A remote encrypted transmission system for 3D printing

Abstract

The present invention provides a remote encrypted transmission system for 3D printing, which relates to the field of data processing technology. The method includes: obtaining an original printing data set, extracting printing path data, material ratio data, and printing parameter data therefrom, respectively calculating a path perturbation matrix, a material perturbation factor, and a parameter adaptive weight to obtain a perturbation parameter data set, mapping and transforming a basic data set to obtain a transformed data set, perturbing the transformed data set according to the perturbation parameter data set to obtain a perturbation data set, calculating a trajectory offset value, a material offset rate, and a parameter offset ratio, and generating a path feature identifier, a material feature identifier, and a parameter feature identifier; packaging the original printing data set and the identifier data set for transmission, and performing anomaly detection on the data set; when an anomaly is detected, generating an anomaly signal, and rejecting the original printing data set from 3D printing. The present invention can detect whether an anomaly occurs during the remote encrypted transmission process of 3D printing.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a remote encrypted transmission system for 3D printing. Background Art

[0002] 3D printing technology is widely used in manufacturing, medical and other fields. Remote 3D printing data transmission usually relies on the Internet. Users can upload 3D printing files to the cloud server through a proprietary cloud interface. The printing terminal then downloads the data from the server, parses it and executes the printing task. However, since 3D printing files may involve sensitive information such as commercial secrets, unprotected remote transmission methods may cause data to be maliciously intercepted or tampered with during transmission, affecting the reliability of the printing results.

[0003] Existing technologies usually use encryption technology to improve the security of data transmission, and encrypt the transmission channel through the TLS protocol to prevent data leakage or tampering. However, in some encrypted transmission schemes, the data integrity verification mechanism is relatively weak, especially when network fluctuations, data packet loss or intermediate nodes are attacked during file transmission, which may cause the encrypted file to be damaged, missing or tampered with after decryption. For example, some encryption schemes do not provide an effective file verification method. When data tampering occurs during the transmission process, the system may not be able to detect the abnormality in time, causing the printer to execute the wrong printing path or material ratio under the wrong data instructions, ultimately affecting the print quality. Summary of the Invention

[0004] The purpose of the present invention is to provide a remote encrypted transmission system for 3D printing, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0006] A remote encrypted transmission system for 3D printing, comprising:

[0007] The parsing module is used to obtain the original printing data set and extract the printing path data, material ratio data and printing parameter data from it to obtain the basic data set;

[0008] A calculation module is used to calculate the path perturbation matrix, material perturbation factor and parameter adaptive weight according to the basic data set to obtain the perturbation parameter data set;

[0009] A conversion module is used to map and convert the printing path data, material ratio data and printing parameter data in the basic data set to obtain a conversion data set;

[0010] A perturbation module, configured to perform perturbation processing on the transformed data set according to the perturbation parameter data set to obtain a perturbation data set;

[0011] An identification module is used to calculate the trajectory offset value, material offset rate and parameter offset ratio according to the disturbance data set, and generate a path feature identifier, a material feature identifier and a parameter feature identifier to obtain an identification data set;

[0012] A transmission module, used for packaging and transmitting the original printing data set and the identification data set to obtain a transmission data stream;

[0013] The detection module is used to receive the transmission data stream and perform anomaly detection on it. When an anomaly is detected, an anomaly signal is generated and the original printing data set is rejected for 3D printing.

[0014] Furthermore, the calculation module includes:

[0015] A path feature unit is used to extract path coordinate information based on the printing path data and obtain the coordinate mean and coordinate variance;

[0016] A path perturbation matrix unit is used to calculate a reference offset matrix according to the coordinate mean, and adjust the reference offset matrix according to the coordinate variance to obtain a path perturbation matrix;

[0017] The material feature unit is used to identify the variation range of the material ratio according to the material ratio data, and extract the number of times the material is used to obtain the ratio change rate and material use frequency;

[0018] The material disturbance factor calculation unit is used to calculate the average value of the ratio of the material ratio value to the ratio value variance, the exponential decay value of the material frequency in historical tasks, and the cumulative value of each material ratio deviation and usage frequency; then the weighted sum of the average value of the ratio, the exponential decay value and the cumulative value is used to obtain the material disturbance factor;

[0019] A printing parameter feature unit, used to calculate the parameter adjustment rate of adjacent printing layers based on the printing parameter data;

[0020] The parameter adaptive weight unit is used to calculate the initial adjustment weight according to the parameter adjustment rate, and adjust the initial adjustment weight according to the preset printing stability to obtain the parameter adaptive weight.

[0021] Furthermore, the conversion module includes:

[0022] A projection coefficient unit, used to construct a projection matrix according to the path coordinate information of the printing path data, and calculate the projection coefficient according to the projection matrix;

[0023] A preliminary projection data unit, configured to perform coordinate transformation on the printing path data according to the projection coefficient to obtain preliminary projection data;

[0024] The projection path data unit is used to detect whether the preliminary projection data exceeds the printing range according to the printing boundary parameters of the 3D printer. When the result is yes, the preliminary projection data exceeding the printing range is projected and adjusted to obtain the projection path data.

[0025] Furthermore, the conversion module further includes:

[0026] An interval division unit is used to determine a material usage ratio range according to the number of times the material is used in the material ratio data, and to divide the material ratio data according to the range to obtain a discrete interval set;

[0027] A standardized proportion unit is used to determine the discrete interval according to the material usage ratio values ​​of different materials and obtain a standardized proportion value;

[0028] A preliminary discretization unit is used to replace the material usage ratio value in the material ratio data according to the standardized ratio value to obtain preliminary discretized material data;

[0029] The error compensation unit is used to perform error compensation on the preliminary discretized material data according to the physical properties of different materials, adjust the discretization accuracy, and obtain discretized material data.

[0030] Furthermore, the conversion module further includes:

[0031] A parameter change rate calculation unit is used to extract parameter change curves of adjacent printing layers based on the time series of printing parameter data to obtain parameter change rates;

[0032] A parameter gradient calculation unit, used to calculate the parameter gradients of adjacent printing layers based on the parameter change rate;

[0033] A gradient sequence generating unit, configured to obtain a smoothed gradient sequence by smoothing the parameter gradient;

[0034] A gradient sequence increment unit is used to determine the incremental step size according to the printing process requirements, and increment the smooth gradient sequence based on the incremental step size to obtain a parameter incremental sequence;

[0035] The parameter conversion unit is used to convert the printing parameter data according to the parameter increment sequence to obtain enhanced parameter data.

[0036] Furthermore, the disturbance module includes:

[0037] A perturbation path unit is used to offset the coordinate values ​​of the projected path data according to the path perturbation matrix to obtain perturbation path data;

[0038] The disturbed material unit is used to randomly replace the standardized ratio values ​​in the discretized material data according to the material disturbance factor to obtain the disturbed material data;

[0039] The disturbance parameter unit is used to perform weighted adjustment on the enhanced parameter data according to the parameter adaptive weight to obtain the disturbance parameter data.

[0040] Furthermore, the identification module includes:

[0041] A preliminary trajectory offset value calculation unit is used to calculate the coordinate difference based on the path coordinate information of the disturbed path data and the projected path data to obtain a preliminary trajectory offset value;

[0042] a trajectory offset value calculation unit, configured to smooth the preliminary trajectory offset value, remove abnormal values ​​caused by noise, and obtain a trajectory offset value;

[0043] The path feature identification unit is used to compare and analyze the printing path data according to the trajectory offset value to determine whether there is an abnormal deviation. When the result is no, a path feature identification is generated.

[0044] Furthermore, the identification module further includes:

[0045] A preliminary material offset calculation unit is used to compare the disturbed material data with the discretized material data, calculate the numerical difference, and obtain the preliminary material offset;

[0046] A material offset rate calculation unit is used to calculate the offset ratio of different materials based on the preliminary material offset amount, and normalize the offset ratio to obtain the material offset rate;

[0047] The material feature identification unit is used to perform statistical analysis on the material ratio data according to the material deviation rate to determine whether there is an abnormal ratio. When the result is no, a material feature identification is generated.

