CN108227636B - Laser engraving machine working system and method based on cloud load balance control - Google Patents
Laser engraving machine working system and method based on cloud load balance control Download PDFInfo
- Publication number
- CN108227636B CN108227636B CN201810045651.0A CN201810045651A CN108227636B CN 108227636 B CN108227636 B CN 108227636B CN 201810045651 A CN201810045651 A CN 201810045651A CN 108227636 B CN108227636 B CN 108227636B
- Authority
- CN
- China
- Prior art keywords
- laser engraving
- load
- engraving machine
- cloud
- cloud control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/414—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller
- G05B19/4142—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller characterised by the use of a microprocessor
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/34—Director, elements to supervisory
- G05B2219/34013—Servocontroller
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Human Computer Interaction (AREA)
- Manufacturing & Machinery (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Laser Beam Processing (AREA)
- Numerical Control (AREA)
Abstract
The invention discloses a laser engraving machine working system based on cloud load balancing control, which comprises a plurality of laser engraving machines, a cloud control end and a plurality of mobile intelligent terminals. The invention also discloses a laser engraving machine working method based on cloud load balance control, wherein the cloud control end receives the image transmitted by the mobile intelligent terminal and converts the image into a G code; evaluating the load condition of the current global laser engraving machine, searching a target laser engraving machine and keeping the system load balance; sending the G code to a target laser engraving machine; and (4) analyzing and interpolating numerical control of the target scheduling laser engraving machine, and engraving the workpiece to be machined. According to the technical scheme, the laser engraving machine is subjected to distributed control through the cloud end, real-time dynamic management and load balancing scheduling of the laser engraving machine are achieved, the degree of freedom, the portability and the maintainability of the laser engraving machine are expanded, the utilization rate of the laser engraving machine is improved, and the large-scale application of the laser engraving machine in the fields of creative design and handicraft design is facilitated.
Description
Technical Field
The invention belongs to the technical field of laser engraving, and particularly relates to a cloud-controlled laser engraving machine working system and method.
Background
The laser engraving machine is a device for cutting or engraving non-metallic materials such as organic glass, plastics, paper and the like by utilizing laser beams, and under the control of a control system, a driving motor drives a laser engraving head to engrave or cut a workpiece to be machined on an objective table. The conventional laser engraving machine consists of upper computer software and a lower computer, wherein the upper computer software is responsible for image processing, issues a working instruction to the lower computer and transmits sample track data, and a driving motor of the lower computer controls the X-direction slide way and the laser engraving head to slide respectively to engrave workpieces. The laser engraving has the advantages of high speed, high precision, good quality, low power consumption and the like, and is widely applied to the industries of advertisement industry, process industry, die industry, building industry, decoration industry, leather industry and the like.
Chinese patent application publication No. 201820113U, entitled "a laser engraving machine control device", includes: an upper computer (PC), a lower computer (singlechip, preceding stage drive, power drive stage, stepping motor and current control link); the PC transmits information to the singlechip through an RS232 interface and an asynchronous serial communication mode; the singlechip transmits data to a preceding stage driving circuit; the stepper is driven by a power driver stage. But the upper computer is a PC machine, has large volume, is not easy to carry and has high price.
Chinese patent application publication No. 206029024U, publication No. 2017-03-22, entitled "a small laser engraving machine based on mobile terminal control", includes: the mobile terminal comprises a processor, a clock signal generator and a Bluetooth transmitting unit; the laser engraving machine comprises a Bluetooth receiving unit, an Arduino core development board, a PLC, a peripheral power supply circuit, a mechanical device and a laser transmitter. The utility model tries to solve the problem of the volume of the upper computer by adopting the control of the mobile terminal, emphasizes that the mobile terminal and the laser engraving machine ensure the clock synchronization but the mobile terminal has weak processing capacity and limited moving distance; the method is suitable for personal creative design and small-craft design and processing, but faults are difficult to be processed in time.
Chinese patent application publication No. 206335254U, publication No. 2017-7-8, entitled "a 3D laser automated interior carving system", includes: the mobile terminal, the cloud server and the control host are mainly characterized in that an individual 3D figure image is generated by the mobile terminal APP, an order is formed after the image is processed by the cloud server, parameters or settings are carried out after the image is downloaded by the control host, and then the laser inner carving equipment is controlled to process read data. However, it is not described how to control the internal working mechanism of the main machine, and the focus is on the mechanical working part.
The invention patent of Chinese patent application publication No. 106292535A, published as 2017-1-4 and named numerical control machining system and cloud platform-based numerical control machining system, comprises a numerical control machine, a machine simulation platform and a cloud platform for sending workpiece machining programs to the numerical control machine. The cloud platform monitors and judges whether the numerical control machine tool is abnormal in real time; after receiving the workpiece machining program sent by the simulation platform, the cloud platform can recommend the numerical control machine tool to a machine tool simulation platform user according to the precision, the distance and the time by combining the set information sent by the simulation platform. But how to judge the abnormality and how to acquire the recommended parameters are not specifically described and do not take over; the machine tool has the advantages of being convenient to use and study, reducing the danger of a beginner operating the machine tool, reducing the loss caused by processing errors and enabling the machine tool to be more controllable in working.
