WO2022041809A1 - 一种多规格船用管材智能成形车间及控制方法 - Google Patents

一种多规格船用管材智能成形车间及控制方法 Download PDF

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Publication number
WO2022041809A1
WO2022041809A1 PCT/CN2021/089551 CN2021089551W WO2022041809A1 WO 2022041809 A1 WO2022041809 A1 WO 2022041809A1 CN 2021089551 W CN2021089551 W CN 2021089551W WO 2022041809 A1 WO2022041809 A1 WO 2022041809A1
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processing
equipment
pipe
area
module
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French (fr)
Inventor
唐文献
王为民
林洪才
张建
苏世杰
杭世峰
陶志高
王月阳
郭胜
林剑波
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JIANGSU HEFENG MECHANICAL MAKING CO Ltd
Zhenjiang Yucheng Intelligent Equipment Technology Co Ltd
Jiangsu University of Science and Technology
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JIANGSU HEFENG MECHANICAL MAKING CO Ltd
Zhenjiang Yucheng Intelligent Equipment Technology Co Ltd
Jiangsu University of Science and Technology
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device
    • G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
    • G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • the invention relates to an intelligent forming workshop and a control method for multi-specification marine pipes, belonging to the field of pipe processing.
  • the intelligent workshop is to realize the interconnection and intercommunication of automation equipment (production equipment, testing equipment, transportation equipment, manipulators, etc.) through the network and software management system to achieve the perception state (production demand, equipment, production process and other information), real-time data analysis, so as to achieve A workshop for self-organized production with automatic decision-making and precise execution of orders; in the process of shipbuilding, pipe manufacturing is an important link in the shipyard's production organization.
  • automation equipment production equipment, testing equipment, transportation equipment, manipulators, etc.
  • the intelligent workshop is to realize the interconnection and intercommunication of automation equipment (production equipment, testing equipment, transportation equipment, manipulators, etc.) through the network and software management system to achieve the perception state (production demand, equipment, production process and other information), real-time data analysis, so as to achieve A workshop for self-organized production with automatic decision-making and precise execution of orders; in the process of shipbuilding, pipe manufacturing is an important link in the shipyard's production organization.
  • the use of steel ship pipes is huge, and the number of pipes used in a 200,000-t
  • the nominal diameter of the seam steel pipe is 10-300mm, and the wall thickness is 2-8mm; the nominal diameter of the welded steel pipe is 10-140mm, and the wall thickness is 0.5-5.5mm; the nominal diameter of the low-pressure fluid conveying pipe is 15-150mm, The wall thickness is 2.75 ⁇ 4.5mm; the outer diameter of the aluminum tube is 6 ⁇ 50mm, and the wall thickness is 0.5 ⁇ 5mm; the outer diameter of the bimetal tube is 6 ⁇ 70mm, and the wall thickness is 1.5 ⁇ 6mm.
  • marine pipes have the characteristics of many forming sizes and specifications, a wide range of wall thicknesses, many varieties of materials and large differences in materials.
  • the active marine pipe forming workshop lacks the necessary workshop fault monitoring system and processing method.
  • maintenance personnel need to spend a lot of time to confirm the cause of the fault and carry out maintenance, which in turn affects the processing progress of the workshop.
  • the fault detection method of micro-inverter based on neural network expert system described in patent ZL103293415B describes the fault detection method of micro-inverter through neural network expert system, but this method lacks the detailed construction process of neural network expert system .
  • the invention provides a multi-specification marine pipe intelligent forming workshop and a control method, which can formulate an optimal scheduling strategy according to orders and perform fault monitoring on the entire workshop, which is beneficial to the information management of the multi-specification marine pipe intelligent forming workshop.
  • An intelligent forming workshop for multi-specification marine pipes includes a pre-treatment processing area and a processing station area arranged in sequence on a production line, a raw material storage area is arranged upstream of the production line, and a side of the production line is arranged for storing semi-finished pipes and pipes. Storage area for finished products and flanges;
  • the intelligent control system sends control signals to the raw material storage area, pretreatment processing area and processing station area to realize the retrieval and processing of multi-specification pipes.
  • the intelligent control system sends control signals to the transportation system at the same time. , to realize the transportation and transshipment of multi-specification pipes on the transportation line;
  • the aforementioned raw material storage area is provided with a raw material storage area for classifying and storing multi-specification pipes, which realizes the transportation of raw materials by driving;
  • the aforementioned intelligent control system includes an interconnected master control system, MES system, shared cloud and monitoring system, and the master control system controls the MES system, shared cloud and monitoring system with instructions;
  • the total control system includes an analysis and calculation module, an instruction sending module and a condition judgment module, wherein the analysis and calculation module obtains signals from the raw material storage area, pre-processing processing area, processing station area and transportation system for analysis, and the instruction sending module will receive The received signal is sent to the analysis and calculation module, and the execution instruction is sent to the raw material storage area, the pre-processing processing area, the processing station area and the transportation system, and the condition judgment module judges the product quality;
  • the MES system includes a production scheduling module, a data acquisition module, a quality management module, a warehouse management module, an order management module and an equipment management module.
  • the production scheduling module is used to schedule the production procedures in the workshop, and the data acquisition module is used to The internal production information is collected, the quality management module is used to manage the quality of the products, the warehouse management module is used to manage the raw material storage area and warehousing system in the workshop, the order module is used to manage the product order information, and the equipment management module is used. Used to manage the equipment in the workshop;
  • the shared cloud includes an RFID information storage module, a processing data storage module, an equipment monitoring data storage module, and a load capacity data storage module.
  • the RFID information storage module is used to store RFID scanning information
  • the processing data storage module is used to store processing data in the workshop.
  • the data is stored
  • the equipment monitoring data storage module is used to store the equipment monitoring data in the workshop
  • the load data storage module is used to store the load data in the workshop;
  • the monitoring system is used to monitor various parts in the workshop;
  • the aforementioned pretreatment processing area includes a feeding conveyor line, a first straightening device, a second straightening device, a first cutting device, a second cutting device, a first testing device, and a second testing device.
  • temporary storage area for semi-finished products and the first unqualified storage area in which the feeding conveyor line is located upstream of the production line, and the first straightening equipment, the first cutting equipment and the first testing equipment are sequentially arranged on one side of the production line, and the other side of the production line is arranged.
  • a second straightening device, a second cutting device and a second testing device are arranged in sequence on one side, the first straightening device and the second straightening device, the first cutting device and the second cutting device, the first testing device and the second
  • the testing equipment is arranged symmetrically, and also includes a first manipulator, which picks and transfers the tested products to the temporary storage area for semi-finished products, and the first manipulator picks and transfers the unqualified products after testing to the first unqualified storage area;
  • the aforementioned storage system includes a tray storage area, a first RFID scanner, a flange storage area, a storage area for semi-finished pipes and a storage area for finished pipes, and several trays are placed in the tray storage area.
  • the RFID scanner is used to scan and record the information of the material tray.
  • a first buffer area is set at the entrance of the flange storage area
  • a second buffer area is set at the entrance of the semi-finished pipe storage area
  • a second buffer area is set at the entrance of the finished pipe storage area.
  • the transportation system transports the material tray to the corresponding buffer area, and the transportation system transports the corresponding products in the flange storage area, the semi-finished pipe storage area and the finished pipe storage area to the corresponding buffer area, in the first buffer area.
  • a first pipe grabbing device is provided, which grabs and places the flange in the material tray located in the first buffer area, and a second pipe grabber device is installed in the second buffer area, which grabs and places the semi-finished pipe material in the second buffer area.
  • a third pipe grabbing device is arranged in the third buffer area, which grabs the finished pipe material and places it in the material tray of the third buffer area;
  • the aforementioned processing station area includes a bending processing area, a beveling processing area, a shrinking or flaring processing area, a welding processing area and a two-dimensional code spraying area, and a second RFID scanner is also installed.
  • the trays with products are scanned by the second RFID scanner and distributed to various areas in the processing station area through the transportation system;
  • the bending processing area includes the first pipe bending equipment, the second pipe bending equipment, the first processing buffer area and the first unqualified storage area.
  • the transportation system transports the qualified products from the matching area to the first processing buffer area, and the second manipulator transports the products to the first processing buffer area.
  • the unqualified products after the bending treatment are clamped and placed in the second unqualified storage area;
  • the groove processing area includes the first groove equipment, the second groove equipment, the second processing buffer area and the second unqualified storage area.
  • the transportation system transports the qualified products from the matching area to the second processing buffer area, and the third manipulator will After the product is clamped from the second processing buffer area to the first beveling equipment and the second beveling equipment for beveling treatment, the unqualified products after beveling treatment are clamped and placed in the third unqualified storage area;
  • the shrinking or flaring processing area includes the first shrinking or flaring equipment, the second shrinking or flaring equipment, the third processing buffer area and the third unqualified storage area.
  • the matching area transports qualified products from the storage system to the third processing buffer.
  • the fourth manipulator clamps the product from the third processing buffer area to the first shrinking or flaring equipment, the second shrinking or flaring equipment for shrinking or flaring processing, and then the unqualified shrinking or flaring The product is clamped and sent to the fourth unqualified storage area;
  • the welding processing area includes the first welding equipment, the second welding equipment, the fourth processing buffer area and the fourth unqualified storage area.
  • the transportation system transports the qualified products from the matching area to the fourth processing buffer area, and the fifth robot moves the products from the first processing buffer area.
  • the fourth processing buffer area is clamped to the first welding equipment and the second welding equipment for welding processing, and then the unqualified products are clamped and sent to the fifth unqualified storage area;
  • the two-dimensional code spraying area includes the first two-dimensional code spraying equipment, the second two-dimensional code spraying equipment and the fifth processing buffer area.
  • the transportation system transports the qualified products from the matching area to the fifth processing buffer area, and the sixth manipulator transports the products from the matching area to the fifth processing buffer area.
  • the fifth processing buffer area is clamped to the first two-dimensional code spraying equipment and the second two-dimensional code spraying equipment for spraying processing;
  • the aforementioned transportation system includes a first AGV trolley and a second AGV trolley, and a charging area for charging the first AGV trolley and the second AGV trolley is also installed;
  • a laser displacement sensor is installed on the first detection device and the second detection device, and an angle sensor, a torque sensor and a first scanner are installed on the first pipe bending equipment and the second pipe bending equipment.
  • a second scanner, a pressure sensor and a displacement sensor are installed on a shrinking or flaring device and a second shrinking or flaring device, and a speed sensor, a third scanner and a surface are installed on the first beveling device and the second beveling device Roughness tester, install voltage sensor, current sensor and ultrasonic non-destructive flaw detector on the first welding equipment and the second welding equipment;
  • the scheduling method specifically includes the following steps:
  • Step 1 The workshop receives the order
  • Step 1.1 the multi-specification marine pipe intelligent forming workshop receives the nth batch of pipe processing orders, where n ⁇ 2, the content of the pipe processing order includes the orderer, delivery date, required pipe specifications, processing procedures, and welding flange information and the required quantity;
  • Step 1.2 the warehouse management module obtains the address stored in the RFID chip of the vacant tray in the storage system through the first RFID scanner;
  • Step 1.3 the order management module generates the processing technology file of each pipe according to the order content received by the workshop, and writes the processing technology file into the obtained storage address;
  • Step 2 Obtain workshop status information
  • the equipment management module obtains the status of each processing equipment in the workshop, including equipment type, equipment performance, current working status of equipment and current load of equipment;
  • Step 3 Schedule the order content according to the status of the processing equipment
  • Step 3.1 determine the time required to process the content of the order, the master control system obtains the types of pipe specifications processed by the order through the order management module, and the analysis and calculation module calculates the processing time required for all types of pipes to complete all processes;
  • Step 3.2 Determine the waiting time for processing of the nth batch of orders, and the analysis and calculation module calculates the time required to complete the processing of all types of pipes in the order;
  • Step 3.3 Determine the transportation time of the pipe.
  • the general control system obtains the load information of the processing equipment for different specifications of pipes from the load data storage module according to the pipe specifications, and the analysis and calculation module calculates the transportation distance between each processing equipment and the storage, all the The number of times of transportation and the transportation time required for each specification of pipe, and finally the transportation time required for all types of pipes in the order;
  • Step 3.4 determine the total time required to complete the order processing
  • Step 3.5 Determine the optimal scheduling strategy.
  • the production scheduling module specifies several different production scheduling plans, calculates the total processing time of different production scheduling plans, and uses the intelligent scheduling algorithm to complete the total processing time required for different production scheduling plans. Carry out optimization to obtain the production scheduling plan with the shortest total processing time, and send the optimal scheduling strategy to the master control system;
  • Step 4 Transportation of semi-finished pipes
  • Step 4.1 the command sending module sends a transportation command to the first AGV car and the second AGV car, and the first AGV car and the second AGV car feed back their status information, which includes the transportation status and power information;
  • Step 4.2 the analysis and calculation module selects the first AGV car or the second AGV car according to the feedback status information
  • Step 4.3 in the storage system, the transportation system inside the semi-finished pipe storage area transports the required semi-finished pipe to the second buffer area, while the first AGV or the second AGV trolley transports the material tray to the second buffer area.
  • the second pipe grabbing device grabs the semi-finished pipe and puts it into the tray, and the first AGV trolley or the second AGV trolley transports the semi-finished pipe to the processing station area;
  • Step 5 Semi-finished pipe processing
  • Step 5.1 the first RFID scanner scans and obtains the RFID chip on the material tray, and the second RFID scanner accesses the pipe processing information through the storage address of the RFID chip, including the pipe forming process and forming requirements;
  • the analysis and calculation module selects the groove processing area, bending processing area, shrinking or flaring processing area or welding processing area, the first AGV trolley or the second AGV in the processing station area according to the obtained pipe processing process sequence.
  • the trolley transports the material tray to the first processing buffer area or the second processing buffer area or the third processing buffer area or the fourth processing buffer area;
  • the instruction sending module sends the corresponding processing instructions, and controls the relevant processing equipment to complete the processing of the pipe.
  • the data acquisition module collects processing data and processing equipment monitoring data through the sensing devices installed on each equipment. , respectively stored in the processing data storage module and the equipment monitoring data storage module;
  • the quality management module accesses the shared cloud according to the pipe specification information, obtains the pipe processing data, analyzes the data, completes the online quality inspection of the pipe, and transmits the results to the general control system; the condition judgment module judges the product quality: If the product quality is qualified, the first or second or third or fourth manipulator grabs the pipe and places it in the relevant processing buffer area; if the product quality is unqualified, the first or second or third or third manipulator or the third The four manipulators grab the pipe and place it in the second unqualified storage area or the third unqualified storage area or the fourth unqualified storage area or the fifth unqualified storage area;
  • step 5.5 the condition judgment module makes the following judgment: Is the required processing procedure of the pipe completed? If not completed, perform steps 5.1 to 5.5; if completed, perform step 5.6;
  • step 5.6 the condition judgment module makes the following judgment: Is the order completed? If the order is not completed, perform steps 4 to 5; if the order is completed, perform step 6;
  • step 6.1 the first AGV trolley or the second AGV trolley transports the trays storing qualified products to the fifth processing buffer area;
  • step 6.2 the first QR code spraying equipment or the second QR code spraying equipment accesses the shared cloud according to the pipe specification information, obtains the pipe information, and generates the corresponding QR code;
  • step 6.3 the instruction sending module sends the two-dimensional code spraying instruction, and controls the sixth manipulator to grab the pipe and place it on the first two-dimensional code spraying equipment or the second two-dimensional code spraying equipment to complete the spraying operation; Place the pipe in the tray;
  • step 6.4 the condition judgment module makes the following judgment: Is the coding operation of all pipes completed? If not completed, perform steps 6.1 to 6.4; if completed, perform step 7;
  • Step 7 Qualified products are put into storage
  • Step 7.1 the command sending module sends a transport command to the first AGV or the second AGV, and the first AGV or the second AGV feeds back its status information, including the transport status and power information;
  • Step 7.2 the analysis and calculation module selects the appropriate AGV car according to the status information fed back by the first AGV car or the second AGV car;
  • step 7.3 the first AGV trolley or the second AGV trolley transports the material tray to the third buffer area, and the third pipe grabbing device transfers the finished pipe material to the specific material tray in the finished pipe storage area to complete the storage;
  • the eighth step the warehouse management module judges whether the semi-finished pipe storage area needs to be replenished, if necessary, execute the ninth to eleventh steps; otherwise, execute the twelfth step;
  • the ninth step the transportation of pipe raw materials
  • step 9.1 the warehouse management module produces supplementary documents according to the specifications of the missing pipe semi-finished products, including the specifications and quantities of the required pipe semi-finished products;
  • step 9.2 the instruction sending module sends a reclaiming signal, and the cranes in the raw material storage area take out the corresponding pipe raw materials from the raw material storage area and place them on the feeding conveyor line;
  • Step 10 Pipe raw material processing
  • Step 10.1 the analysis and calculation module selects the processing equipment, namely the first straightening equipment or the second straightening equipment or the first cutting equipment or the second cutting equipment or the first testing equipment or the second testing equipment, and sends the instruction
  • the module sends raw material processing instructions and controls it to complete the processing of pipe raw materials;
  • the data acquisition module collects relevant process processing data and relevant processing equipment monitoring data through the sensing devices arranged on each equipment, and stores them in the processing.
  • the quality management module accesses the shared cloud according to the pipe specification information, obtains the pipe processing data, processes the data, performs online quality inspection on the pipe, and transmits the results to the general control system; the condition judgment module judges the product quality: If the product quality is qualified, the first manipulator grabs the semi-finished pipe and places it in the semi-finished product temporary storage area; if the product quality is unqualified, the first manipulator grabs the semi-finished pipe and places it in the first unqualified storage area;
  • step 10.3 the condition judgment module makes the following judgment: Is the replenishment order completed? If the order is not completed, perform steps 9 to 10; if the order is completed, perform step 13;
  • Step 11.1 the command sending module sends a transport command to the first AGV or the second AGV, and the first AGV or the second AGV feeds back its status information, including the transport status and power information;
  • Step 11.2 the analysis and calculation module selects the appropriate AGV car according to the status information fed back by the first AGV car or the second AGV car;
  • step 11.3 the first AGV car or the second AGV car transports the material tray to the third buffer area, and the third pipe grabbing device transfers the semi-finished pipe to the specific material tray in the semi-finished pipe storage area, and completes the storage;
  • step 12.1 the warehouse management module determines whether the flange storage area needs to be replenished? If the material needs to be replenished, an alarm will be issued to remind the management personnel to load the material; otherwise, go to step 12.2;
  • step 12.2 the warehouse management module determines whether the raw material storage area needs to be replenished? If the material needs to be replenished, an alarm will be issued to remind the management personnel to load the material; otherwise, the thirteenth step will be executed;
  • the thirteenth step the master control system judges whether a new order is generated: if a new order is generated, execute the first to the thirteenth steps; if no new order is generated, end;
  • the fault detection method specifically includes the following steps:
  • Step a build the database
  • a fault database is constructed.
  • the database contains known possible fault types and corresponding fault manifestations;
  • Step b build a convolutional neural network expert system
  • Step d analyze and process the data collected in step c through the constructed convolutional neural network expert system
  • the monitoring system accesses the fault database according to the output result ⁇ i of the convolutional neural network expert system; if the corresponding fault is queried in the fault database, it will send the fault to the fault display module for display, which is used to guide maintenance workers to maintain and start the standby equipment ; If the corresponding fault is not queried in the database, perform step f;
  • Step f database update
  • the expert judges the fault and the corresponding fault's manifestation. If the fault and the corresponding fault's manifestation match, the fault and the corresponding fault's manifestation will be included in the database, and the fault will be sent to the fault display module for display to guide maintenance. Workers repair and start the standby equipment; at the same time, the convolutional neural network expert system is updated; if the manifestation of the fault and the corresponding fault do not match, the fault corresponding to the corresponding manifestation will be obtained according to the experience of the experts, and incorporated into the database, and the volume will be updated at the same time. Integrated neural network expert system.
  • the present invention has the following beneficial effects:
  • the multi-specification marine pipe intelligent forming workshop of the present invention can formulate different scheduling schemes according to the pipe processing orders and take the delivery date as the deadline, and use intelligent scheduling algorithms (such as genetic algorithms) to carry out each scheme.
  • intelligent scheduling algorithms such as genetic algorithms
  • the convolutional neural network expert system of the present invention analyzes and processes the detection data of each equipment in the intelligent forming workshop, and compares the analysis results with the fault database to obtain intelligent
  • the failure type of each equipment in the forming workshop is used to guide the maintenance operation of the relevant personnel, and at the same time, the backup equipment is activated to reduce the impact of equipment failure on the processing progress.
  • the convolutional neural network expert system has the function of continuous self-learning and updating, and improves the database to improve the accuracy of its detection, and at the same time, it can reduce the difficulty of troubleshooting for maintenance personnel, thereby saving a lot of time;
  • the data generated in the processing process is collected by each sensing device arranged at each equipment, and stored in the shared cloud, which is conducive to the information integration of the enterprise, realizes the information management of the workshop, and improves the management and control ability of the enterprise.
  • Fig. 1 is the layout diagram of the intelligent forming workshop of multi-specification marine pipes according to the preferred embodiment provided by the present invention
  • Fig. 2 is the intelligent scheduling flow chart of the multi-specification marine pipe intelligent forming workshop of the preferred embodiment provided by the present invention
  • Fig. 3 is the intelligent processing process control and data acquisition diagram of the multi-specification marine pipe of the preferred embodiment provided by the present invention
  • Fig. 4 shows the fault types and manifestations of the multi-specification marine pipe intelligent forming workshop according to the preferred embodiment of the present invention.
  • 2 is the intelligent control system
  • 20 is the general control system
  • 201 is the analysis and calculation module
  • 202 is the instruction sending module
  • 203 is the condition judgment module
  • 21 is the MES system
  • 211 is the production scheduling module
  • 212 is the data Acquisition module
  • 213 is quality management module
  • 214 is warehouse management module
  • 215 is order management module
  • 216 is equipment management module
  • 22 is shared cloud
  • 221 is RFID information storage module
  • 222 is processing data storage module
  • 223 is equipment monitoring Data storage module
  • 224 is the load data storage module
  • 23 is the monitoring system;
  • 3 is the pre-processing area
  • 30 is the feeding and conveying line
  • 31 is the first straightening equipment
  • 32 is the first cutting equipment
  • 33 is the first testing equipment
  • 34 is the first manipulator
  • 35 It is the temporary storage area for semi-finished products
  • 36 is the first unqualified storage area
  • 37 is the second straightening equipment
  • 38 is the second cutting equipment
  • 39 is the second testing equipment
  • 4 is the transportation system, 40 is the first AGV trolley, 41 is the second AGV trolley, and 42 is the charging area;
  • 5 is the storage system
  • 50 is the flange storage area
  • 51 is the semi-finished pipe storage area
  • 52 is the finished pipe storage area
  • 53 is the first buffer area
  • 54 is the second buffer area
  • 55 is the third buffer area 56 is the first RFID scanner
  • 57 is the first pipe grabbing device
  • 58 is the second pipe grabbing device
  • 59 is the third pipe grabbing device
  • 510 is the material tray storage area
  • 511 is the material tray;
  • 6 is the processing station area
  • 60 is the bending processing area
  • 601 is the first pipe bending equipment
  • 602 is the second pipe bending equipment
  • 603 is the first processing buffer area
  • 604 is the second unqualified area.
  • Storage area 605 is the second manipulator
  • 61 is the beveling processing area
  • 611 is the first beveling equipment
  • 612 is the second beveling equipment
  • 613 is the second processing buffer area
  • 614 is the third unqualified storage area
  • 615 It is the third manipulator
  • 62 is the shrinking or flaring processing area
  • 621 is the first shrinking or flaring equipment
  • 622 is the second shrinking or flaring equipment
  • 623 is the third processing buffer area
  • 624 is the fourth unqualified storage area
  • 625 is the fourth manipulator
  • 63 is the welding processing area
  • 631 is the first welding equipment
  • 632 is the second welding equipment
  • 633 is the fourth processing buffer area
  • 634 is the fifth unqualified storage area
  • 635
  • 701 is a laser displacement sensor
  • 702 is a torque sensor
  • 703 is an angle sensor
  • 704 is a first scanner
  • 705 is a second scanner
  • 706 is a pressure sensor
  • 707 is a displacement sensor
  • 708 is a speed sensor
  • 709 is a third scan 710 is a surface roughness meter
  • 711 is a voltage sensor
  • 712 is a current sensor
  • 713 is an ultrasonic nondestructive flaw detector.
  • the marine pipe forming workshop has several problems as pointed out in the background art. For example, it is not suitable for the marine pipe forming workshop with many types of pipes and various forming processes. It takes a lot of time to find the cause of the failure, and the lack of In order to overcome the above problems, the relevant data collection of the processing process and the effective management of information, the present application proposes an intelligent forming workshop for multi-specification marine pipes.
  • Figure 1 shows the specific structure of a multi-specification marine pipe intelligent forming workshop provided by this application. It can be clearly seen from the figure that it specifically includes the following parts: raw material storage area 1, pre-processing Jianggan area, storage area System 5 and processing station area 6, the control part of the whole workshop is the intelligent control system 2, the transportation channel of the whole workshop is the transportation system 4, the intelligent control system controls the whole workshop, and realizes the straightening, cutting and bending of multi-specification pipes. Forming, pipe end forming, end flange welding, two-dimensional code spraying, and the delivery and storage of pipe blanks, semi-finished products, and finished products, etc., through the transportation system to transport the products required in each area;
  • the raw material storage area is provided with a raw material storage area for classifying and storing multi-specification pipes, which realizes the transportation of raw materials by traveling 11.
  • the multi-specification pipes are classified according to their materials and specifications (pipe diameter ⁇ wall thickness);
  • the intelligent control system includes a master control system 20, an MES system 21, a shared cloud 22 and a monitoring system 23 that are connected to each other, and the master control system performs instruction regulation on the MES system, the shared cloud and the monitoring system;
  • the total control system includes an analysis and calculation module 201, an instruction sending module 202, and a condition judgment module 203, wherein the analysis and calculation module obtains signals from the raw material storage area, the pre-processing processing area 3, the processing station area and the transportation system for analysis, and the instruction
  • the sending module sends the received signal to the analysis and calculation module, and at the same time sends the execution instruction to the raw material storage area, the pre-processing processing area, the processing station area and the transportation system, and the condition judgment module judges the product quality;
  • the MES system includes a production scheduling module 211, a data acquisition module 212, a quality management module 213, a warehouse management module 214, an order management module 215, and an equipment management module 216.
  • the production scheduling module is used to schedule the production procedures in the workshop, and the data
  • the collection module is used to collect production information in the workshop
  • the quality management module is used to manage the quality of products
  • the warehouse management module is used to manage the raw material storage area and storage system in the workshop
  • the order module is used to manage product order information.
  • the equipment management module is used to manage the equipment in the workshop;
  • the shared cloud includes an RFID information storage module 221, a processing data storage module 222, an equipment monitoring data storage module 223, and a load data storage module 224, wherein the RFID information storage module is used for storing RFID scanning information, and the processing data storage module is used for The processing data in the workshop is stored, the equipment monitoring data storage module is used to store the equipment monitoring data in the workshop, and the load data storage module is used to store the load data in the workshop;
  • the monitoring system is used to monitor various parts in the workshop;
  • the pre-processing area includes a feeding conveyor line 30, a first straightening device 31, a second straightening device 37, a first cutting device 32, a second cutting device 38, a first testing device 33, a second testing device 39, and semi-finished products.
  • a second straightening device, a second cutting device and a second testing device are arranged in sequence on one side, the first straightening device and the second straightening device, the first cutting device and the second cutting device, the first testing device and the second
  • the inspection equipment is symmetrically arranged, and also includes a first manipulator 34, which clamps and transfers the inspected products to the temporary storage area for semi-finished products, and the first manipulator clamps and transfers the inspected unqualified products to the first unqualified storage area. ;
  • the storage system includes a tray storage area 510, a first RFID scanner 56, a flange storage area 50, a semi-finished pipe storage area 51, and a pipe finished storage area 52.
  • Several trays 511 are placed in the tray storage area, and the first RFID scanner It is used to scan and record the information of the material tray.
  • the first buffer area 53 is set at the entrance of the flange storage area
  • the second buffer area 54 is set at the entrance of the semi-finished pipe storage area
  • the second buffer area 54 is set at the entrance of the finished pipe storage area.
  • the transportation system transports the material trays to the corresponding buffer areas, while the transportation system transports the corresponding products in the flange storage area, the semi-finished pipe storage area and the finished pipe storage area to the corresponding buffer areas, in the first buffer area.
  • a first pipe grabbing device 57 is provided, which grabs and places the flange in the tray located in the first buffer area, and a second pipe grabbing device 58 is installed in the second buffer area, which grabs and places the semi-finished pipe in the second buffer area.
  • a third pipe grabbing device 59 is arranged in the third buffer area, which grabs the finished pipe material and places it in the material tray of the third buffer area;
  • the processing station area includes a bending processing area 60, a beveling processing area 61, a shrinking or flaring processing area 62, a welding processing area 63 and a two-dimensional code spraying area 65, and a second RFID scanner 64 is also installed. After being scanned by the second RFID scanner, the material tray is distributed to each area in the processing station area through the transportation system;
  • the bending processing area includes a first bending pipe equipment 601, a second pipe bending equipment 602, a first processing buffer area 603 and a first unqualified storage area.
  • the transportation system transports qualified products from the matching area to the first processing buffer area, and the second processing buffer area.
  • the manipulator 605 clamps the products from the first processing buffer area to the first pipe bending equipment and the second pipe bending equipment for bending processing, and then clamps the unqualified products after bending and places them in the second unqualified storage area 604 Inside;
  • the beveling processing area includes the first beveling equipment 611, the second beveling equipment 612, the second processing buffer area 613 and the second unqualified storage area.
  • the transportation system transports the qualified products from the matching area to the second processing buffer area.
  • the three manipulators 615 clamp the products from the second processing buffer area to the first beveling equipment and the second beveling equipment for beveling treatment, and then pick and place the unqualified products after beveling treatment to the third unqualified product. in storage area 614;
  • the shrinking or flaring processing area 621 includes a first shrinking or flaring equipment, a second shrinking or flaring equipment 622, a third processing buffer area 623, and a third unqualified storage area, and the transportation system transports the qualified products from the matching area to the first.
  • the third processing buffer area, the fourth manipulator 625 clamps the product from the third processing buffer area to the first shrinking or flaring equipment and the second shrinking or flaring equipment for shrinking or flaring processing, and then shrinking or flaring The subsequent unqualified products are clamped and sent to the fourth unqualified storage area 624;
  • the welding processing area includes a first welding equipment 631, a second welding equipment 632, a fourth processing buffer area 633 and a fourth unqualified storage area.
  • the transportation system transports qualified products from the matching area to the fourth processing buffer area, and the fifth robot arm 635 After clamping the products from the fourth processing buffer area to the first welding equipment and the second welding equipment for welding processing, the unqualified products are then clamped and sent to the fifth unqualified storage area 634;
  • the two-dimensional code spraying area includes the first two-dimensional code spraying equipment 651, the second two-dimensional code spraying equipment 652 and the fifth processing buffer area 653.
  • the transportation system transports qualified products from the matching area to the fifth processing buffer area, and the sixth manipulator 654 Clip the product from the fifth processing buffer area to the first two-dimensional code spraying equipment and the second two-dimensional code spraying equipment for spraying processing;
  • qualified products are delivered to the designated area through the transportation system.
  • the matching area here is not only from the storage system, but also from other processing areas, such as the groove processing area, shrinkage area in the processing station area. Or flare processing area and welding processing area.
  • the transportation system includes a first AGV trolley 40 and a second AGV trolley 41, and a charging area 42 for charging the first AGV trolley and the second AGV trolley is also installed;
  • a laser displacement sensor 701 is installed on the first inspection device and the second inspection device, an angle sensor 703, a torque sensor 702 and a first scanner 704 are installed on the first bending device and the second bending device, and the first bending or A second scanner 705, a pressure sensor 706 and a displacement sensor 707 are installed on the flaring equipment and the second shrinking or flaring equipment, and a speed sensor 708 and a third scanner 709 are installed on the first and second beveling equipment
  • a voltage sensor 711, a current sensor 712 and an ultrasonic nondestructive flaw detector 713 are installed on the first welding equipment and the second welding equipment, which can realize the collection and integration of processing data of each equipment during the pipe processing process.
  • FIG. 2 and Fig. 3 show the usage of the multi-specification marine pipe intelligent forming workshop provided by this application.
  • Fig. 2 is a method of using it for intelligent scheduling
  • Fig. 3 is a schematic diagram of using it for control and data collection. specific
  • the scheduling method specifically includes the following steps:
  • Step 1 The workshop receives the order
  • Step 1.1 the multi-specification marine pipe intelligent forming workshop receives the nth batch of pipe processing orders, where n ⁇ 2, the content of the pipe processing order includes the orderer, delivery date, required pipe specifications, processing procedures, and welding flange information and the required quantity, etc.;
  • Step 1.2 the warehouse management module obtains the address stored in the RFID chip of the vacant tray in the storage system through the first RFID scanner;
  • Step 1.3 the order management module generates the processing technology file of each pipe according to the order content received by the workshop, and writes the processing technology file into the obtained storage address;
  • Step 2 Obtain workshop status information
  • the equipment management module obtains the status of each processing equipment in the workshop, including equipment type, equipment performance, current working status of equipment and current load of equipment;
  • Step 3 Schedule the order content according to the status of the processing equipment
  • Step 3.1 determine the time required to process the content of the order
  • the master control system obtains the types of pipe specifications processed by the order through the order management module, and the analysis and calculation module calculates the processing time required for all types of pipes to complete all processes; specifically,
  • the analysis and calculation module calculates the processing time required for the i-th specification pipe to complete all processes:
  • t ij represents the processing time of the jth process of the i-th specification pipe, including the pipe processing time and auxiliary time, and the auxiliary time includes the time spent on pipe loading and unloading, equipment startup, etc.
  • Ni represents the quantity to be processed of the i -th specification pipe
  • the analysis and calculation module calculates the time required to complete the processing of all types of pipes in the order:
  • Step 3.2 Determine the waiting time for processing of the nth batch of orders, and the analysis and calculation module calculates the time required to complete the processing of all types of pipes in the order; specifically,
  • the analysis and calculation module calculates the processing time required to complete all the processes for the unprocessed pipe in the n-1 batch:
  • t mj represents the processing time of the j-th process of the m-th specification of the remaining unprocessed pipes (0 ⁇ m ⁇ c; 1 ⁇ j ⁇ b), and c is the unprocessed in the n-1th batch.
  • the type of pipe with specifications, E mj represents the current load of the m-th specification of the remaining unprocessed pipes on the j-th processing equipment, which can be obtained through the equipment management module;
  • the analysis and calculation module calculates the time required to complete the processing of all types of pipes in the order:
  • Step 3.3 Determine the pipe transportation time.
  • the total control system obtains the load capacity information of the processing equipment for different specifications of pipes from the load capacity data storage module according to the pipe specifications. M 1 , M 2 , .
  • the analysis and calculation module calculates the required transportation times, and forms the times matrix:
  • the analysis and calculation module calculates the transportation time required for the i-th specification of the pipe:
  • v is the transportation speed of the AGV car
  • Se is the transportation distance of the e -th segment (1 ⁇ e ⁇ c);
  • the analysis calculation module calculates the required transportation time for all types of pipes in the order:
  • Step 3.4 determine the total time required to complete the order processing
  • the total time T required to complete the processing of the nth batch of orders includes the time required for order processing, the waiting time for processing and the transportation time, namely:
  • Step 3.5 Determine the optimal scheduling strategy.
  • the production scheduling module specifies several different production scheduling plans, respectively calculates the total processing time of different production scheduling plans, and uses intelligent scheduling algorithms (such as genetic algorithms) for different production scheduling plans.
  • the total time required to complete the processing is optimized, the production scheduling plan with the shortest total processing time is obtained, and the optimal scheduling strategy is sent to the master control system;
  • Step 4 Transportation of semi-finished pipes
  • Step 4.1 the command sending module sends a transportation command to the first AGV car and the second AGV car, and the first AGV car and the second AGV car feed back their status information, which includes the transportation status (idle or on duty), power information ( Insufficient power, sufficient power), etc.;
  • step 4.2 the analysis and calculation module selects the first AGV car or the second AGV car according to the feedback status information.
  • the first AGV car is selected;
  • Step 4.3 in the storage system, the transportation system inside the semi-finished pipe storage area transports the required semi-finished pipe to the second buffer area, while the first AGV trolley transports the material tray to the second buffer area, and the second pipe grabs
  • the pick-up device grabs the semi-finished pipe and puts it into the tray, and the first AGV trolley transports the semi-finished pipe to the processing station area;
  • Step 5 Semi-finished pipe processing
  • Step 5.1 the first RFID scanner scans and obtains the RFID chip on the material tray, and the second RFID scanner accesses the pipe processing information through the storage address of the RFID chip, including the pipe forming process (assuming that the pipe needs to be bent, beveled, and necked) and flange welding) and forming requirements;
  • step 5.2 the analysis and calculation module selects the groove processing area, bending processing area, shrinking or flaring processing area or welding processing area in the processing station area according to the obtained pipe processing technology sequence, and the first AGV handlebar transports the material tray to the first processing buffer area or the second processing buffer area or the third processing buffer area or the fourth processing buffer area;
  • the instruction sending module sends the corresponding processing instructions, and controls the relevant processing equipment to complete the processing of the pipe.
  • the data acquisition module collects processing data and processing equipment monitoring data through the sensing devices installed on each equipment. , respectively stored in the processing data storage module and the equipment monitoring data storage module;
  • the quality management module accesses the shared cloud according to the pipe specification information, obtains the pipe processing data, analyzes the data, completes the online quality inspection of the pipe, and transmits the results to the general control system; the condition judgment module judges the product quality: If the product quality is qualified, the first or second or third or fourth manipulator grabs the pipe and places it in the relevant processing buffer area; if the product quality is unqualified, the first or second or third or third manipulator or the third The four manipulators grab the pipe and place it in the second unqualified storage area or the third unqualified storage area or the fourth unqualified storage area or the fifth unqualified storage area;
  • step 5.5 the condition judgment module makes the following judgment: Is the required processing procedure of the pipe completed? If not completed, perform steps 5.1 to 5.5; if completed, perform step 5.6;
  • step 5.6 the condition judgment module makes the following judgment: Is the order completed? If the order is not completed, perform steps 4 to 5; if the order is completed, perform step 6;
  • step 6.1 the first AGV trolley or the second AGV trolley transports the trays storing qualified products to the fifth processing buffer area;
  • step 6.2 the first QR code spraying equipment or the second QR code spraying equipment accesses the shared cloud according to the pipe specification information, obtains the pipe information (pipe specification, processing quality, welding flange specification, etc.), and generates the corresponding two dimensional code;
  • step 6.3 the instruction sending module sends the two-dimensional code spraying instruction, and controls the sixth manipulator to grab the pipe and place it on the first two-dimensional code spraying equipment or the second two-dimensional code spraying equipment to complete the spraying operation; Place the pipe in the tray;
  • step 6.4 the condition judgment module makes the following judgment: Is the coding operation of all pipes completed? If not completed, perform steps 6.1 to 6.4; if completed, perform step 7;
  • Step 7 Qualified products are put into storage
  • Step 7.1 the command sending module sends a transportation command to the first AGV or the second AGV, and the first AGV or the second AGV feeds back its status information, including transportation status (idle or on-duty), power information (insufficient power, sufficient power), etc.;
  • step 7.2 the analysis and calculation module selects the appropriate AGV car according to the status information fed back by the first AGV car or the second AGV car. Here, it is still assumed that the first AGV car is selected;
  • step 7.3 the first AGV trolley or the second AGV trolley transports the material tray to the third buffer area, and the third pipe grabbing device transfers the finished pipe material to the specific material tray in the finished pipe storage area to complete the storage;
  • the eighth step the warehouse management module judges whether the semi-finished pipe storage area needs to be replenished, if necessary, execute the ninth to eleventh steps; otherwise, execute the twelfth step;
  • the ninth step the transportation of pipe raw materials
  • step 9.1 the warehouse management module produces supplementary documents according to the specifications of the missing pipe semi-finished products, including the specifications and quantities of the required pipe semi-finished products;
  • step 9.2 the instruction sending module sends a reclaiming signal, and the crane in the raw material storage area takes out the corresponding pipe raw material from the raw material storage area 10 and places it on the feeding conveyor line;
  • Step 10 Pipe raw material processing
  • Step 10.1 the analysis and calculation module selects the processing equipment, namely the first straightening equipment or the second straightening equipment or the first cutting equipment or the second cutting equipment or the first testing equipment or the second testing equipment, and sends the instruction
  • the module sends raw material processing instructions and controls it to complete the processing of pipe raw materials; in the processing process, the data acquisition module collects related process processing through the sensing devices (laser displacement sensor, torque sensor, displacement sensor, etc.) arranged on each equipment
  • Data and related processing equipment monitoring data are stored in the processing data storage module and the equipment monitoring data storage module respectively;
  • the quality management module accesses the shared cloud according to the pipe specification information, obtains the pipe processing data, processes the data, performs online quality inspection on the pipe, and transmits the results to the general control system; the condition judgment module judges the product quality: If the product quality is qualified, the first manipulator grabs the semi-finished pipe and places it in the semi-finished product temporary storage area; if the product quality is unqualified, the first manipulator grabs the semi-finished pipe and places it in the first unqualified storage area;
  • step 10.3 the condition judgment module makes the following judgment: Is the replenishment order (including the processing of all types of pipes and the required number of pipes) completed? If the order is not completed, perform steps 9 to 10; if the order is completed, perform step 13;
  • Step 11.1 the command sending module sends a transportation command to the first AGV or the second AGV, and the first AGV or the second AGV feeds back its status information, including transportation status (idle or on duty), power information (insufficient power, sufficient power), etc.;
  • step 11.2 the analysis and calculation module selects the appropriate AGV car according to the status information fed back by the first AGV car or the second AGV car. Here, it is assumed that the first AGV car is selected;
  • step 11.3 the first AGV car or the second AGV car transports the material tray to the third buffer area, and the third pipe grabbing device transfers the semi-finished pipe to the specific material tray in the semi-finished pipe storage area, and completes the storage;
  • step 12.1 the warehouse management module determines whether the flange storage area needs to be replenished? If the material needs to be replenished, an alarm will be issued to remind the management personnel to load the material; otherwise, go to step 12.2;
  • step 12.2 the warehouse management module determines whether the raw material storage area needs to be replenished? If the material needs to be replenished, an alarm will be issued to remind the management personnel to load the material; otherwise, the thirteenth step will be executed;
  • the thirteenth step the master control system judges whether a new order is generated: if a new order is generated, execute the first to the thirteenth steps; if no new order is generated, end;
  • the fault detection method specifically includes the following steps:
  • Step a build the database
  • a fault database is constructed.
  • the database contains known possible fault types and corresponding fault manifestations, as shown in the table in Figure 4.
  • the corresponding fault type is the motor coil phase-to-phase Short circuit, as well as failure of rocker arm of pipe bending equipment, failure of welding gun, broken gear of beveling equipment, damage of bearing of beveling equipment, damage to rotating parts of beveling equipment, phase loss of motor of cutting equipment, underpressure of cutting equipment air supply, coding equipment Abnormal ink line splitting, AGV trolley optocoupler switch failure, AGV trolley screw hoist not regularly lubricated and other faults; in particular, the database has a self-updating function, that is, when the faults of various equipment in the smart workshop have
  • Step b build a convolutional neural network expert system, specifically,
  • Step b.2 based on the measured values and fault types in the database, construct the input matrix X of the convolutional neural network expert system (the number is N, which is known) and the corresponding fault matrix Y:
  • Step b.3 perform convolution calculation on the input matrix X, the formula is as follows:
  • X i is the ith input mapping (1 ⁇ i ⁇ N)
  • Li is the total number of kernels in the ith convolutional layer
  • r denotes the local region of shared weights.
  • Step b.4 increase the convolution output map by the following formula
  • Step b.5 through the calculation of the pooling layer, increase the translation invariance of the data and prevent over-fitting, the formula is as follows:
  • Step b.6 calculate the output size of the convolutional neural network expert system:
  • Step b.7 calculate each neuron according to the following formula Probability distribution of corresponding failures
  • exp( ⁇ i ) is the ith neuron
  • the probability distribution of , is a neuron
  • the weight of , S is the number of elements contained in the output matrix
  • step b.8 the final output matrix W is determined according to the probability distribution of each fault; in step b.9, the convolutional neural network expert system compares and analyzes the output matrix W and the known fault matrix Y:
  • step b.12 If the fault types in the output matrix W calculated by the convolutional neural network expert system are all the same as the fault types in the known fault matrix Y, then perform step b.12;
  • step b.10 the convolution components are calculated as follows:
  • Step b.11 convert the output size ⁇ i into the input matrix X, and execute steps b.3 to b.9;
  • Step b.12 determine the value of the number M of convolution components and each scale factor , and construct a convolutional neural network expert system
  • Step d analyze and process the data collected in step c through the constructed convolutional neural network expert system; specifically,
  • Step d.2 construct the input matrix X of the convolutional neural network expert system:
  • Step d.3 using the convolutional neural network expert system constructed in step b to analyze the input matrix X;
  • Step d.4 calculate the convolution components as follows:
  • Step d.5 the convolutional neural network expert system judges whether j ⁇ M is established? If it is established, then the output size ⁇ i is converted into the input matrix X, and steps d.3 to d.5 are performed; if not established, the convolutional neural network expert system outputs the output matrix W;
  • the monitoring system accesses the fault database according to the output result W of the convolutional neural network expert system; if the corresponding fault is queried in the fault database, the fault is sent to the fault display module for display, which is used to guide the maintenance workers to maintain and start the standby equipment; If the corresponding fault is not queried in the database, go to step f;
  • Step f database update
  • the expert judges the fault and the corresponding fault's manifestation. If the fault and the corresponding fault's manifestation match, the fault and the corresponding fault's manifestation will be included in the database, and the fault will be sent to the fault display module for display to guide maintenance. Workers repair and start the standby equipment; at the same time, the convolutional neural network expert system is updated; if the manifestation of the fault and the corresponding fault do not match, the fault corresponding to the corresponding manifestation will be obtained according to the experience of the experts, and incorporated into the database, and the volume will be updated at the same time. Integrated neural network expert system.
  • connection may be a direct connection between components or an indirect connection between components through other components.

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Abstract

一种多规格船用管材智能成形车间及控制方法，多规格船用管材智能成形车间包括顺次布设在生产线上的前处理加工区（3）和加工工位区（6），在生产线的上游布设原材料存储区（1），在生产线的一侧布设用于存放管材半成品、管材成品以及法兰的仓储区；还包括运输系统（4）和智能控制系统（2），智能控制系统（2）对原材料存储区（1）、前处理加工区（3）以及加工工位区（6）发送控制信号，实现对多规格管材的调取加工，智能控制系统（2）同时对运输系统（4）发送控制信号，在运输线上实现对多规格管材的运输转运；上述方法可根据订单制定最优调度策略，对整个车间进行故障监测，有利于信息化管理多规格船用管材智能成形车间。

Description

一种多规格船用管材智能成形车间及控制方法 技术领域
本发明涉及一种多规格船用管材智能成形车间及控制方法，属于管材加工领域。
背景技术
智能车间是通过网络及软件管理系统把自动化设备(生产设备、检测设备、运输设备、机械手等)实现互联互通，达到感知状态(生产需求、设备、生产工艺等信息)，实时数据分析，从而实现自动决策和精确执行命令的自组织生产的车间；在船舶制造的过程中，管材加工制造是船厂生产组织中的一个重要环节。据统计，钢质船舶管材使用量巨大，一艘20万吨的油船管材使用数量超过2万根，因此管材加工的工作量巨大，尤其是在多艘船同时建造时，更会加重管材生产车间的加工任务，导致管材加工车间极易处于混乱状态，造成了管材加工车间成为造船企业的发展瓶颈，制约着造船企业向智能化方向发展。
由于船舶是定制化产品，不同类型，甚至每一艘船舶，所用管材的材质都不同，比如钢管、铝管、铜管及双金属管等，同时，不同船舶所用管材的规格也不同，比如无缝钢管的公称通径为10～300mm，壁厚为2～8mm；焊接钢管的公称通径为10～140mm，壁厚为0.5～5.5mm；低压流体输送管的公称通径为15～150mm，壁厚为2.75～4.5mm；铝管的外径为6～50mm，壁厚为0.5～5mm；双金属管的外径为6～70mm，壁厚为1.5～6mm。这就造成船用管材具有成形尺寸规格多，壁厚范围广，材质品种多且材质差别大的特点。
上述船用管材的特点，使得现役船用管材成形车间存在如下问题：
⑴订单中管材种类众多，并且由于管材加工车间缺少合理有效的智能调度方法，导致管材加工耗时长、无法按照交货期完成订单、进而导致订单积压。专利ZL201710282923.4中所述的基于智能车间的流动式多智能体实时调度系统描述智能车间的通用调度系统和方法，并未给出如何确定调度策略所要优化的目标函数，且其并不适用于调度复杂的管材智能成形车间；专利ZL201610403522.5中所述的工厂智能车间实时调度系统同样描述了一般工厂车间的调度系统，并不适用于管材种类众多、成形工艺多样的船用管材成形车间。
⑵现役船用管材成形车间缺少必要的车间故障监测系统及处理方法，导致当某一设备出现故障时，需要维修人员花费大量时间确认故障原因并进行维修，进而影响车间的加工进度。专利ZL103293415B中所述的基于神经网络专家系统的微逆变器故障检测方法，描述了通过神经网络专家系统进行微逆变器的故障检测方法，但是该方法缺少详细的神经网络专家系统的构建过程。
此外，现役船用管材成形车间还存在由于缺少加工过程相关数据采集和有效的信息管理系统，导致生产车间无法实现信息化管理，且企业信息集成困难等问题。
发明内容
本发明提供一种多规格船用管材智能成形车间及控制方法，可根据订单制定最优调度策略，对整个车间进行故障监测，有利于信息化管理多规格船用管材智能成形车间。
本发明解决其技术问题所采用的技术方案是：
一种多规格船用管材智能成形车间，包括顺次布设在生产线上的前处理加工区和加工工位区，在生产线的上游布设原材料存储区，在生产线的一侧布设用于存放管材半成品、管材成品以及法兰的仓储区；
还包括运输系统和智能控制系统，智能控制系统对原材料存储区、前处理加工区以及加工工位区发送控制信号，实现对多规格管材的调取加工，智能控制系统同时对运输系统发送控制信号，在运输线上实现对多规格管材的运输转运；
作为本发明的进一步优选，前述的原材料储存区设有对多规格管材进行分类储存的原材料存放区，其通过行车实现原材料的运输；
前述的智能控制系统包括相互连通的总控系统、MES系统、共享云以及监测系统，总控系统对MES系统、共享云以及监测系统进行指令调控；
其中，总控系统包括分析计算模块、指令发送模块以及条件判断模块，其中，分析计算模块从原材料存储区、前处理加工区、加工工位区以及运输系统获取信号进行分析，指令发送模块将接收到的信号发送至分析计算模块，同时将施行指令发送至原材料存储区、前处理加工区、加工工位区以及运输系统，条件判断模块对产品质量进行判断；
MES系统包括生产调度模块、数据采集模块、质量管理模块、仓库管理模块、订单管理模块以及设备管理模块，其中，生产调度模块用于对车间内的生产程序进行调度，数据采集模块用于对车间内生产信息进行收集，质量管理模块用于对产品的质量进行管理，仓库管理模块用于对车间内原材料存储区、仓储系统施行管理，订单模块用于对产品的订单信息进行管理，设备管理模块用于对车间内的设备进行管理；
共享云包括RFID信息存储模块、加工数据存储模块、设备监测数据存储模块以及负载量数据存储模块，其中，RFID信息存储模块用于对RFID扫描信息的存储，加工数据存储模块用于对车间内加工数据进行存储，设备监测数据存储模块用于对车间内设备监测数据进行存储，负载量数据存储模块用于对车间内负载量数据进行存储；
监测系统用于对车间内各部分的监测；
作为本发明的进一步优选，前述的前处理加工区包括上料输送线、第一矫直设备、第二矫直设备、第一切割设备、第二切割设备、第一检测设备、第二检测设备、半成品暂存区以及第一不合格存放区，其中上料输送线位于生产线的上游，在生产线的一侧顺次布设第一矫直设备、第一切割设备以及第一检测设备，生产线的另一侧顺次布设第二矫直设备、第二切割设备以及第二检测设备，第一矫直设备与第二矫直设备、第一切割设备与第二切割设备、第一检测设备与第二检测设备对称排布，还包括第一机械手，其将经过检测后的产品夹取转送至半成品暂存区，第一机械手将经过检测后的不合格产品夹取转送至第一不合格存放区；
作为本发明的进一步优选，前述的仓储系统包括料盘存放区、第一RFID扫描仪、法兰存放区、管材半成品存放区以及管材成品存放区，料盘存放区内放置若干料盘，第一RFID扫描仪用于对料盘信息进行扫描记录，在法兰存放区的入口处设置第一缓存区，在管材半成品存放区的入口处设置第二缓存区，在管材成品存放区的入口处设置第三缓存区，运输系统将料盘运送至相应缓存区，同时运输系统将法兰存放区、管材半成品存放区以及管材成品存放区内的对应产品运输至相应缓存区，在第一缓存区内设置第一管材抓取装置，其 将法兰抓取放置位于第一缓存区的料盘内，第二缓存区内设置第二管材抓取装置，其将管材半成品抓取放置位于第二缓存区的料盘内，第三缓存区内设置第三管材抓取装置，其将管材成品抓取放置第三缓存区的料盘内；
作为本发明的进一步优选，前述的加工工位区包括弯曲加工区、坡口加工区、缩或扩口加工区、焊接加工区以及二维码喷涂区，还安装有第二RFID扫描仪，装有产品的料盘经过第二RFID扫描仪扫描后通过运输系统分配至加工工位区内的各个区；
弯曲加工区包括第一弯管设备、第二弯管设备、第一加工缓存区以及第一不合格存放区，运输系统将合格产品从匹配区域运送至第一加工缓存区，第二机械手将产品从第一加工缓存区夹取至第一弯管设备、第二弯管设备处进行弯曲处理后，再将弯曲处理后的不合格产品夹取放至第二不合格存放区内；
坡口加工区包括第一坡口设备、第二坡口设备、第二加工缓存区以及第二不合格存放区，运输系统将合格产品从匹配区域运送至第二加工缓存区，第三机械手将产品从第二加工缓存区夹取至第一坡口设备、第二坡口设备处进行坡口处理后，再将坡口处理后的不合格产品夹取放至第三不合格存放区内；
缩或扩口加工区包括第一缩或扩口设备、第二缩或扩口设备、第三加工缓存区以及第三不合格存放区，匹配区域将合格产品从仓储系统运送至第三加工缓存区，第四机械手将产品从第三加工缓存区夹取至第一缩或扩口设备、第二缩或扩口设备处进行缩或扩口处理后，再将缩或扩口后的不合格产品夹取送至第四不合格存放区；
焊接加工区包括第一焊接设备、第二焊接设备、第四加工缓存区以及第四不合格存放区，运输系统将合格产品从匹配区域运送至第四加工缓存区，第五机械手将产品从第四加工缓存区夹取至第一焊接设备、第二焊接设备进行焊接处理后，再将不合格产品夹取送至第五不合格存放区；
二维码喷涂区包括第一二维码喷涂设备、第二二维码喷涂设备以及第五加工缓存区，运输系统将合格产品从匹配区域运送至第五加工缓存区，第六机械手将产品从第五加工缓存区夹取至第一二维码喷涂设备、第二二维码喷涂设备进行喷涂处理；
作为本发明的进一步优选，前述的运输系统包括第一AGV小车和第二AGV小车，还安装有为第一AGV小车和第二AGV小车充电的充电区；
作为本发明的进一步优选，在第一检测设备以及第二检测设备上安装激光位移传感器，在第一弯管设备以及第二弯管设备上安装角度传感器、扭矩传感器以及第一扫描仪，在第一缩或扩口设备以及第二缩或扩口设备上安装第二扫描仪、压力传感器和位移传感器，在第一坡口设备以及第二坡口设备上安装速度传感器、第三扫描仪以及表面粗糙度仪，在第一焊接设备、第二焊接设备上安装电压传感器、电流传感器和超声无损探伤仪；
一种基于上述任意权利要求所述的多规格船用管材智能成形车间的控制方法，分为两个部分，第一部分为调度方法，第二部分为故障检测方法，
其中调度方法具体包括以下步骤：
第一步：车间接收订单
第1.1步，多规格船用管材智能成形车间收到第n批管材加工订单，其中n≥2，管材加工订单的内容包含订货方、交货期、所需管材规格、加工工序、焊接法兰信息以及所需数量；
第1.2步，仓库管理模块通过第一RFID扫描仪获取位于仓储系统内的处于空置状态料盘的RFID芯片内所存储地址；
第1.3步，订单管理模块根据车间接收到的订单内容生成各管材的加工工艺文件，并将加工工艺文件写入所获取的存储地址内；
第二步：获取车间状态信息
设备管理模块获取车间内各加工设备的状态，状态包括设备类型、设备性能、设备当前工作状态以及设备当前负载量；
第三步：根据加工设备状态对订单内容进行调度
第3.1步，确定对订单内容进行加工所需的时间，总控系统通过订单管理模块获取订单所加工管材规格的种类，分析计算模块计算所有种类管材完成所有工序所需加工的时间；
第3.2步，确定第n批订单等待加工时间，分析计算模块计算订单中所有种类的管材完成加工所需的时间；
第3.3步，确定管材运输时间，总控系统根据管材规格从负载量数据存储模块处获取加工设备针对不同规格管材的负载量信息，分析计算模块计算各加工设备和仓储之间的运输距离、所需运输次数以及每种规格管材所需运输时间，最终获取订单中所有种类管材所需运输时间；
第3.4步，确定订单加工完成所需要的总时间；
第3.5步，确定最优的调度策略，生产调度模块指定若干种不同的生产调度计划，分别计算出不同生产调度计划的总加工时间，并采用智能调度算法对不同排产加工完成所需总时间进行优化，得到总加工时间最短的排产方案，并将最优调度策略发送至总控系统；
第四步：半成品管材运输
第4.1步，指令发送模块向第一AGV小车、第二AGV小车发送运输指令，第一AGV小车、第二AGV小车反馈其状态信息，此状态信息包括运输状态以及电量信息；
第4.2步，分析计算模块根据反馈状态信息，选择第一AGV小车或者第二AGV小车；
第4.3步，在仓储系统中，管材半成品存放区内部的运输系统把所需管材半成品运送至第二缓存区处，同时第一AGV小车或者第二AGV小车把料盘运送至第二缓存区处，第二管材抓取装置抓取管材半成品放入料盘内，第一AGV小车或者第二AGV小车运输管材半成品至加工工位区；
第五步：半成品管材加工
第5.1步，第一RFID扫描仪扫描获取料盘上的RFID芯片，第二RFID扫描仪通过RFID芯片的存储地址访问管材加工信息，包括管材成形工艺以及成形要求；
第5.2步，分析计算模块根据所获取的管材加工工艺顺序选择加工工位区中的坡口加工区、弯曲加工区、缩或扩口加工区或者焊接加工区，第一AGV小车或者第二AGV小车把料盘运输至第一加工缓存区或者第二加工缓存区或者第三加工缓存区或者第四加工缓存区；
第5.3步，指令发送模块发送相应的加工指令，并控制相关加工设备完成对管材的加工，在加工过程中，数据采集模块通过安装在各设备上的传感装置采集加工数据以及加工设备监测数据，分别储存于加工数据存储模块以及设备监测数据存储模块内；
第5.4步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行分析，完成管材的在线质量检测，并把结果传输至总控系统；条件判断模块进行产品质量判断：若产品质量合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在相关加工缓存区内；若产品质量不合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在第二不合格存放区或者第三不合格存放区或者第四不合格存放区或者第五不合格存放区内；
第5.5步，条件判断模块进行如下判断：管材要求加工工序是否完成？若未完成，执行第5.1步至第5.5步；若完成，执行第5.6步；
第5.6步，条件判断模块进行如下判断：订单是否完成？若订单未完成，执行第四步至第五步；若订单完成，执行第六步；
第六步，二维码喷涂
第6.1步，第一AGV小车或第二AGV小车将存放合格产品的料盘运输至第五加工缓存区；
第6.2步，第一二维码喷涂设备或第二二维码喷涂设备根据管材规格信息访问共享云，获取管材的信息，生成相对应的二维码；
第6.3步，指令发送模块发送二维码喷涂指令，并控制第六机械手抓取管材放置在第一二维码喷涂设备或第二二维码喷涂设备上，完成喷码操作；第六机械手再把管材放置于料盘内；
第6.4步，条件判断模块进行如下判断：所有管材的喷码操作是否完成？若未完成，执行第6.1步至第6.4步；若完成，执行第七步；
第七步：合格产品入库
第7.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态以及电量信息；
第7.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车；
第7.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把成品管材转移至管材成品存放区特定料盘内，完成入库；
第八步，仓库管理模块判断管材半成品存放区是否需要补料，若需要，执行第九步至第十一步；否则，执行第十二步；
第九步，管材原材料运输
第9.1步，仓库管理模块根据所缺管材半成品规格，生产补料文件，包括所需管材半成品的规格和数量；
第9.2步，指令发送模块发送取料信号，原材料存储区的行车从原材料存放区取出相应管材原材料放置在上料输送线上；
第十步：管材原材料加工
第10.1步，分析计算模块根据设备的状态，选择加工设备即第一矫直设备或者第二矫直设备或者第一切割设备或者第二切割设备或者第一检测设备或者第二检测设备，指令发送模块发送原材料加工指令，并控制其完成对管材原材料的加工；在加工过程中，数据采集模块通过布置在各设备上的传感装置采集相关工艺加工数据和相关加工设备监测数 据，分别储存于加工数据存储模块和设备监测数据存储模块内；
第10.2步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行处理，对管材进行在线质量检测，并把结果传输至总控系统；条件判断模块进行产品质量判断：若产品质量合格，第一机械手抓取管材半成品放置在半成品暂存区内；若产品质量不合格，第一机械手抓取管材半成品放置在第一不合格存放区内；
第10.3步，条件判断模块进行如下判断：补料订单是否完成？若订单未完成，执行第九步至第十步；若订单完成，执行第十三步；
第十一步，管材半成品入库
第11.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态以及电量信息；
第11.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车；
第11.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把半成品管材转移至管材半成品存放区特定料盘内，完成入库；
第十二步，仓储系统存料判断
第12.1步，仓库管理模块判断法兰存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第12.2步；
第12.2步，仓库管理模块判断原材料存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第十三步；
第十三步，总控系统进行判断是否有新订单产生：若有新订单产生，执行第一步至第十三步；若无新订单产生，结束；
故障检测方法具体包括以下步骤：
步骤a，构建数据库
根据智能车间各设备在工作过程中故障类型和原因，并结合专家人员的建议，构建故障数据库，数据库包含已知的有可能产生的故障类型和相应故障的表现形式；
步骤b，构建卷积神经网络专家系统
步骤c，数据采集
通过设置在智能车间各设备上各传感设备采集相关数据，包括弯管设备电机三相电流I u、I v、I w和三相电压U u、U v、U w、弯管设备摇臂转角θ、弯管设备摇臂扭矩T、焊枪振动dB 1、焊枪温度t 1、坡口设备温度t 2、坡口设备工作声音dB 2、切割设备刀片上升速度v、切割设备声响dB 3、AGV小车运动距离s以及AGV小车举升机构声音dB 4；
步骤d，通过构建的卷积神经网络专家系统对步骤c所采集的数据进行分析处理；
步骤e，故障查询
监测系统根据卷积神经网络专家系统的输出结果δ i，访问故障数据库；若在故障数据库内查询到相应故障，则将故障发送至故障显示模块显示，用于指导维修工人维修，并启动备用设备；若在数据库内未查询到相应故障，执行步骤f；
步骤f，数据库更新
专家人员对故障和相应故障的表现形式进行判断，若故障和相应故障的表现形式相匹配，则把故障和相应故障的表现形式纳入数据库，并将故障发送至故障显示模块显示， 用于指导维修工人维修，并启动备用设备；同时更新卷积神经网络专家系统；若故障和相应故障的表现形式不匹配，则根据专家人员的经验，获得相应表现形式对应的故障，并纳入数据库，同时更新卷积神经网络专家系统。
通过以上技术方案，相对于现有技术，本发明具有以下有益效果：
1、在智能调度方面，本发明多规格船用管材智能成形车间可以根据管材加工订单，以交货期为期限，制定不同的调度方案，并采用智能调度算法(如：遗传算法)对各方案进行优化，获得最优调度策略，并指导整个车间的运行控制，不仅提高了整个车间的加工效率，杜绝了订单逾期的现象，还使得整个车间运行有序，减少人工干预，提高了车间的智能化；
2、在多规格船用管材智能成形车间故障检测方面，本发明的卷积神经网络专家系统对智能成形车间内各设备的检测数据进行分析处理，并把分析结果与故障数据库进行对比分析，获取智能成形车间内各设备的故障类型，以指导相关人员的维修操作，同时启用备用设备，用于减少设备故障对加工进度的影响。卷积神经网络专家系统具有不断自我学习和更新的功能，并对数据库进行完善，以提高其检测的精确性，同时可降低维修人员的故障排除难度，从而节约大量时间；
3、通过布置在各设备处的各传感装置对加工过程中产生的数据进行采集，并保存于共享云中，有利于企业的信息集成，实现车间的信息化管理，提高企业的管控能力。
附图说明
下面结合附图和实施例对本发明进一步说明。
图1是本发明提供的优选实施例的多规格船用管材智能成形车间布局图；
图2是本发明提供的优选实施例的多规格船用管材智能成形车间智能调度流程图；
图3是本发明提供的优选实施例的多规格船用管材智能加工过程控制及数据采集图；
图4是本发明提供的优选实施例的多规格船用管材智能成形车间的故障类型和表现形式。
图中：在原材料存储区中，1为原材料存储区，10为原材料存放区，11为行车；
在智能控制系统中，2为智能控制系统，20为总控系统，201为分析计算模块，202为指令发送模块，203为条件判断模块，21为MES系统，211为生产调度模块，212为数据采集模块，213为质量管理模块，214为仓库管理模块，215为订单管理模块，216为设备管理模块，22为共享云，221为RFID信息存储模块，222为加工数据存储模块，223为设备监测数据存储模块，224为负载量数据存储模块，23为监测系统；
在前处理加工区中，3为前处理加工区，30为上料输送线，31为第一矫直设备，32为第一切割设备，33为第一检测设备，34为第一机械手，35为半成品暂存区，36为第一不合格存放区，37为第二矫直设备，38为第二切割设备，39为第二检测设备；
在运输系统中，4为运输系统，40为第一AGV小车，41为第二AGV小车，42为充电区；
在仓储系统中，5为仓储系统，50为法兰存放区，51为管材半成品存放区，52为管材成品存放区，53为第一缓存区，54为第二缓存区，55为第三缓存区，56为第一RFID扫描仪，57 为第一管材抓取装置，58为第二管材抓取装置，59为第三管材抓取装置，510为料盘存放区，511为料盘；
在加工工位区中，6为加工工位区，60为弯曲加工区，601为第一弯管设备，602为第二弯管设备，603为第一加工缓存区，604为第二不合格存放区，605为第二机械手，61为坡口加工区，611为第一坡口设备，612为第二坡口设备，613为第二加工缓存区，614为第三不合格存放区，615为第三机械手，62为缩或扩口加工区，621为第一缩或扩口设备，622为第二缩或扩口设备，623为第三加工缓存区，624为第四不合格存放区，625为第四机械手，63为焊接加工区，631为第一焊接设备，632为第二焊接设备，633为第四加工缓存区，634为第五不合格存放区，635为第五机械手，64为第二RFID扫描仪，65为二维码喷涂区，651为第一二维码喷涂设备，652为第二二维码喷涂设备，653为第五加工缓存区，654为第六机械手；
701为激光位移传感器，702为扭矩传感器，703为角度传感器，704为第一扫描仪，705为第二扫描仪，706为压力传感器，707为位移传感器，708为速度传感器，709为第三扫描仪，710为表面粗糙度仪，711为电压传感器，712为电流传感器，713为超声无损探伤仪。
具体实施方式
现在结合附图对本发明作进一步详细的说明。这些附图均为简化的示意图，仅以示意方式说明本发明的基本结构，因此其仅显示与本发明有关的构成。
在现有技术中的关于船用管材成形车间存在如背景技术中所指出的几个问题，如不适用于管材种类众多、成形工艺多样的船用管材成形车间，需要花费大量时间查找故障原因，以及缺少加工过程的相关数据采集、对信息的有效管理，为了克服以上的问题，本申请提出了一种多规格船用管材智能成形车间。
图1所示，是本申请提供的一种多规格船用管材智能成形车间的具体结构，从图中可以清楚的看出，具体包括以下几个部分，原材料存储区1、前处理江干区、仓储系统5以及加工工位区6，整个车间的控制部分为智能控制系统2，整个车间的运输渠道为运输系统4，智能控制系统对整个车间进行调控，实现多规格管材的矫直、切断、弯曲成形、管端成形、端部法兰焊接、二维码喷涂以及管材毛坯、半成品、成品的出库入库等，通过运输系统将各个区域所需产品进行运输传送；
具体的，
原材料储存区设有对多规格管材进行分类储存的原材料存放区，其通过行车11实现原材料的运输，对多规格管材进行分类是根据其材质、规格(管径×壁厚)进行分类；
智能控制系统包括相互连通的总控系统20、MES系统21、共享云22以及监测系统23，总控系统对MES系统、共享云以及监测系统进行指令调控；
其中，总控系统包括分析计算模块201、指令发送模块202以及条件判断模块203，其中，分析计算模块从原材料存储区、前处理加工区3、加工工位区以及运输系统获取信号进行分析，指令发送模块将接收到的信号发送至分析计算模块，同时将施行指令发送至原材料存储区、前处理加工区、加工工位区以及运输系统，条件判断模块对产品质量进行判断；
MES系统包括生产调度模块211、数据采集模块212、质量管理模块213、仓库管理模块214、订单管理模块215以及设备管理模块216，其中，生产调度模块用于对车间内的生产 程序进行调度，数据采集模块用于对车间内生产信息进行收集，质量管理模块用于对产品的质量进行管理，仓库管理模块用于对车间内原材料存储区、仓储系统施行管理，订单模块用于对产品的订单信息进行管理，设备管理模块用于对车间内的设备进行管理；
共享云包括RFID信息存储模块221、加工数据存储模块222、设备监测数据存储模块223以及负载量数据存储模块224，其中，RFID信息存储模块用于对RFID扫描信息的存储，加工数据存储模块用于对车间内加工数据进行存储，设备监测数据存储模块用于对车间内设备监测数据进行存储，负载量数据存储模块用于对车间内负载量数据进行存储；
监测系统用于对车间内各部分的监测；
前处理加工区包括上料输送线30、第一矫直设备31、第二矫直设备37、第一切割设备32、第二切割设备38、第一检测设备33、第二检测设备39、半成品暂存区35以及第一不合格存放区36，其中上料输送线位于生产线的上游，在生产线的一侧顺次布设第一矫直设备、第一切割设备以及第一检测设备，生产线的另一侧顺次布设第二矫直设备、第二切割设备以及第二检测设备，第一矫直设备与第二矫直设备、第一切割设备与第二切割设备、第一检测设备与第二检测设备对称排布，还包括第一机械手34，其将经过检测后的产品夹取转送至半成品暂存区，第一机械手将经过检测后的不合格产品夹取转送至第一不合格存放区；每种设备均设置两个，是达到一备一用的目的，避免其中一个出现故障导致车间生产的停止；
仓储系统包括料盘存放区510、第一RFID扫描仪56、法兰存放区50、管材半成品存放区51以及管材成品存放区52，料盘存放区内放置若干料盘511，第一RFID扫描仪用于对料盘信息进行扫描记录，在法兰存放区的入口处设置第一缓存区53，在管材半成品存放区的入口处设置第二缓存区54，在管材成品存放区的入口处设置第三缓存区55，运输系统将料盘运送至相应缓存区，同时运输系统将法兰存放区、管材半成品存放区以及管材成品存放区内的对应产品运输至相应缓存区，在第一缓存区内设置第一管材抓取装置57，其将法兰抓取放置位于第一缓存区的料盘内，第二缓存区内设置第二管材抓取装置58，其将管材半成品抓取放置位于第二缓存区的料盘内，第三缓存区内设置第三管材抓取装置59，其将管材成品抓取放置第三缓存区的料盘内；
加工工位区包括弯曲加工区60、坡口加工区61、缩或扩口加工区62、焊接加工区63以及二维码喷涂区65，还安装有第二RFID扫描仪64，装有产品的料盘经过第二RFID扫描仪扫描后通过运输系统分配至加工工位区内的各个区；
弯曲加工区包括第一弯管设备601、第二弯管设备602、第一加工缓存区603以及第一不合格存放区，运输系统将合格产品从匹配区域运送至第一加工缓存区，第二机械手605将产品从第一加工缓存区夹取至第一弯管设备、第二弯管设备处进行弯曲处理后，再将弯曲处理后的不合格产品夹取放至第二不合格存放区604内；
坡口加工区包括第一坡口设备611、第二坡口设备612、第二加工缓存区613以及第二不合格存放区，运输系统将合格产品从匹配区域运送至第二加工缓存区，第三机械手615将产品从第二加工缓存区夹取至第一坡口设备、第二坡口设备处进行坡口处理后，再将坡口处理后的不合格产品夹取放至第三不合格存放区614内；
缩或扩口加工区621包括第一缩或扩口设备、第二缩或扩口设备622、第三加工缓存区623以及第三不合格存放区，运输系统将合格产品从匹配区域运送至第三加工缓存区， 第四机械手625将产品从第三加工缓存区夹取至第一缩或扩口设备、第二缩或扩口设备处进行缩或扩口处理后，再将缩或扩口后的不合格产品夹取送至第四不合格存放区624；
焊接加工区包括第一焊接设备631、第二焊接设备632、第四加工缓存区633以及第四不合格存放区，运输系统将合格产品从匹配区域运送至第四加工缓存区，第五机械手635将产品从第四加工缓存区夹取至第一焊接设备、第二焊接设备进行焊接处理后，再将不合格产品夹取送至第五不合格存放区634；
二维码喷涂区包括第一二维码喷涂设备651、第二二维码喷涂设备652以及第五加工缓存区653，运输系统将合格产品从匹配区域运送至第五加工缓存区，第六机械手654将产品从第五加工缓存区夹取至第一二维码喷涂设备、第二二维码喷涂设备进行喷涂处理；
需要说明的是，合格产品通过运输系统进行传送至指定的区域，这里的匹配区域不仅仅是从仓储系统，也可以是从其他加工区运送，如加工工位区内的坡口加工区、缩或扩口加工区以及焊接加工区。
运输系统包括第一AGV小车40和第二AGV小车41，还安装有为第一AGV小车和第二AGV小车充电的充电区42；
在第一检测设备以及第二检测设备上安装激光位移传感器701，在第一弯管设备以及第二弯管设备上安装角度传感器703、扭矩传感器702以及第一扫描仪704，在第一缩或扩口设备以及第二缩或扩口设备上安装第二扫描仪705、压力传感器706和位移传感器707，在第一坡口设备以及第二坡口设备上安装速度传感器708、第三扫描仪709以及表面粗糙度仪710，在第一焊接设备、第二焊接设备上安装电压传感器711、电流传感器712和超声无损探伤仪713，可实现在管材加工过程中对各设备加工数据的采集与集成。
接着图2和图3给出了本申请提供的多规格船用管材智能成形车间的使用方式，图2为利用其进行智能调度的方法，图3为利用其进行控制及数据采集的示意图，下面做具体阐述
调度方法具体包括以下步骤：
第一步：车间接收订单
第1.1步，多规格船用管材智能成形车间收到第n批管材加工订单，其中n≥2，管材加工订单的内容包含订货方、交货期、所需管材规格、加工工序、焊接法兰信息以及所需数量等；
第1.2步，仓库管理模块通过第一RFID扫描仪获取位于仓储系统内的处于空置状态料盘的RFID芯片内所存储地址；
第1.3步，订单管理模块根据车间接收到的订单内容生成各管材的加工工艺文件，并将加工工艺文件写入所获取的存储地址内；
第二步：获取车间状态信息
设备管理模块获取车间内各加工设备的状态，状态包括设备类型、设备性能、设备当前工作状态以及设备当前负载量；
第三步：根据加工设备状态对订单内容进行调度
第3.1步，确定对订单内容进行加工所需的时间，总控系统通过订单管理模块获取订单所加工管材规格的种类，分析计算模块计算所有种类管材完成所有工序所需加工的时间；具体的，总控系统通过订单管理模块获取订单所加工管材规格的种类为a(a≥1)种，并 获取每种管材所需数量，构成数量矩阵N＝[N 1，N 2，...，N a]，每种管材的加工工序种类为b(1≤b≤4)种，
分析计算模块计算第i种规格的管材完成所有工序所需加工时间：
Figure PCTCN2021089551-appb-000001
式中，t ij表示第i种规格管材的第j道工序的加工时间，包括管材加工时间和辅助时间，辅助时间包括管材装卸、设备启动等所耗时间(1≤i≤a；1≤j≤b)，N i表示第i种规格的管材所要加工数量；
分析计算模块计算订单所有种类的管材完成加工所需时间：
Figure PCTCN2021089551-appb-000002
第3.2步，确定第n批订单等待加工时间，分析计算模块计算订单中所有种类的管材完成加工所需的时间；具体的，
分析计算模块计算第n-1批中未加工规格的管材完成所有工序所需加工时间：
Figure PCTCN2021089551-appb-000003
式中，t mj表示所剩未加工管材中第m种规格的管材的第j道工序的加工时间(0≤m≤c；1≤j≤b)，c为第n-1批中未加工规格的管材种类，E mj表示所剩未加工管材中第m种规格的管材在第j道加工设备上的当前负载量，可通过设备管理模块获取；
分析计算模块计算订单所有种类的管材完成加工所需时间：
Figure PCTCN2021089551-appb-000004
第3.3步，确定管材运输时间，总控系统根据管材规格从负载量数据存储模块处获取加工设备针对不同规格管材的负载量信息(不同规格的管材负载量不同)，构成负载量矩阵M＝[M 1，M 2，...，M a]；分析计算模块计算各加工设备和仓储之间的运输距离、所需运输次数以及每种规格管材所需运输时间，最终获取订单中所有种类管材所需运输时间，其中，分析计算模块计算各加工设备和仓储之间的运输距离构成距离矩阵：
S＝[S 1，S 2，...，S c](3≤c)
分析计算模块计算所需运输次数，构成次数矩阵：
Figure PCTCN2021089551-appb-000005
分析计算模块计算第i种规格的管材所需运输时间：
Figure PCTCN2021089551-appb-000006
式中，v为AGV小车的运输速度，S e为第e段运输距离(1≤e≤c)；
分析计算模块计算订单所有种类的管材所需运输时间：
Figure PCTCN2021089551-appb-000007
第3.4步，确定订单加工完成所需要的总时间；具体的，
第n批订单加工完成所需总时间T包括订单加工所需时间、等待加工时间以及运输时间，即：
Figure PCTCN2021089551-appb-000008
第3.5步，确定最优的调度策略，生产调度模块指定若干种不同的生产调度计划，分别计算出不同生产调度计划的总加工时间，并采用智能调度算法(如：遗传算法)对不同排产加工完成所需总时间进行优化，得到总加工时间最短的排产方案，并将最优调度策略发送至总控系统；
第四步：半成品管材运输
第4.1步，指令发送模块向第一AGV小车、第二AGV小车发送运输指令，第一AGV小车、第二AGV小车反馈其状态信息，此状态信息包括运输状态(空闲或者在岗)、电量信息(电量不足、电量充足)等；
第4.2步，分析计算模块根据反馈状态信息，选择第一AGV小车或者第二AGV小车，在提供的实施例中如图2所示，选用的是第一AGV小车；
第4.3步，在仓储系统中，管材半成品存放区内部的运输系统把所需管材半成品运送至第二缓存区处，同时第一AGV小车把料盘运送至第二缓存区处，第二管材抓取装置抓取管材半成品放入料盘内，第一AGV小车运输管材半成品至加工工位区；
第五步：半成品管材加工
第5.1步，第一RFID扫描仪扫描获取料盘上的RFID芯片，第二RFID扫描仪通过RFID芯片的存储地址访问管材加工信息，包括管材成形工艺(假设管材需要弯曲成形、坡口、缩口以及法兰焊接)以及成形要求；
第5.2步，分析计算模块根据所获取的管材加工工艺顺序选择加工工位区中的坡口加工区、弯曲加工区、缩或扩口加工区或者焊接加工区，第一AGV小车把料盘运输至第一加工缓存区或者第二加工缓存区或者第三加工缓存区或者第四加工缓存区；
第5.3步，指令发送模块发送相应的加工指令，并控制相关加工设备完成对管材的加工，在加工过程中，数据采集模块通过安装在各设备上的传感装置采集加工数据以及加工设备监测数据，分别储存于加工数据存储模块以及设备监测数据存储模块内；
第5.4步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行分析，完成管材的在线质量检测，并把结果传输至总控系统；条件判断模块进行产品质量判断：若产品质量合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在相关加工缓存区内；若产品质量不合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在第二不合格存放区或者第三不合格存放区 或者第四不合格存放区或者第五不合格存放区内；
第5.5步，条件判断模块进行如下判断：管材要求加工工序是否完成？若未完成，执行第5.1步至第5.5步；若完成，执行第5.6步；
第5.6步，条件判断模块进行如下判断：订单是否完成？若订单未完成，执行第四步至第五步；若订单完成，执行第六步；
第六步，二维码喷涂
第6.1步，第一AGV小车或第二AGV小车将存放合格产品的料盘运输至第五加工缓存区；
第6.2步，第一二维码喷涂设备或第二二维码喷涂设备根据管材规格信息访问共享云，获取管材的信息(管材规格、加工质量、焊接法兰规格等)，生成相对应的二维码；
第6.3步，指令发送模块发送二维码喷涂指令，并控制第六机械手抓取管材放置在第一二维码喷涂设备或第二二维码喷涂设备上，完成喷码操作；第六机械手再把管材放置于料盘内；
第6.4步，条件判断模块进行如下判断：所有管材的喷码操作是否完成？若未完成，执行第6.1步至第6.4步；若完成，执行第七步；
第七步：合格产品入库
第7.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态(空闲或者在岗)、电量信息(电量不足、电量充足)等；
第7.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车，在这里依然假设选用第一AGV小车；
第7.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把成品管材转移至管材成品存放区特定料盘内，完成入库；
第八步，仓库管理模块判断管材半成品存放区是否需要补料，若需要，执行第九步至第十一步；否则，执行第十二步；
第九步，管材原材料运输
第9.1步，仓库管理模块根据所缺管材半成品规格，生产补料文件，包括所需管材半成品的规格和数量；
第9.2步，指令发送模块发送取料信号，原材料存储区的行车从原材料存放区10取出相应管材原材料放置在上料输送线上；
第十步：管材原材料加工
第10.1步，分析计算模块根据设备的状态，选择加工设备即第一矫直设备或者第二矫直设备或者第一切割设备或者第二切割设备或者第一检测设备或者第二检测设备，指令发送模块发送原材料加工指令，并控制其完成对管材原材料的加工；在加工过程中，数据采集模块通过布置在各设备上的传感装置(激光位移传感器、扭矩传感器、位移传感器等)采集相关工艺加工数据和相关加工设备监测数据，分别储存于加工数据存储模块和设备监测数据存储模块内；
第10.2步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行处理，对管材进行在线质量检测，并把结果传输至总控系统；条件判断模块进行产 品质量判断：若产品质量合格，第一机械手抓取管材半成品放置在半成品暂存区内；若产品质量不合格，第一机械手抓取管材半成品放置在第一不合格存放区内；
第10.3步，条件判断模块进行如下判断：补料订单(包括所有种类的管材的加工以及所需管材数量)是否完成？若订单未完成，执行第九步至第十步；若订单完成，执行第十三步；
第十一步，管材半成品入库
第11.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态(空闲或者在岗)、电量信息(电量不足、电量充足)等；
第11.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车，这里假设选用第一AGV小车；
第11.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把半成品管材转移至管材半成品存放区特定料盘内，完成入库；
第十二步，仓储系统存料判断
第12.1步，仓库管理模块判断法兰存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第12.2步；
第12.2步，仓库管理模块判断原材料存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第十三步；
第十三步，总控系统进行判断是否有新订单产生：若有新订单产生，执行第一步至第十三步；若无新订单产生，结束；
故障检测方法具体包括以下步骤：
步骤a，构建数据库
根据智能车间各设备在工作过程中故障类型和原因，并结合专家人员的建议，构建故障数据库，数据库包含已知的有可能产生的故障类型和相应故障的表现形式，如图4中提供的表1所示，例如当监测到弯管设备(第一弯管设备或第二弯管设备)电机的三相电流I u、I v、I w过高时，其对应的故障类型为电机线圈相间短路，还有类似弯管设备摇臂故障、焊枪故障、坡口设备齿轮断裂、坡口设备轴承损坏、坡口设备转动件损坏、切割设备电机缺相、切割设备气源欠压、喷码设备墨线分裂异常、AGV小车光耦开关失灵、AGV小车丝杆提升机未定期润滑等故障；特别地，数据库具有自我更新功能，即当智能车间各设备所发生的故障未曾在数据库出现时，数据库可以自动把该故障纳入其中，进行不断的更新完善；
步骤b，构建卷积神经网络专家系统，具体的，
步骤b.1，预设卷积神经网络专家系统卷积分量的数量M，并初始化M＝1；
步骤b.2，基于数据库内的测量值与故障类型，构建卷积神经网络专家系统的输入矩阵X(数量为N，为已知)和对应的故障矩阵Y：
X＝[dB 3 t 2 T … I u I v I w]
Y＝[切割设备气源欠压…电机线圈相间短路]
步骤b.3，对输入矩阵X进行卷积计算，公式如下：
Figure PCTCN2021089551-appb-000009
Figure PCTCN2021089551-appb-000010
……
Figure PCTCN2021089551-appb-000011
式中，X i是第i个输入映射(1≤i≤N)，
Figure PCTCN2021089551-appb-000012
是第l个卷积核，L i是第i个卷积层中的总核数，
Figure PCTCN2021089551-appb-000013
是偏差，
Figure PCTCN2021089551-appb-000014
是第l个卷积输出映射，r表示共享权重的局部区域。
步骤b.4，通过如下公式增加卷积输出映射
Figure PCTCN2021089551-appb-000015
的非线性属性：
Figure PCTCN2021089551-appb-000016
步骤b.5，通过池化层计算，增加数据的平移不变性和防止过拟合，公式如下：
Figure PCTCN2021089551-appb-000017
式中，每个神经元
Figure PCTCN2021089551-appb-000018
都汇集在
Figure PCTCN2021089551-appb-000019
中的2×2区域上。
步骤b.6，计算卷积神经网络专家系统的输出尺寸：
Figure PCTCN2021089551-appb-000020
步骤b.7，根据以下公式计算各神经元
Figure PCTCN2021089551-appb-000021
对应故障的概率分布
Figure PCTCN2021089551-appb-000022
Figure PCTCN2021089551-appb-000023
式中，exp(θ i)是第i个神经元
Figure PCTCN2021089551-appb-000024
的概率分布，
Figure PCTCN2021089551-appb-000025
Figure PCTCN2021089551-appb-000026
是神经元
Figure PCTCN2021089551-appb-000027
的权重，S为输出矩阵所含元素个数；
步骤b.8，根据各故障的概率分布确定最终输出矩阵W；步骤b.9，卷积神经网络专家系统对输出矩阵W与已知故障矩阵Y进行对比分析：
若通过卷积神经网络专家系统计算的输出矩阵W内的故障类型与已知故障矩阵Y内的故障类型不完全相同，则执行步骤b.10至步骤b.11；
若通过卷积神经网络专家系统计算的输出矩阵W内的故障类型与已知故障矩阵Y内的故障类型全部相同，则执行步骤b.12；
步骤b.10，对卷积分量进行如下计算：
M＝M+1
步骤b.11，把输出尺寸δ i转变成输入矩阵X，执行步骤b.3至步骤b.9；
步骤b.12，确定卷积分量的数量M的取值与各比例因子
Figure PCTCN2021089551-appb-000028
的数值，并构建出卷积神经网络专家系统；
步骤c，数据采集
通过设置在智能车间各设备上各传感设备采集相关数据，包括弯管设备电机三相电流I u、I v、I w和三相电压U u、U v、U w、弯管设备摇臂转角θ、弯管设备摇臂扭矩T、焊枪振动dB 1、 焊枪温度t 1、坡口设备温度t 2、坡口设备工作声音dB 2、切割设备刀片上升速度v、切割设备声响dB 3、AGV小车运动距离s以及AGV小车举升机构声音dB 4；
步骤d，通过构建的卷积神经网络专家系统对步骤c所采集的数据进行分析处理；具体的，
步骤d.1，初始化卷积神经网络专家系统执行次数j＝0；
步骤d.2，构建卷积神经网络专家系统的输入矩阵X：
X＝[t 1 dB 1 t 2 v … I w s]
步骤d.3，采用步骤b构建的卷积神经网络专家系统对输入矩阵X进行分析；
步骤d.4，对卷积分量进行如下计算：
j＝j+1
步骤d.5，卷积神经网络专家系统判断j≤M是否成立？若成立，则把输出尺寸δ i转变成输入矩阵X，执行步骤d.3至步骤d.5；若不成立，卷积神经网络专家系统输出输出矩阵W；
步骤e，故障查询
监测系统根据卷积神经网络专家系统的输出结果W，访问故障数据库；若在故障数据库内查询到相应故障，则将故障发送至故障显示模块显示，用于指导维修工人维修，并启动备用设备；若在数据库内未查询到相应故障，执行步骤f；
步骤f，数据库更新
专家人员对故障和相应故障的表现形式进行判断，若故障和相应故障的表现形式相匹配，则把故障和相应故障的表现形式纳入数据库，并将故障发送至故障显示模块显示，用于指导维修工人维修，并启动备用设备；同时更新卷积神经网络专家系统；若故障和相应故障的表现形式不匹配，则根据专家人员的经验，获得相应表现形式对应的故障，并纳入数据库，同时更新卷积神经网络专家系统。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)具有与本申请所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像这里一样定义，不会用理想化或过于正式的含义来解释。
本申请中所述的“和/或”的含义指的是各自单独存在或两者同时存在的情况均包括在内。
本申请中所述的“连接”的含义可以是部件之间的直接连接也可以是部件间通过其它部件的间接连接。
以上述依据本发明的理想实施例为启示，通过上述的说明内容，相关工作人员完全可以在不偏离本项发明技术思想的范围内，进行多样的变更以及修改。本项发明的技术性范围并不局限于说明书上的内容，必须要根据权利要求范围来确定其技术性范围。

Claims (8)

  1. 一种多规格船用管材智能成形车间，其特征在于：包括顺次布设在生产线上的前处理加工区和加工工位区，在生产线的上游布设原材料存储区，在生产线的一侧布设用于存放管材半成品、管材成品以及法兰的仓储区；
    还包括运输系统和智能控制系统，智能控制系统对原材料存储区、前处理加工区以及加工工位区发送控制信号，实现对多规格管材的调取加工，智能控制系统同时对运输系统发送控制信号，在运输线上实现对多规格管材的运输转运。
  2. 根据权利要求1所述的多规格船用管材智能成形车间，其特征在于：前述的原材料储存区设有对多规格管材进行分类储存的原材料存放区，其通过实现原材料的运输；
    前述的智能控制系统包括相互连通的总控系统、MES系统、共享云以及监测系统，总控系统对MES系统、共享云以及监测系统进行指令调控；
    其中，总控系统包括分析计算模块、指令发送模块以及条件判断模块，其中，分析计算模块从原材料存储区、前处理加工区、加工工位区以及运输系统获取信号进行分析，指令发送模块将接收到的信号发送至分析计算模块，同时将施行指令发送至原材料存储区、前处理加工区、加工工位区以及运输系统，条件判断模块对产品质量进行判断；
    MES系统包括生产调度模块、数据采集模块、质量管理模块、仓库管理模块、订单管理模块以及设备管理模块，其中，生产调度模块用于对车间内的生产程序进行调度，数据采集模块用于对车间内生产信息进行收集，质量管理模块用于对产品的质量进行管理，仓库管理模块用于对车间内原材料存储区、仓储系统施行管理，订单模块用于对产品的订单信息进行管理，设备管理模块用于对车间内的设备进行管理；
    共享云包括RFID信息存储模块、加工数据存储模块、设备监测数据存储模块以及负载量数据存储模块，其中，RFID信息存储模块用于对RFID扫描信息的存储，加工数据存储模块用于对车间内加工数据进行存储，设备监测数据存储模块用于对车间内设备监测数据进行存储，负载量数据存储模块用于对车间内负载量数据进行存储；
    监测系统用于对车间内各部分的监测。
  3. 根据权利要求2所述的多规格船用管材智能成形车间，其特征在于：前述的前处理加工区包括上料输送线、第一矫直设备、第二矫直设备、第一切割设备、第二切割设备、第一检测设备、第二检测设备、半成品暂存区以及第一不合格存放区，其中上料输送线位于生产线的上游，在生产线的一侧顺次布设第一矫直设备、第一切割设备以及第一检测设备，生产线的另一侧顺次布设第二矫直设备、第二切割设备以及第二检测设备，第一矫直设备与第二矫直设备、第一切割设备与第二切割设备、第一检测设备与第二检测设备对称排布，还包括第一机械手，其将经过检测后的产品夹取转送至半成品暂存区，第一机械手将经过检测后的不合格产品夹取转送至第一不合格存放区。
  4. 根据权利要求3所述的多规格船用管材智能成形车间，其特征在于：前述的仓储系统包括料盘存放区、第一RFID扫描仪、法兰存放区、管材半成品存放区以及管材成品存放区，料盘存放区内放置若干料盘，第一RFID扫描仪用于对料盘信息进行扫描记录，在法兰存放区的入口处设置第一缓存区，在管材半成品存放区的入口处设置第二缓存区，在管材成品存放区的入口处设置第三缓存区，运输系统将料盘运送至相应缓存区，同时运输系统将法兰存放区、管材半成品存放区以及管材成品存放区内的对应产品运输至相应缓存区，在第一缓存区内设置第一管材抓取装置，其将法兰抓取放置位于第一缓存区的料盘内，第二缓 存区内设置第二管材抓取装置，其将管材半成品抓取放置位于第二缓存区的料盘内，第三缓存区内设置第三管材抓取装置，其将管材成品抓取放置第三缓存区的料盘内。
  5. 根据权利要求4所述的多规格船用管材智能成形车间，其特征在于：前述的加工工位区包括弯曲加工区、坡口加工区、缩或扩口加工区、焊接加工区以及二维码喷涂区，还安装有第二RFID扫描仪，装有产品的料盘经过第二RFID扫描仪扫描后通过运输系统分配至加工工位区内的各个区；
    弯曲加工区包括第一弯管设备、第二弯管设备、第一加工缓存区以及第一不合格存放区，运输系统将合格产品从匹配区域运送至第一加工缓存区，第二机械手将产品从第一加工缓存区夹取至第一弯管设备、第二弯管设备处进行弯曲处理后，再将弯曲处理后的不合格产品夹取放至第二不合格存放区内；
    坡口加工区包括第一坡口设备、第二坡口设备、第二加工缓存区以及第二不合格存放区，运输系统将合格产品从匹配区域运送至第二加工缓存区，第三机械手将产品从第二加工缓存区夹取至第一坡口设备、第二坡口设备处进行坡口处理后，再将坡口处理后的不合格产品夹取放至第三不合格存放区内；
    缩或扩口加工区包括第一缩或扩口设备、第二缩或扩口设备、第三加工缓存区以及第三不合格存放区，运输系统将合格产品从匹配区域运送至第三加工缓存区，第四机械手将产品从第三加工缓存区夹取至第一缩或扩口设备、第二缩或扩口设备处进行缩或扩口处理后，再将缩或扩口后的不合格产品夹取送至第四不合格存放区；
    焊接加工区包括第一焊接设备、第二焊接设备、第四加工缓存区以及第四不合格存放区，运输系统将合格产品从匹配区域运送至第四加工缓存区，第五机械手将产品从第四加工缓存区夹取至第一焊接设备、第二焊接设备进行焊接处理后，再将不合格产品夹取送至第五不合格存放区；
    二维码喷涂区包括第一二维码喷涂设备、第二二维码喷涂设备以及第五加工缓存区，运输系统将合格产品从匹配区域运送至第五加工缓存区，第六机械手将产品从第五加工缓存区夹取至第一二维码喷涂设备、第二二维码喷涂设备进行喷涂处理。
  6. 根据权利要求5所述的多规格船用管材智能成形车间，其特征在于：前述的运输系统包括第一AGV小车和第二AGV小车，还安装有为第一AGV小车和第二AGV小车充电的充电区。
  7. 根据权利要求6所述的多规格船用管材智能成形车间，其特征在于：在第一检测设备以及第二检测设备上安装激光位移传感器，在第一弯管设备以及第二弯管设备上安装角度传感器、扭矩传感器以及第一扫描仪，在第一缩或扩口设备以及第二缩或扩口设备上安装第二扫描仪、压力传感器和位移传感器，在第一坡口设备以及第二坡口设备上安装速度传感器、第三扫描仪以及表面粗糙度仪，在第一焊接设备、第二焊接设备上安装电压传感器、电流传感器和超声无损探伤仪。
  8. 一种基于上述任意权利要求所述的多规格船用管材智能成形车间的控制方法，其特征在于：分为两个部分，第一部分为调度方法，第二部分为故障检测方法，
    其中调度方法具体包括以下步骤：
    第一步：车间接收订单
    第1.1步，多规格船用管材智能成形车间收到第n批管材加工订单，其中n≥2，管材加工订单的内容包含订货方、交货期、所需管材规格、加工工序、焊接法兰信息以及所需数量；
    第1.2步，仓库管理模块通过第一RFID扫描仪获取位于仓储系统内的处于空置状态料盘的RFID芯片内所存储地址；
    第1.3步，订单管理模块根据车间接收到的订单内容生成各管材的加工工艺文件，并将加工工艺文件写入所获取的存储地址内；
    第二步：获取车间状态信息
    设备管理模块获取车间内各加工设备的状态，状态包括设备类型、设备性能、设备当前工作状态以及设备当前负载量；
    第三步：根据加工设备状态对订单内容进行调度
    第3.1步，确定对订单内容进行加工所需的时间，总控系统通过订单管理模块获取订单所加工管材规格的种类，分析计算模块计算所有种类管材完成所有工序所需加工的时间；
    第3.2步，确定第n批订单等待加工时间，分析计算模块计算订单中所有种类的管材完成加工所需的时间；
    第3.3步，确定管材运输时间，总控系统根据管材规格从负载量数据存储模块处获取加工设备针对不同规格管材的负载量信息，分析计算模块计算各加工设备和仓储之间的运输距离、所需运输次数以及每种规格管材所需运输时间，最终获取订单中所有种类管材所需运输时间；
    第3.4步，确定订单加工完成所需要的总时间；
    第3.5步，确定最优的调度策略，生产调度模块指定若干种不同的生产调度计划，分别计算出不同生产调度计划的总加工时间，并采用智能调度算法对不同排产加工完成所需总时间进行优化，得到总加工时间最短的排产方案，并将最优调度策略发送至总控系统；
    第四步：半成品管材运输
    第4.1步，指令发送模块向第一AGV小车、第二AGV小车发送运输指令，第一AGV小车、第二AGV小车反馈其状态信息，此状态信息包括运输状态以及电量信息；
    第4.2步，分析计算模块根据反馈状态信息，选择第一AGV小车或者第二AGV小车；
    第4.3步，在仓储系统中，管材半成品存放区内部的运输系统把所需管材半成品运送至第二缓存区处，同时第一AGV小车或者第二AGV小车把料盘运送至第二缓存区处，第二管材抓取装置抓取管材半成品放入料盘内，第一AGV小车或者第二AGV小车运输管材半成品至加工工位区；
    第五步：半成品管材加工
    第5.1步，第一RFID扫描仪扫描获取料盘上的RFID芯片，第二RFID扫描仪通过RFID芯片的存储地址访问管材加工信息，包括管材成形工艺以及成形要求；
    第5.2步，分析计算模块根据所获取的管材加工工艺顺序选择加工工位区中的坡口加工区、弯曲加工区、缩或扩口加工区或者焊接加工区，第一AGV小车或者第二AGV小车把料盘运输至第一加工缓存区或者第二加工缓存区或者第三加工缓存区或者第四加工缓存区；
    第5.3步，指令发送模块发送相应的加工指令，并控制相关加工设备完成对管材的加工，在加工过程中，数据采集模块通过安装在各设备上的传感装置采集加工数据以及加工设备监测数据，分别储存于加工数据存储模块以及设备监测数据存储模块内；
    第5.4步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行分析，完成管材的在线质量检测，并把结果传输至总控系统；条件判断模块进行产品质 量判断：若产品质量合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在相关加工缓存区内；若产品质量不合格，第一机械手或者第二机械手或者第三机械手或者第四机械手抓取管材放置在第二不合格存放区或者第三不合格存放区或者第四不合格存放区或者第五不合格存放区内；
    第5.5步，条件判断模块进行如下判断：管材要求加工工序是否完成？若未完成，执行第5.1步至第5.5步；若完成，执行第5.6步；
    第5.6步，条件判断模块进行如下判断：订单是否完成？若订单未完成，执行第四步至第五步；若订单完成，执行第六步；
    第六步，二维码喷涂
    第6.1步，第一AGV小车或第二AGV小车将存放合格产品的料盘运输至第五加工缓存区；
    第6.2步，第一二维码喷涂设备或第二二维码喷涂设备根据管材规格信息访问共享云，获取管材的信息，生成相对应的二维码；
    第6.3步，指令发送模块发送二维码喷涂指令，并控制第六机械手抓取管材放置在第一二维码喷涂设备或第二二维码喷涂设备上，完成喷码操作；第六机械手再把管材放置于料盘内；
    第6.4步，条件判断模块进行如下判断：所有管材的喷码操作是否完成？若未完成，执行第6.1步至第6.4步；若完成，执行第七步；
    第七步：合格产品入库
    第7.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态以及电量信息；
    第7.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车；
    第7.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把成品管材转移至管材成品存放区特定料盘内，完成入库；
    第八步，仓库管理模块判断管材半成品存放区是否需要补料，若需要，执行第九步至第十一步；否则，执行第十二步；
    第九步，管材原材料运输
    第9.1步，仓库管理模块根据所缺管材半成品规格，生产补料文件，包括所需管材半成品的规格和数量；
    第9.2步，指令发送模块发送取料信号，原材料存储区的行车从原材料存放区取出相应管材原材料放置在上料输送线上；
    第十步：管材原材料加工
    第10.1步，分析计算模块根据设备的状态，选择加工设备即第一矫直设备或者第二矫直设备或者第一切割设备或者第二切割设备或者第一检测设备或者第二检测设备，指令发送模块发送原材料加工指令，并控制其完成对管材原材料的加工；在加工过程中，数据采集模块通过布置在各设备上的传感装置采集相关工艺加工数据和相关加工设备监测数据，分别储存于加工数据存储模块和设备监测数据存储模块内；
    第10.2步，质量管理模块根据管材规格信息访问共享云，获取管材加工数据，并对数据进行处理，对管材进行在线质量检测，并把结果传输至总控系统；条件判断模块进行产品质 量判断：若产品质量合格，第一机械手抓取管材半成品放置在半成品暂存区内；若产品质量不合格，第一机械手抓取管材半成品放置在第一不合格存放区内；
    第10.3步，条件判断模块进行如下判断：补料订单是否完成？若订单未完成，执行第九步至第十步；若订单完成，执行第十三步；
    第十一步，管材半成品入库
    第11.1步，指令发送模块向第一AGV小车或者第二AGV小车发送运输指令，第一AGV小车或者第二AGV小车反馈其状态信息，包括运输状态以及电量信息；
    第11.2步，分析计算模块根据第一AGV小车或者第二AGV小车反馈的状态信息，选择合适的AGV小车；
    第11.3步，第一AGV小车或者第二AGV小车把料盘运输至第三缓存区，第三管材抓取装置把半成品管材转移至管材半成品存放区特定料盘内，完成入库；
    第十二步，仓储系统存料判断
    第12.1步，仓库管理模块判断法兰存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第12.2步；
    第12.2步，仓库管理模块判断原材料存放区是否需要补料？若需要补料，则发出报警，提示管理人员上料；否则，执行第十三步；
    第十三步，总控系统进行判断是否有新订单产生：若有新订单产生，执行第一步至第十三步；若无新订单产生，结束；
    故障检测方法具体包括以下步骤：
    步骤a，构建数据库
    根据智能车间各设备在工作过程中故障类型和原因，并结合专家人员的建议，构建故障数据库，数据库包含已知的有可能产生的故障类型和相应故障的表现形式；
    步骤b，构建卷积神经网络专家系统
    步骤c，数据采集
    通过设置在智能车间各设备上各传感设备采集相关数据，包括弯管设备电机三相电流I u、I v、I w和三相电压U u、U v、U w、弯管设备摇臂转角θ、弯管设备摇臂扭矩T、焊枪振动dB 1、焊枪温度t 1、坡口设备温度t 2、坡口设备工作声音dB 2、切割设备刀片上升速度v、切割设备声响dB 3、AGV小车运动距离s以及AGV小车举升机构声音dB 4；
    步骤d，通过构建的卷积神经网络专家系统对步骤c所采集的数据进行分析处理；
    步骤e，故障查询
    监测系统根据卷积神经网络专家系统的输出结果δ i，访问故障数据库；若在故障数据库内查询到相应故障，则将故障发送至故障显示模块显示，用于指导维修工人维修，并启动备用设备；若在数据库内未查询到相应故障，执行步骤f；
    步骤f，数据库更新
    专家人员对故障和相应故障的表现形式进行判断，若故障和相应故障的表现形式相匹配，则把故障和相应故障的表现形式纳入数据库，并将故障发送至故障显示模块显示，用于指导维修工人维修，并启动备用设备；同时更新卷积神经网络专家系统；若故障和相应故障的表现形式不匹配，则根据专家人员的经验，获得相应表现形式对应的故障，并纳入数据库，同时更新卷积神经网络专家系统。
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Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114742360A (zh) * 2022-03-15 2022-07-12 湘南学院 一种作业车间多agv的组合充电系统的分析方法
CN114942614A (zh) * 2022-03-25 2022-08-26 上海江南船舶管业有限公司 一种焊机管控方法、系统、存储介质及智能终端
CN115113598A (zh) * 2022-07-19 2022-09-27 湖北三环锻造有限公司 一种锻件生产调度系统
CN115187213A (zh) * 2022-07-15 2022-10-14 河南科技大学 一种汽车零部件制造转运管理系统
CN116542467A (zh) * 2023-05-06 2023-08-04 深圳市易立德信息科技有限公司 一种产品开发需求管理系统以及方法
CN116796998A (zh) * 2023-08-03 2023-09-22 深圳市儒道数据分析有限公司 一种车间的动态排产系统及方法
CN117301465A (zh) * 2023-09-21 2023-12-29 昆山万丰达智能装备有限公司 一种化纤制备智能系统
CN117666486A (zh) * 2022-09-08 2024-03-08 宝山钢铁股份有限公司 一种实现钢管逐支跟踪的系统及其控制方法
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106056298A (zh) * 2016-06-08 2016-10-26 宁波赛夫科技有限公司 工厂智能车间实时调度系统
CN109917770A (zh) * 2019-04-18 2019-06-21 成都飞机工业（集团）有限责任公司 一种大型结构件自动化生产线智能管控系统
CN110217525A (zh) * 2019-06-25 2019-09-10 哈尔滨工程大学 一种船舶管材加工车间管材自动化仓库设备
JP2020515958A (ja) * 2017-10-17 2020-05-28 広東工業大学Ｇｕａｎｇｄｏｎｇ Ｕｎｉｖｅｒｓｉｔｙ Ｏｆ Ｔｅｃｈｎｏｌｏｇｙ スマート工場の透明なモニタリング方法及びシステム
CN111319730A (zh) * 2020-02-28 2020-06-23 徐州尚航船舶配件有限公司 一种用于船舶支架配件的生产流水线
CN112184473A (zh) * 2020-08-28 2021-01-05 江苏科技大学 一种多规格船用管材智能成形车间及控制方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106873564B (zh) * 2017-04-26 2019-09-20 南京航空航天大学 基于智能车间的流动式多智能体实时调度方法
CN107832497B (zh) * 2017-10-17 2018-08-28 广东工业大学 一种智能车间快速定制设计方法及系统
CN107861478B (zh) * 2017-10-17 2018-08-14 广东工业大学 一种智能车间平行控制方法及系统
CN109634229A (zh) * 2018-11-19 2019-04-16 东莞理工学院 一种基于大数据的智能工厂制造管理系统
KR102102346B1 (ko) * 2019-10-21 2020-04-22 (주) 리얼웹 함정설비의 상태기반 정비지원 시스템 및 방법

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106056298A (zh) * 2016-06-08 2016-10-26 宁波赛夫科技有限公司 工厂智能车间实时调度系统
JP2020515958A (ja) * 2017-10-17 2020-05-28 広東工業大学Ｇｕａｎｇｄｏｎｇ Ｕｎｉｖｅｒｓｉｔｙ Ｏｆ Ｔｅｃｈｎｏｌｏｇｙ スマート工場の透明なモニタリング方法及びシステム
CN109917770A (zh) * 2019-04-18 2019-06-21 成都飞机工业（集团）有限责任公司 一种大型结构件自动化生产线智能管控系统
CN110217525A (zh) * 2019-06-25 2019-09-10 哈尔滨工程大学 一种船舶管材加工车间管材自动化仓库设备
CN111319730A (zh) * 2020-02-28 2020-06-23 徐州尚航船舶配件有限公司 一种用于船舶支架配件的生产流水线
CN112184473A (zh) * 2020-08-28 2021-01-05 江苏科技大学 一种多规格船用管材智能成形车间及控制方法

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114742360A (zh) * 2022-03-15 2022-07-12 湘南学院 一种作业车间多agv的组合充电系统的分析方法
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CN114942614A (zh) * 2022-03-25 2022-08-26 上海江南船舶管业有限公司 一种焊机管控方法、系统、存储介质及智能终端
CN115187213A (zh) * 2022-07-15 2022-10-14 河南科技大学 一种汽车零部件制造转运管理系统
CN115187213B (zh) * 2022-07-15 2023-04-07 河南科技大学 一种汽车零部件制造转运管理系统
CN115113598A (zh) * 2022-07-19 2022-09-27 湖北三环锻造有限公司 一种锻件生产调度系统
CN115113598B (zh) * 2022-07-19 2023-02-21 湖北三环锻造有限公司 一种锻件生产调度系统
CN117666486A (zh) * 2022-09-08 2024-03-08 宝山钢铁股份有限公司 一种实现钢管逐支跟踪的系统及其控制方法
CN116542467A (zh) * 2023-05-06 2023-08-04 深圳市易立德信息科技有限公司 一种产品开发需求管理系统以及方法
CN116796998A (zh) * 2023-08-03 2023-09-22 深圳市儒道数据分析有限公司 一种车间的动态排产系统及方法
CN117301465A (zh) * 2023-09-21 2023-12-29 昆山万丰达智能装备有限公司 一种化纤制备智能系统
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CN119458381A (zh) * 2025-01-13 2025-02-18 山西兰一科技有限公司 一种机器人控制数据处理方法

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