[0048] Furthermore, the identification module further includes:

[0049] a preliminary parameter offset ratio calculation unit, configured to compare the disturbance parameter data with the enhancement parameter data, calculate the parameter difference, and obtain a preliminary parameter offset ratio;

[0050] A parameter offset ratio calculation unit is used to analyze the parameter change trend of adjacent printing layers based on the preliminary parameter offset ratio, and perform curve fitting on the change trend to obtain the parameter offset ratio;

[0051] The parameter feature identification unit is used to perform error analysis on the printing parameter data according to the parameter offset ratio to determine whether there is abnormal fluctuation. When the result is no, a parameter feature identification is generated.

[0052] Furthermore, the detection module includes:

[0053] A path detection unit is used to compare the trajectory offset value with a preset trajectory offset value according to the path feature identifier, and when the trajectory offset value exceeds the trajectory threshold, it is determined that the original printing data set is abnormal;

[0054] A material detection unit is used to compare the material offset rate with a preset material offset rate according to a material feature identifier, and when the material offset rate exceeds the preset material offset rate, it is determined that the original printing data set is abnormal;

[0055] a parameter detection unit, configured to compare the parameter offset ratio with a preset parameter offset ratio according to the parameter feature identifier, and determine that the original printing data set is abnormal when the parameter offset ratio exceeds the preset parameter offset ratio;

[0056] The abnormal signal unit is used to generate an abnormal signal when any abnormal data is detected.

[0057] The above solution of the present invention includes at least the following beneficial effects:

[0058] The present invention can provide nonlinear perturbations for subsequent data encryption through the calculation of the perturbation matrix, thereby greatly improving the security of the data. The perturbation factor can dynamically adjust the encryption strategy in combination with the changes in the printing path, material ratio and printing parameters to avoid the possibility of data tampering. An adaptive weight calculation method is also introduced, so that the degree of encryption can be adjusted according to the complexity of the printing task, thereby improving flexibility. For example, for fine printing tasks, the perturbation amplitude can be increased to prevent the printing parameters from being illegally tampered with. For general printing tasks, moderate perturbations can be used to ensure data transmission efficiency. Compared with traditional encryption methods, this system combines the characteristics of 3D printing for targeted encryption, thereby improving security and taking into account transmission efficiency.

[0059] The present invention randomly perturbs the specific printing path, material ratio and printing parameters, making it difficult for attackers to restore the original data even if the data is intercepted. For example, introducing a perturbation offset in the path data can prevent printing path errors caused by malicious tampering; introducing random perturbations in the material ratio can increase the difficulty of decryption and improve security. It can also automatically adjust the degree of perturbation according to different printing tasks, maximizing data security while ensuring printing quality. Compared with existing technologies, this system can more accurately combine the characteristics of 3D printing tasks, provide data encryption protection, and prevent data from being intercepted or tampered with during transmission.

[0060] The present invention performs feature calculations on paths, materials, and parameters and generates specific identification values, so that the receiving end can compare these identification values ​​to verify the integrity of the data. For example, through the path feature identification, it can be determined whether the printing path data has been tampered with; through the material feature identification, it can be checked whether the material ratio is abnormal; through the parameter feature identification, it can be detected whether the printing parameters conform to the original settings. Compared with traditional hash verification, this system combines the specific data structure of 3D printing for verification, provides a data integrity verification mechanism, and ensures that the data has not been tampered with during transmission.

[0061] The present invention uses a data conversion method to enable seamless compatibility of data between different devices, thereby enhancing the versatility of the system. At the same time, the system can optimize the data storage structure during the conversion process, reduce the storage volume of data, and improve transmission efficiency. For example, when transmitting path data, a projection conversion method can be used to project three-dimensional coordinates into a specific space to improve the compactness of the data. The system also has an error compensation function, which can reduce information loss and improve data accuracy during the data conversion process. Compared with the existing direct transmission method, this module can better adapt to different printing devices, improve data consistency, and reduce errors that occur when data is converted between different devices.

[0062] The present invention can analyze the integrity of transmitted data in real time and issue an alarm in time when an anomaly is detected, thereby preventing erroneous data from entering the 3D printing system. For example, if the system detects that the trajectory offset value exceeds the threshold, it can refuse to execute the printing task, thereby avoiding printing failure due to path data tampering. The system can also perform anomaly detection based on historical data to improve detection accuracy and reduce false alarms. Compared with the traditional post-transmission verification method, the system can perform real-time detection during data transmission, improve the overall security of the system, and effectively prevent printing quality problems caused by data tampering. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flowchart of a remote encrypted transmission system for 3D printing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0065] like Figure 1As shown, an embodiment of the present invention provides a remote encrypted transmission system for 3D printing, the system comprising:

[0066] The parsing module is used to obtain the original printing data set and extract the printing path data, material ratio data and printing parameter data from it to obtain the basic data set;

[0067] A calculation module is used to calculate the path perturbation matrix, material perturbation factor and parameter adaptive weight according to the basic data set to obtain the perturbation parameter data set;

[0068] A conversion module is used to map and convert the printing path data, material ratio data and printing parameter data in the basic data set to obtain a conversion data set;

[0069] A perturbation module, configured to perform perturbation processing on the transformed data set according to the perturbation parameter data set to obtain a perturbation data set;

[0070] An identification module is used to calculate the trajectory offset value, material offset rate and parameter offset ratio according to the disturbance data set, and generate a path feature identifier, a material feature identifier and a parameter feature identifier to obtain an identification data set;

[0071] A transmission module, used for packaging and transmitting the original printing data set and the identification data set to obtain a transmission data stream;

[0072] The detection module is used to receive the transmission data stream and perform anomaly detection on it. When an anomaly is detected, an anomaly signal is generated and the original printing data set is rejected for 3D printing.

[0073] In an embodiment of the present invention, a parsing module is used to obtain an original printing data set and extract printing path data, material ratio data and printing parameter data therefrom to obtain a basic data set, thereby ensuring the accuracy and completeness of data classification and improving data processing efficiency; a calculation module is used to calculate the path perturbation matrix, material perturbation factor and parameter adaptive weight according to the basic data set to obtain a perturbation parameter data set. By dynamically calculating the perturbation parameters, the data encryption strength can be adjusted for different printing tasks, thereby improving the flexibility of encryption; a conversion module is used to map and convert the printing path data, material ratio data and printing parameter data in the basic data set to obtain a converted data set, thereby optimizing the data structure and improving the compatibility and stability of the data; a perturbation module is used to perturb the converted data set according to the perturbation parameter data set to obtain a perturbation data set, thereby increasing the security of the data and making it difficult for the data in transmission to be recovered without authorization, thereby preventing data leakage and tampering.

[0074] The identification module is used to calculate the trajectory offset value, material offset rate and parameter offset ratio based on the disturbance data set, and generate path feature identification, material feature identification and parameter feature identification to obtain the identification data set, and provide a data integrity verification mechanism so that the receiving end can verify whether the data has been tampered with during transmission, thereby improving the reliability of data transmission; the transmission module is used to package and transmit the original printing data set and the identification data set to obtain a transmission data stream, and improve network adaptability and reduce data loss rate by optimizing the data packaging strategy; the detection module is used to receive the transmission data stream and perform anomaly detection on it. When an anomaly is detected, an anomaly signal is generated and the original printing data set is rejected for 3D printing, data integrity is monitored in real time, and tampered data is prevented from entering the 3D printing process, thereby ensuring the security and stability of the printing task.

[0075] The parsing module is used to obtain the original printing data set and extract the printing path data, material ratio data and printing parameter data from it to obtain the basic data set, which specifically includes:

[0076] The parsing module is used to receive and process the raw data in the 3D printing task to ensure that the data can be correctly identified and used in the subsequent calculation, conversion and transmission processes.

[0077] First, the system receives 3D printing files submitted by users through the user interface or network interface. These files can be in G-code, STL, OBJ or AMF format, and contain information such as printing path, material ratio and printing parameters. Due to the differences in data structures of different formats, the parsing module first identifies the file type and converts the format according to the corresponding data parsing rules to ensure that all data can be stored and processed in a standardized manner.