The invention patent of Chinese patent application publication No. 105260794A, 2016-1-20, entitled load prediction method of cloud data center, comprises the following steps: collecting historical data of a prediction cloud data center; calculating the correlation between the CPU historical data and other performance indexes; extracting a time window; extracting characteristics; fusing the characteristics; compressing the features based on a self-encoding neural network; supervised learning is available; and predicting the result.
Chinese patent application publication No. 107197053a, published 2017-09-22, entitled "a load balancing method and apparatus", the method comprising: acquiring load data of each monitoring resource of a virtual machine in a cloud data center management platform at regular time; judging whether the virtual machine needs to be subjected to capacity expansion or capacity reduction according to the obtained load data and a pre-established load balancing strategy in the load balancer; and executing corresponding capacity expansion or capacity reduction operation according to the judgment result and the load balancing strategy. The monitoring resources include: CPU, memory, disk, and/or network traffic.
Chinese patent application publication No. 107026908A, published as 2017-8-8, entitled "a load balancing method, load balancer, and load balancing", mainly includes the following load balancing methods at present: (1) the static load balancing algorithm is used for distributing the request to the server according to a fixed rule; the ith request is distributed to the ith (mod n) server, for example, according to a polling algorithm. (2) The dynamic load balancing algorithm is used for distributing the request to the server with the lowest current load; the degree of server load is based on the number of active connections, response time, etc. (3) The source address hash scheduling algorithm is that the IP address of the client is calculated through a hash function to obtain a numerical value, and the numerical value performs modular operation on the size of the server list to obtain the server to be accessed by the client. The same client is mapped to the same back-end server for access each time.
Based on the above description, the laser engraving technology still belongs to a weaker field, mainly represented by: if the upper computer adopts a PC, the problems of large volume, inconvenience in carrying, high price and the like exist; if the mobile terminal is adopted, the calculation and processing capabilities are limited, and the large-scale application is difficult. The upper computer and the lower computer are connected in a one-to-one mode, so that the carving task is easily failed due to the faults of the laser carving machine and the errors of the carving program. The laser engraving machine based on the cloud platform is an effective way for overcoming the defects of the traditional engraving machine (an upper computer and a lower computer are in a one-to-one connection mode), and the cloud processing and cloud manufacturing are realized by managing, controlling and load balancing and scheduling a plurality of laser engraving machines.
Disclosure of Invention
The invention aims to provide a laser engraving machine working system and method based on cloud load balance control, which comprehensively utilize the technologies of Internet of things, cloud computing, mechanical control and the like, realize real-time dynamic management and load balance scheduling of a laser engraving machine through the distribution control of a cloud end on the laser engraving machine, expand the degree of freedom, portability and maintainability of the laser engraving machine, improve the utilization rate of the laser engraving machine and contribute to promoting the large-scale application of the laser engraving machine in the fields of creative design and handicraft design.
In order to achieve the above purpose, the solution of the invention is:
a laser engraving machine working system based on cloud load balance control comprises a plurality of laser engraving machines, a cloud control end and a plurality of mobile intelligent terminals;
the laser engraving machine is internally provided with a wireless transceiving module supporting WIFI, and is connected with the cloud control end based on the WIFI and keeps interaction;
the mobile intelligent terminal is internally provided with a wireless communication module, is in communication connection with the cloud control terminal based on a GPRS or wireless WIFI mode, and submits a carving task to the cloud control terminal;
when the mobile intelligent terminal submits the engraving task to the cloud control terminal, the cloud control terminal schedules the target laser engraving machine to execute the task and keeps the system load balanced.
A laser engraving machine working method based on cloud load balance control comprises the following steps:
step S1, the laser engraving machine is powered on and is automatically connected with a cloud control end;
step S2, after the mobile intelligent terminal is successfully connected with the cloud control terminal, normal communication is kept;
step S3, the cloud control end periodically collects the state information and the load condition parameters of the global laser engraving machine;
step S4, the mobile intelligent terminal submits an image which meets the carving specification to the cloud control terminal;
step S5, the cloud control end receives the image transmitted by the mobile intelligent terminal and converts the image into a G code; evaluating the load condition of the current global laser engraving machine, searching a target laser engraving machine and keeping the system load balance; sending the G code to a target laser engraving machine;
and step S6, the target dispatching laser engraving machine receives the G code, analyzes and interpolates numerical control, and engraves the workpiece to be machined.
In step S3, the operating state of the laser engraving machine includes the following cases:
if the working state is offline, the connection between the laser engraving machine and the cloud control end is not established;
if the working state is 'carving', the laser carving machine is in use, and the load parameters are displayed;
if the working state is 'error', the laser engraving machine is in fault;
if the working state is idle, the laser engraving machine is idle, and the printing task is not executed.
The specific content of the step S3 is:
step S31, the laser engraving machine collects current load data and sends the current load data to the cloud control end in a WIFI mode;
and step S32, the cloud control end receives the load data, resets the format, filters and arranges the format, evaluates the load condition of the current laser engraving machine and determines the working state.
