtain the normalized material type, color, and weight; Step S104: Obtain the total running distance of a certain historical printing record, and calculate the printing difficulty score according to the following formula: ； Where W represents the printing difficulty score, A represents the total running distance, B represents the normalized number of material types, C represents the normalized number of colors, D represents the normalized weight of used materials, and UA, UB, UC, and UD represent the weights of the total running distance, number of material types, number of colors, and weight of used materials, respectively. Step S105: Preset a number of printing difficulty levels, obtain a printing difficulty score corresponding to each printing difficulty level, and determine the printing difficulty level corresponding to the historical printing record.

3. The 3D printing equipment security management method based on dynamic analysis according to claim 1, characterized in that: The step S400 includes the following steps: Step S401: When printing is completed, the number of times the operator performs the second operation is collected, and the operator's operation score is calculated according to the following formula: ； Among them, G represents the operator's operation score, R n Expressed as the number of the nth second operation behavior, q n It is expressed as the characteristic score of the nth second operational behavior; Step S402: Obtain the date of the last safety operation training for the operator, calculate the time interval from the last training to the completion of the current printing job, and calculate the next training time interval according to the following formula: ； T1 represents the time interval for the next training, and T2 represents the time interval from the last training to the completion of this printing job; Step S403: Preset a regular training time interval for operators. When the next training time interval is shorter than the regular training time interval, the operators need to be trained in safe operation in advance.

4. A 3D printing equipment safety management system based on dynamic analysis, used to implement the 3D printing equipment safety management method based on dynamic analysis according to any one of claims 1 to 3, characterized in that: The system includes a printing difficulty level module, an operation behavior module, an execution step module, and a management training module; The printing difficulty level module: in the 3D printing device, obtains the slice data of the printed model, collects the running instructions of each slice layer, calculates the total running distance of the printed model, obtains the number of material types and colors of the printed model, and the weight of the materials used, calculates the printing difficulty score, and determines each printing difficulty level; The operation behavior module summarizes historical printing records of the same printing difficulty level, determines characteristic records, classifies the characteristic records according to the event time points corresponding to abnormal events in the characteristic records and the operation time points at which the operator performs the operation behavior, calculates characteristic scores of the operation behavior, and determines the first operation behavior and the second operation behavior; The execution step module: obtains slice data of the model to be printed, calculates a printing difficulty score of the model to be printed, determines the printing difficulty level of the model to be printed, obtains a first operation behavior set of the printing difficulty level, calculates the first operation behavior score based on real-time monitoring of the operator's operation behavior, and determines the execution step based on the first operation behavior score; The management training module: when printing is completed, collects the number of second operation behaviors performed by the operator, calculates the operator's operation score, calculates the operator's next training time interval, and determines the training behavior based on the next training time interval.

5. The 3D printing equipment safety management system based on dynamic analysis according to claim 4 is characterized in that: The printing difficulty level module includes a unit for calculating the total running distance and a unit for determining the printing difficulty level: The total running distance calculation unit: obtains slice data of a model to be printed by a 3D printing device, collects running instructions for printing each slice layer, monitors the device operating parameters during the printing process through the sensor device of the 3D printing device, and when a device operating parameter exceeds the device operating parameter threshold, the device operating parameter is set as an abnormal parameter, an abnormal event is generated, and the running distance of the nozzle on the X, Y, and Z axes when executing the running instruction is obtained, and the total running distance of the running instruction is calculated, and the total running distance of all running instructions is added to obtain the total running distance of the printed model; The unit for determining the printing difficulty level obtains historical printing records, collects the number of material types, the number of colors, and the weight of materials used in a certain historical printing record when printing a model, summarizes the number of material types, the number of colors, and the weight of materials used for all historical printing records, performs normalization calculations to obtain the normalized number of material types, the number of colors, and the weight of materials used, obtains the total running distance of a certain historical printing record, calculates a printing difficulty score, presets several printing difficulty levels, obtains the printing difficulty score corresponding to each printing difficulty level, and determines the printing difficulty level corresponding to the historical printing record.

6. The 3D printing equipment safety management system based on dynamic analysis according to claim 4 is characterized in that: The operation behavior module includes a feature recording unit and an operation behavior determination unit: The feature record determination unit: summarizes historical printing records of the same printing difficulty level, collects historical printing records with abnormal events in the historical printing record set of each printing difficulty level and sets them as feature records, summarizes the same abnormal events in the feature record set of a certain printing difficulty level to obtain a feature record set of a certain abnormal event, collects the event time point corresponding to a certain abnormal event in a certain feature record, obtains the operation behavior of the operator in the certain feature record, and obtains the operation time point corresponding to the execution of the operation behavior, sets the operation behavior with an operation time point less than the event time point as the first feature record, sets the operation behavior with an operation time point greater than or equal to the event time point as the second feature record, summarizes the first feature records of the same operation behavior, and collects the abnormal parameters of a certain first feature record at the operation time point and the event time point , and draw a quality change curve of the abnormal parameter, calculate the slope change value of the abnormal parameter, summarize all first feature records, calculate the average slope change value of the operation behavior, and count the number of first feature records of the operation behavior, use the average slope change value and the number of first feature records as the first feature data group of the operation behavior, summarize the second feature records of the same operation behavior, collect the value of the abnormal parameter of a second feature record between the operation time point and the event time point, and draw a quality change curve of the abnormal parameter, calculate the slope change value of the abnormal parameter, summarize all second feature records, calculate the average slope change value of the operation behavior, and count the number of second feature records of the operation behavior, use the average slope change value and the number of second feature records as the second feature data group of the operation behavior; The operation behavior determination unit: establishes an operation behavior formula to calculate the feature score of the operation behavior, inputs the first feature data group and the second feature data group of a certain operation behavior into the operation behavior formula respectively, calculates the first feature score and the second feature score of the certain operation behavior, presets a feature score threshold, sets the operation behavior whose first feature score exceeds the feature score threshold as the first operation behavior, and sets the operation behavior whose second feature score exceeds the feature score threshold as the second operation behavior, to obtain a first operation behavior set and a second operation behavior set.

7. The 3D printing equipment safety management system based on dynamic analysis according to claim 4 is characterized in that: The execution step module includes a first operation behavior scoring unit and an execution step determination unit: The first operation behavior scoring calculating unit is configured to obtain slice data of the model to be printed, calculate a printing difficulty score of the model to be printed, determine a printing difficulty level of the model to be printed, obtain a first operation behavior set and a second operation behavior set corresponding to the printing difficulty level, monitor the operation behaviors performed by the operator during printing in real time, identify the operation behaviors, and if the first operation behavior exists, record and count the number of the first operation behaviors, and calculate the first operation behavior score; The determining execution step unit: presets a first operation score threshold, if the operator's first operation score exceeds the operation score threshold, stops printing and immediately trains the operator; if the operator's first operation score does not exceed the operation score threshold, executes step S302 until printing is completed.

8. The 3D printing equipment safety management system based on dynamic analysis according to claim 4 is characterized in that: The management training module includes a calculation operation scoring unit and an analysis training unit: The operation score calculating unit collects the number of times the operator performs the second operation when printing is completed, and calculates the operator's operation score; The analysis and training unit obtains the date of the last safety operation training for the operator, calculates the time interval from the last training to the completion of this printing job, calculates the next training time interval, and presets the operator's regular training time interval. When the next training time interval is less than the regular training time interval, the operator needs to be trained in safety operation in advance.

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