[0078] After the file format recognition is completed, the parsing module begins to perform structured parsing of the data. For G-code files, the system reads the instructions line by line, extracts the path coordinate information, and parses printing parameters such as nozzle temperature, layer thickness, and injection speed. For STL or OBJ files, the parsing module calculates the bounding box of the model and extracts key point data for path calculation. For AMF files, the system further extracts the ratio information of different materials and records the data of various materials involved in the printing process to ensure that subsequent calculations can be performed accurately. During the parsing process, the system automatically detects the integrity of the data, such as checking whether there are duplicate points in the coordinate data, whether the path is closed, and whether the material ratio meets the configuration requirements of the printer to ensure data quality.

[0079] After the data analysis is completed, the system will perform preprocessing operations to optimize the readability and transmission efficiency of the data. The system will optimize the path data, merge repeated path points, and adjust the printing order to reduce the nozzle's movement distance and improve printing efficiency. The system will then normalize the material ratio data to ensure that all material data are within a unified numerical range to facilitate disturbance processing by the subsequent calculation module. In terms of printing parameters, the analysis module will analyze the change curve of the printing parameters, filter out abnormal data, and smooth the parameters to reduce the impact of data fluctuations on printing quality. Finally, all analyzed and preprocessed data are stored in the basic data set to form three core data sets: printing path data, material ratio data, and printing parameter data, providing standardized input for subsequent calculations and conversions.

[0080] The transmission module is used to package and transmit the original print data set and the identification data set to obtain a transmission data stream, which specifically includes:

[0081] The main task of the transmission module is to transmit the parsed printing data to the 3D printing terminal safely and efficiently, ensuring that the data is not tampered with or lost during the transmission process.

[0082] First, the system packages the basic data set provided by the parsing module to form a data stream to be transmitted. During the packaging process, the transmission module will encode the printing path data, material ratio data and printing parameter data respectively, and add data format identifiers to ensure that the receiving end can parse it correctly. The system will then compress the data to reduce the amount of transmitted data and improve the efficiency of network transmission. Data compression uses a lossless compression algorithm, such as LZ77, to ensure that the compressed data can be restored accurately at the receiving end.

[0083] After the data is packaged, the system will encrypt the data to prevent it from being intercepted or tampered with during transmission. The encryption uses the AES symmetric encryption algorithm to ensure data security. At the same time, in order to ensure the integrity of the data, the system will also calculate the hash value of the data and attach a digital signature to facilitate data verification at the receiving end. In addition, in order to prevent the data from being maliciously tampered with, the transmission module will embed path feature identifiers, material feature identifiers and parameter feature identifiers in each data packet, so that the receiving end can compare the data before and after transmission to ensure data security and reliability.

[0084] After data packaging and encryption are completed, the system establishes a secure communication channel through TLS and establishes a connection with the receiving end. During the transmission process, the system adopts a block transmission mechanism to split the large data stream into multiple small data blocks and attach a sequence number to each data block to ensure that the receiving end can reassemble the data in order. In addition, the system will also monitor the network status and dynamically adjust the data packet size according to the bandwidth and delay to ensure transmission efficiency. In a high-bandwidth environment, the system will increase the size of the data packet to increase the transmission rate; when the network is unstable or the bandwidth is low, the system will reduce the data packet size to avoid data loss and improve transmission reliability.

[0085] During data transmission, the system adopts the ACK / NACK mechanism. The receiving end will return a confirmation signal after receiving the data. If a data block is lost or erroneous, the receiving end will send a negative signal, requiring the sending end to retransmit the data block. At the same time, in order to improve the data's anti-interference ability, the system also uses forward error correction coding to add redundant information to the transmitted data so that the receiving end can automatically recover the data when some data is lost without requesting retransmission, thereby improving transmission efficiency.

[0086] When all data transmission is completed, the receiving end will perform an integrity check on the received data. First, the system calculates the hash value of the received data and compares it with the hash value before transmission to verify whether the data has been tampered with during the transmission process. Then, the system uses the stored public key to verify the digital signature of the data to ensure the authenticity of the data. The receiving end will also use the path feature identifier, material feature identifier and parameter feature identifier of the parsing module to compare the data before and after transmission to ensure that the data has not been tampered with or lost. If data anomalies are detected, the system will refuse to execute the 3D printing task and notify the user to retransmit to prevent erroneous data from causing printing failure.

[0087] In a preferred embodiment of the present invention, the calculation module includes:

[0088] A path feature unit is used to extract path coordinate information based on the printing path data and obtain the coordinate mean and coordinate variance;

[0089] A path perturbation matrix unit is used to calculate a reference offset matrix according to the coordinate mean, and adjust the reference offset matrix according to the coordinate variance to obtain a path perturbation matrix;

[0090] The material feature unit is used to identify the variation range of the material ratio according to the material ratio data, and extract the number of times the material is used to obtain the ratio change rate and material use frequency;

[0091] The material disturbance factor calculation unit is used to calculate the average value of the ratio of the material ratio value to the ratio value variance, the exponential decay value of the material frequency in historical tasks, and the cumulative value of each material ratio deviation and usage frequency; then the weighted sum of the average value of the ratio, the exponential decay value and the cumulative value is used to obtain the material disturbance factor;

[0092] A printing parameter feature unit, used to calculate the parameter adjustment rate of adjacent printing layers based on the printing parameter data;

[0093] The parameter adaptive weight unit is used to calculate the initial adjustment weight according to the parameter adjustment rate, and adjust the initial adjustment weight according to the preset printing stability to obtain the parameter adaptive weight.

[0094] In an embodiment of the present invention, a path feature unit is configured to extract path coordinate information based on printing path data to obtain a coordinate mean and coordinate variance, thereby accurately capturing the spatial distribution characteristics of the printing path. A path perturbation matrix unit is configured to calculate a reference offset matrix based on the coordinate mean and adjust the reference offset matrix based on the coordinate variance to obtain a path perturbation matrix, thereby ensuring that the perturbation operation does not cause excessive errors in the original printing path. A material feature unit is configured to identify the variation range of the material ratio based on the material ratio data and extract the number of times the material is used to obtain a ratio change rate and a material use frequency, thereby effectively analyzing the usage of different materials. A material perturbation factor calculation unit is configured to calculate a basic perturbation factor based on the ratio change rate and adjust the basic perturbation factor based on the material use frequency to obtain a material perturbation factor, thereby ensuring a relatively high degree of encryption for commonly used materials. A printing parameter feature unit is configured to calculate a parameter adjustment rate of adjacent printing layers based on the printing parameter data to obtain a trend of printing parameter changes with height. A parameter adaptive weight unit is configured to calculate an initial adjustment weight based on the parameter adjustment rate and adjust the initial adjustment weight based on a preset printing stability to obtain a parameter adaptive weight, thereby dynamically adjusting the perturbation amplitude of the printing parameters.

[0095] The path perturbation matrix unit is used to calculate the reference offset matrix according to the coordinate mean and adjust the reference offset matrix according to the coordinate variance to obtain the path perturbation matrix, which specifically includes:

[0096] First, the unit extracts all path coordinate points from the basic data set and calculates their mean coordinates. The calculation of the mean coordinates is achieved by averaging the coordinate axis values ​​of all path points. Next, the unit constructs a reference offset matrix, which is used to represent the initial path perturbation structure. The construction method is usually to set the perturbation coefficients in each direction to make them adaptive. The initial value of the reference offset matrix can be a diagonal matrix, in which the elements correspond to the initial perturbation amplitudes in each coordinate direction.

[0097] After obtaining the reference offset matrix, the unit further calculates the variance of the path coordinates. The calculation of the variance is based on the degree of deviation of all path points from the mean, reflecting the discreteness of the path data. Subsequently, the calculated variance information is introduced into the adjustment process of the reference offset matrix, so that the degree of path disturbance can adaptively change with the distribution of the path data. Specifically, the direction with larger variance of the path coordinates will have a correspondingly increased disturbance amplitude to provide stronger disturbance protection, while the direction with smaller variance will have a properly reduced disturbance amplitude to ensure printing accuracy. The adjusted path disturbance matrix will be used in subsequent data conversion and encryption steps, which ensures the security of the printed data while also ensuring the recoverability and consistency of the printed path data.