The specific content of the step S5 is:
step S51, according to the step 2, periodically obtaining the working state information and the load condition parameters of the global laser engraving machine, and evaluating the load of the laser engraving machine, the average load of the global laser engraving machine and the load unbalance; if the load imbalance degree is smaller than the allowable value delta, the system is considered to be stable in operation and balanced in load under the condition of the current allowable value, load balancing scheduling is not needed, and the step S55 is switched; otherwise, executing step S52;
step S52, pre-processing is performed: presetting a load adjusting parameter lambda, calculating the difference value of the load condition of each laser engraving machine and the average load of the overall laser engraving machines, and determining a heavy load set H, a medium load set M and a light load set L; the heavy load concentrated laser engraving machine and the light load concentrated laser engraving machine are ranked from strong to weak according to comprehensive processing capacity, and corresponding tasks are ranked from big to small according to load requirements; evaluating the average load of the current local laser engraving machine;
step S53, local unbalance redistribution: the tasks are sequentially and preferentially distributed to the laser engraving machines with strong comprehensive processing capacity according to the magnitude sequence of the load requirements, and the minimum constraint of the average load of the local laser engraving machines is met;
step S54, updating the set: updating the classification of the laser engraving machine set, and re-determining a heavy load set H ', a medium load set M ' and a light load set L '; if the number of the elements in the heavy load set and the light load set is 0, go to step S56;
step S55, update iteration: calculating the average load of the global laser engraving machine, adjusting a preset load adjusting parameter lambda, and turning to the step S52;
and step S56, outputting the current load balancing optimal scheduling result.
The specific content of the step S7 is:
step S71, collecting the operation data of the laser engraving machine;
step S72, carrying out multi-channel signal filtering, amplification, A/D conversion and convergence on the collected operation data, and sending the operation data to a cloud control end;
step S73, the cloud control end receives the operation signal and carries out fault diagnosis;
step S74, the cloud control end sends fault estimation information to the mobile intelligent terminal, and the working state displays 'error'; and (4) manually intervening to remove the fault according to the type and the position of the fault and the reason causing the fault.
In step S73, the process of performing the fault diagnosis is:
①, collecting signals of the laser engraving machine in a normal state, and establishing a characteristic parameter standard sample library;
step ②, establishing a common fault diagnosis knowledge base and an inference rule base;
step ③, the sensor keeps continuous and tracking monitoring to the laser engraving machine, the cloud control end receives signals, carries out state estimation and correlation analysis, and compares with the characteristic parameter standard sample library to determine the current state of the engraving machine system;
step ④, if the current state is 'error', determining the fault type, position and fault reason by rule reasoning according to the common fault diagnosis knowledge base;
and ⑤, if the corresponding fault type can not be found in the common fault diagnosis knowledge base, adding the fault type, the position, the characteristic parameter and the fault reason in the common fault diagnosis knowledge base, and updating the inference rule base.
After step S6, the method further includes:
step S7, the cloud control end receives the operation data of the laser engraving machine in real time, and once the laser engraving machine breaks down in the engraving process, the online fault diagnosis is carried out and the result is forwarded to the mobile intelligent terminal;
step S8, when the mobile intelligent terminal receives the carving 'finished' information, the mobile intelligent terminal indicates that the carving task is finished; and if an error prompt is received, the engraving task is selected to be terminated or resubmitted.
After the scheme is adopted, the invention has the following advantages:
(1) off-line carving is realized, and only a carving image is submitted on the mobile intelligent terminal according to specifications;
(2) according to the load condition of the current laser engraving machine, the utilization rate of the engraving machine is improved and the overall task completion time is reduced through cloud control and optimized scheduling;
(3) the user can conveniently adjust the intelligent mobile terminal in time according to the requirements, the freedom degree of completing the carving task is expanded, and the potential threat of production and operation is reduced;
(4) the cloud server receives the operation conditions of the current laser engraving machine in real time, including faults occurring in the engraving process, so that manual management is effectively reduced, and automation and scale of laser engraving machine management are promoted.
Drawings
FIG. 1 is an overall architecture diagram of the system of the present invention;
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
The technical solution and the advantages of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides a laser engraving machine working system based on cloud load balancing control, which comprises a plurality of laser engraving machines, a cloud control end and a plurality of mobile intelligent terminals, wherein the laser engraving machines, the cloud control end and the mobile intelligent terminals are respectively introduced below.
