CN112809274B - Welding robot control system based on big data - Google Patents
Welding robot control system based on big data Download PDFInfo
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- CN112809274B CN112809274B CN202110197960.1A CN202110197960A CN112809274B CN 112809274 B CN112809274 B CN 112809274B CN 202110197960 A CN202110197960 A CN 202110197960A CN 112809274 B CN112809274 B CN 112809274B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K37/00—Auxiliary devices or processes, not specially adapted to a procedure covered by only one of the preceding main groups
- B23K37/02—Carriages for supporting the welding or cutting element
- B23K37/0252—Steering means
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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Abstract
The invention discloses a welding robot control system based on big data, and belongs to the field of welding robots. The automatic welding robot comprises a big data platform, a delivery service module, a fault monitoring module, a diagnosis and analysis module and a feedback maintenance module, wherein the big data platform, the delivery service module, the fault monitoring module, the diagnosis and analysis module and the feedback maintenance module are connected with one another and share data, the delivery service module sends out a welding robot meeting functional requirements according to user requirements, a fault monitoring unit is used for positioning equipment and monitoring operation conditions, the diagnosis and analysis module collects operation index data of the welding robot and compares the operation index data with a normal data model, if abnormal data are detected, the feedback maintenance module rapidly positions a product which is welded by the robot recently, the product is recovered and detected according to a warehousing path and batches, and meanwhile, the repair equipment is replaced, so that the efficiency of the whole automatic welding process is improved, and the outflow of unqualified products and the input of human resources are reduced.
Description
Technical Field
The invention relates to the technical field of welding robots, in particular to a welding robot control system based on big data.
Background
Most of the welding robots currently used in China are automatic control operation machines engaged in industrial welding, cutting and spraying, and due to the richness of various product types in the market, robot products related to electric welding, arc welding and laser welding functions are greatly moved to the market, and the automatic production line taking the welding robots as the leading part is also continuously popularized thanks to the promotion of domestic and foreign enterprises to the market of the welding robots and the development and progress of the technology.
With the popularization of welding robots, the market has higher and higher requirements on welding robot control systems. The automatic welding process of the existing production line has complete facilities and complete functions, but faults occurring occasionally on machinery are still unavoidable, certain delay exists in the fault detection process, some unqualified welding line products inevitably occur in the period of time, and human resources are wasted after the process enters the manual quality inspection link.
What is needed is a big data-based welding robot control system for positioning these unqualified products, recovering and detecting the products according to warehousing routes and batches, and replacing the repair equipment, thereby improving the efficiency of the whole automatic welding process and reducing the outflow of the unqualified products and the investment of the equipment.
Disclosure of Invention
The present invention is directed to a welding robot control system based on big data to solve the above problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme:
a welding robot control system based on big data comprises a big data platform, a delivery service module, a fault monitoring module, a diagnosis and analysis module and a feedback maintenance module, wherein the big data platform is connected with the delivery service module, the fault monitoring module, the diagnosis and analysis module and the feedback maintenance module, and data is shared;
the goods delivery service module is used for receiving user requirements and delivering a welding robot meeting functional requirements to a user, the fault monitoring unit is used for positioning equipment and monitoring the operation condition of the welding robot, the diagnosis and analysis module collects various operation index data of the welding robot and compares the operation index data with a normal data model, if abnormal data is detected, the diagnosis and analysis module feeds back an overhaul module to quickly position a product which is welded recently by the welding robot, the product is recovered and detected according to a warehousing path and batches, and the welding robot is replaced and repaired at the same time, so that the efficiency of the whole automatic welding process is improved, and the outflow of unqualified products and the input of equipment are reduced;
the feedback maintenance module comprises a product positioning unit, a product recovery unit, a product detection unit and a machine repair unit, wherein the product positioning unit is used for each welding robot to mark a label with batch information and position information on each welded product, the labels are stored in sequence in batches, the product recovery unit recovers the welded products of the fault welding robot from the corresponding positions of the inventory according to the corresponding batches, the product detection unit is used for detecting the welding accuracy of the recovered products, and the machine repair unit is used for replacing the welding robot with the component having the fault function from the production line after the error is detected;
the feedback maintenance module helps the big data platform to quickly find out and recover products welded by the fault machine, and the fault machine is maintained and replaced while the products are detected, so that the number of unqualified products entering a manual quality inspection link is reduced, the continuous work of a production line is ensured, and the influence on the working process is reduced;
the product positioning unit comprises a data storage module, welding equipment, a welding operation module, a label setting module and a roller belt distribution model, wherein the welding equipment is connected with the welding operation module, the data storage module is connected with the welding equipment, and the label setting module is connected with the data storage module;
the data storage module is used for storing information of products welded by the welding equipment, the information content comprises a warehousing path, a processing batch and the number of the products, the welding equipment utilizes the welding operation module to complete the starting and the regulation of welding, the label setting module comprises a label classification submodule, a processing batch submodule and a storage position setting submodule, the label classification submodule marks different labels on the products in different batches, the label content comprises the welding time and the storage position condition, the storage position setting submodule distributes storage positions to the products in each batch according to the number of the products and puts the storage positions in the labels together with the time information, and the warehousing path of the products is obtained by contrasting a roller belt distribution model on a production line through position information on the labels;
the product positioning unit positions the products by using the label information and stores the products in a warehouse according to batches, and the related information of the products is connected with the corresponding equipment so as to accurately find out the products which are likely to be careless and missed on the corresponding production line when the equipment fails, thereby effectively improving the product recovery efficiency;
the product recovery unit comprises a control center, a welding machine, an intelligent cabinet, a transmission roller, a return roller and a product recovery library, wherein the control center is connected with the welding machine, the intelligent cabinet is connected with the control center, the welding machine is connected with the intelligent cabinet through the transmission roller, and the product recovery library is connected with the intelligent cabinet through the return roller;
the control center receives a platform instruction, analyzes and processes products which are welded before a welding robot breaks down and are not subjected to manual quality inspection according to batches, regulates and stops the operation of a welding machine, controls the opening of the intelligent cabinet, the welding machine conveys the products to the intelligent cabinet through a conveying roller after welding, stores and records the products according to the batch sequence when the products are put in storage, the intelligent cabinet receives the regulation and control of the control center, puts down the products of corresponding batches and quantity according to a control command, and the product recycling bin recycles the products through a return roller;
the product recovery unit utilizes the control center to connect the welding equipment and the product storage, can timely regulate and stop the operation of the welding robot when receiving the information of equipment faults, reduces unnecessary material loss, automatically transfers products which are likely to be careless and careless by using the intelligent cabinet, is convenient and quick to operate, and reduces the waste of human resources;
the intelligent cabinet comprises a label identification unit, a cabinet opening regulation and control unit, a counter and a lower opening, wherein the label identification unit is positioned at a passage opening of the intelligent cabinet connected with the conveying roller, the counter is positioned at the front end of the lower opening, and the lower opening is positioned at a passage opening of the intelligent cabinet connected with the return roller;
the label identification unit is used for identifying the batch and quantity information on the product label, storing the corresponding quantity of products into the corresponding cabinet grids according to the batch, the cabinet opening regulation and control unit is used for receiving a command sent by the control center, opening the cabinet grids filled with the corresponding batch and placing the products to the lower opening, the counter monitors and counts the number of the products at the lower opening, and the cabinet grids are automatically closed after the number is reached;
the intelligent cabinet box carries out label identification when products are put into the cabinet, counts the batch information of the products, utilizes the cabinet opening regulation and control unit to automatically open the cabinet lattices storing the corresponding batches of the products when the products are regulated and controlled by the control center to be released, releases the products, is quick and labor-saving, and saves the time for searching and finding the products;
the delivery service module comprises a user unit, a supply demand unit and a delivery dispatching unit, wherein the user unit is connected with the supply demand unit, the other end of the supply demand unit is connected with the big data platform, one end of the delivery dispatching unit is connected with the user unit, and the other end of the delivery dispatching unit is connected with the big data platform;
the user unit feeds back the demand to a supply demand unit, the supply demand unit transmits the demand of the user to a big data platform, the big data platform sorts and evaluates according to the demand of the user, screens, customizes and improves the welding robot meeting the functional requirements of the user, then sends the welding robot to the user unit through a conveying and dispatching unit, and records the demand data of the user;
the delivery service module is used for interaction between a user and a welding robot manufacturer, communication between a supply party and a demand party is facilitated, equipment which best meets the requirements of the user is delivered to the hand of the user through big data platform sorting evaluation, barrier-free communication between the supply party and the demand party is achieved, the user can obtain satisfactory equipment and good service, data records are reserved, requirements are convenient to analyze, and efficiency and quality of delivery service are improved;
the fault monitoring module comprises a machine positioning unit, an equipment monitoring unit, a running track unit and a function service unit, wherein the machine positioning unit is arranged and positioned on the welding robots, the position of each piece of equipment on a production line is displayed in a big data platform, the equipment monitoring unit is provided with a camera on each welding robot, whether the equipment runs normally is monitored, the running track unit records the action track of each welding robot when the welding seam is welded, and the function service unit records the service life and the maintenance condition of the welding robots;
the fault monitoring module monitors the welding robot in real time, judges the operation condition of equipment in a positioning, monitoring and data recording mode, takes the motion trail as reference, and takes the service life and the maintenance times as auxiliary reference, so that the judgment accuracy is improved, and the fault diagnosis is timely carried out on the welding robot on the corresponding station after the equipment is judged to have a fault;
the diagnostic analysis module comprises a data acquisition unit, an operation index unit, an abnormality detection unit, an analysis unit and a result unit, and the diagnostic analysis process of the welding robot needs to pass through the data acquisition unit, the operation index unit, the abnormality detection unit, the analysis unit and the result unit in sequence;
the data acquisition unit is used for acquiring various technical indexes and component conditions of the welding robot, the operation index unit records various index data of the welding robot under normal work, the data serving as reference standards comprises a tool center point position, a welding rod diameter, welding current and welding speed, the abnormality detection unit is used for respectively generating abnormality detection models for various normal index data, the analysis unit diagnoses the error position of the welding robot through analysis of the abnormal data according to the abnormal conditions of the model detection data, the result unit transmits the diagnosis result to the big data platform, and the big data platform gives a subsequent solution of the fault;
the diagnosis and analysis unit analyzes and diagnoses the parts with faults of the welding robot in a data acquisition, recording and data model checking mode, and visually analyzes the fault parts by using numerical values, so that a large data platform can timely process the working abnormity of the production line of the equipment;
the welding robot comprises a controller, a programming command unit, a data storage unit, an error feedback unit, an alarm unit and an equipment parameter set, wherein the programming command unit is connected with the controller;
the programming command unit is used for compiling an operation program of the robot, the data storage unit is used for storing equipment parameters, an operation track and finished welding product information of the welding robot, the error feedback unit transmits the information to the alarm unit after detecting an error in the equipment, the alarm unit gives an alarm to the controller, the equipment parameter set comprises an inertia control unit, an electric welding unit, a temperature regulating unit, a pressure regulating unit and a dust collecting unit, the inertia control unit records the influence of inertia on the response speed of the equipment, the electric welding unit regulates the opening degree of a welding tongs and the welding period, the temperature regulating unit controls the welding temperature, the pressure regulating unit controls the pressure of the welding tongs of the welding robot during closing and pressurizing, and the dust collecting unit is arranged in the dust collecting unit to avoid the influence of dust in the environment on moving parts;
the welding robot utilizes the controller to control the change of various parameters in a centralized manner, so that the equipment can be automatically adjusted and efficiently operated according to the requirement, and in addition, the welding robot stores all data generated in the operation in the equipment, so that the equipment can be called and checked and backed up in time when a fault occurs;
the abnormal detection unit detects data abnormality on the abnormal detection model by adopting a K nearest neighbor algorithm, firstly, all normal points are marked in the model, the normal points are distributed in a cluster mode and represent different numerical values in indexes, all index numerical values of each data cluster are marked by using a minimum circle, and two chords are arbitrarily made on the circleThen respectively making vertical bisector of said two chords, making the intersection point of two vertical bisectors be centre of circle O, calculating maximum distance L between centre of circle O and peripheral point max ，L max Namely the radius of a circle, a coordinate axis and a grid line are established on the abnormity detection model, the circle center O is set as the center of the coordinate axis, and a near-adjacent point P to be detected is newly added i ＝{P 1 ，P 2 ，P 3 ，P 4 ……P n And (4) each adjacent point has a unique coordinate in the model, and the center of a circle O and the adjacent point P are calculated by using an Euclidean distance formula i The distance formula is as follows:
if L (O, P)<L max Then the neighbor point P i Belongs to the data group, belongs to the normal index range, if L (O, P)>L max Then the neighboring point P i Abnormal data;
the abnormal detection unit analyzes abnormal data on the abnormal detection model by using a K nearest neighbor algorithm, so that the distribution and the quantity of the data can be visually known, and the accuracy of data judgment is improved.
Compared with the prior art, the invention has the following beneficial effects:
a welding robot control system based on big data is characterized in that a product welded by a robot is rapidly positioned after an index abnormality is monitored, the product is recovered and detected according to a warehousing path and batches, the outflow of unqualified products and the investment of equipment are reduced, a big data platform is helped to rapidly find out and recover the welded product of a fault machine, the fault machine is overhauled and replaced while the product is detected, the number of unqualified products entering a manual quality inspection link is reduced, the continuous work of a production line is ensured, and the influence on a working process is reduced.
The product is positioned and stored in a warehouse according to batches by utilizing the label, and the related information of the product is connected with the corresponding equipment structure, so that the product which is possibly careless and overlooked on the corresponding production line can be accurately found when the equipment breaks down, the operation of the welding robot can be timely dispatched when the information of the equipment fault is received, unnecessary material loss is reduced, the product which is possibly careless and overlooked is automatically transferred by using the intelligent cabinet, the operation is convenient and fast, the waste of human resources is reduced, and the time for searching and finding the product is saved.
The user and the welding robot manufacturer interact directly, exchange between the supply and demand parties is facilitated, the equipment which best meets the user requirements is dispatched to the hands of the user through big data platform sorting and evaluation, barrier-free communication between the supply and demand parties is achieved, the user can obtain satisfactory equipment and good service, data records are reserved, analysis requirements are facilitated, and the efficiency and quality of delivery service are improved.
Use fault monitoring module real time monitoring welding robot, through the location, the operation condition of control and data record's mode judgement equipment, make the reference with the motion track, do the auxiliary reference with service life and maintenance number of times, be favorable to improving the accurate nature of judgement, and in time carry out fault diagnosis to the welding robot on the corresponding station after judging equipment breaks down, the diagnostic analysis unit carries out analysis and diagnosis through the part that welding robot broke down of data acquisition record and the mode of checking the data model, utilize numerical value to analyze out the fault part directly perceivedly, be convenient for big data platform in time handle the work anomaly of this equipment place production line.
The welding robot utilizes the change of each item parameter of controller centralized control, is favorable to equipment to carry out autonomic adjustment and high-efficient operation as required, and in addition, the welding robot still with the whole storages of data that produce in the operation among the equipment, in time transfer when the trouble of being convenient for takes place look over and back-up, use K neighbour's algorithm to do unusual data analysis to equipment parameter on unusual detection model, do benefit to directly perceived understanding data distribution and quantity, improve the accuracy that data were judged.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a big data based welding robot control system according to the present invention;
FIG. 2 is a schematic diagram of a product positioning unit of a big data based welding robot control system of the present invention;
FIG. 3 is a schematic diagram of a product recovery unit of a big data based welding robot control system of the present invention;
FIG. 4 is a schematic view of a welding robot of a big data based welding robot control system of the present invention;
fig. 5 is a schematic diagram of an anomaly detection model of a big data based welding robot control system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides the following technical solutions:
as shown in fig. 1, a big data based welding robot control system comprises a big data platform, a delivery service module, a fault monitoring module, a diagnosis and analysis module and a feedback maintenance module, wherein the big data platform is connected with the delivery service module, the fault monitoring module, the diagnosis and analysis module and the feedback maintenance module, and shares data, the delivery service module is connected with the fault monitoring module, the fault monitoring module is connected with the diagnosis and analysis module, and the diagnosis and analysis module is connected with the feedback maintenance module;
the goods delivery service module is used for receiving user requirements and delivering a welding robot meeting functional requirements to a user, the fault monitoring unit is used for positioning equipment and monitoring the operation condition of the welding robot, the diagnostic analysis module acquires various operation index data of the welding robot and compares the operation index data with a normal data model, if abnormal data is detected, the diagnostic analysis module feeds back an overhaul module to quickly position a product which is welded by the robot recently, the product is recovered and detected according to a warehousing path and batches, and the welding robot is replaced at the same time, so that the efficiency of the whole automatic welding process is improved, and the outflow of unqualified products and the investment of equipment are reduced;
the feedback maintenance module comprises a product positioning unit, a product recovery unit, a product detection unit and a machine repair unit, wherein the product positioning unit is used for each welding robot to mark a label with batch information and position information on each welded product, the labels are stored in sequence in batches, the product recovery unit recovers the welded products of the fault welding robot from the corresponding positions of the inventory according to the corresponding batches, the product detection unit is used for detecting the welding accuracy of the recovered products, and the machine repair unit is used for replacing the welding robot with the component having the fault function from the production line after the error is detected;
the delivery service module comprises a user unit, a supply demand unit and a delivery dispatching unit, wherein the user unit is connected with the supply demand unit, the other end of the supply demand unit is connected with the big data platform, one end of the delivery dispatching unit is connected with the user unit, and the other end of the delivery dispatching unit is connected with the big data platform;
the user unit feeds back the demand to the supply demand unit, the supply demand unit transmits the demand of the user to the big data platform, the big data platform sorts and evaluates according to the demand of the user, screens, customizes and improves the welding robot meeting the functional requirements of the user, then sends the welding robot to the user unit through the conveying and dispatching unit, and records the demand data of the user;
the fault monitoring module comprises a machine positioning unit, an equipment monitoring unit, a running track unit and a function service unit, wherein the machine positioning unit is arranged and positioned on the welding robots, the position of each piece of equipment on a production line is displayed in a big data platform, the equipment monitoring unit is provided with a camera on each welding robot, whether the equipment runs normally is monitored, the running track unit records the action track of each welding robot when a welding seam is welded, and the function service unit records the service life and the maintenance condition of the welding robots;
the diagnostic analysis module comprises a data acquisition unit, an operation index unit, an abnormality detection unit, an analysis unit and a result unit, and the diagnostic analysis process of the welding robot needs to pass through the data acquisition unit, the operation index unit, the abnormality detection unit, the analysis unit and the result unit in sequence;
the data acquisition unit is used for acquiring various technical indexes and component conditions of the welding robot, the operation index unit records various index data of the welding robot under normal work, the data serving as reference standards comprises a tool center point position, a welding rod diameter, welding current and welding speed, the abnormality detection unit respectively generates abnormality detection models for various normal index data, the analysis unit diagnoses the error position of the welding robot through analysis of the abnormal data according to the abnormal conditions of the model detection data, the result unit transmits the diagnosis result to the big data platform, and the big data platform gives a subsequent solution of the fault;
as shown in fig. 2, the product positioning unit includes a data storage module, a welding device, a welding operation module, a label setting module, and a roll belt distribution model, wherein the welding device is connected to the welding operation module, the data storage module is connected to the welding device, and the label setting module is connected to the data storage module;
the data storage module is used for storing information of products welded by the welding equipment, the information content comprises a warehousing path, a processing batch and the number of the products, the welding equipment utilizes the welding operation module to complete the starting and the regulation of welding, the label setting module comprises a label classification submodule, a processing batch submodule and a storage position setting submodule, the label classification submodule marks different labels on the products in different batches, the label content comprises the welding time and the storage position condition, the storage position setting submodule distributes storage positions to the products in each batch according to the number of the products and puts the storage positions in the labels together with the time information, and the warehousing path of the products is obtained by contrasting a roller belt distribution model on a production line through position information on the labels;
as shown in fig. 3, the product recovery unit includes a control center, a welding machine, an intelligent cabinet, a transfer roller, a return roller, and a product recovery warehouse, the control center is connected to the welding machine, the intelligent cabinet is connected to the control center, the welding machine is connected to the intelligent cabinet through the transfer roller, and the product recovery warehouse is connected to the intelligent cabinet through the return roller;
the control center receives platform instructions, products which are welded before the welding robot breaks down and are not subjected to manual quality inspection are analyzed and processed according to batches, the operation of the welding machine is mediated, the opening of the intelligent cabinet is controlled, the welding machine conveys the products to the intelligent cabinet through the conveying rollers after welding is finished, the products are stored and recorded according to the batch sequence when being put in storage, the intelligent cabinet receives the control center regulation, the products of corresponding batches and quantity are put down according to the control commands, and the products are taken back by the product recycling storage through the return rollers;
the intelligent cabinet comprises a label identification unit, a cabinet opening regulation and control unit, a counter and a lower opening, wherein the label identification unit is positioned at a passage opening of the intelligent cabinet connected with the conveying roller, the counter is positioned at the front end of the lower opening, and the lower opening is positioned at a passage opening of the intelligent cabinet connected with the return roller;
the label identification unit is used for identifying batch and quantity information on product labels, storing products in corresponding quantities in corresponding cabinet grids according to the batch, the cabinet opening regulation and control unit is used for receiving a command sent by the control center, opening the cabinet grids filled with the corresponding batches, placing the products to the downward placing opening, monitoring and counting the number of the products at the downward placing opening by the counter, and automatically closing the cabinet grids after the number is reached;
as shown in fig. 4, the data acquisition unit acquires various parameter indexes from a welding robot, the welding robot includes a controller, a programming command unit, a data storage unit, an error feedback unit, an alarm unit and an equipment parameter set, the programming command unit is connected with the controller, the data storage unit is connected with the controller, the sensing unit is connected with the controller, the error feedback unit is connected with the alarm unit, and the equipment parameter set is connected with the controller;
the programming command unit is used for compiling an operation program of the robot, the data storage unit is used for storing equipment parameters, an operation track and finished welding product information of the welding robot, the error feedback unit transmits the information to the alarm unit after detecting an error in the equipment, the alarm unit gives an alarm to the controller, the equipment parameter set comprises an inertia control unit, an electric welding unit, a temperature regulating unit, a pressure regulating unit and a dust collecting unit, the inertia control unit records the influence of inertia on the response speed of the equipment, the electric welding unit regulates the opening degree of a welding tongs and the welding period, the temperature regulating unit controls the welding temperature, the pressure regulating unit controls the pressure of the welding tongs of the welding robot during closing and pressurizing, and the dust collecting unit is arranged in the dust collecting unit to avoid the influence of dust in the environment on moving parts;
as shown in fig. 5, the abnormality detection unit detects data abnormality on the abnormality detection model by using the K nearest neighbor algorithm, and firstly marks all normal points in the model, the normal points are gathered and distributed in groups, and represent different values in the index, and marks all index values of each data group with a smallest circle, and arbitrarily makes two chords on the circle, and then respectively makes perpendicular bisectors of the two chords, and the intersection point of the two perpendicular bisectors is the circle center O of the circle, and calculates the maximum distance L between the circle center O and the peripheral point max ，L max Namely the radius of a circle, a coordinate axis and a grid line are established on the abnormity detection model, the center of the circle O is set as the center of the coordinate axis, and a near-adjacent point P to be detected is newly added i ＝{P 1 ，P 2 ，P 3 ，P 4 ……P n And (4) each adjacent point has a unique coordinate in the model, and a circular point O and an adjacent point P are calculated by using an Euclidean distance formula i The distance formula is as follows:
if L is(O，P)<L max Then the neighbor point P i Belongs to the data group, belongs to the normal index range, if L (O, P)>L max Then the neighboring point P i Is the exception data.
The first embodiment is as follows:
assuming that it is necessary to check the welding speed of the welding robot using an abnormality detection model in an abnormality detection unit, the maximum distance L between the center O of the circle and the peripheral point max 50.21, neighbor point P 1 The coordinates in the abnormality detection model are (30.31, 39.05), and the neighboring points P 2 Coordinates in the abnormality detection model are (40.89, 29.87), and the circular point O and the neighboring point P are calculated using the euclidean distance formula 1 And P 2 Distance (c):
because of L (P) 1 ，O)<L max Then P is 1
Belongs to the data group, is the normal welding speed, because L (P) 1 ，O)>L max Then P is 1 The method belongs to abnormal data, and the welding robot has problems in welding speed and needs to analyze and overhaul in time.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (7)
1. A welding robot control system based on big data which characterized in that: the system comprises a big data platform, a delivery service module, a fault monitoring module, a diagnosis and analysis module and a feedback maintenance module, wherein the big data platform is mutually connected with the delivery service module, the fault monitoring module, the diagnosis and analysis module and the feedback maintenance module, and shares data;
the goods delivery service module is used for receiving user requirements and delivering a welding robot meeting functional requirements to a user, the fault monitoring unit is used for positioning equipment and monitoring the operation condition of the welding robot, the diagnosis and analysis module acquires various operation index data of the welding robot and compares the operation index data with a normal data model, if abnormal data is detected, the diagnosis and analysis module feeds back an overhaul module to quickly position a product which is welded recently by the welding robot, and the product is recovered and detected according to a warehousing path and batches, and meanwhile, the welding robot is repaired;
the feedback maintenance module comprises a product positioning unit, a product recovery unit, a product detection unit and a machine repair unit, wherein the product positioning unit is used for each welding robot to mark a label with batch information and position information on each welded product, the labels are stored in sequence in batches, the product recovery unit recovers the welded products of the fault welding robot from the corresponding positions of the inventory according to the corresponding batches, the product detection unit is used for detecting the welding accuracy of the recovered products, and the machine repair unit is used for replacing the welding robot with the component having the fault function from the production line after the error is detected;
the product positioning unit comprises a data storage module, welding equipment, a welding operation module, a label setting module and a roller belt distribution model, wherein the welding equipment is connected with the welding operation module, the data storage module is connected with the welding equipment, and the label setting module is connected with the data storage module;
the data storage module is used for storing information of products welded by the welding equipment, the information content comprises a warehousing path, a processing batch and the number of the products, the welding equipment utilizes the welding operation module to complete the starting and the regulation of welding, the label setting module comprises a label classification submodule, a processing batch submodule and a storage position setting submodule, the label classification submodule marks different labels on the products in different batches, the label content comprises the welding time and the storage position condition, the storage position setting submodule distributes storage positions to the products in each batch according to the number of the products and puts the storage positions in the labels together with the time information, and the warehousing path of the products is obtained by contrasting a roller belt distribution model on a production line through the position information on the labels;
the product recovery unit comprises a control center, a welding machine, an intelligent cabinet, a transmission roller, a return roller and a product recovery library, wherein the control center is connected with the welding machine, the intelligent cabinet is connected with the control center, the welding machine is connected with the intelligent cabinet through the transmission roller, and the product recovery library is connected with the intelligent cabinet through the return roller;
the control center receives platform instructions, products which are welded before the welding robot breaks down and are not subjected to manual quality inspection are analyzed and processed in batches, operation of the welding machine is mediated, opening of the intelligent cabinet is controlled, the welding machine conveys the products to the intelligent cabinet through the conveying rollers after the products are welded, storage records are carried out in batches when the products are put in storage, the intelligent cabinet receives control center regulation, the products corresponding to batches and the number are put down according to control commands, and the products are taken back by the product recycling bin through the return rollers.
2. The big data based welding robot control system according to claim 1, wherein: the intelligent cabinet comprises a label identification unit, a cabinet opening regulation and control unit, a counter and a lower discharge opening, wherein the label identification unit is positioned at a passage opening of the intelligent cabinet connected with the conveying roller, the counter is positioned at the front end of the lower discharge opening, and the lower discharge opening is positioned at a passage opening of the intelligent cabinet connected with the return roller;
the label identification unit is used for identifying the batch and quantity information on the product label, storing the corresponding quantity of products into the corresponding cabinet grids according to the batch, the cabinet opening regulation and control unit is used for receiving a command sent by the control center, opening the cabinet grids filled with the corresponding batch and placing the products to the downward opening, the counter monitors and counts the number of the products at the downward opening, and the cabinet grids are automatically closed after the number is reached.
3. The big data based welding robot control system according to claim 1, wherein: the delivery service module comprises a user unit, a supply demand unit and a delivery dispatching unit, wherein the user unit is connected with the supply demand unit, the other end of the supply demand unit is connected with the big data platform, one end of the delivery dispatching unit is connected with the user unit, and the other end of the delivery dispatching unit is connected with the big data platform;
the user unit feeds back the demand to the supply demand unit, the supply demand unit transmits the user demand to the big data platform, the big data platform sorts and evaluates according to the user demand, screens, customizes and improves the welding robot meeting the functional requirements of the user, then sends the welding robot to the user unit through the conveying and dispatching unit, and records the user demand data.
4. The big data based welding robot control system according to claim 1, wherein: the fault monitoring module comprises a machine positioning unit, an equipment monitoring unit, a running track unit and a function service unit, wherein the machine positioning unit is arranged and positioned on a welding robot, the position of each piece of equipment on a production line is displayed in a big data platform, a camera is arranged on each welding robot by the equipment monitoring unit, whether the operation of the monitoring equipment is normal or not is monitored, the running track unit records the action track of each welding robot when the welding seam is welded, and the function service unit records the service life and the maintenance condition of the welding robot.
5. The big data based welding robot control system according to claim 4, wherein: the diagnosis and analysis module comprises a data acquisition unit, an operation index unit, an abnormality detection unit, an analysis unit and a result unit, and the diagnosis and analysis process of the welding robot needs to sequentially pass through the data acquisition unit, the operation index unit, the abnormality detection unit, the analysis unit and the result unit;
the data acquisition unit is used for gathering each item technical indicator and the part condition of welding robot, operation index unit gets down each item index data record of welding robot under with normal work, and the data as reference standard includes instrument central point position, welding rod diameter, welding current and welding speed, unusual detecting element is the abnormal detection model that generates each item normal index data respectively, detects the data abnormal conditions according to the model, the analysis unit is through the position of the error that takes place of welding robot to the analysis diagnosis of abnormal data, the result unit spreads into big data platform with the diagnostic result, gives out the follow-up solution of trouble by the big platform of data.
6. The big data based welding robot control system according to claim 5, wherein: the welding robot comprises a controller, a programming command unit, a data storage unit, an error feedback unit, an alarm unit and an equipment parameter set, wherein the programming command unit is connected with the controller;
the programming command unit is used for compiling the function procedure of robot, data storage unit is used for saving welding robot's equipment parameter, operation orbit and the welding product information of accomplishing, error feedback unit conveys alarm unit with information after detecting the inside error of equipment, alarm unit sends the warning to the controller, the equipment parameter set includes inertia control unit, electric welding unit, thermoregulation unit, pressure regulating unit and dust absorption unit, inertia control unit records inertia to equipment response speed's influence, electric welding unit adjusts welding tongs opening, welding cycle, thermoregulation unit control welding temperature, the pressure size when the closed pressurization of pressure regulating unit control welding robot welding tongs, the inside dust extraction that sets up of dust absorption unit avoids the dust in the environment to moving part's influence.
7. The big data based welding robot control system according to claim 6, wherein: the abnormal detection unit detects data abnormality on the abnormal detection model by adopting a K nearest neighbor algorithm, firstly, all normal points are marked in the model, the normal points are in cluster gathering distribution and represent different numerical values in indexes, all index numerical values of each data group are marked by using a minimum circle, two chords are arbitrarily made on the circle, then perpendicular bisectors of the two chords are respectively made, the intersection point of the two perpendicular bisectors is the circle center O of the circle, and the maximum distance L between the circle center O and a peripheral point is calculated max ，L max Namely the radius of a circle, a coordinate axis and a grid line are established on the abnormity detection model, the center of the circle O is set as the center of the coordinate axis, and a near-adjacent point P to be detected is newly added i ＝{P 1 ，P 2 ，P 3 ，P 4 ……P n And (4) each adjacent point has a unique coordinate in the model, and a central O and an adjacent point P are calculated by using an Euclidean distance formula i The distance formula is as follows:
if L (O, P)<L max Then the neighboring point P i Belongs to the data group, belongs to the normal index range, if L (O, P)>L max Then the neighbor point P i Is the exception data.
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