[0098] The calculation formula of the material disturbance factor is:

[0099] ,

[0100] in, is the material disturbance factor, is the total number of material types, For the index of the material, For the The ratio of the materials, is the variance of the ratio values ​​of all materials in the material ratio data, For the The number of times a material appears in historical printing tasks, is the total number of historical printing tasks, is the frequency of material use, , is the mean of the ratio values ​​of all materials in the material ratio data, is the coefficient, is a constant;

[0101] in, is the weight coefficient, which has different values ​​in different 3D printing, including:

[0102] When printing high-precision metal 3D printing, The value range is 1.2-1.3. Slight deviations in the material ratio will lead to reduced printing quality, so the ratio impact factor is relatively high. The value range is 1.3-1.4. The large amount of process data accumulated in historical printing tasks is crucial for optimizing the current printing task, so historical tasks have a higher impact; The value range is 1.4-1.5. The deviation of the material must be strictly corrected to ensure printing consistency, so the material deviation correction factor is relatively high.

[0103] When printing in consumer-grade FDM 3D printing, The value range is 0.7-0.9. Consumer-grade FDM printing materials are single and the influence of the ratio is small, so the coefficient is relatively low. The value range is 0.6-0.8. The impact of historical tasks is not significant because each printing task can start from scratch without relying on past data. The value range is 0.8-1.0. The deviation of the material mean has little impact. Even if the material fluctuates slightly, it will not significantly affect the quality of the finished product.

[0104] When conducting scientific research and experimental 3D printing, The value range is 1.3-1.4. The influence of material ratio is extremely great because the experimental variables need to be precisely controlled to study the material properties; The value range is 0.5-0.7. The influence of historical data is small because experiments are usually exploratory rather than relying on past data for optimization; The value range is 1.0-1.2. Material deviation needs to be moderately corrected, but since it is an experimental study, appropriate fluctuations are acceptable.

[0105] When 3D printing medical implants, The value range is 1.1-1.2. Medical implants require highly precise material ratios, but the requirements are slightly lower than those in aerospace. Therefore, the ratio impact factor is moderately high. The value range is 1.0-1.1. Historical data has a greater impact, but because personalized needs vary greatly, the weight is medium; The value range is 1.2-1.3. Material deviation correction is still important for medical applications to ensure that the printed parts meet biocompatibility requirements.

[0106] The parameter adaptive weight unit is used to calculate the initial adjustment weight according to the parameter adjustment rate, and adjust the initial adjustment weight according to the preset printing stability to obtain the parameter adaptive weight, which specifically includes:

[0107] First, the unit extracts printing parameters from the basic data set, including key parameters such as nozzle temperature, printing speed, and layer thickness, and constructs a parameter change trajectory according to the printing layer sequence. After obtaining these parameters, the unit calculates the parameter adjustment rate between adjacent printing layers. The calculation method is to reflect the parameter change amplitude through the ratio of the difference between the parameter values ​​of two adjacent layers to the layer height. The parameter adjustment rate can characterize the dynamic change characteristics of the parameters during the printing process. When the rate is large, it indicates that the printing parameters change faster and there may be a larger adjustment space. When the rate is small, it indicates that the printing parameters are relatively stable and the amplitude of the disturbance needs to be properly controlled.

[0108] After obtaining the parameter adjustment rate, the unit further calculates the initial adjustment weight. The calculation of the initial adjustment weight is based on the parameter adjustment rate and a set of preset coefficients. These coefficients are used to map the relationship between the parameter rate and the adjustment weight. When the parameter adjustment rate is large, the initial adjustment weight will also increase accordingly to ensure the effectiveness of the parameter disturbance. When the parameter adjustment rate is small, the initial adjustment weight tends to decrease to reduce unnecessary disturbance.

[0109] After calculating the initial adjustment weight, it is optimized and adjusted in combination with the printing stability. Printing stability is an indicator to measure the impact of parameter changes on printing quality during the printing process. Generally, it is obtained from historical printing data statistics and is equivalent to the historical parameter variance. When the system detects that the printing stability is high, the unit will attenuate the initial adjustment weight to appropriately reduce the amplitude of the parameter disturbance, thereby avoiding interference with the stable printing process. In the case of low printing stability, the unit will appropriately increase the adjustment weight to enhance the dynamic adaptability of the parameter adjustment and improve the anti-interference ability of the printing data. Finally, the parameter adaptive weight output by the unit will be applied to the subsequent parameter disturbance calculation process, making the encryption and disturbance of the printing parameters more intelligent, and effectively taking into account both printing quality and data security.

[0110] The calculation formula of the parameter adaptive weight is:

[0111] ,

[0112] in, is the parameter adaptive weight, is the parameter adjustment rate, To preset printing stability, The maximum preset printing stability in history, is the coefficient.

[0113] In a preferred embodiment of the present invention, the conversion module includes:

[0114] A projection coefficient unit, used to construct a projection matrix according to the path coordinate information of the printing path data, and calculate the projection coefficient according to the projection matrix;

[0115] A preliminary projection data unit, configured to perform coordinate transformation on the printing path data according to the projection coefficient to obtain preliminary projection data;

[0116] The projection path data unit is used to detect whether the preliminary projection data exceeds the printing range according to the printing boundary parameters of the 3D printer. When the result is yes, the preliminary projection data exceeding the printing range is projected and adjusted to obtain the projection path data.

[0117] In an embodiment of the present invention, a projection coefficient unit is used to construct a projection matrix based on the path coordinate information of the printing path data, and calculate the projection coefficient based on the projection matrix, so as to ensure that the three-dimensional printing path data can be uniformly projected between different devices and improve the compatibility of the data format; a preliminary projection data unit is used to perform coordinate transformation on the printing path data according to the projection coefficient to obtain preliminary projection data, which can reduce the calculation complexity of the printing path data and improve data processing efficiency; a projection path data unit is used to detect whether the preliminary projection data exceeds the printing range according to the printing boundary parameters of the 3D printer. When the result is yes, the preliminary projection data that exceeds the printing range is projected and adjusted to obtain projection path data, which can prevent the 3D printing path from exceeding the working range of the device and ensure that the printer can perform the printing task normally.

[0118] The projection coefficient unit is used to construct a projection matrix according to the path coordinate information of the printing path data, and calculate the projection coefficient according to the projection matrix, specifically including:

[0119] The system first needs to obtain the path coordinate information in the printing path data. This information usually includes three-dimensional coordinate points, which are used to represent the motion trajectory of the 3D printer nozzle. After obtaining the path coordinate information, the projection coefficient unit needs to construct a projection matrix, which is used to determine the mapping relationship between the three-dimensional space coordinates on a specific projection plane. The construction of the projection matrix can be based on a variety of methods, such as orthogonal projection, perspective projection or adaptive projection. Among them, orthogonal projection is suitable for industrial-grade 3D printing with high precision requirements, while perspective projection is usually used for visual optimization and rendering. In the specific implementation process, the system will calculate the rotation matrix and translation matrix required for the projection transformation based on the working parameters of the printing device, such as the nozzle motion range, printing boundary, nozzle angle, etc., and synthesize them into the final projection matrix. The core function of this matrix is ​​to project the three-dimensional coordinate points to a two-dimensional or other specific coordinate system to adapt to the requirements of different types of printers or data formats.

[0120] After completing the construction of the projection matrix, the projection coefficient unit will further calculate the projection coefficients, which are the scale factors and transformation relationships used to describe how the original three-dimensional coordinates are converted to the target projection plane. This calculation process usually involves matrix operations. For example, the original three-dimensional coordinate points are represented as homogeneous coordinates, and then their projection coordinates on the projection plane are calculated through matrix multiplication. The calculation of the projection coefficients must not only consider the proportional relationship of the coordinate transformation, but also optimize the accuracy of the data mapping to avoid the impact of numerical overflow or rounding errors on the printing path.