The laser engraving machine is internally provided with a controller module, a laser control module, a motor driving module, a wireless transceiving module, a data acquisition module, a power supply module and an auxiliary module. The controller module is the core of the control and data processing of the laser engraving machine; the laser control module is responsible for protecting and driving the laser head to work; the motor driving module is used for driving the X axis and the Y axis of the stepping motor to move; the wireless transceiver module is in charge of wireless communication with the cloud control end; the data acquisition module is responsible for acquiring the operating data of the laser engraving machine; the auxiliary module provides auxiliary functions of cooling and dehumidifying a fan for the laser engraving machine; and the power supply module is responsible for providing power supply support for the modules. In specific implementation, the controller module adopts an Arduino UNO development board and a CNC Shield v3 expansion board; the laser control module adopts an ULN2003 compound transistor to protect and drive a 250w laser head; the motor drive adopts an A4988 stepping driver to drive and control a 42 stepping motor; the wireless transceiving module adopts a WIFI data transceiving module based on STM 32; the data acquisition module consists of a sensor group (including sensors of speed, displacement, acceleration, temperature, current, voltage, frequency and the like) and a conditioning board. The power supply adopts a 12V2A power supply.
The cloud control end comprises an image conversion G code module, a load balancing scheduling module, a fault diagnosis module, server software and the like. The image conversion G code module is responsible for converting the image into G code. The load balancing scheduling module makes full use of the processing capacity of each laser engraving machine, so that the engraving tasks are uniformly distributed on each laser engraving machine, and the constraint premise of minimizing the average load of local laser engraving machines is met. And the fault diagnosis module is responsible for processing, analyzing and receiving signals acquired by the fault acquisition device, carrying out state estimation and correlation analysis, comparing with the characteristic parameter standard sample library and judging whether faults exist. The server software is the operation supporting software of the image conversion G code module, the load balancing scheduling module and the fault diagnosis module.
The mobile intelligent terminal is a software and hardware integrated device, and is composed of hardware modules such as a central processing unit, a memory, an LCD display, a touch screen input interface, a communication conversion interface and the like, and a wireless communication module is arranged in the mobile intelligent terminal. The method comprises the following steps that the mobile intelligent terminal interacts and shares with a cloud control terminal in real time, Android is developed based on a hardware structure, and the following system functions are integrated, wherein the functions comprise: and the application software system integrates functions of submitting a carving picture on line, receiving fault alarm, checking carving progress, processing a fault suggestion and the like.
Fig. 1 is a system architecture diagram of the laser engraving machine working for realizing cloud load balancing control according to the present invention. After the laser engraving machines are started, the laser engraving machines are connected with a cloud control end through a wireless transceiving module based on WIFI and keep interactive; the mobile intelligent terminal is in communication connection with the cloud control terminal based on a GPRS or wireless WIFI mode and submits a carving task to the cloud control terminal, and the cloud control terminal distributes and controls the laser carving machine, performs load balancing and completes the carving task; when the mobile intelligent terminal submits the engraving task to the cloud control terminal, the cloud control terminal schedules the target laser engraving machine to execute the task and keeps the system load balanced. When the mobile intelligent terminal receives the 'completion' information fed back by the cloud control terminal, the mobile intelligent terminal indicates that the carving task is completed smoothly; when the mobile intelligent terminal receives the feedback that the cloud control end receives the error prompt, the fault exists in the carving system, and the task can be selected to be terminated or the carving task can be resubmitted.
As shown in fig. 2, the present invention further provides a working method of a laser engraving machine based on cloud load balancing control, which includes the following steps:
step S1, the laser engraving machine is powered on, each analog port and each digital port in the laser engraving machine are initialized, network connection parameters are set, and the laser engraving machine is automatically connected with a cloud control end;
step S2, after the mobile intelligent terminal is successfully connected with the cloud control terminal through GPRS or wireless WIFI, normal communication is kept;
step S3, the cloud control end periodically collects the state information and the load condition parameters of the global laser engraving machine;
if the working state is offline, the connection between the laser engraving machine and the cloud control end is not established;
if the working state is 'carving', the laser carving machine is in use, and the load parameters are displayed;
if the working state is 'error', the laser engraving machine is in fault;
if the working state is idle, the laser engraving machine is idle, and the printing task is not executed.
The method specifically comprises the following steps:
step S31, the laser engraving machine collects current load data and sends the current load data to the cloud control end in a WIFI mode;
step S32, the cloud control end receives the load data, resets the format, filters and arranges the format, evaluates the load condition of the current laser engraving machine and determines the working state;
step S4, the mobile intelligent terminal submits the tasks to be engraved to the cloud control terminal in an image mode meeting the engraving specification;
step S5, the cloud control end receives the image transmitted by the mobile intelligent terminal and converts the image into a G code; evaluating the load condition of the current global laser engraving machine, searching a target laser engraving machine and keeping the system load balance; sending the G code to a target laser engraving machine;
the method specifically comprises the following steps:
step S51, according to the step 2, the working state information and the load condition parameters (such as carving step pitch, carving speed, power, carving depth and material (such as leather, acrylic, wood board, bicolor board, crystal and bamboo)) of the global laser carving machine are periodically obtained, and the load P required by the laser carving machine to complete all current tasks is evaluatedi(equation (1)), average load of global laser engraving machine
(normalized average of load parameter vector)Value, equation (2)), load imbalance ξ (mean of the arithmetic square root of the sum of load parameter variances, equation (3)):
wherein x isijSetting the jth load parameter value of the ith laser engraving machine; k is a radical ofjIs the corresponding weight of the jth load parameter, and
is the jth load parameter mean; 1,2, …, n; j is 1,2, …, m; n represents the number of laser engravers; m represents the number of load parameters.
