CN116400644A - Intelligent joint control system based on liquid material - Google Patents
Intelligent joint control system based on liquid material Download PDFInfo
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- 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
- G05B19/406—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 characterised by monitoring or safety
- G05B19/4065—Monitoring tool breakage, life or condition
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- G05B2219/00—Program-control systems
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Abstract
The invention relates to the technical field of machine tool joint control, and discloses an intelligent joint control system based on liquid materials, which comprises a server, wherein the server comprises a collection module, a judgment module, a processing module, an optimal module and an execution module, wherein the processing module is used for generating current machining information of each machine tool according to a task list and predicting next machining prediction information of each machine tool; the optimal module is used for generating an optimal oil supply scheme for supplying oil to the current machine tool by other machine tools based on an improved genetic algorithm according to the current machining information, the next machining prediction information and the real-time total amount of lubricating oil in the machine tool group when the lubricating oil amount of the current machine tool is insufficient; and the execution module is used for controlling other machine tools to perform oil supply operation to the current machine tool according to the oil supply scheme. According to the scheme, the problem that in the prior art, a single machine tool is in lubricating oil deficiency and the machining efficiency of a machine tool group is affected can be solved.
Description
Technical Field
The invention relates to the technical field of machine tool joint control, in particular to an intelligent joint control system based on liquid materials.
Background
In the machining process, due to the differences of blanks, rotating speed, feeding amount, cutting depth, machine tool rotating precision and operation skill level, the differences of splashing directions and speeds of lubricating oil (liquid) are inevitably caused, and even a totally-enclosed machining center cannot control oil to drop and leak to the ground and underground of a workshop, so that various problems and hidden troubles such as material cost increase, forklift braking efficiency reduction, personnel safety risk increase, labor intensity increase, production efficiency reduction, water body infiltration pollution are caused.
In order to solve the above problems, in the prior art, the splashed lubricating oil is usually collected and replenished into the oil collecting cavity, but no matter how the lubricating oil is collected, the total amount of the lubricating oil is continuously reduced along with the running of the machine tools, for example, the lubricating oil is taken away by soaking, part transferring or scrap iron cleaning, so that the total liquid amount is reduced, the running of the machine tools is required to be stopped once the total liquid amount is reduced, the lubricating oil replenishment is performed, the service life of the machine tools is greatly influenced, the efficiency of processing tasks is influenced once the machine tools are stopped, meanwhile, a plurality of machine tools are required to run, namely, a corresponding machine tool group is formed when the machine tools are used, and once one of the machine tools is in lubricating oil deficiency, other machine tools of the machine tool group are influenced, so that the influence of the lubricating oil deficiency on the machine tool group is reduced.
Disclosure of Invention
The invention aims to provide an intelligent combined control system based on liquid materials, which can solve the problem that in the prior art, a single machine tool has lubricating oil deficiency and affects the machining efficiency of a machine tool group, can reduce the influence of the lubricating oil deficiency of the machine tool on the machine tool group, greatly improves the linkage among the machine tool groups and promotes the machining efficiency of the machine tool group.
In order to achieve the above purpose, the invention adopts the following technical scheme: an intelligent integrated control system based on liquid materials comprises a server, wherein the server comprises:
the collection module is used for collecting the total oil quantity of the lubricating oil of each machine tool corresponding to the machine tool group in real time and generating the corresponding total oil quantity of the lubricating oil in real time; the task list comprises a current task list and a historical task list;
the judging module is used for judging the oil quantity condition of each machine tool according to the real-time total oil quantity of the lubricating oil of each machine tool and judging whether the current oil quantity of the machine tool is insufficient or not;
the processing module is used for generating current machining information of each machine tool according to the task list and predicting next machining prediction information of each machine tool;
the optimal module is used for generating an optimal oil supply scheme for supplying oil to the current machine tool by other machine tools based on an improved genetic algorithm according to the current machining information, the next machining prediction information and the real-time total amount of lubricating oil in the machine tool group when the lubricating oil amount of the current machine tool is insufficient;
and the execution module is used for controlling other machine tools to perform oil supply operation to the current machine tool according to the oil supply scheme.