[0121] The preliminary projection data unit is used to perform coordinate transformation on the printing path data according to the projection coefficient to obtain preliminary projection data, specifically including:

[0122] The system first needs to traverse all coordinate points in the printing path data and use the projection coefficient to perform transformation calculations to ensure that the transformation of each point complies with the predetermined projection rules. During the calculation process, the system may use matrix operations, interpolation algorithms or optimized projection methods to improve calculation efficiency and reduce errors. For coordinate points that exceed the projection range, the system will perform boundary corrections to ensure that all converted coordinate points are within a reasonable printing range, thereby avoiding the print head running beyond the set area, resulting in printing failure or equipment damage.

[0123] After completing the coordinate transformation, the preliminary projection data unit will perform a series of optimization processes to ensure the quality of the projection data. The system will check whether there are any anomalies in the converted coordinate points, such as too high or too low point density, and then perform data sparseness or interpolation to make the data distribution more even. Secondly, the system will use smoothing methods, such as B-spline curve fitting or Gaussian filtering, to reduce noise points in the projection data and make the printing path smoother. Finally, the projection data will be normalized to ensure that its numerical range adapts to the input requirements of the printer and conforms to the standard format of the subsequent processing module.

[0124] In a preferred embodiment of the present invention, the conversion module further includes:

[0125] An interval division unit is used to determine a material usage ratio range according to the number of times the material is used in the material ratio data, and to divide the material ratio data according to the range to obtain a discrete interval set;

[0126] A standardized proportion unit is used to determine the discrete interval according to the material usage ratio values ​​of different materials and obtain a standardized proportion value;

[0127] A preliminary discretization unit is used to replace the material usage ratio value in the material ratio data according to the standardized ratio value to obtain preliminary discretized material data;

[0128] The error compensation unit is used to perform error compensation on the preliminary discretized material data according to the physical properties of different materials, adjust the discretization accuracy, and obtain discretized material data.

[0129] In an embodiment of the present invention, an interval division unit is used to determine the material usage ratio range according to the number of times the material is used in the material ratio data, and divide the material ratio data according to the range to obtain a discrete interval set, which can improve the interpretability of the data and make the material ratio more efficient and stable during further calculation and encryption; a standardized ratio unit is used to determine the discrete interval in which the material usage ratio value of different materials is located, obtain a standardized ratio value, and eliminate the slight ratio differences between different printing tasks; a preliminary discretization unit is used to replace the material usage ratio value in the material ratio data according to the standardized ratio value, obtain preliminary discretized material data, reduce the randomness of the data, and improve the reproducibility of the data; an error compensation unit is used to perform error compensation on the preliminary discretized material data according to the physical properties of different materials, adjust the discretization accuracy, obtain discretized material data, and ensure that the discretized material data still meets the requirements of the 3D printing process.

[0130] The interval division unit is used to determine the material usage ratio range according to the number of times the material is used in the material ratio data, and divide the material ratio data according to the range to obtain a discrete interval set, which specifically includes:

[0131] First, the system receives and reads the material ratio data, which includes the number of times each type of material is used and its corresponding ratio. The system analyzes the historical usage of all materials, counts the frequency of occurrence of different materials in multiple 3D printing tasks, and calculates the minimum, maximum and average values ​​of each material ratio. Based on the statistical results, the system normalizes the material usage ratio to ensure that the usage range of different materials can be standardized. Subsequently, the system divides the material ratio data into multiple discrete interval sets according to preset division rules, such as equal-interval division or adaptive division based on distribution density. Each interval represents the material ratio within a specific range.

[0132] The standardized ratio unit is used to determine the discrete intervals of different materials based on their material usage ratios to obtain standardized ratio values, specifically including:

[0133] After the interval division is completed, the discrete interval to which it belongs is determined based on the ratio values ​​of different materials. For example, the historical ratio range of a certain material is between 5% and 25%. If the system divides it into 4 equally spaced intervals (5%-10%, 10%-15%, 15%-20%, 20%-25%), then if the ratio value in the current task is 12%, it will be classified into the "10%-15%" interval. After the classification is completed, the system calculates the standardized ratio value of the interval, such as using the center value of the interval (such as 12.5%) or the most common historical value (such as 13%) to represent the standardized value of the interval, and uses this value to replace the original material ratio data.

[0134] The preliminary discretization unit is used to replace the material usage ratio value in the material ratio data according to the standardized ratio value to obtain preliminary discretized material data, which specifically includes:

[0135] After the standardized ratio value is determined, the standardized ratio value will replace the original material ratio data. By looking up the table or formula transformation, it is ensured that the ratio data of each material is matched to the closest standardized value. For example, if the original data is 11.8%, the system finds the standardized ratio value of the interval to which it belongs is 12.5%, and directly replaces 11.8% with 12.5%. In addition, the data of all materials are batch processed to improve calculation efficiency and ensure the unified format of the entire material data set.

[0136] The error compensation unit is used to perform error compensation on the preliminary discretized material data according to the physical properties of different materials, adjust the discretization accuracy, and obtain discretized material data. Specifically, it includes:

[0137] Since there may be certain errors in the initial discretization process, the error compensation unit will correct the errors of the discretized material data according to the physical properties of different materials. First, the physical parameters of the material, such as melting point, fluidity, curing time, etc., are read, and the influence of the standardized ratio value on the material performance is analyzed. The system calculates the error range that may be caused by different material ratios based on historical printing data and experimental data. For example, if a certain material shrinks under the standard ratio, the system will add a small adjustment value (such as +0.2%) to the ratio data of the material to offset the impact of shrinkage.

[0138] In a preferred embodiment of the present invention, the conversion module further includes:

[0139] A parameter change rate calculation unit is used to extract parameter change curves of adjacent printing layers based on the time series of printing parameter data to obtain parameter change rates;

[0140] A parameter gradient calculation unit, used to calculate the parameter gradients of adjacent printing layers based on the parameter change rate;

[0141] A gradient sequence generating unit, configured to obtain a smoothed gradient sequence by smoothing the parameter gradient;

[0142] A gradient sequence increment unit is used to determine the incremental step size according to the printing process requirements, and increment the smooth gradient sequence based on the incremental step size to obtain a parameter incremental sequence;

[0143] The parameter conversion unit is used to convert the printing parameter data according to the parameter increment sequence to obtain enhanced parameter data.

[0144] In an embodiment of the present invention, a parameter change rate calculation unit is used to extract parameter change curves of adjacent printing layers based on the time series of printing parameter data, obtain parameter change rates, and accurately reflect the dynamic changes of printing parameters; a parameter gradient calculation unit is used to calculate the parameter gradients of adjacent printing layers based on the parameter change rates, and analyze the influence of different printing parameters on the stability of the printing layers; a gradient sequence generation unit is used to obtain a smoothed gradient sequence by smoothing the parameter gradients, thereby improving the interpretability of the data and avoiding calculation errors caused by different parameter units; a gradient sequence increment unit is used to determine the incremental step size according to the printing process requirements, and increment the smoothed gradient sequence according to the incremental step size to obtain a parameter increment sequence. Through adaptive step size adjustment, it can be ensured that the parameter changes are not too drastic to cause quality problems; a parameter conversion unit is used to convert the printing parameter data according to the parameter increment sequence to obtain enhanced parameter data. Through parameter conversion, the printing process can be made smoother and printing failures caused by parameter mutations can be reduced.

[0145] The gradient sequence generation unit is used to obtain a smoothed gradient sequence by smoothing the parameter gradient, specifically including:

[0146] The exponentially weighted moving average method is used to refer to the data of the previous layers when calculating the gradient of the current layer, thereby reducing gradient mutations. Gaussian filtering is used to smooth the gradient curve, eliminate random noise, and improve the continuity of gradient changes. Filtering is used to smooth the gradient data to remove unnecessary mutations while keeping the overall trend unchanged. The smoothed gradient data is stored as a gradient sequence, and each data point corresponds to the gradient value of the printing parameter of a layer.

[0147] The gradient sequence increment unit is used to determine the incremental step size according to the printing process requirements, and increment the smooth gradient sequence based on the incremental step size to obtain a parameter incremental sequence, which specifically includes:

[0148] According to the printing process requirements, set the incremental step size of different parameters, for example:

[0149] For temperature adjustment, the step size can be set from 0.5°C to 2°C;

[0150] For nozzle speed adjustment, the step size can be set from 0.1mm / s to 1mm / s;

[0151] For material extrusion rate, the step size can be set to 0.05%-0.5%;

[0152] Adopting adaptive step size algorithm, the incremental step size is dynamically adjusted according to material properties such as melting temperature, fluidity, printing accuracy requirements and historical data, making parameter changes more reasonable.