The smaller the load imbalance, the better the current load condition of the working system of the laser engraving machine. If the load imbalance ξ is smaller than the allowable value δ, the system is considered to be stable in operation and balanced in load under the condition of the current allowable value, load balancing scheduling is not needed, and the step S55 is switched; otherwise, executing step S52;
step S52, pre-processing is performed: presetting a load adjusting parameter lambda, and calculating the difference value between the load condition of each laser engraving machine and the average load of the global laser engraving machines
Determining a heavy load set H, a medium load set M and a light load set L, merging the heavy load set H and the light load set L (H ∪ L), and sequencing the laser engraving machines according to the comprehensive processing capacity from strong to weak, wherein the evaluation indexes of the comprehensive processing capacity comprise engraving speed, engraving step pitch, power (complete machine power and laser power) and engraving speedEvaluating the load requirements and ordering from large to small according to the formula (1) by the corresponding tasks, evaluating the local average load of the H ∪ L set according to the formula (2);
step S53, local unbalance redistribution: the tasks are sequentially and preferentially distributed to the laser engraving machines with strong comprehensive processing capacity according to the size of the load requirement, and the average load minimization requirement of the local laser engraving machines is met. The method specifically comprises the following steps:
suppose that the integrated throughput sequence of the H ∪ L laser engraving machine is CM1≥CM2≥...≥CMn'Task t1,t2,...,tm'Has a load requirement sequence of p1≥p2≥...≥pm'，PiFor the ith laser engraving machine load, n 'and m' are respectively the laser engraving machine and the task number, and the task distribution process is as follows:
step ①: t1Is preferentially allocated to CM1，P1＝p1；
Step ②: t2Is preferentially allocated to CM1，P1＝P1+p2But the requirements are satisfied
Otherwise t2Is preferentially allocated to CM2，P2＝p2；t3Is preferentially allocated to CM1，P1＝P1+p3But the requirements are satisfiedOtherwise t3Is preferentially allocated to CM2，P2＝P2+p3But the requirements are satisfiedOtherwise t3Is preferentially allocated to CM3，P3＝p3(ii) a Continuing to complete task t according to the method4,t5,..,tm'Distributing;
step ③, re-evaluating the average load of the H ∪ L set, and if the average load of the H ∪ L set is attenuated, going to step ①;
and step ④, outputting the result of the last task allocation.
Step S54, updating the set: updating the classification of the laser engraving machine set, and determining a heavy load set H ', a medium load set M ' and a light load set L '; if the number of the elements in the heavy load set and the light load set is 0, go to step S56;
step S55, update iteration: calculating the average load of the global laser engraving machine, adjusting a preset load adjusting parameter (for example, λ ═ λ +0.1), and going to step S52;
and step S56, outputting the current load balancing optimal scheduling result.
Step S6, the target dispatching laser engraving machine receives the G code, analyzes and numerically controls interpolation, and the driving motor respectively controls X, Y to slide to the slide way and the laser engraving head to engrave the workpiece to be processed;
step S7, the cloud control end receives the operation data of the laser engraving machine in real time, and once the laser engraving machine breaks down in the engraving process, the online fault diagnosis is carried out and the result is forwarded to the mobile intelligent terminal; the method specifically comprises the following steps:
step S71, the data acquisition module of the laser engraving machine includes: sensors or conditioning plates for speed, displacement, acceleration, temperature, current, voltage, frequency and the like are used for collecting the operating data of the laser engraving machine;
step S72, the data acquisition module filters, amplifies, A/D converts and converges the multi-channel signals, and sends the signals to the cloud control end in a wireless WIFI mode;
step S73, the cloud control end receives the operation signal and carries out fault diagnosis;
step S74, the cloud control end sends fault estimation information to the mobile intelligent terminal, and the working state displays 'error'; and (4) removing the fault by manual intervention if necessary according to the type and the part of the fault and the reason causing the fault.
The fault diagnosis process is as follows:
①, acquiring signals in a normal state through a data acquisition module attached to the laser engraving machine, and establishing a characteristic parameter standard sample library;
step ②, establishing a common fault diagnosis knowledge base (including fault type, position, characteristic parameter and fault reason) and an inference rule base;
step ③, the sensor keeps continuous and tracking monitoring to the laser engraving machine, the cloud control end receives signals, carries out state estimation and correlation analysis, and compares with the characteristic parameter standard sample library to determine the current state of the engraving machine system;
step ④, if the current state is 'error', determining the fault type, position and fault reason by rule reasoning according to the common fault diagnosis knowledge base;
and ⑤, if the corresponding fault type can not be found in the common fault diagnosis knowledge base, adding the fault type, the position, the characteristic parameter and the fault reason in the common fault diagnosis knowledge base, and updating the inference rule base.
Step S8, when the mobile intelligent terminal receives the carving 'finished' information, the mobile intelligent terminal indicates that the carving task is finished; and if an error prompt is received, the engraving task is selected to be terminated or resubmitted.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.