The principle and the advantages of the scheme are as follows: in the scheme, firstly, when the machine tool group receives a machining task, a list corresponding to the machining task is acquired, meanwhile, a history task list corresponding to each machine tool is acquired, and then, the real-time total oil quantity of lubricating oil of each machine tool in the machine tool group is acquired, so that the oil quantity of the lubricating oil of each machine tool can be monitored in real time.
Then judging the oil quantity of each machine tool, namely judging whether the oil quantity of the corresponding machine tool is insufficient or redundant, judging whether the oil quantity of the machine tool is important, if the oil quantity is insufficient, some operations in the machine tool are blocked, such as stopping the machine to perform operations of adding the oil quantity, and the like, so that the machining efficiency of the machine tool is greatly reduced, after the judgment is finished, judging that the lubricating oil is insufficient, indicating that the machine tool needs to perform the replenishment of the lubricating oil,
at this time, processing information of each machine tool in the machine tool group is generated according to the task list, and next processing prediction information of each machine tool can be predicted.
When the corresponding current machine tool has insufficient lubricating oil quantity, the establishment of an optimal scheme for supplying oil to the current machine tool by other machine tools is carried out based on an improved genetic algorithm, and the oil supply operation is controlled according to the oil supply scheme.
According to the scheme, the oil supply scheme is optimally formulated, linkage between machine tools is greatly improved, the defect that a single machine tool is in lubricating oil deficiency and oil is required to be added by stopping machine, machining efficiency of a machine tool group is greatly improved, namely the problem that the machining efficiency of the machine tool group is affected due to the fact that the lubricating oil deficiency occurs in the single machine tool in the prior art can be solved, the influence of the lubricating oil deficiency of the machine tool on the machine tool group can be reduced, linkage between the machine tool groups is greatly improved, and the machining efficiency of the machine tool group is promoted.
Preferably, as an improvement, the optimizing module includes:
the calling module is used for selecting other machine tools with preset quantity near the current machine tool when judging that the lubricating oil quantity of the current machine tool is insufficient, and calling the basic information of the current machine tool and the selected other machine tools from the database;
the determining module is used for determining a service set for supplying oil to the current machine tool and planning an oil supply path by each other machine tool according to the selected other machine tools;
the constraint condition determining module is used for determining constraint conditions corresponding to all the services in the service set;
the objective function establishing module is used for establishing objective functions corresponding to all the services in the service set;
the mathematical model module is used for realizing multi-objective optimization of the oil supply path in the service set based on the improved genetic algorithm, the determined objective function and the constraint condition;
and the oil supply route optimization module is used for optimizing the oil supply path scheme of the service set according to the multi-objective optimization result.
The missing calculation module is used for calculating the total adding amount of the lubricating oil of the current machine tool according to the basic information of the machine tool of the current machine tool and the predicted machining information;
the demand acquisition module is used for determining constraint conditions and objective functions corresponding to all the businesses in the business set, wherein the objective functions comprise a first objective function for realizing the shortest oil transportation path and a second objective function for affecting the minimum next processing; the constraint conditions comprise a supply quantity sum constraint condition and a single maximum oil supply quantity constraint condition;
the mathematical model module is used for realizing multi-objective optimization of the oil supply path in the service set based on the first objective function, the second objective function and the constraint condition established by the improved genetic algorithm;
and the oil supply route optimization module is used for optimizing the oil supply path scheme of the service set according to the multi-objective optimization result.
The beneficial effects are that: in the scheme, when the oil quantity of the current machine tool is determined to be insufficient, a preset number of other machine tools and corresponding machine tool basic information are selected, then service set determination is carried out according to the basic information, namely, the oil quantity of each machine tool for supplying oil to the current machine tool is not fixed, various, constraint conditions and target functions are determined, and after the determination, multiple targets of oil supply paths in the service set are optimized based on an improved genetic algorithm, the constraint conditions and the target functions.
Preferably, as an improvement, the calling module includes:
the identifying module is used for identifying the number of the machine tool groups according to the current machine tool groups when the judging result corresponding to the current machine tool is that the lubricating oil quantity corresponding to the machine tool is insufficient, and generating corresponding machine tool number information;
the selection module is used for calling a selection strategy from the database according to the corresponding machine tool number information and determining the number of the selected machine tools;
the position information acquisition module is used for acquiring the position information of each machine tool in the machine tool group;
the machine tool determining module is used for determining other machine tools for supplying oil to the current machine tool based on the nearby principle according to the acquired position information of each machine tool and the number of the selected machine tools;
and the data calling module is used for calling the corresponding machine tool basic information from the database according to the determined other machine tools and the current machine tool.