[0153] An adaptive gradient adjustment algorithm is used to calculate the increments. If the parameter gradients of the first few layers change slightly, the incremental step size is gradually increased to improve printing efficiency. If the parameter gradients of the first few layers change significantly, the incremental step size is reduced to maintain stable printing quality. Bayesian optimization is used to select the optimal incremental step size to improve the adaptability of the incremental calculation. The parameter increment sequence, that is, the parameter change value of each layer, is obtained through incremental calculation.

[0154] The parameter conversion unit is used to convert the printing parameter data according to the parameter increment sequence to obtain enhanced parameter data, specifically including:

[0155] The original printing parameter data is mapped and converted according to the parameter increment sequence. For example, if the original value of the nozzle temperature is 200°C and the increment is +1.5°C, the target temperature of the next layer is set to 201.5°C. If the original value of the printing speed is 50mm / s and the increment is -0.5mm / s, the next layer is set to 49.5mm / s. A nonlinear interpolation algorithm is used to make parameter changes smoother and improve the accuracy of parameter conversion.

[0156] Neural network regression is used to analyze historical printing data and optimize parameter conversion results, making parameter adjustment more intelligent. The optimal parameter combination is selected in combination with genetic algorithm to ensure that parameter adjustment meets the printing process requirements.

[0157] Combined with the printer's real-time sensor data, the parameter adjustment error is calculated and the PID control algorithm is used for error compensation. If the actual temperature deviates from the set value, the heating power is adjusted to improve temperature stability. If the printing speed fluctuates greatly, the pulse signal of the stepper motor is adjusted to ensure stability. Through error compensation, the parameter adjustment error is made less than the set threshold, such as ±0.1%.

[0158] The parameters after mapping conversion, nonlinear optimization and error compensation form enhanced parameter data.

[0159] In a preferred embodiment of the present invention, the disturbance module includes:

[0160] A perturbation path unit is used to offset the coordinate values ​​of the projected path data according to the path perturbation matrix to obtain perturbation path data;

[0161] The disturbed material unit is used to randomly replace the standardized ratio values ​​in the discretized material data according to the material disturbance factor to obtain the disturbed material data;

[0162] The disturbance parameter unit is used to perform weighted adjustment on the enhanced parameter data according to the parameter adaptive weight to obtain the disturbance parameter data.

[0163] In an embodiment of the present invention, a perturbation path unit is used to offset the coordinate values ​​of the projected path data according to the path perturbation matrix to obtain perturbation path data, and to perform micro-perturbations on the path data without affecting the printing accuracy, so that even if the data is intercepted during transmission, it is difficult to directly restore the true printing path; a perturbation material unit is used to randomly replace the standardized ratio values ​​in the discretized material data according to the material perturbation factor to obtain perturbation material data, and by randomly perturbing the material ratio data during data transmission, it is prevented that malicious attackers infer the printing process or product formula by analyzing the material ratio; a perturbation parameter unit is used to perform weighted adjustment on the enhanced parameter data according to the parameter adaptive weight to obtain perturbation parameter data, and by perturbing the printing parameters during data transmission, it is improved that the data is tamper-resistant and the printing quality is prevented from being degraded due to parameter tampering during the printing process.

[0164] The perturbation path unit is used to offset the coordinate values ​​of the projected path data according to the path perturbation matrix to obtain the perturbation path data, specifically including:

[0165] First, it is necessary to obtain the projection path data. This data is the path coordinate information followed by the nozzle or laser head of the 3D printer when performing a printing task. These path data are composed of multiple continuous coordinate points and usually represent the motion trajectory in three-dimensional space. In the traditional 3D printing data transmission process, the path data is directly stored and transmitted, which is easy to be intercepted or tampered with, resulting in unauthorized printing or path deviation. To solve this problem, the perturbation path unit will fine-tune these coordinate points based on the path perturbation matrix, so that even if the path data is intercepted during transmission, it is difficult to directly restore the actual printing trajectory.

[0166] When calculating the path perturbation matrix, the system first analyzes the overall characteristics of the projected path data, including the path's coordinate mean and distribution range. Based on this data, the system calculates a perturbation offset matrix, which adds a random offset value within a reasonable range to each coordinate point to ensure that the perturbation does not affect print quality. Next, the system iterates through each coordinate point in the path data and adjusts the coordinate values ​​according to the calculated offset matrix. The adjusted coordinate data still ensures the continuity of the print path, but for an external attacker, the data has undergone nonlinear changes, making it difficult to directly exploit.

[0167] After the disturbance is completed, the system generates disturbed path data, which can be directly used for subsequent encrypted transmission. Since the path data has been processed, even if an external attacker successfully intercepts it, it is impossible to accurately restore the original printing path, thus avoiding unauthorized copying.

[0168] The disturbed material unit is used to randomly replace the standardized ratio values ​​in the discretized material data according to the material disturbance factor to obtain the disturbed material data, which specifically includes:

[0169] First, the discrete material data is obtained. This data contains the material ratio information used in the 3D printing task. In traditional 3D printing tasks, the material ratio data is usually fixed and can be easily analyzed and inferred by attackers to determine the specific material formula, thus posing a threat to the intellectual property rights of the printing task. To solve this problem, the material perturbation factor is calculated and the material ratio data is dynamically adjusted to give it a certain degree of randomness during transmission.

[0170] When calculating the material disturbance factor, the system analyzes the material usage in the historical printing data, including the material ratio change trend and the frequency of use of different materials. Based on this data, the system determines the disturbance range of each material and generates a random disturbance value to ensure the security of the data. During specific execution, the system randomly replaces the standardized ratio value according to the calculated disturbance factor. For example, if the original ratio of a certain material is a standardized value, the system may fine-tune it within a reasonable range, so that the final stored data is slightly different from the original data.

[0171] After the disturbance is completed, the system generates disturbed material data, which can be used for subsequent secure transmission. Through this processing method, even if an attacker intercepts the material ratio data, it is difficult to accurately infer the actual material formula, thereby protecting the core technology of the printing task.

[0172] The disturbance parameter unit is used to perform weighted adjustment on the enhanced parameter data according to the parameter adaptive weight to obtain the disturbance parameter data, which specifically includes:

[0173] First, the enhanced parameter data is obtained. This data contains key process parameters in the printing process, such as nozzle temperature, printing pressure, nozzle movement speed, layer thickness adjustment, etc. These parameters determine the final quality of the print. Therefore, the security of the parameters is crucial during data transmission. In traditional 3D printing tasks, these parameters are usually fixed values ​​or manually adjusted by the user. In remote data transmission scenarios, the parameters may be tampered with, resulting in printing failure or deterioration in print quality. To solve this problem, the perturbation parameter unit dynamically adjusts these key parameters by calculating the parameter adaptive weights to increase data security.

[0174] When calculating the adaptive weight of parameters, the system will comprehensively analyze the stability parameters of historical printing tasks and determine the adjustable range of each parameter. Then, the system will calculate an adaptive weight value based on these historical data. This value is used to determine the amplitude of the disturbance. During the specific execution process, the system will make weighted adjustments to the printing parameters based on the calculated weights. For example, the set value of the nozzle temperature may be fine-tuned within a reasonable range, so that there is a certain deviation between the transmitted data and the original data, and this deviation will not affect the final print quality. Similarly, the printing movement speed can also be slightly adjusted to ensure the security of the transmitted data.

[0175] After the disturbance is completed, the system generates disturbance parameter data and uses it for subsequent secure transmission. In this way, even if an external attacker intercepts the printing parameter data, it is difficult to accurately infer the original printing setting value, thereby improving the security of data transmission.