Claims (7)
1. A laser engraving machine working method based on cloud load balance control is characterized by comprising the following steps:
step S1, the laser engraving machine is powered on and is automatically connected with a cloud control end;
step S2, after the mobile intelligent terminal is successfully connected with the cloud control terminal, normal communication is kept;
step S3, the cloud control end periodically collects the state information and the load condition parameters of the global laser engraving machine;
step S4, the mobile intelligent terminal submits an image which meets the carving specification to the cloud control terminal;
step S5, the cloud control end receives the image transmitted by the mobile intelligent terminal and converts the image into a G code; evaluating the load condition of the current global laser engraving machine, searching a target laser engraving machine and keeping the system load balance; sending the G code to a target laser engraving machine;
the specific content of the step S5 is:
step S51, according to the working state information and the load condition parameters of the global laser engraving machine obtained periodically in the step S3, the load P of the laser engraving machine is evaluatediGlobal laser engraver average load
And a load imbalance ξ;
wherein x isijSetting the jth load parameter value of the ith laser engraving machine; k is a radical ofjIs the corresponding weight of the jth load parameter, and
is the jth load parameter mean; 1,2, …, n; j is 1,2, …, m; n represents the number of laser engravers; m represents the number of load parameters;
the smaller the load unbalance degree is, the better the current load state of the working system of the laser engraving machine is; if the load imbalance ξ is smaller than the allowable value δ, the system is considered to be stable in operation and balanced in load under the condition of the current allowable value, load balancing scheduling is not needed, and the step S55 is switched; otherwise, executing step S52;
step S52, pre-processing is performed: presetting a load adjusting parameter lambda, and calculating the load condition and the overall situation of each laser engraving machineDifference of average load of laser engraving machine
Determining a heavy load set H, a medium load set M and a light load set L, merging the heavy load set H and the light load set L to obtain H ∪ L, and sequencing the laser engraving machines from strong to weak according to the comprehensive processing capacity, wherein the evaluation indexes of the comprehensive processing capacity comprise engraving speed, engraving step pitch, power, engraving depth and applicable materials;
step S53, local unbalance redistribution: the tasks are sequentially and preferentially distributed to the laser engraving machines with strong comprehensive processing capacity according to the magnitude sequence of the load requirements, and the minimum constraint of the average load of the local laser engraving machines is met; the method specifically comprises the following steps:
suppose that the integrated throughput sequence of the H ∪ L laser engraving machine is CM1≥CM2≥...≥CMn'Task t1,t2,...,tm'Has a load requirement sequence of p1≥p2≥...≥pm'，PiFor the ith laser engraving machine load, n 'and m' are respectively the laser engraving machine and the task number, and the task distribution process is as follows:
step ①: t1Is preferentially allocated to CM1，P1＝p1；
Step ②: t2Is preferentially allocated to CM1，P1＝P1+p2But the requirements are satisfied
Otherwise t2Is preferentially allocated to CM2，P2＝p2；t3Is preferentially allocated to CM1，P1＝P1+p3But the requirements are satisfied
Otherwise t3Is preferentially allocated to CM2，P2＝P2+p3But the requirements are satisfied
Otherwise t3Is preferentially allocated to CM3，P3＝p3(ii) a Continuing to complete task t according to the method4,t5,..,tm'Distributing;
step ③, re-evaluating the average load of the H ∪ L set, and if the average load of the H ∪ L set is attenuated, going to step ①;
step ④, outputting the last task distribution result;
step S54, updating the set: updating the classification of the laser engraving machine set, and determining a heavy load set H ', a medium load set M ' and a light load set L '; if the number of the elements in the heavy load set and the light load set is 0, go to step S56;
step S55, update iteration: calculating the average load of the global laser engraving machine, adjusting preset load adjusting parameters, and turning to the step S52;
step S56, outputting the current load balancing optimal scheduling result;
and step S6, the target dispatching laser engraving machine receives the G code, analyzes and interpolates numerical control, and engraves the workpiece to be machined.
2. The cloud load balancing control-based laser engraving machine working method of claim 1, wherein: in step S3, the operating state of the laser engraving machine includes the following cases:
if the working state is offline, the connection between the laser engraving machine and the cloud control end is not established;
if the working state is 'carving', the laser carving machine is in use, and the load parameters are displayed;
if the working state is 'error', the laser engraving machine is in fault;
if the working state is idle, the laser engraving machine is idle, and the printing task is not executed.
3. The cloud load balancing control-based laser engraving machine working method of claim 1, wherein: the specific content of the step S3 is:
step S31, the laser engraving machine collects current load data and sends the current load data to the cloud control end in a WIFI mode;
and step S32, the cloud control end receives the load data, resets the format, filters and arranges the format, evaluates the load condition of the current laser engraving machine and determines the working state.
4. The cloud load balancing control-based laser engraving machine working method of claim 1, wherein: after step S6, the method further includes:
step S7, the cloud control end receives the operation data of the laser engraving machine in real time, and once the laser engraving machine breaks down in the engraving process, the online fault diagnosis is carried out and the result is forwarded to the mobile intelligent terminal;
step S8, when the mobile intelligent terminal receives the carving 'finished' information, the mobile intelligent terminal indicates that the carving task is finished; and if an error prompt is received, the engraving task is selected to be terminated or resubmitted.
