An integrated control framework for adaptive assembly of tiny parts and its design method

Abstract

The application relates to an integrated control framework for adaptive assembly of micro parts and a design method thereof, the design method comprising a self-defined heterogeneous equipment information model, an assembly robot, an assembly platform, an OPC UA server of a collaborative robot, and an OPC UA client of integrated heterogeneous equipment. The OPC UA client comprises data and method interfaces provided by the equipment server, the assembly sequence is sorted according to a heuristic algorithm, and automatic assembly is carried out by using a step-based automatic assembly algorithm. Assembly quality information is transmitted to the client in real time through the server and displayed in the client, the assembly state is detected according to the information, and faults are predicted, so that the assembly process is intelligentized and automated, and assembly quality is tracked throughout the process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent manufacturing, in particular to an integrated control framework for adaptive assembly of micro parts and a design method thereof. BACKGROUND

[0002] With the development of science and technology, people's demand for the performance of electromechanical products is also getting higher and higher, and assembly is an important link in the production of electromechanical products. With the miniaturization and precision of assembly devices, micro parts of different manufacturing processes are assembled and integrated through certain connection methods to ensure the assembly quality precision, which requires micro assembly technology and micro assembly system to complete. Many scholars and researchers have conducted in-depth research on this issue. For example, Xu Zheng of Dalian University of Technology adopts a visual system for human-computer interaction, and realizes the assembly of a micro flexible swing system through a look-then-move mode. Cao Yang establishes a digital development software platform for parallel robots, and completes the whole cycle management and maintenance of the research and development and operation process in combination with digital twinning. Huang Xiang of Huazhong University of Science and Technology designs a control software to solve the problems of low assembly precision and efficiency of sub-millimeter micro parts, and proposes a general "four-layer architecture" design mode based on the.NET architecture, which greatly improves the assembly precision and efficiency.

[0003] These research results lay a foundation for realizing automatic assembly of micro devices, but there are still the following problems in realizing automatic assembly of multi-variety and small-batch micro devices:

[0004] 1. The existing micro device automatic / semi-automatic assembly system can only realize the automatic assembly of one kind of micro device or a certain assembly process, and lacks a variable variety automatic assembly process, so the variable variety assembly efficiency is low.

[0005] 2. There is a lack of standardized control framework of micro assembly system with strong universality.

[0006] 3. There is a lack of reference interconnection and intercommunication construction process between micro assembly devices.

[0007] Therefore, the existing micro assembly system needs to match an integrated control method that can complete the high-precision and flexible automatic assembly of micro devices. The control method should allow the micro assembly system to freely add and delete modules and functions, and should not lose the functions of the original assembly system when new devices are added or updated. The creation of the overall assembly system is completed based on the modular idea, and the data communication between modules is ensured to improve the applicability of the micro assembly system to different micro products. SUMMARY

[0008] In view of the problems existing in the prior art, the purpose of the present application is to provide an integrated control framework for adaptive assembly of micro parts and a design method thereof, which is beneficial to the information interconnection and intercommunication and unified control of various heterogeneous devices, and is suitable for multi-variety and variable batch assembly production operations.

[0009] In order to achieve the above object, the application adopts the following technical solutions:

[0010] An integrated control framework for adaptive assembly of micro parts mainly includes the following four layers:

[0011] The micro assembly equipment layer mainly includes a set of micro part assembly system developed by the team, including three main modules of micro assembly robot, micro assembly platform, micro assembly collaborative robot, etc. The main modules include corresponding actuators with multiple degrees of freedom. The communication methods of the equipment and the host computer are different. In the debugging stage, different personnel program in the sub host computer to control. Therefore, after the team develops each module, a general host computer control system compatible with multiple modules is needed to complete the automatic calling of each module. The characteristics of this modular development make the entire assembly system can quickly expand new modules without affecting the functions of existing modules when adding and deleting modules due to the adjustment of assembly products and assembly processes. In addition, it also includes four industrial cameras, feeding platform, discharging platform, clamp library, tool changer, part library, slide rail and other auxiliary modules. The auxiliary modules that need to be controlled use STM32 single-chip microcomputer to connect with the similar main module host computer through serial port RS232, as part of the main module, not separately divided into modules.