[0176] In a preferred embodiment of the present invention, the identification module includes:

[0177] A preliminary trajectory offset value calculation unit is used to calculate the coordinate difference based on the path coordinate information of the disturbed path data and the projected path data to obtain a preliminary trajectory offset value;

[0178] a trajectory offset value calculation unit, configured to smooth the preliminary trajectory offset value, remove abnormal values ​​caused by noise, and obtain a trajectory offset value;

[0179] The path feature identification unit is used to compare and analyze the printing path data according to the trajectory offset value to determine whether there is an abnormal deviation. When the result is no, a path feature identification is generated.

[0180] In an embodiment of the present invention, a preliminary trajectory offset value calculation unit is used to calculate the coordinate difference based on the path coordinate information of the disturbance path data and the projection path data to obtain a preliminary trajectory offset value, and obtain a preliminary estimate of the trajectory offset value through a numerical calculation method; the trajectory offset value calculation unit is used to smooth the preliminary trajectory offset value, remove outliers caused by noise, and obtain a trajectory offset value. Through filtering and outlier removal, the reliability of the trajectory offset data can be improved and misjudgment due to small errors can be avoided; the path feature identification unit is used to compare and analyze the printing path data based on the trajectory offset value to determine whether there is an abnormal deviation. When the result is no, a path feature identification is generated, thereby ensuring the accuracy of the 3D printing path and improving the integrity of the printing data.

[0181] The trajectory offset value calculation unit is used to smooth the preliminary trajectory offset value, remove abnormal values ​​caused by noise, and obtain the trajectory offset value, specifically including:

[0182] When performing smoothing, the unit adopts a sliding window method, that is, for each data point in the preliminary trajectory offset value, the offset values ​​of several adjacent data points before and after it are averaged to obtain the smoothed offset value of the data point. The size of the sliding window can be determined according to the system preset parameters. For example, if the window size is five data points, the smoothed value of a data point is obtained by the weighted average of the offset values ​​of the data point and the two data points before and after it. In this way, the impact of short-term random fluctuations on the data can be effectively reduced, making the trajectory offset value more continuous.

[0183] After completing the preliminary smoothing process, outliers are then removed. The determination of outliers is based on statistical analysis methods. First, the mean and standard deviation of the trajectory offset sequence are calculated, and the principle of three times the standard deviation is adopted. That is, if the difference between the offset value of a data point and the mean of the trajectory offset sequence exceeds three times the standard deviation, then the data point is determined to be an outlier. For the processing of outliers, interpolation method is used for correction. For example, the mean of its two adjacent normal data points can be used as a substitute value to ensure the smoothness and rationality of the trajectory offset data.

[0184] In a preferred embodiment of the present invention, the identification module further includes:

[0185] A preliminary material offset calculation unit is used to compare the disturbed material data with the discretized material data, calculate the numerical difference, and obtain the preliminary material offset;

[0186] A material offset rate calculation unit is used to calculate the offset ratio of different materials based on the preliminary material offset amount, and normalize the offset ratio to obtain the material offset rate;

[0187] The material feature identification unit is used to perform statistical analysis on the material ratio data according to the material deviation rate to determine whether there is an abnormal ratio. When the result is no, a material feature identification is generated.

[0188] In an embodiment of the present invention, a preliminary material offset calculation unit is used to compare the disturbed material data and the discretized material data, calculate the numerical difference, and obtain the preliminary material offset, which can accurately measure the offset of the material proportion data before and after the disturbance; the material offset rate calculation unit is used to calculate the offset ratio of different materials based on the preliminary material offset, and normalize the offset ratio to obtain the material offset rate, quantify the material proportion offset, and enable the system to quickly determine whether there is an abnormal material offset; the material feature identification unit is used to perform statistical analysis on the material proportion data based on the material offset rate to determine whether there is an abnormal proportion. When the result is no, a material feature identification is generated, which can monitor the integrity of the material proportion in real time during data transmission.

[0189] In a preferred embodiment of the present invention, the identification module further includes:

[0190] a preliminary parameter offset ratio calculation unit, configured to compare the disturbance parameter data with the enhancement parameter data, calculate the parameter difference, and obtain a preliminary parameter offset ratio;

[0191] A parameter offset ratio calculation unit is used to analyze the parameter change trend of adjacent printing layers based on the preliminary parameter offset ratio, and perform curve fitting on the change trend to obtain the parameter offset ratio;

[0192] The parameter feature identification unit is used to perform error analysis on the printing parameter data according to the parameter offset ratio to determine whether there is abnormal fluctuation. When the result is no, a parameter feature identification is generated.

[0193] In an embodiment of the present invention, a preliminary parameter offset ratio calculation unit is used to compare the disturbance parameter data and the enhancement parameter data, calculate the parameter difference, and obtain a preliminary parameter offset ratio, which can quantify the impact of the disturbance on the printing parameters; the parameter offset ratio calculation unit is used to analyze the parameter change trend of adjacent printing layers according to the preliminary parameter offset ratio, and perform curve fitting on the change trend to obtain the parameter offset ratio. By analyzing the parameter change trend, the detection capability of abnormal fluctuations in the printing parameters is improved; the parameter feature identification unit is used to perform error analysis on the printing parameter data according to the parameter offset ratio to determine whether there is abnormal fluctuation. When the result is no, a parameter feature identification is generated to provide a printing parameter integrity verification mechanism to ensure that the parameters have not been abnormally modified during the transmission and disturbance process.

[0194] The parameter offset ratio calculation unit is used to analyze the parameter change trend of adjacent printing layers based on the preliminary parameter offset ratio, and perform curve fitting on the change trend to obtain the parameter offset ratio, which specifically includes:

[0195] During the 3D printing process, the printing parameters of each layer will be adjusted, which may involve multiple parameters such as printing temperature, printing speed, nozzle pressure, etc. In order to analyze the parameter change trend, it is necessary to first calculate the parameter offset ratio of adjacent printing layers. Based on the preliminary parameter offset ratio, by analyzing the changes in parameters between layers, the overall change trend is identified. The system normalizes the parameter values ​​of each layer according to the order of printing layers, so as to eliminate the influence of different printing tasks or equipment on the parameter value range in subsequent processing.

[0196] Next, it is necessary to analyze the parameter change trend between adjacent layers. It is necessary to compare the parameter offset values ​​of two adjacent layers and calculate the relative change, that is, the difference between the offset value of the current layer and the offset value of the previous layer. Then, divide it by the offset value of the previous layer to obtain the relative change rate. This ensures that the system not only focuses on the absolute change value, but also can identify small continuous offsets, making the overall trend analysis more accurate.

[0197] The changing data is smoothed by a curve fitting algorithm. During the fitting process, the system first selects an appropriate fitting order, usually based on the complexity of the data. If the data changes relatively smoothly, a lower-order polynomial is selected; if the data fluctuates greatly, a higher-order polynomial or piecewise spline interpolation method can be used. The system uses the least squares method to optimize the parameters of the fitting function so that the fitting curve can match the original data to the greatest extent possible.

[0198] After the curve fitting is completed, the system verifies the fitting results to ensure that the fitting curve can accurately reflect the changing trend of the parameter offset ratio. The system calculates the error between the fitting curve and the actual data, and evaluates the fitting quality through indicators such as the mean square error. If the error exceeds the set threshold, the system will adjust the fitting method, such as changing the fitting function or adding data smoothing steps to improve accuracy. If the fitting quality meets expectations, the system can store the fitting results of the parameter offset ratio and use them for subsequent detection and anomaly identification.

[0199] In a preferred embodiment of the present invention, the detection module includes:

[0200] A path detection unit is used to compare the trajectory offset value with a preset trajectory offset value according to the path feature identifier, and when the trajectory offset value exceeds the trajectory threshold, it is determined that the original printing data set is abnormal;

[0201] A material detection unit is used to compare the material offset rate with a preset material offset rate according to a material feature identifier, and when the material offset rate exceeds the preset material offset rate, it is determined that the original printing data set is abnormal;

[0202] a parameter detection unit, configured to compare the parameter offset ratio with a preset parameter offset ratio according to the parameter feature identifier, and determine that the original printing data set is abnormal when the parameter offset ratio exceeds the preset parameter offset ratio;

[0203] The abnormal signal unit is used to generate an abnormal signal when any abnormal data is detected.