5. The cloud load balancing control-based laser engraving machine working method of claim 4, wherein: the specific content of the step S7 is:
step S71, collecting the operation data of the laser engraving machine;
step S72, carrying out multi-channel signal filtering, amplification, A/D conversion and convergence on the collected operation data, and sending the operation data to a cloud control end;
step S73, the cloud control end receives the operation signal and carries out fault diagnosis;
step S74, the cloud control end sends fault estimation information to the mobile intelligent terminal, and the working state displays 'error'; and (4) manually intervening to remove the fault according to the type and the position of the fault and the reason causing the fault.
6. The cloud load balancing control-based laser engraving machine working method of claim 5, wherein: in step S73, the process of performing the fault diagnosis is:
①, collecting signals of the laser engraving machine in a normal state, and establishing a characteristic parameter standard sample library;
step ②, establishing a common fault diagnosis knowledge base and an inference rule base;
step ③, the sensor keeps continuous and tracking monitoring to the laser engraving machine, the cloud control end receives signals, carries out state estimation and correlation analysis, and compares with the characteristic parameter standard sample library to determine the current state of the engraving machine system;
step ④, if the current state is 'error', determining the fault type, position and fault reason by rule reasoning according to the common fault diagnosis knowledge base;
and ⑤, if the corresponding fault type can not be found in the common fault diagnosis knowledge base, adding the fault type, the position, the characteristic parameter and the fault reason in the common fault diagnosis knowledge base, and updating the inference rule base.
7. The utility model provides a laser engraving machine operating system based on high in clouds load balance control which characterized in that: the system comprises a plurality of laser engraving machines, a cloud control end and a plurality of mobile intelligent terminals;
the laser engraving machine is internally provided with a wireless transceiving module supporting WIFI, and is connected with the cloud control end based on the WIFI and keeps interaction;
the mobile intelligent terminal is internally provided with a wireless communication module, is in communication connection with the cloud control terminal based on a GPRS or wireless WIFI mode, and submits a carving task to the cloud control terminal;
when the mobile intelligent terminal submits the engraving task to the cloud control terminal, the cloud control terminal adopts the laser engraving machine working method based on cloud load balancing control in claim 1 to schedule the target laser engraving machine to execute the task and keep the system load balanced.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810045651.0A CN108227636B (en) | 2018-01-17 | 2018-01-17 | Laser engraving machine working system and method based on cloud load balance control |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810045651.0A CN108227636B (en) | 2018-01-17 | 2018-01-17 | Laser engraving machine working system and method based on cloud load balance control |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108227636A CN108227636A (en) | 2018-06-29 |
| CN108227636B true CN108227636B (en) | 2020-01-17 |
Family
ID=62641374
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810045651.0A Active CN108227636B (en) | 2018-01-17 | 2018-01-17 | Laser engraving machine working system and method based on cloud load balance control |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108227636B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109079335A (en) * | 2018-10-19 | 2018-12-25 | 深圳德宝牛科技有限公司 | One kind being based on bluetooth miniature laser engraving machine and its operating method |
| CN110549021B (en) * | 2019-08-19 | 2020-06-12 | 济南邦德激光股份有限公司 | Control method and system of laser cutting equipment and cloud server |
| CN111401673A (en) * | 2019-09-16 | 2020-07-10 | 国营武汉新宇机器厂 | Dot matrix engraving effect evaluation method of laser engraving machine |
| CN111906442B (en) * | 2020-06-15 | 2022-06-21 | 宁波大学 | Intelligent laser engraving system based on industrial 4.0 |
| CN111791634A (en) * | 2020-07-01 | 2020-10-20 | 合肥晌玥科技有限公司 | Carving machine management and control method and system based on asynchronous receiving and sending framework |
| CN111600910A (en) * | 2020-07-01 | 2020-08-28 | 合肥晌玥科技有限公司 | Jade processing method and system |
| CN117191130B (en) * | 2023-09-27 | 2024-07-23 | 深圳市英博伟业科技有限公司 | Multi-scene online temperature and humidity monitoring method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002035595A1 (en) * | 2000-10-24 | 2002-05-02 | Advanced Systems Automattion Limited | Flexible laser system for severing semiconductor wafers |
| CA2359739A1 (en) * | 2001-10-04 | 2003-04-04 | Douglas John James | Task and resource integration method and system |
| WO2007143151A3 (en) * | 2006-06-02 | 2008-10-16 | Cymer Inc | High power laser flat panel workpiece treatment |
| WO2010070448A3 (en) * | 2008-12-15 | 2010-08-12 | Michael Grail | Method and apparatus for engraving objects |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100519219C (en) * | 2006-06-30 | 2009-07-29 | 格兰达技术（深圳）有限公司 | Control system of laser marking machine |
