Research On Lightweight Method Of MBD Model In 3D Digital Process Design

At present,Intelligent manufacturing and smart factories have become the development trend of technology in the manufacturing industry.A large amount of digital intelligent manufacturing data is stored in the cloud,and there is a problem of large amount of data and slow transmission in the process of downloading to the local and applying to the manufacturing equipment.Therefore,based on 3D digital MBD model data,this thesis design a lightweight scheme for data processing in combination with the embedded system: For the MBD model data stored in the cloud,the improved non-recursive depth-first traversal algorithm and the improved adaptive Huffman compression algorithm studied in this thesis are used to extract and compress the required data information without downloading all the data information;By defining the LwIP TCP/IP protocol and transmitting it to the local ARM embedded system,the data is decompressed by the improved adaptive Huffman compression algorithm studied in this thesis;then the data is transmitted to the CNC machine through the USB.Firstly,the MBD model data of Step file format is converted into Xml extensible markup language,data exchange and sharing between different systems are completed,MBD data model is established,and data information is extracted by improved non-recursive depth first traversal algorithm.The MBD model data is stored in the cloud database as an Xml field.After receiving the STM32F407 TCP client request instruction,the database Xml file is accessed,the improved non-recursive depth first traversal algorithm in this thesis is used to extract the data information.The improved extraction algorithm is experimentally verified to prove the feasibility of the method and meet the needs of different operators.Secondly,the data is compressed using a modified adaptive Huffman compression algorithm.The Huffman compression algorithm is used for data compression,which solves the problem that the model data is large and difficult to store and transmit.However,the compression rate and compression ratio of this algorithm are low.After adding the greedy algorithm to improve,the compression rate is not ideal.Therefore,this thesis adopts the improved adaptive Huffman compression algorithm to improve the compression rate and low compression ratio.And experimental verification to achieve better compression rate and compression ratio.Finally,STM32 is used as the embedded core controller to design lightweight data for cloud MBD model data processing and transmission.First define the LwIP TCP/IP protocol of STM32F407 hardware and cloud communication,configure the STM32F407 pin,and complete the communication between the hardware structure of the STM32F407 and the cloud through the driver connected by the Ethernet network cable and the router.Through the instruction,the MBD model data stored in the cloud is extracted and compressed,transmitted to the local ARM and the data is decompressed;and transmitted to the numerical control machine tool.The lightweight method based on 3D digital MBD model data transmission in this thesis can help enterprises solve the problems of large data volume,slow processing data of process system platform and slow transmission of information files.The data processing extraction and compression algorithm studied in this paper can also be applied to the acquisition of data based on predictive maintenance,operation and maintenance and machine learning of cloud-based devices,which has great application value.