The beneficial effects are that: in this scheme, in order to carry out the interrelation of lubricating oil between the lathe that can be better, can carry out the determination of lathe quantity through the selection strategy according to the quantity that the lathe crowd corresponds, namely the lathe crowd of different quantity is when carrying out the fuel feeding for current lathe, select certain quantity to carry out, other lathes that these quantities correspond are screened out according to the principle of nearby simultaneously, so make other lathes for current lathe fuel feeding relatively all nearer, just avoided other relatively distant lathes to the current lathe fuel feeding, just also reduced the adhesion of lubricating oil on the pipeline, very big improvement the availability factor of lubricating oil.
Preferably, as an improvement, the server side further comprises an alarm module, which is used for carrying out alarm reminding at the position information of the current machine tool when the judging result corresponding to the current machine tool is that the lubricating oil corresponding to the machine tool is absent, and sending the alarm reminding to the client side corresponding to the operator.
The beneficial effects are that: when the machine tool is in lubricating oil absence, the position of the machine tool is alarmed, so that an operator can know the position of the machine tool in which lubricating oil is absent very quickly, and the operator can pay attention to the machine tool in the follow-up oiling process or the starting process, so that the problem of lubricating oil absence can be better avoided.
Through sending the alarm reminding to the client side of the client operator, remote alarm can be realized, and the operator can manage the machine tool better.
Preferably, as an improvement, the server further includes:
the task progress real-time recording module is used for recording the processing progress of the current processing information corresponding to each machine tool in real time and generating corresponding real-time task progress information;
the processing efficiency calculation module is used for calculating the processing average efficiency corresponding to each machine tool according to the historical task list corresponding to each machine tool;
and the dynamic adjustment module is used for dynamically adjusting the preset minimum liquid level threshold value corresponding to the current moment according to the real-time task progress information and the processing average efficiency.
The beneficial effects are that: in the scheme, the average processing efficiency of each machine tool is calculated by acquiring the historical task list of each machine tool, and then the preset minimum liquid level threshold value at the current moment can be dynamically adjusted through the corresponding real-time task progress information and the processing average efficiency, so that the accuracy of the minimum liquid level is greatly improved, and the machine tool processing service can be better realized.
Preferably, as an improvement, the server further includes:
the real-time comparison module is used for calculating the actual oil-reducing speed of the lubricating oil at the current moment according to the real-time total amount of the lubricating oil at the previous moment and the real-time total amount of the lubricating oil at the current moment, and judging that the current machine tool is an abnormal machine tool if the corresponding actual oil-reducing speed is greater than a preset oil-reducing threshold;
the alarm module is also used for sending alarm information to the client of the operator when judging that the current machine tool is an abnormal machine tool;
the position information acquisition module is used for acquiring the position information of the client side receiving the alarm information;
and the path planning module is used for planning a path of an operator to the position where the current machine tool is located according to the acquired client position information and the position information of the current machine tool, generating a corresponding maintenance path and sending the maintenance path to the client.
Has the beneficial effects that; according to the scheme, when the machine tool is abnormal and the lubricating oil missing speed is too high, an operator can be informed at the first time, and path planning is performed, so that the operator can arrive at the site at the first time to check.
Preferably, as an improvement, the mathematical model module includes:
the first screening module is used for randomly generating an initial population with the scale of N, wherein the individuals of the initial population are oil supply paths of other selected machine tools to the current machine tool, and judging and screening the individuals of the initial population through constraint conditions, wherein the constraint conditions comprise a total supply quantity constraint condition and a single maximum oil supply quantity constraint condition, if the constraint conditions are met, the corresponding oil supply paths become feasible solutions, and if the constraint conditions are not met, the corresponding oil supply paths become infeasible solutions;
the fitness calculation module is used for respectively carrying out first fitness calculation and second fitness calculation on the screened population, and the first fitness calculation is as follows:
the method comprises the steps that D1 is the sum of oil transportation distances in an initial population, xi is the distance from a machine tool i to the current machine tool, and f1 is a first fitness;
the second fitness is calculated as follows:
f2＝D2
wherein D2 is the influence value of each individual in the initial population on the next processing, and Y is j The influence value of the lubricating oil conveying of the machine tool j on the next machining is given, and f2 is the second fitness;
the selection module is used for selecting a population with the first fitness being greater than or equal to a first fitness threshold value according to the first fitness corresponding to the population in the first preset iteration times, selecting the first three populations with the second lowest fitness from the populations rejected at the moment, and storing the first three populations in the standby library;
when the number of iterations exceeds the first preset number of iterations, combining the current population with the population in the standby library to form a new population, and selecting the population with the second fitness smaller than the preset second fitness corresponding to the current population;
the cross mutation module is used for obtaining a offspring population through hybridization and mutation of the selected population through a genetic algorithm;
the circulation module is used for continuing to execute the fitness calculation module after the offspring population is obtained until the preset iteration number is met;
and the output module is used for outputting the child population as an optimal solution set of the multi-objective optimization.
The beneficial effects are that: in the scheme, whether all individuals in the initial population meet the requirements or not is judged through constraint conditions, namely a total supply quantity constraint condition and a single maximum oil supply quantity constraint condition, namely whether all oil supply quantities of the population are larger than or equal to the quantity required by a current machine tool or not and whether the oil supply quantities of all the individuals exceed the standard or not is judged, so that the refinement of the huge initial population is realized.
When the population is selected, the calculation of the fitness comprises oil transportation distance and the influence value on the next processing, the existing genetic algorithm generally generates the optimal scheme according to the existing data, the predictive mechanism is introduced into the genetic algorithm by the development of the scheme, the possibility of the optimal solution with the least influence on the subsequent processing by the oil supply operation is reserved,
meanwhile, during specific selection, in a first preset iteration number, the first fitness of the population is mainly considered, namely, the first fitness is larger than or equal to a preset first fitness threshold value, so that the population with relatively small oil transportation distance can be matched, the rejected population is selected in the process, the first three populations with the smallest second fitness are selected for storing the reserve library, after the iteration of the first preset iteration number is completed, the influence of the corresponding key scheme on the next processing is exerted, the populations stored in the reserve library and the current population are concentrated at the moment, and a new population is formed, wherein the population at the moment comprises the population selected according to the first fitness and the first three populations with the smallest second fitness in each rejected population, the offspring population obtained through the method is better, a gene with relatively small processing influence can be better reserved, and the subsequent offspring population is better.
Drawings
Fig. 1 is a logic block diagram of an intelligent integrated control system based on liquid materials according to a first embodiment of the present invention.
Detailed Description
The following is a further detailed description of the embodiments:
an example is substantially as shown in figure 1: an intelligent combined control system based on liquid materials comprises a server, wherein the server comprises an acquisition module, and is used for acquiring the total oil quantity of lubricating oil of each machine tool corresponding to a machine tool group in real time to generate the corresponding real-time total oil quantity of the lubricating oil; in this embodiment, the collection module collects a detection result corresponding to the detection end of the machine tool, that is, a corresponding real-time total oil amount of the lubricating oil. The machine tool detection end comprises a controller, a liquid level sensor and a communication module, wherein the liquid level sensor and the communication module are arranged in the oil collecting cavity, the controller is respectively electrically connected with the liquid level sensor and the communication module, and the controller is used for detecting the liquid level of lubricating oil in the oil collecting cavity through the liquid level sensor and sending a detection result to the service end through the communication module.
The method is also used for acquiring task lists to be processed by all machine tools of the current machine tool group; the task list comprises a current task list and a historical task list; when the machine tool group is used, a task list is uploaded, for example, a part A is produced, 200 parts B is produced, and 100 parts B are produced.