[0012] The data transmission layer mainly uses the OPC UA communication protocol to complete the communication between each module and the general host computer, including OPC UA server and client. In the sub host computer unit of the above micro assembly equipment layer, according to the fixed attributes given by the bottom layer equipment manufacturer and the dynamic data transmitted back in the running process, a tree-shaped information modeling method is proposed in this paper to create information model and sub server for sub module. Based on this method, the nodes in the information model in the server bind the data of the bottom layer equipment. Changing the node data or calling the method can directly act on the bottom layer equipment actuator. In the general host computer, a client that can connect the server needs to be created. OPCUA communication protocol allows trusted clients to access the information model in the server using method calls, variable reading and writing, subscription and publication methods to complete various types of operations on the nodes in the server, and then complete the control and data monitoring of the bottom layer equipment actuator.

[0013] Control system layer: established in a well-performing general control computer, used to monitor and control all micro-assembly devices. The main body is the assembly system integrated control software, which includes the client in the data transmission layer, the assembly control module, and the data processing module. First, the control system software allocates memory for the data obtained by the client connecting the server in the general control computer. During operation, the memory can be read through the human-computer interaction interface to display the current device data or send control instructions to the operator. The assembly control module is the basis for automatic assembly of micro parts, including sequence planning before assembly, process generation, automatic execution during assembly, process monitoring, quality monitoring after assembly, and other functions, realizing intelligent and automated assembly operation throughout the process. The data processing module mainly deals with possible faults during assembly and stores log information and bottom-layer device running data during software operation, etc., to assist operators in checking and repairing the equipment.

[0014] Digital twin layer: the memory information obtained by the client in the control system layer is used as information to establish a server that aggregates multiple device modules. This server can provide device data and control methods for other applications. The assembly system has intelligent control functions, and a digital twin can be established for newly developed mechanical systems to achieve virtual and real integration. The present application uses Unity to create a digital twin. Unity is based on the.NET framework program design and allows TCP communication, so the server / client mode based on OPC UA is used to connect the data between the bottom-layer physical entity devices and the virtual twin in the software layer. Normally, the connection between the OPC UA server and the client requires both to be in the same local area network. As mentioned above, all connections are made in the same local area network, but in order to fully understand the product assembly status for operators and developers who are not on site, a Web application can also be used to transmit data over the Internet under the premise of ensuring safety, so as to integrate the automatic assembly system into the Manufacturing Execution System (MES) and Enterprise Resource Planning (ERP), enabling information exchange between the automatic assembly system and the MES system.

[0015] The above four-layer architecture integrated control framework implementation method flow is as follows:

[0016] S1, embed an OPC UA server in each device's sub-upper computer, determine the unstructured data generated by the micro part assembly system during production, classify the data, and build the corresponding OPC UA information model;

[0017] S2, the information model of the corresponding device in the assembly system is instantiated and configured into the OPC UA server, the assembly system device data is bound with the corresponding node in the OPC UA information model, and the mapping of the physical model to the data model is completed;

[0018] S3, the information model in the OPC UA server in the sub-upper computer is accessed by the OPC UA client, the nodes in the information model are queried, the real-time monitoring of the assembly system underlying device data is performed, and the system operation is mastered.

[0019] S4, the assembly sequence planning, step-based automated assembly process and assembly quality monitoring method are added to the control interface, the assembly whole process is intelligentized, automated and efficient.

[0020] S5, the OPC UA client is integrated on the control interface of the general control computer, the monitoring information is displayed in real time, the data is reserved, and the stability of the device in operation is predicted according to the effective BP neural network and related data.

[0021] S6, based on the expansibility of OPC UA, the control interface in the general control computer can also integrate the OPC UA aggregation server as a transfer point of data transmission, through the cross-platform compatibility of OPC UA, different platform control systems can be developed, or the client is embedded in the digital twin, data transmission is completed, and virtual and real combination is achieved.