[0204] In an embodiment of the present invention, a path detection unit is used to compare a trajectory offset value with a preset trajectory offset value based on a path feature identifier. When the trajectory offset value exceeds a trajectory threshold, the original printing data set is determined to be abnormal. Through the path feature identifier and the trajectory offset calculation, it is possible to accurately identify whether the printing path data has been tampered with, thereby improving the security of the transmitted data; the material detection unit is used to compare a material offset rate with a preset material offset rate based on a material feature identifier. When the material offset rate exceeds the preset material offset rate, the original printing data set is determined to be abnormal. Through the material feature identifier and the material offset rate calculation, changes in material ratios can be monitored in real time to ensure that the printing task is strictly carried out in accordance with the set material ratio; the parameter detection unit is used to compare a parameter offset ratio with a preset parameter offset rate ratio based on a parameter feature identifier. When the parameter offset ratio exceeds the preset parameter offset rate ratio, the original printing data set is determined to be abnormal. Through the parameter offset ratio calculation, it is possible to accurately monitor whether the printing parameters meet the set requirements, thereby preventing printing failures caused by parameter abnormalities; the abnormal signal unit is used to generate an abnormal signal when any abnormal data is detected, thereby responding to data abnormalities in real time and improving system security.

[0205] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A remote encrypted transmission system for 3D printing, characterized in that: The system comprises: The parsing module is used to obtain the original printing data set and extract the printing path data, material ratio data and printing parameter data from it to obtain the basic data set; A calculation module is used to calculate the path perturbation matrix, material perturbation factor and parameter adaptive weight according to the basic data set to obtain the perturbation parameter data set; A conversion module is used to map and convert the printing path data, material ratio data and printing parameter data in the basic data set to obtain a conversion data set; A perturbation module, configured to perform perturbation processing on the transformed data set according to the perturbation parameter data set to obtain a perturbation data set; An identification module is used to calculate the trajectory offset value, material offset rate and parameter offset ratio according to the disturbance data set, and generate a path feature identifier, a material feature identifier and a parameter feature identifier to obtain an identification data set; A transmission module, used for packaging and transmitting the original printing data set and the identification data set to obtain a transmission data stream; A detection module is used to receive the transmission data stream and perform anomaly detection on it. When an anomaly is detected, an anomaly signal is generated and the original printing data set is rejected for 3D printing; The calculation module includes: A path feature unit is used to extract path coordinate information based on the printing path data and obtain the coordinate mean and coordinate variance; A path perturbation matrix unit is used to calculate a reference offset matrix according to the coordinate mean, and adjust the reference offset matrix according to the coordinate variance to obtain a path perturbation matrix; The material feature unit is used to identify the variation range of the material ratio according to the material ratio data, and extract the number of times the material is used to obtain the ratio change rate and material use frequency; The material disturbance factor calculation unit is used to calculate the average value of the ratio of the material ratio value to the ratio value variance, the exponential decay value of the material frequency in historical tasks, and the cumulative value of each material ratio deviation and usage frequency; then the weighted sum of the average value of the ratio, the exponential decay value and the cumulative value is used to obtain the material disturbance factor; A printing parameter feature unit, used to calculate the parameter adjustment rate of adjacent printing layers based on the printing parameter data; A parameter adaptive weight unit is used to calculate an initial adjustment weight according to a parameter adjustment rate, and adjust the initial adjustment weight according to a preset printing stability to obtain a parameter adaptive weight; The identification module includes: A preliminary trajectory offset value calculation unit is used to calculate the coordinate difference based on the path coordinate information of the disturbed path data and the projected path data to obtain a preliminary trajectory offset value; a trajectory offset value calculation unit, configured to smooth the preliminary trajectory offset value, remove abnormal values ​​caused by noise, and obtain a trajectory offset value; A path feature identification unit is used to compare and analyze the printing path data according to the trajectory offset value to determine whether there is an abnormal deviation. If the result is no, a path feature identification is generated; The identification module further includes: A preliminary material offset calculation unit is used to compare the disturbed material data with the discretized material data, calculate the numerical difference, and obtain the preliminary material offset; A material offset rate calculation unit is used to calculate the offset ratio of different materials based on the preliminary material offset amount, and normalize the offset ratio to obtain the material offset rate; The material feature identification unit is used to perform statistical analysis on the material ratio data according to the material deviation rate to determine whether there is an abnormal ratio. If the result is no, a material feature identification is generated; The identification module further includes: a preliminary parameter offset ratio calculation unit, configured to compare the disturbance parameter data with the enhancement parameter data, calculate the parameter difference, and obtain a preliminary parameter offset ratio; A parameter offset ratio calculation unit is used to analyze the parameter change trend of adjacent printing layers based on the preliminary parameter offset ratio, and perform curve fitting on the change trend to obtain the parameter offset ratio; The parameter feature identification unit is used to perform error analysis on the printing parameter data according to the parameter offset ratio to determine whether there is abnormal fluctuation. When the result is no, a parameter feature identification is generated.

2. A remote encrypted transmission system for 3D printing according to claim 1, characterized in that: The conversion module includes: A projection coefficient unit, used to construct a projection matrix according to the path coordinate information of the printing path data, and calculate the projection coefficient according to the projection matrix; A preliminary projection data unit, configured to perform coordinate transformation on the printing path data according to the projection coefficient to obtain preliminary projection data; The projection path data unit is used to detect whether the preliminary projection data exceeds the printing range according to the printing boundary parameters of the 3D printer. When the result is yes, the preliminary projection data exceeding the printing range is projected and adjusted to obtain the projection path data.

3. A remote encrypted transmission system for 3D printing according to claim 2, characterized in that: The conversion module further includes: An interval division unit is used to determine a material usage ratio range according to the number of times the material is used in the material ratio data, and to divide the material ratio data according to the range to obtain a discrete interval set; A standardized proportion unit is used to determine the discrete interval according to the material usage ratio values ​​of different materials and obtain a standardized proportion value; A preliminary discretization unit is used to replace the material usage ratio value in the material ratio data according to the standardized ratio value to obtain preliminary discretized material data; The error compensation unit is used to perform error compensation on the preliminary discretized material data according to the physical properties of different materials, adjust the discretization accuracy, and obtain discretized material data.

4. A remote encrypted transmission system for 3D printing according to claim 3, characterized in that: The conversion module also includes: A parameter change rate calculation unit is used to extract parameter change curves of adjacent printing layers based on the time series of printing parameter data to obtain parameter change rates; A parameter gradient calculation unit, used to calculate the parameter gradients of adjacent printing layers based on the parameter change rate; A gradient sequence generating unit, configured to obtain a smoothed gradient sequence by smoothing the parameter gradient; The gradient sequence increment unit is used to determine the incremental step size according to the printing process requirements, and increment the smooth gradient sequence based on the incremental step size to obtain a parameter incremental sequence; The parameter conversion unit is used to convert the printing parameter data according to the parameter increment sequence to obtain enhanced parameter data.

5. A remote encrypted transmission system for 3D printing according to claim 4, characterized in that: The disturbance module includes: A perturbation path unit is used to offset the coordinate values ​​of the projected path data according to the path perturbation matrix to obtain perturbation path data; The disturbed material unit is used to randomly replace the standardized ratio values ​​in the discretized material data according to the material disturbance factor to obtain the disturbed material data; The disturbance parameter unit is used to perform weighted adjustment on the enhanced parameter data according to the parameter adaptive weight to obtain the disturbance parameter data.

6. A remote encrypted transmission system for 3D printing according to claim 5, characterized in that: The detection module includes: A path detection unit is used to compare the trajectory offset value with a preset trajectory offset value according to the path feature identifier, and when the trajectory offset value exceeds the trajectory threshold, it is determined that the original printing data set is abnormal; A material detection unit is used to compare the material offset rate with a preset material offset rate according to a material feature identifier, and when the material offset rate exceeds the preset material offset rate, it is determined that the original printing data set is abnormal; a parameter detection unit, configured to compare the parameter offset ratio with a preset parameter offset ratio according to the parameter feature identifier, and determine that the original printing data set is abnormal when the parameter offset ratio exceeds the preset parameter offset ratio; The abnormal signal unit is used to generate an abnormal signal when any abnormal data is detected.

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