The judging module is used for judging the oil quantity condition of each machine tool according to the real-time total oil quantity of the lubricating oil of each machine tool and judging whether the current oil quantity of the machine tool is insufficient or not; specifically, when the real-time total oil quantity of the lubricating oil is smaller than a preset minimum liquid level threshold, the judging result is that the lubricating oil corresponding to the machine tool is insufficient, and when the real-time total oil quantity of the lubricating oil is larger than or equal to the preset maximum liquid level threshold, the judging result is that the lubricating oil corresponding to the machine tool is redundant; when the real-time total oil quantity of the lubricating oil is larger than or equal to a preset minimum liquid level threshold value and smaller than a preset maximum liquid level threshold value, judging that the lubricating oil allowance corresponding to the machine tool is normal;
further comprises:
the task progress real-time recording module is used for recording the processing progress of the current processing information corresponding to each machine tool in real time and generating corresponding real-time task progress information;
the processing efficiency calculation module is used for calculating the processing average efficiency corresponding to each machine tool according to the historical task list corresponding to each machine tool;
and the dynamic adjustment module is used for dynamically adjusting the preset minimum liquid level threshold value corresponding to the current moment according to the real-time task progress information and the processing average efficiency.
In this embodiment, in order to make the oil quantity of the current machine tool accurately and pointedly determined in real time, the oil quantity of the current machine tool is dynamically adjusted when the corresponding preset minimum liquid level threshold is set, specifically, according to the historical task list of each machine tool, the respective evaluation processing efficiency of each machine tool can be intuitively determined, so that when the total quantity of the lubricating oil of the current machine tool is compared in real time, the corresponding preset minimum liquid level threshold is adjusted according to the real-time task progress information and the average processing efficiency at the current time, for example, when the corresponding machine tool is a machine tool, the total quantity of the lubricating oil is A at the current time, and the preset minimum liquid level threshold which is not adjusted at the beginning is B, wherein B is slightly greater than A, if the machine tool is possibly stopped at the previous time, but only one part is possibly required to be processed at the present according to the actual processing condition, the quantity corresponding to A is enough to process the part, the machine tool can not be stopped completely, and the replenishment of the lubricating oil is performed when the last part is completed, for the corresponding B is not regulated, and the loss of the machine tool is greatly reduced, and the loss of the machine tool is not damaged greatly is greatly, and the loss of the machine tool is greatly is not reduced.
The processing module is used for generating current machining information of each machine tool according to the task list and predicting next machining prediction information of each machine tool;
the optimal module is used for generating an optimal oil supply scheme for supplying oil to the current machine tool by other machine tools based on an improved genetic algorithm according to the current machining information, the next machining prediction information and the real-time total amount of lubricating oil in the machine tool group when the lubricating oil amount of the current machine tool is insufficient;
the optimizing module comprises:
the calling module is used for selecting other machine tools with preset quantity near the current machine tool when judging that the lubricating oil quantity of the current machine tool is insufficient, and calling the basic information of the current machine tool and the selected other machine tools from the database;
the calling module comprises:
the identifying module is used for identifying the number of the machine tool groups according to the current machine tool groups when the judging result corresponding to the current machine tool is that the lubricating oil quantity corresponding to the machine tool is insufficient, and generating corresponding machine tool number information;
the selection module is used for calling a selection strategy from the database according to the corresponding machine tool number information and determining the number of the selected machine tools;
the position information acquisition module is used for acquiring the position information of each machine tool in the machine tool group;
the machine tool determining module is used for determining other machine tools for supplying oil to the current machine tool based on the nearby principle according to the acquired position information of each machine tool and the number of the selected machine tools;
and the data calling module is used for calling the corresponding machine tool basic information from the database according to the determined other machine tools and the current machine tool.
In this embodiment, considering the problem of oil quantity deficiency, when the machine tools are replenished with lubricating oil, it is impossible to consider all the machine tools, and when the machine tools with relatively long distances are supplied with lubricating oil, a part of lubricating oil adheres to a pipeline due to the fact that the machine tools with relatively long distances are far away from the machine tools, and the more the distance is wasted, based on the consideration, when the machine tools are selected, the method firstly determines the number of the machine tools according to the number of the machine tools corresponding to the machine tool group through a selection strategy, and the selection strategy is dynamically adjusted according to the number information of the machine tools. After the number of machine tools is determined, the selection of the machine tools is started, in order to avoid excessive waste of lubricating oil on a pipeline caused by the distance, the position information of each machine tool in a machine tool group is firstly determined during the selection, then the selection of other machine tools is carried out by utilizing a nearby principle according to the position information of the other machine tools and the position information of the current machine tool, and of course, the lubricating oil corresponding to the selected other machine tools is not lost, and if the lubricating oil is lost, the machine tools are replaced, so that the other machine tools for supplying oil to the current machine tools are ensured to be the lubricating oil.