[0022] Further, the unstructured data in step S1 specifically includes position and angle information, motion speed, motor temperature of each shaft in the five-degree-of-freedom assembly robot, collaborative robot mechanical arm and assembly platform, and image and sensor signals for visual servo and position detection, and also includes voltage information of piezoelectric ceramics in the micro-motion platform. For data classification, the unstructured data of mechanical equipment can be divided into static data set and dynamic data set; the static data set saves the inherent information of the equipment, including manufacturer, product label, equipment size; the dynamic data set saves the information changing in the production process of the equipment, including equipment operation mode, power, actuator running state, and abstracts the common data of the equipment into a class, and then instantiates the class into an object according to the actual requirements, stores the created object into the address space according to a specific structure level, and generates an information model.

[0023] Further, the specific OPC UA information model of the device is constructed by different devices in step S2, the interface for collecting data from the device host computer is directly exposed to the corresponding node in the information model, the mapping of the device physical data to the server information model data is completed, the data is bound in the node of the information model in real time, and the subsequent client and aggregation server subscription and read-write are facilitated.

[0024] Further, step S3 specifically includes embedding an OPC UA client in the control interface of the integrated system in the general control computer, connecting OPC UA servers of all underlying devices, thereby obtaining physical data information exposed by each device through the information model, placing the information to be monitored on the control interface, and completing monitoring of the entire assembly system. The device data is finally integrated in the general control computer, realizing interconnection and intercommunication between devices.

[0025] Further, step S4 specifically includes that the assembly sequence planning algorithm developed by the control interface is an improved pollination algorithm, which converts the problem solving process into a process simulating the pollination of flowers of showy plants in nature, is widely used in optimization problems, and has the characteristics of fast convergence speed. According to the requirements of sequence planning, the assembly relationship parameters of the product to be assembled are selected as the parameters in the solving process, including the priority relationship between parts, stability, assembly direction and tool change, etc. These parameters are calculated according to the influence on the calculation of the cost function, including the assembly time cost, connection stability, direction and tool change frequency, etc. The minimum cost is obtained through iteration, and the corresponding sequence is the optimal assembly sequence.

[0026] Based on the step-based automated assembly process, when a product is assembled for the first time, each module is debugged by using a man-machine interactive method according to the process. The process parameters, calculation data, etc. obtained in the debugging process are saved to the micro device assembly database, so that each process has corresponding parameters and device method calls. When the product is assembled subsequently, i.e. without manual debugging, the corresponding device method is directly called according to the process, and a process detection module is added to check the assembly quality of each process. The parameters of the steps that do not meet the standards are adjusted again or the operator is notified to intervene, and the feedback function automated assembly is completed.

[0027] Further, step S5 specifically includes that the prediction of the stability of the device needs to collect historical data for a period of time into the database by the OPC UA client to form a training set, and after training, the real-time collected data is put into the BP neural network for calculation to predict the stability of the device being operated.

[0028] For step S6, the specific implementation is that the OPC UA information model has rich semantics, and after the unified information model is created in steps 1-5, data transmission becomes simple. As an extension of the control system, creating a digital twin can perform virtual assembly simulation, verify the rationality of the assembly sequence, assembly path planning, motion interference, etc. planning results, and has a guiding role for assembly work. Similarly, the developed system should be easy to integrate. The integrated control framework faces production and should be able to integrate with the existing MES system, providing the data required for product quality management, material management, and production process management.

[0029] In general, the present invention has the following advantages:

[0030] 1. Based on the OPC UA protocol, a modular equipment information integration framework for assembly systems is proposed, which is conducive to the interconnection and unified management of information of various heterogeneous equipment.

[0031] 2. Develop a reconfigurable information model node editor, embedded in the device server, and use a tree diagram modeling method to simplify the OPC UA information model creation process, which is convenient for operators to use.

[0032] 3. An information integration method for industrial assembly equipment is proposed. While the modules are highly correlated, the data information is decoupled and the information is independent of each other. When replacing modules, there is no need to change the overall framework, which can adapt to multi-variety and variable batch assembly production operations.

[0033] 4. An automatic assembly method is proposed. The integrated system provides an assembly method that automatically runs the entire process from assembly sequence, assembly process, assembly instructions, assembly equipment operation, assembly quality inspection, etc., to achieve repeated assembly and diversified assembly.

[0034] 5. A digital twin based on the visualization of the assembly process was designed. The assembly process was realized through the digital twin, which provided macro-coarse positioning coordinates before physical assembly, detected interference, and monitored the operation of the equipment during assembly.

[0035] (1) Compared with traditional assembly, micro-assembly usually requires multiple modules and devices to collaborate to complete the assembly process in order to meet high-precision requirements. The present invention divides various main devices into modules according to the functions of the micro-assembly system. The modules are independent of each other, have no obvious coupling, and are fixed in the system software framework. When developers need to update software and hardware, they only need to update the code of the module that controls the hardware without changing the code of other parts. This makes the code clearer and easier to optimize, and can quickly respond to hardware updates and changes in market demand. To meet module integrated control, each sub-module creates a corresponding OPC UA information model and server, and the control system is embedded in the client to complete communication with the sub-module through the OPC UA communication protocol. The integration and informatization level of micro-parts assembly equipment is improved.

[0036] (2) A set of micro-parts automatic assembly control software was developed to achieve the integration of various parts. This system software can achieve high-precision assembly of various complex micro-devices, solving the automation and flexibility issues of micro-device integrated assembly control. After the assembly debugging is completed, this control system software can save the assembly path, assembly sequence and assembly process parameters in the database to achieve automatic and repeated assembly of different micro-devices. This software has good human-computer interaction. It greatly improves assembly efficiency, has good stability, operates without abnormalities, and improves the flexibility and automation level of micro-parts assembly equipment. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 It is a schematic diagram of an integrated control method of a micro part adaptive assembly system based on OPC UA.

[0038] Figure 2 It is a schematic diagram of the device OPC UA information model and server creation software in the application.

[0039] Figure 3 It is a schematic diagram of the assembly robot module information model in the embodiment.

[0040] Figure 4 It is a flowchart of creating OPC UA nodes in the application.

[0041] Figure 5 It is an automatic assembly flowchart in the embodiment. DETAILED DESCRIPTION

[0042] The application will be further described in detail below.

[0043] Embodiment 1

[0044] The present example provides a tree diagram information modeling method.

[0045] Firstly, the information model of OPC UA has eight basic node types, including object type node, object node, variable type node, variable node, data type node, method node, reference type node and view node. For the present application, the reference type node and the view node use the nodes contained in the SDK, and the remaining six nodes are not created separately, but need to be created according to the needs.

[0046] Secondly, the data that can be fed back from each bottom device by the upper computer of the assembly system needs to be determined, and according to the types, it is divided into static data, dynamic data and calling method and drawing the information model with legends. Since the information model has the function of facing objects, when creating the information model, the specific object needs to be abstracted into a class with common characteristics first, and then the class is referenced and instantiated to create a new object. For the special object without universality, the object can be directly created to reduce the complexity. This operation has good adaptability and expansibility when managing the information model.

[0047] Subsequently, according to the information model drawn by the legend, the static data is supplemented by text, which includes the manufacturer of the equipment, product label, key size, workspace, working condition requirements and other inherent properties set by the factory, which will not change when the equipment starts. The dynamic data is mapped to the physical entity, which includes the data that can be read by the gateway, Ethernet and other programmable control data interfaces exposed to the customer by the manufacturer when the equipment leaves the factory, such as the data packet returned to the host computer by the equipment through RS485, RS232 and other serial ports. The data packet is parsed by the protocol supported by the equipment to complete the reading of the parsed packet data, so as to bind to the dynamic data node and complete real-time monitoring.

[0048] After that, for the method of controlling the equipment in the host computer, the corresponding identifier of the Bool type is provided to represent the default value of False. A new thread is opened in the host computer to monitor whether the identifier changes. When the identifier changes from False to True, the method is called. In the information model, the identifier is bound to the input variable in the corresponding method node. In the OPC UA server and client, the value of the input variable can be changed by calling the method node to realize the calling of the equipment method.

[0049] The above-mentioned text-supplemented data belongs to structured data, which can be supplemented by a database. Taking the equipment label as the key, the rest of the keys can be derived, effectively reducing the programming pressure. The above-mentioned mapping is generated at runtime and has high real-time requirements. The method of storing the read data in the global variable in the host computer is adopted. Then the dynamic data node in the information model creates a pointer to the address of the global variable relative to it. When the global variable changes by reading the serial port data, the dynamic data node also changes because it points to the same storage space.

[0050] The above-mentioned data supplementing and binding method is implemented by using a self-developed demo based on the cross-platform software development framework QT programming, as shown in the attached Figure 2The information model creation framework includes an added type module, which encapsulates the object and variable types required when modeling the device; a node creation module, which creates corresponding variable, object, collection, method and event nodes according to the drawn information model; a data source binding module, which binds static variable nodes with data existing in the database, binds dynamic data nodes with data sources provided by the device, and binds method variable nodes with identifiers provided by the device; and a node tree module, which displays the created nodes, references and hierarchical relationships in a tree diagram, similar to the address space in UaExpert, and allows users to instantiate similar objects and variables by copying nodes in the node tree, thereby reducing the workload of creating nodes. Finally, a server creation module creates an address space, assigns a unique NoldId to the nodes, sets the NoldId as a keyword, saves the node tree in the form of a database, and saves the information model. When the software is opened subsequently, the database can be directly loaded to complete the rapid deployment of the server without creating the information model again.

[0051] Further, after the OPC UA server forms the address space, the OPC UA server can add monitoring, event, historical data and other functions based on the needs of the user. After starting the OPC UA server, any client with a server security policy can access the address space in the server, and then access the data in the information model through the nodes of the address space, so that the client can obtain the data and information of the device embedded in the host computer of the server, and realize the information communication between the master control and each device.

[0052] Finally, based on the interfaces provided to the client in the OPC UA protocol, such as reading and writing node values, subscribing to monitoring items, and calling functions, a system control interface is created in the master control computer based on QT, which includes functions such as visually viewing device information, changing the dynamic data of the underlying device, and encapsulating the methods of the underlying device into controls. At this point, the communication module between each device and the master control computer is completed.

[0053] Example 2

[0054] This embodiment takes a three-dimensional acceleration sensor assembly system as the main research object. The assembly system is mainly composed of a five-degree-of-freedom assembly robot, a six-axis collaborative robot, a nine-degree-of-freedom redundant assembly platform, a clamped part area industrial camera group (Vision A), a platform macro-micro combined industrial camera group (Vision B), and a slide rail. To achieve precise assembly, each module can be decomposed into multiple units. For example, the assembly robot can be divided into three linear motors, a rotary motor, and a domestic brand servo rotary motor for increased load, making up the five degrees of freedom of the assembly robot. The end of the assembly robot is a variety of constant force clamps developed in the laboratory, which are used to clamp different types of parts for assembly. During the replacement of the clamp and the clamped parts, two telecentric industrial cameras, Vision A, are used for visual servoing. The collaborative robot is a mature six-axis robot purchased, but to complete the collaborative function, a tool changing operation and a collision detection function are designed. The assembly platform is composed of a parallel mechanism, which can achieve small displacement, large pose, large angle, high precision motion, and uses a Beckhoff controller to control the nine input motors of the parallel mechanism. The assembly platform is also the place where the fixed parts and the clamped parts are assembled, and Vision B is used to provide visual guidance for the assembly process.

[0055] Firstly, the three-dimensional acceleration sensor assembly system has different members responsible for different modules during the development process. The assembly system executive mechanism can be divided into assembly platform module, collaborative robot module, assembly robot module, and the remaining simple mechanical structure, sensor and vision module embedded in the corresponding module as needed. Therefore, when the system is not integrated, it should include three independent host computer systems. When integrated, the modules need to be classified to prevent system data from being messy and redundant. Based on the different languages used for programming on the host computer of different module equipment and the different interfaces used for data collection, a distributed integration method is adopted, that is, an OPC UA server is embedded in the host computer developed by each member, and finally an OPC UA client is embedded in the general control computer to manage and monitor the three independent host computer servers.

[0056] Subsequently, to embed a server in the host computer, the first step is to create a corresponding information model. In this case, although the main executive mechanisms included in each module are different, they are essentially multi-input mechanical structures guided by the vision system. This case takes the assembly robot module as an example to show the drawing process of its information model diagram, and the rest is omitted.

[0057] For this module, it can be divided into three units, one is the five input five degree of freedom assembly robot, which is the core unit of this module. Use static data collection nodes to record and describe the manufacturer of the equipment, product model, key dimensions, workspace, working condition requirements, etc. Among them, the node variable of String type is used, which can input English and Chinese. Use dynamic data collection nodes to record data generated during equipment operation, such as motor feedback position, angle, speed, voltage, current, power information, and end mechanism position information calculated by the host computer. For a single variable, use Double type node variable to record its value. For multiple data variables such as coordinate information, use custom type node variable to describe, which can effectively reduce the number of nodes and reduce system load. Use method collection nodes to record the methods created in the host computer to call the equipment, create method nodes based on the input parameters required by the method. Use event set to record the state change of a component. Event class is the parent class of condition class, and condition class is the parent class of warning class. The created events will trigger warnings and events according to the conditions, which is the main measure to ensure the safe operation of the system.

[0058] With the creation of the information model, the OPC UA server can be created in the host computer. The method in case 1 is adopted to create specific nodes for the information model in the above figure and bind specific device data sources to the variables. After this step, the address space of the server can be obtained, which contains a unique node number for each node. The node can be accessed through the node number to read the node information. For users with modification authority, they can also change the node after accessing it. Finally, the security policy supported by the OPC UA protocol needs to be called, and base256; signature and certificate are used in this example. Create an account and password to complete the creation and start of the server in the host computer.

[0059] Finally, the OPC UA client in the total control computer needs to be created. The specific steps are as follows: first, add the custom type nodes in the three information models to the client code to avoid the problem of not being able to read and modify custom type variable nodes due to undefined types. Then, create internal index matching nodes in the information model, and then get the corresponding node number according to the node name. With the node number, you can access the object, variable, and method information stored in the address space. Not only can you display the information you need through the visual interface, but you can also bind the method node call to buttons or other event controls to facilitate user operation. The monitoring and method calling functions of the control system are realized.

[0060] To build a complete automatic control system, the following automatic assembly strategies are needed.

[0061] Firstly, before assembly, the sequence of parts assembly is needed. Assembly Sequence Planning (ASP) is an NP problem, using various methods and techniques to find the optimal assembly sequence, plays an important role in generating satisfactory assembly sequence for assembly process. With a large number of studies introducing group optimization algorithm into the optimization of practical engineering, such as ant colony algorithm, fruit fly optimization algorithm, particle swarm optimization algorithm, genetic algorithm, etc. It is proved that the optimal sequence of product assembly can be effectively given. But similar to this case, the sequence planning of multiple actuators operating in parallel is less studied, and the improved pollination algorithm is used for the micro-assembly system in this case. The algorithm calculation process is as follows:

[0062] (1) According to the assembly relationship given by the engineering modeling SolidWorks, the assembly relationship, constraint conditions can be extracted to express the assembly priority matrix, interference matrix, connection matrix and other initialization parameters in mathematical model, and then the initial population, that is, the assembly sequence, is obtained by the opposite learning method. The conversion probability p is affected by the number of iterations and is in the range of (0, 1).

[0063] (2) Calculate the fitness value of each population, and solve the current optimal solution and optimal value.

[0064] (3) Get a random number rand in the range of [0, 1], if p> rand, update the next generation according to the global pollination formula.

[0065] Because the formula will produce a decimal number, and it may be greater than the part number and the number is repeated, the generated new population number needs to be integerized and unique, which is called population repair.

[0066] (4) If p<rand, update the next generation according to the local pollination formula, and also perform population repair.

[0067] (5) Calculate the fitness value of the new population obtained in (3) or (4), if it is better than the current optimal fitness, replace the current optimal solution and optimal fitness.

[0068] (6) Judge the end condition, meet the output optimal solution and optimal fitness, otherwise go to (3).

[0069] Secondly, in the assembly, the closed loop assembly needs to be completed. After getting the address space provided by the client and the optimal assembly sequence in the first step, this example proposes an automatic assembly process based on steps, as shown in Figure 5 . First, according to the optimal assembly sequence, for the parts that need to be assembled, each step needs to save its called device operation method and parameter in the database during the first manual debugging, as well as its pre-step. Let the i-th step S i be a row vector, where: Si [1] represents step number, S i [2] represents execution module name, S i [3] represents operation to be executed, S i [4] represents current device state, S i [5,7...2n+1] represents preceding step number, S i [6,8,,,2n+2] represents preceding step state (may have multiple preceding steps), after virtual execution to automatically assemble the process, add a column S i [2n+3] represents the step order of the current automatic assembly process.

[0070] During assembly, first need to read the database, according to the process in the appendix Figure 5 Find the operation without preceding step to start creating thread, and execute these operations in parallel, such as S pre [3], these operations in the database are only English or Chinese identifiers, so the program also needs to find the corresponding method node number for these operations according to the internal table, so that the method node can be accessed in the control system, and then the method node is called to call the method function of the host computer where the server is located, and the host computer transmits the instruction to the device through the gateway to make the device move. If the device can accept the instruction, it will return the feedback data to identify the state of the device at this time, and the feedback data has created a monitoring item in the OPCUA server, which will notify the client of the change. After the client receives the state change notification, it will do subsequent processing according to the returned digital identifier, such as returning state 1, which represents that the device has successfully completed this operation and allows the execution of subsequent operations, and the identifier S[5,7,,,2n+1] of the same name as S pre [3] is also set to state 1, representing that the preceding step has been completed and there is no need to wait for the step; returning state 2, representing that the device has received the instruction and has moved, but cannot reach the preset position of the operation, and needs to adjust the parameters to make the device or the instruction; returning state 3, representing that the device has not moved, and a fault or warning is popped up to remind the operator to check the device problem. If the instruction cannot be accepted, the connection between the server and the client needs to be checked.

[0071] The above is the initial operation, the next operation needs to find the initial operation identifier in the preceding operation library, that is, to find S next [5,7,,,2n+1]=S pre [3], then find the next operation corresponding to this row, and start calling the method to execute S next[3] For the operation with multiple pre-operations, all pre-operations need to return the state allowing the subsequent operation before the execution can be started. The loop continues until the identification of the current operation cannot be found in the pre-operation library, which represents the end of the thread, the thread is closed, and the control system is notified of the assembly completion.

[0072] In the above assembly process, in addition to the state change, the device motion information, the start time and end time of each assembly step, the part information used in the assembly, and the quality of the operation completed can be monitored to provide overall monitoring for the assembly motion.

[0073] Finally, after completing multiple assemblies, the following analysis should be made for whether the assembly system is stable. First, during the assembly, the information of each motion unit of the device should be collected, because the place where the assembly action occurs is basically fixed on the assembly platform, and the motion data of each unit of the device should not have a large change, and the overall conforms to the normal distribution. The data is placed in a statistical chart for analysis. If it does not conform to the law, a warning information should be provided to prompt the staff that the device is not stable.

[0074] The above steps can realize the full-automatic assembly integration control method of the three-dimensional acceleration sensor. In addition to the three-dimensional acceleration sensor, for the small products with given assembly information, the automatic assembly flow can also be generated step by step through the assembly sequence planning, and the monitoring of the assembly process can be realized.

[0075] The above embodiments are the preferred embodiments of the present application, but the embodiments of the present application are not limited by the above embodiments, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application should be equivalent replacement methods, which are all included in the protection scope of the present application.

Claims

1. A design method for an integrated control framework for adaptive assembly of tiny parts, characterized by: The following steps are included: An OPC UA server is configured in the sub-host computer of each device in the micro-assembly equipment layer to identify the unstructured data generated by the equipment during the production process of the micro-parts assembly system, classify the data, and construct a corresponding OPC UA information model; Instantiate the information model of the equipment in the assembly system and configure it in the OPC UA server. Bind the assembly system equipment data to the corresponding nodes in the OPC UA information model to complete the mapping from the physical model to the data model. Use the OPC UA client to access the information model in the OPC UA server in the slave host computer. By querying the nodes in the information model, the data of the underlying equipment of the assembly system can be monitored in real time to understand the system operation status. Add assembly sequence planning, step-based automated assembly processes, and assembly quality monitoring methods to the control interface; Integrate the OPC UA client on the control interface of the master computer to display monitoring information in real time and predict equipment operation stability; Based on the scalability of OPC UA, the control interface in the master computer is integrated with the OPC UA aggregation server as a transit point for data transmission. Through the cross-platform compatibility of OPC UA, control systems under different platforms can be developed, or clients can be embedded in the digital twin to complete data transmission and reception.

2. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: Unstructured data includes the position and angle information of each axis in the five-degree-of-freedom assembly robot, collaborative robot arm and assembly platform, movement speed, motor temperature, images and sensor signals used for visual servoing and position detection, and voltage information of piezoelectric ceramics in the micro-motion platform.

3. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 2, characterized in that: The unstructured data of mechanical equipment is divided into static data sets and dynamic data sets. The static data sets store the inherent information of the equipment, including the manufacturer, product number, and equipment size; the dynamic data sets store the information that changes continuously during the production process of the equipment, including the equipment operation mode, power, and actuator operation status. The common data of the equipment are abstracted into classes, and then the classes are instantiated into objects according to actual requirements. The created objects are stored in the address space according to a specific structural hierarchy to generate an information model.

4. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: Building an OPC UA information model involves exposing the interface for collecting data from the device's sub-host computer directly to the corresponding node in the information model, completing the mapping of the device's physical data to the server's information model data. The data is bound to the nodes of the information model in real time, facilitating subsequent subscription and reading and writing by clients and aggregation servers.

5. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: Real-time monitoring of the underlying device data of the assembly system involves embedding the OPC UA client in the control interface of the integrated system written in the master computer, connecting to the OPC UA servers of all underlying devices, thereby obtaining the physical data information exposed by each device through the information model, placing the information to be monitored on the control interface, and completing the monitoring of the entire assembly system. The data of each device is finally integrated into the master computer to achieve interconnection and interoperability between devices.

6. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: The assembly sequence planning algorithm developed by the control interface is an improved flower pollination algorithm. According to the requirements of sequence planning, the assembly relationship parameters of the products to be assembled are selected as parameters in the solution process. The minimum cost is obtained through iteration, and the corresponding sequence is the optimal assembly sequence.

7. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: The assembly relationship parameters of the product to be assembled include the priority relationship between parts, stability, assembly direction and tool change, and the cost includes the assembly time, connection stability, direction and number of tool changes.

8. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: Predicting equipment stability involves the OPC UA client collecting historical data over a period of time into a database to form a training set. After training, the real-time collected data is put into a BP neural network for calculation to predict the stability of the equipment in operation.

9. The method for designing an integrated control framework for adaptive assembly of micro parts according to claim 1, characterized in that: As an extension of the control system, a digital twin is created for virtual assembly simulation, verifying the rationality of the assembly sequence, assembly path planning, and motion interference planning results, and providing guidance for assembly work. The integrated control framework is production-oriented and integrated with the existing MES system to provide the data required for product quality management, material management, and production process management.

10. An integrated control framework for adaptive assembly of tiny parts, characterized by: include Micro-assembly equipment layer: including micro-assembly robot module, micro-assembly platform module, and micro-assembly collaborative robot module. Each module is equipped with equipment, and each equipment is equipped with a corresponding sub-host computer; Data transmission layer: includes OPC UA servers and clients configured for each sub-host computer. It is used to implement communication between each sub-host computer and the main host computer using the OPC UA communication protocol. It determines the unstructured data generated by the equipment in the small parts assembly system during the production process, classifies the data and constructs the corresponding OPC UA information model. It instantiates the information model for the corresponding equipment in the assembly system and configures it in the OPC UA server. It binds the assembly system equipment data to the corresponding nodes in the OPC UA information model to complete the mapping from the physical model to the data model. The OPC UA client is used to access the information model in the OPC UA server in the sub-host computer. By querying the nodes in the information model, the underlying equipment data of the assembly system can be monitored in real time. Control system layer: includes a master computer compatible with each module of the micro-assembly equipment layer, used to monitor the equipment in each module to achieve assembly sequence planning, automatic assembly process generation, assembly process monitoring, fault detection, data storage and analysis, and predict the stability of the equipment during operation; Digital twin layer: This layer includes an aggregation server connected to the main host computer. Through the cross-platform compatibility of OPC UA, control systems for different platforms can be developed, or clients can be embedded in the digital twin to complete data transmission and reception.

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