| JP4963205B2 (en) * | 2006-08-29 | 2012-06-27 | ヤマザキマザック株式会社 | Support system for failure prediction / warning / repair work of processing machines |
| CN101625565B (en) * | 2008-07-10 | 2011-12-14 | 上海华虹Nec电子有限公司 | Automation control system and method for controlling same |
| CN103056511A (en) * | 2011-10-19 | 2013-04-24 | 上海边光自动化科技有限公司 | Laser numerical control system based on Internet of Things |
| CN202394100U (en) * | 2011-12-05 | 2012-08-22 | 济南钢铁股份有限公司 | Intelligent management system for large character inkjet printer |
| CN102736562B (en) * | 2012-07-10 | 2014-06-04 | 北京信息科技大学 | Knowledge base construction method oriented to fault diagnosis and fault prediction of numerical control machine tool |
| EP3907033A1 (en) * | 2015-02-12 | 2021-11-10 | Glowforge Inc. | Visual preview for laser fabrication |
| JP6695102B2 (en) * | 2015-05-26 | 2020-05-20 | 株式会社ディスコ | Processing system |
| CN105700495B (en) * | 2016-01-13 | 2018-02-23 | 济南大学 | Flexible job shop scheduling machine choice method based on process time grade |
| JP6114421B1 (en) * | 2016-02-19 | 2017-04-12 | ファナック株式会社 | Machine learning device, industrial machine cell, manufacturing system and machine learning method for learning work sharing of a plurality of industrial machines |
| CN105808176B (en) * | 2016-03-02 | 2018-01-26 | 深圳市创鑫激光股份有限公司 | A kind of laser index carving method and system based on mobile terminal, Cloud Server |
| CN106583941B (en) * | 2016-12-10 | 2018-08-21 | 浙江圣石激光科技股份有限公司 | 3D body laser inner carving method and system based on mobile end data acquisition |
| CN107350633A (en) * | 2017-06-27 | 2017-11-17 | 安徽联亚智能装备制造有限公司 | A kind of long-range networked control systems based on ZigBee |
| CN107486630A (en) * | 2017-09-30 | 2017-12-19 | 广州市普汉科技有限公司 | A kind of laser process equipment and its processing method for possessing internet self-action engraving and cutting function |
-
2018
- 2018-01-17 CN CN201810045651.0A patent/CN108227636B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002035595A1 (en) * | 2000-10-24 | 2002-05-02 | Advanced Systems Automattion Limited | Flexible laser system for severing semiconductor wafers |
| CA2359739A1 (en) * | 2001-10-04 | 2003-04-04 | Douglas John James | Task and resource integration method and system |
| WO2007143151A3 (en) * | 2006-06-02 | 2008-10-16 | Cymer Inc | High power laser flat panel workpiece treatment |
| WO2010070448A3 (en) * | 2008-12-15 | 2010-08-12 | Michael Grail | Method and apparatus for engraving objects |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108227636A (en) | 2018-06-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108227636B (en) | Laser engraving machine working system and method based on cloud load balance control | |
| JP6892704B2 (en) | Smart factory parallel control method and system | |
| CN109598416B (en) | Dynamic scheduling system and scheduling method for composite material workshop | |
| CN103823409B (en) | Digit Control Machine Tool machining state multiparameter online actively monitoring system and its implementation | |
| CN103390195B (en) | A kind of machine shop task scheduling energy saving optimizing system based on intensified learning | |
| CN102909844B (en) | Production method for injection molding machine workpiece production line | |
| KR102626984B1 (en) | Managing apparatus and managing system | |
| WO2017063453A1 (en) | Industrial robot process cloud system and working method therefor | |
| KR102626985B1 (en) | Managing apparatus and managing system | |
| JP6781242B2 (en) | Controls, machine learning devices and systems | |
| CN113837532B (en) | Dynamic scheduling system for job shop | |
| CN117709617A (en) | MES-based intelligent scheduling system for production workshop | |
| CN114186791A (en) | Multi-model small-batch-oriented dynamic scheduling method for debugging production of complex equipment products | |
| CN115129004A (en) | Intelligent production system and method based on edge calculation and digital twinning | |
| CN102854870A (en) | Distributed control system and data report generating method | |
| CN111144710A (en) | Construction and dynamic scheduling method of sustainable hybrid flow shop | |
| CN116466665A (en) | Digital twin multi-protocol intelligent dispatching acquisition system and method for ship production workshop | |
| US11340563B2 (en) | Management system and management device for a plurality of industrial machines supplied with power from a power supply facility | |
| CN110174871B (en) | Control device, machine learning device, and system | |
| CN107331230A (en) | A kind of intelligence manufacture production, teaching ＆ research platform processed towards Metal Flake handicraft | |
| CN117148806B (en) | Automatic assembly mixed flow production line layout optimization method and device based on digital twin | |
| JP6928031B2 (en) | Control device and control system | |
| Shan et al. | Simulation and optimization of production line in Em-plant based assembly workshop | |
| CN114723220B (en) | Digital twin flexible workshop real-time scheduling method based on variable time window | |
| CN117930757A (en) | Industrial processing numerical control robot's regulation supervisory systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |