An intelligent leveling-free system for 3D printers based on data analysis

Abstract

The present invention discloses a data analysis-based intelligent leveling-free 3D printer system, specifically relating to the field of 3D printing technology. The system includes a sensor module for scanning printer position data, a feature extraction module for integrating sensor data, a model building module for converting data for user reference, a master control server for data collection and processing, a visualization module for converting data models, a control module for user operation, and a motor module for printer leveling. The system utilizes a local storage module, a data anomaly detection module, a data proofreading module, a data optimization module, and a format cloud conversion module to stably store printing solution data and prevent data loss. The system then performs integrity checks on uploaded data to ensure solution data availability. The system then compares and optimizes uploaded and local data to improve data accuracy and practicality.

Description

Technical Field

[0001] The present invention relates to the technical field of 3D printing, and in particular to an intelligent leveling-free system for a 3D printer based on data analysis. Background Art

[0002] Existing 3D printer systems face the risk of data loss and corruption when uploading print plan data. Incompatible plan formats can also prevent the printer from recognizing and printing. Furthermore, system reliability and stability are hampered by data issues that can render plans unusable or even fail during the upload process, reducing the practicality of such 3D printers. Therefore, we propose an intelligent, leveling-free 3D printer system based on data analysis. Summary of the Invention

[0003] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent leveling-free system for 3D printers based on data analysis.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] A data analysis-based intelligent leveling-free 3D printer system includes a sensor module for scanning printer position data, a feature extraction module for integrating sensor data, a model building module for converting data for user reference, a master control server for data collection and processing, a visualization module for data conversion models, a control module for user operation, and a motor module for printer leveling.

[0006] The sensor module includes a laser sensor module for detecting whether the printing platform is uneven, a pressure sensor module for detecting whether the printing platform is uneven, an acceleration sensor for detecting the tilt or vibration of the printing platform, and a trigger sensor for detecting the position or stability of the printing platform;

[0007] The feature extraction module includes a data acquisition module for collecting and processing raw data, a signal processing module for converting data information, a feature extraction algorithm module for extracting data information, and a model generation module for converting digital data into model data;

[0008] The model building module includes a data preprocessing module for transmission data preprocessing, a model selection module for algorithm learning and neural network construction, a model training module for model training, and a model debugging module for model performance debugging and upgrading;

[0009] The data pre-processing module includes a local storage module for preventing data from being uploaded to the master control server database, a data anomaly detection module for checking the integrity of uploaded data, a data proofreading module for comparing the master control server database with the uploaded data, a data comparison module for optimizing the data storage format, and a format cloud conversion module for converting the printing solution format.

[0010] The visualization module includes a data visualization module for converting data into image models, a model structure visualization module for converting model position data into image data, an interface design module for user operations, and a UI interaction module for responding to user operations;

[0011] The control module includes a logic control module for controlling the intelligent leveling-free system, a data processing and transmission module for transmitting and processing data from various sensors and feature extraction modules, integrating, analyzing, aggregating, and coordinating data with other systems, a visualization module for displaying data processing results in a graphical manner, and an equipment debugging module for providing support for equipment debugging and optimization;

[0012] The motor module includes a motor drive control module for receiving and sending control signals and controlling motor power, a motor sensor encoding module for monitoring motor parameters and motor measurements, and a motor drive heat dissipation module for dissipating and controlling the motor.

[0013] The laser sensor module and pressure sensor module convert the planar layout data of the 3D printer's location into digital information and transmit it to the feature extraction module for data extraction. The acceleration sensor and trigger sensor transmit the placement information on the 3D printing surface to the feature extraction module through scanning for data extraction.

[0014] The data of the laser sensor module, pressure sensor module, acceleration sensor module and trigger sensor module are transmitted to the signal processing data to convert the signal data into digital data for storage. The signal processing module extracts useful data from the data acquisition module, and then extracts and transmits the data indicating the unevenness of the position from the data through the feature extraction algorithm module to the model generation module, and converts the digital information into model information for user reference.

[0015] The present invention is further configured as follows: the data preprocessing module optimizes the processed model data by removing outliers and filling missing values; the local storage module prints and deploys the printing plan by uploading it to the master control server to prevent data loss due to upload failure during the upload process due to problems with the server or local area network; after the data upload fails, the database is stored and protected in a local backup storage manner; the data anomaly detection module detects the uploaded data to prevent the problem of file compression data loss during upload compression, which makes the plan unusable; the data proofreading module and the data comparison module repeatedly compare the uploaded data with the local data and upload and save the comparison results in an optimal manner; the format cloud conversion module converts the plan format uploaded to the server into a format that can be recognized and printed by the 3D printer through a cloud conversion method for storage; the model selection module repeatedly compares the optimized data model with the data in the signal processing module to screen approximate data; the model training module optimizes the screened digital model through training and polishing and stores it in the database; and the model tuning module selects the models in the library according to the optimal ratio and uploads them to the master control server.

[0016] The present invention is further configured as follows: the master control server transmits the optimal model in the database to the visualization module via a transmission method; the data visualization module allows the user to select the 3D information and data information of the model at the location for reference; the model result visualization module retrieves the optimal model from the database of the master control server for user reference; the interface design module and the UI interaction module enable the user to interact with the master control server for operation information through the operation panel on the 3D printer.

[0017] The present invention is further configured as follows: the logic control module can convert the protrusion information into pre-processed information according to the protrusion information value provided by the sensor module and transmit it to the motor module for leveling; the data processing and transmission module transmits the user's interactive data on the interactive panel to the master control server via digital information data, and transmits the data in a processed manner to the motor module through the master control server for processing; the equipment debugging module is used by the user to debug and compare the data of the master control server through the control panel.

[0018] The present invention is further configured as follows: the motor drive control module processes the data transmitted from the master control server by transcoding, and transmits the processed data to the motor sensor encoding module for data encoding operation; the motor drive heat dissipation module controls the motor start-up and leveling by passing the encoded data through the drive board, and dissipates the heat generated during the operation of the motor.

[0019] The beneficial effects of the present invention are:

[0020] The present invention designs a local storage module, a data anomaly detection module, a data proofreading module, a data comparison module and a format cloud conversion module to stably store printing solution data and prevent data loss. It then performs integrity detection on the uploaded data to ensure the availability of solution data. It will then be used to compare and optimize uploaded and local data to improve data accuracy and practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The figure is a flow chart of the intelligent leveling-free system for 3D printers based on data analysis in the present invention.

[0022] Figure 2 This is a partial system flow diagram of the data preprocessing module in the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0024] Example 1

[0025] like Figure 1-2 As shown, a data analysis-based intelligent leveling-free system for 3D printers includes a sensor module for scanning printer position data, a feature extraction module for integrating sensor data, a model building module for converting data for user reference, a master control server for data collection and processing, a visualization module for data conversion models, a control module for user operation, and a motor module for printer leveling.

[0026] The sensor module includes a laser sensor module for detecting whether the printing platform is uneven, a pressure sensor module for detecting whether the printing platform is uneven, an acceleration sensor for detecting the tilt or vibration of the printing platform, and a trigger sensor for detecting the position or stability of the printing platform;

[0027] The feature extraction module includes a data acquisition module for collecting and processing raw data, a signal processing module for converting data information, a feature extraction algorithm module for extracting data information, and a model generation module for converting digital data into model data;

[0028] The model building module includes a data preprocessing module for transmission data preprocessing, a model selection module for algorithm learning and neural network construction, a model training module for model training, and a model debugging module for model performance debugging and upgrading;

[0029] The data pre-processing module includes a local storage module for preventing data upload failure to the master control server database, a data anomaly detection module for comparing uploaded data integrity, a data proofreading module for comparing the master control server database with uploaded data, a data comparison module for optimizing and comparing data storage formats, and a format cloud conversion module for converting printing solution formats.

[0030] The visualization module includes a data visualization module for converting data into image models, a model structure visualization module for converting model position data into image data, an interface design module for user operations, and a UI interaction module for responding to user operations;

[0031] The control module includes a logic control module for controlling the intelligent leveling-free system, a data processing and transmission module for transmitting and processing data from various sensors and feature extraction modules, integrating, analyzing, aggregating, and coordinating data with other systems, a visualization module for graphically displaying data processing results, and an equipment debugging module for providing support for equipment debugging and optimization.

[0032] The motor module includes a motor drive control module for sending and receiving control signals and controlling motor power, a motor sensor encoding module for monitoring motor parameters and motor measurements, and a motor drive heat dissipation module for dissipating and controlling the motor.

[0033] In the above-mentioned embodiments, the preprocessing module primarily performs data optimization, typically including removing outliers and filling missing values. However, the preprocessing module also has significant drawbacks. First, it requires significant time and computing resources to complete data processing, which can impact system performance. Second, during data preprocessing, certain assumptions about the model are often required to optimize data processing. This also means that if the assumptions are inaccurate, the effectiveness of data preprocessing may be affected, thereby impacting system performance. Finally, the results of the preprocessing module may be affected by the unique characteristics of the data, resulting in potential uncertainty. The local storage module utilizes a local backup method for storage. Compared to printing deployment that uploads to a master control server, this method is more effective in preventing upload failures and data loss caused by special circumstances. In the event of a data upload failure, the local storage module can promptly back up the data, preventing complete data loss and ensuring that users' printing requests are promptly processed and responded to. Furthermore, the local backup method provides multiple backup sources for subsequent operations, further ensuring the security and reliability of important data.

[0034] Among them, the laser sensor module and the pressure sensor module convert the planar layout data of the 3D printer's location into digital information and transmit it to the feature extraction module for data extraction. The acceleration sensor and the trigger sensor transmit the placement information on the 3D printing surface to the feature extraction module through scanning for data extraction.

[0035] Among them, the data of the laser sensor module, pressure sensor module, acceleration sensor module and trigger sensor module are transmitted to the signal processing data to convert the signal data into digital data for storage. The signal processing module extracts useful data from the data acquisition module, and then uses the feature extraction algorithm module to extract the data indicating the unevenness of the position and transmit it to the model generation module, converting the digital information into model information for user reference.

[0036] Among them, the data preprocessing module optimizes the processed model data by removing outliers and filling missing values. The local storage module prints and deploys the printing plan by uploading it to the master control server to prevent the problem of data loss caused by upload failure due to problems with the server or local area network during the upload process. After the data upload fails, the database is stored and protected through local backup storage. The data anomaly detection module detects the uploaded data to prevent the problem of file compression data loss during upload compression, which makes the plan unusable. The data proofreading module and the data comparison module repeatedly compare the uploaded data with the local data and upload and save the comparison results in the best way. The format cloud conversion module converts the plan format uploaded to the server into a format that can be recognized and printed by the 3D printer through cloud conversion for storage. The model selection module repeatedly compares the optimized data model with the data in the signal processing module to screen the approximate data. The model training module optimizes the screened digital model through training and polishing and puts it into the warehouse. The model tuning module selects the models in the library according to the optimal ratio and uploads them to the master control server.

[0037] The data anomaly detection module checks uploaded data to prevent data loss during file compression, which could lead to unusable solutions. The data proofreading and optimization modules repeatedly compare uploaded data with local data and upload and save the results in the optimal format. This effectively prevents issues such as printing solution failure and file corruption caused by data loss during compression, ensuring the integrity of uploaded data. Furthermore, the results of the data anomaly detection module help users identify and quickly resolve any issues that may arise during file upload, optimizing the user experience. By repeatedly comparing uploaded data with local data, the data proofreading and optimization modules significantly improve data accuracy and reliability, ensuring consistency between uploaded and local data and avoiding mismatches in printing solutions. Based on the comparison results, the optimal format is uploaded and saved, saving storage space while ensuring data security and stability. Furthermore, data proofreading and optimization processing provide strong support for subsequent data analysis and mining, enhancing the credibility and practical value of data applications.

[0038] Example 2

[0039] like Figure 1-2 As shown, a 3D printer intelligent leveling-free system based on data analysis is shown. The master control server transmits the optimal model in the database to the visualization module via a transmission method. The data visualization module allows users to select 3D information and data information of the model at their location for reference. The model result visualization module retrieves the optimal model from the master control server's database for user reference. The interface design module and the UI interaction module allow users to interact with the master control server through the operation panel on the 3D printer. The logic control module can convert the protrusion information provided by the sensor module into pre-processed information based on the protrusion information value and transmit it to the motor module for leveling. The data processing and transmission module transmits the user's interactive data on the interactive panel to the master control server via digital information data, and then transmits the data to the motor module for processing through the master control server. The device debugging module allows users to debug and compare the data of the master control server through the control panel. The motor drive control module processes the data transmitted from the master control server through a transcoding method and transmits the processed data to the motor sensor encoding module for data encoding. The motor drive heat dissipation module controls the motor by controlling the driver board based on the encoded data to start the motor for leveling and dissipate the heat generated during the motor operation.

[0040] In the above embodiment, the user transmits the debugging data to the motor module through the master control server according to the device debugging module in the control module through the control panel of the 3D printer and implements the adjustment data through the motor module.

[0041] Among them, the interface design module and the UI interaction module allow users to interact with the master control server for operational information through the operation panel on the 3D printer. The format cloud conversion module converts the solution format uploaded to the server into a cloud format that can be recognized by the 3D printer, and stores the converted file. In this way, no matter what format the solution uploaded by the user is, after uploading it to the server, it can be processed by the format cloud conversion module and converted into a format that can be recognized and printed by the 3D printer, ensuring the availability and practical application effect of the user's uploaded solution. In addition, the conversion method of the format cloud conversion module is more flexible, efficient, and intelligent than the traditional file conversion method, and can support the conversion of multiple different formats at the same time, greatly improving the convenience and use effect of user-uploaded solutions.

[0042] Among them, the motor drive control module processes the data transmitted from the master control server through transcoding, and transmits the processed data to the motor sensor encoding module for data encoding operation.

[0043] Working principle: When the present invention is in use, after the 3D printer is placed at a fixed point and fixed, the staff needs to use the laser sensor module and the pressure sensor module to collect data, and convert the collected data into digital data through the signal processing module and transmit it to the data acquisition module. In order to extract useful information, the collected data needs to be analyzed by the feature extraction algorithm module, and the prominent data is selected and a brief graphic of the location of the 3D printer is drawn. The processed data needs to pass through the data preprocessing module to extract the data containing information indicating the unevenness of the location of the 3D printer and transmit it to the model generation module, and convert the digital information into model information for user reference. The generated model needs to undergo model selection, training and tuning to make it more accurate and optimized and uploaded to the database of the master control server for storage.

[0044] The data visualization module allows users to select the desired model's 3D and data information. The model result visualization module retrieves the optimal model from the master control server's database for user reference. The interface design module and UI interaction module allow users to easily interact with the master control server from the 3D printer's control panel. The data processing and transmission module transmits user interaction data to the master control server for digital information transmission, where it is processed and then transferred to the motor module for further processing. The device debugging module provides users with convenient debugging and comparison of master control server data on the control panel.

[0045] In the motor drive control module, data transmitted from the master control server is transcoded and transmitted to the motor sensor encoding module for encoding. The encoded data is then transmitted to the motor drive heat dissipation module. The motor drive heat dissipation module transmits the encoded data to the motor via the control driver board, enabling it to start and level, and dissipate the heat generated during motor operation.

[0046] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A 3D printer intelligent leveling-free system based on data analysis, characterized in that: The system comprises a sensor module for scanning printer position data, a feature extraction module for integrating sensor data, a model building module for converting data for user reference, a master control server for data collection and processing, a visualization module for data conversion model, a control module for user operation and a motor module for leveling the printer. The sensor module comprises a laser sensor module for detecting whether the printing platform is uneven, a pressure sensor module for detecting whether the printing platform is uneven, an acceleration sensor module for detecting the tilt or vibration of the printing platform and a trigger sensor module for detecting the position or stability of the printing platform. The feature extraction module comprises a data acquisition module for collecting and processing raw data, a signal processing module for converting data information, a feature extraction algorithm module for extracting data information and a model generation module for converting digital data into model data. The model building module comprises a data preprocessing module for preprocessing transmission data, a model selection module for algorithm learning and neural network construction, a model training module for model training and a model debugging module for debugging and upgrading model performance. The data preprocessing module comprises a module for preventing A local storage module is provided to prevent data from being uploaded to the master control server database, a data anomaly detection module is used to compare the integrity of data uploaded, a data proofreading module is used to compare the master control server database with the uploaded data, a data comparison module is used to optimize and compare the data storage format, and a format cloud conversion module is used to convert the printing solution format. The visualization module includes a data visualization module for converting data into an image model, a model result visualization module for converting model position data into image data, an interface design module for user operation, and a UI interaction module for responding to user operations. The control module includes a logic control module for controlling the intelligent leveling-free system, a data processing and transmission module for transmitting and processing data from various sensors and feature extraction modules, integrating, analyzing, aggregating, and co-processing data with other systems, a visualization display module for displaying data processing results in a graphical manner, and an equipment debugging module for providing support for equipment debugging and optimization. The motor module includes a motor drive control module for receiving and sending control signals and controlling motor power, a motor sensor encoding module for monitoring motor parameters and motor measurements, and a motor drive heat dissipation module for dissipating and controlling the motor.

2. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The laser sensor module and pressure sensor module convert the planar layout data of the 3D printer's location into digital information and transmit it to the feature extraction module for data extraction. The acceleration sensor module and trigger sensor module transmit the placement information on the 3D printing surface to the feature extraction module through scanning for data extraction.

3. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The data of the laser sensor module, pressure sensor module, acceleration sensor module and trigger sensor module are transmitted to the signal processing module to convert the signal data into digital data for storage. The signal processing module extracts useful data from the data acquisition module, and then extracts the data indicating the unevenness of the position from the data through the feature extraction algorithm module and transmits it to the model generation module, which converts the digital information into model information for user reference.

4. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The data preprocessing module optimizes the processed model data by removing outliers and filling missing values. The local storage module prevents data loss due to upload failure caused by server or local area network problems during the upload process in order to print and deploy the printing plan of the 3D printer. After the data upload fails, the database is stored and protected through local backup storage. The data anomaly detection module detects the uploaded data to prevent the loss of file compression data during upload compression, which makes the plan unusable. The data proofreading module and the data comparison module repeatedly compare the uploaded data with the local data and upload and save the comparison results in the optimal way. The format cloud conversion module converts the plan format uploaded to the server into a format that can be recognized and printed by the 3D printer through cloud conversion for storage. The model selection module repeatedly compares the optimized data model with the data in the signal processing module to screen the approximate data. The model training module optimizes the screened digital model through training and polishing and stores it in the library. The model tuning module selects the models in the library according to the optimal ratio and uploads them to the master control server.

5. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The master control server transmits the optimal model in the database to the visualization module via a transmission method. The data visualization module allows users to select 3D information and data information of the model at their location for reference. The model result visualization module retrieves the optimal model from the database of the master control server for user reference. The interface design module and UI interaction module enable users to interact with the master control server for operation information through the operation panel on the 3D printer.

6. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The logic control module can convert the protrusion information into pre-processed information according to the protrusion information value provided by the sensor module and transmit it to the motor module for leveling. The data processing and transmission module transmits the user's interactive data on the interactive panel to the master control server via digital information data, and transmits the data to the motor module for processing via the master control server in a converted manner. The equipment debugging module allows the user to debug and compare the data of the master control server through the control panel.

7. The intelligent leveling-free system for 3D printers based on data analysis according to claim 1, characterized in that: The motor drive control module processes the data transmitted from the master control server by transcoding, and transmits the processed data to the motor sensor encoding module for data encoding operation. The motor drive heat dissipation module controls the motor start-up and leveling by passing the encoded data through the driver board, and dissipates the heat generated during the operation of the motor.

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