The determining module is used for determining a service set for supplying oil to the current machine tool and planning an oil supply path by each other machine tool according to the selected other machine tools;
the constraint condition determining module is used for determining constraint conditions corresponding to all the services in the service set; the constraint conditions comprise a supply quantity sum constraint condition and a single maximum oil supply quantity constraint condition;
the objective function establishing module is used for establishing objective functions corresponding to all the services in the service set;
the mathematical model module is used for realizing multi-objective optimization of the oil supply path in the service set based on the improved genetic algorithm, the determined objective function and the constraint condition;
the mathematical model module includes:
the first screening module is used for randomly generating an initial population with the scale of N, wherein the individuals of the initial population are oil supply paths of other selected machine tools to the current machine tool, and judging and screening the individuals of the initial population through constraint conditions, wherein the constraint conditions comprise a total supply quantity constraint condition and a single maximum oil supply quantity constraint condition, if the constraint conditions are met, the corresponding oil supply paths become feasible solutions, and if the constraint conditions are not met, the corresponding oil supply paths become infeasible solutions;
the fitness calculation module is used for respectively carrying out first fitness calculation and second fitness calculation on the screened population, and the first fitness calculation is as follows:
the method comprises the steps that D1 is the sum of oil transportation distances in an initial population, xi is the distance from a machine tool i to the current machine tool, and f1 is a first fitness;
the second fitness is calculated as follows:
f2＝D2
wherein D2 is the influence value of each individual in the initial population on the next processing, and Y is j The influence value of the lubricating oil conveying of the machine tool j on the next machining is given, and f2 is the second fitness;
the selection module is used for selecting a population with the first fitness being greater than or equal to a first fitness threshold value according to the first fitness corresponding to the population in the first preset iteration times, selecting the first three populations with the second lowest fitness from the populations rejected at the moment, and storing the first three populations in the standby library;
when the number of iterations exceeds the first preset number of iterations, combining the current population with the population in the standby library to form a new population, and selecting the population with the second fitness smaller than the preset second fitness corresponding to the current population;
the cross mutation module is used for obtaining a offspring population through hybridization and mutation of the selected population through a genetic algorithm;
the circulation module is used for continuing to execute the fitness calculation module after the offspring population is obtained until the preset iteration number is met;
and the output module is used for outputting the child population as an optimal solution set of the multi-objective optimization.
For example, when the machine tool 1 has an insufficient amount of lubrication oil, the machine tools 2, 3, 4, 5, 6 are known to perform the oil supply operation to the machine tool 1.
In order to find the best solution, the machine tools 2, 3, 4, 5, 6 are used to randomly generate an initial population of size N, i.e. each machine tool is set randomly with respect to an oil supply.
The initial population is then screened based on whether the individual oil delivery of each machine exceeds the maximum oil supply and whether the total oil delivery of the machine exceeds the desired oil supply.
And then, calculating the fitness, wherein in the calculation process, the first fitness and the second fitness are calculated for one population, but in a first preset iteration number, only the first fitness is screened, namely, the populations with the oil transportation distance not reaching the standard are screened, the sizes of the second fitness of the rejected populations are sorted, and the first three populations with the minimum second fitness are selected for storing a standby library.
After the iteration of the first preset iteration number is completed, the formed population is combined with the population in the standby library to form a new population, and then the population at the moment is subjected to second fitness screening, so that a child population is obtained.
And the oil supply route optimization module is used for optimizing the oil supply path scheme of the service set according to the multi-objective optimization result.
And the execution module is used for controlling other machine tools to perform oil supply operation to the current machine tool according to the oil supply scheme.
And the alarm module is used for carrying out alarm reminding at the position information of the current machine tool when the judging result corresponding to the current machine tool is that the lubricating oil corresponding to the machine tool is absent, and sending the alarm reminding to the client corresponding to the operator. In the embodiment, the remote notification function is realized through the alarm module, so that the convenience of supervision of operators is greatly improved.
The server side further comprises:
the real-time comparison module is used for calculating the actual oil-reducing speed of the lubricating oil at the current moment according to the real-time total amount of the lubricating oil at the previous moment and the real-time total amount of the lubricating oil at the current moment, and judging that the current machine tool is an abnormal machine tool if the corresponding actual oil-reducing speed is greater than a preset oil-reducing threshold;
the alarm module is also used for sending alarm information to the client of the operator when judging that the current machine tool is an abnormal machine tool;
the position information acquisition module is used for acquiring the position information of the client side receiving the alarm information;
and the path planning module is used for planning a path of an operator to the position where the current machine tool is located according to the acquired client position information and the position information of the current machine tool, generating a corresponding maintenance path and sending the maintenance path to the client.
In this embodiment, by detecting the total amount of each time of the lubricating oil, whether the current machine tool has abnormal behavior due to the lack of the lubricating oil can be monitored rapidly, and once the abnormal behavior is sent, the problem that the specific position is unclear when the equipment to be managed by the operator is relatively more is considered and the equipment to be managed is likely to face the abnormal, so that the path planning is performed on the site to which the operator needs to arrive at the first time, and thus the operator can arrive at the site rapidly and repair or check the abnormal behavior in time.
In this embodiment, any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The foregoing is merely exemplary of the present invention, and specific technical solutions and/or features that are well known in the art have not been described in detail herein. It should be noted that, for those skilled in the art, several variations and modifications can be made without departing from the technical solution of the present invention, and these should also be regarded as the protection scope of the present invention, which does not affect the effect of the implementation of the present invention and the practical applicability of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (7)
1. An intelligent integrated control system based on liquid materials is characterized in that: the server comprises a server, wherein the server comprises:
the collection module is used for collecting the total oil quantity of the lubricating oil of each machine tool corresponding to the machine tool group in real time and generating the corresponding total oil quantity of the lubricating oil in real time; the task list comprises a current task list and a historical task list;
the judging module is used for judging the oil quantity condition of each machine tool according to the real-time total oil quantity of the lubricating oil of each machine tool and judging whether the current oil quantity of the machine tool is insufficient or not;
the processing module is used for generating current machining information of each machine tool according to the task list and predicting next machining prediction information of each machine tool;
the optimal module is used for generating an optimal oil supply scheme for supplying oil to the current machine tool by other machine tools based on an improved genetic algorithm according to the current machining information, the next machining prediction information and the real-time total amount of lubricating oil in the machine tool group when the lubricating oil amount of the current machine tool is insufficient;
and the execution module is used for controlling other machine tools to perform oil supply operation to the current machine tool according to the oil supply scheme.
2. The intelligent integrated control system based on liquid materials according to claim 1, wherein: the optimizing module comprises:
the calling module is used for selecting other machine tools with preset quantity near the current machine tool when judging that the lubricating oil quantity of the current machine tool is insufficient, and calling the basic information of the current machine tool and the selected other machine tools from the database;
the determining module is used for determining a service set for supplying oil to the current machine tool and planning an oil supply path by each other machine tool according to the selected other machine tools;
the constraint condition determining module is used for determining constraint conditions corresponding to all the services in the service set;
the objective function establishing module is used for establishing objective functions corresponding to all the services in the service set;
the mathematical model module is used for realizing multi-objective optimization of the oil supply path in the service set based on the improved genetic algorithm, the determined objective function and the constraint condition;
and the oil supply route optimization module is used for optimizing the oil supply path scheme of the service set according to the multi-objective optimization result.
3. The intelligent integrated control system based on liquid materials according to claim 2, wherein: the calling module comprises:
the identifying module is used for identifying the number of the machine tool groups according to the current machine tool groups when the judging result corresponding to the current machine tool is that the lubricating oil quantity corresponding to the machine tool is insufficient, and generating corresponding machine tool number information;
the position information acquisition module is used for acquiring the position information of each machine tool in the machine tool group;
the machine tool determining module is used for determining other machine tools for supplying oil to the current machine tool based on the nearby principle according to the acquired position information of each machine tool and the preset quantity;
and the data calling module is used for calling the corresponding machine tool basic information from the database according to the determined other machine tools and the current machine tool.
4. An intelligent integrated control system based on liquid materials as set forth in claim 3, wherein: the server side further comprises an alarm module, wherein the alarm module is used for carrying out alarm reminding at the position information of the current machine tool when the judging result corresponding to the current machine tool is that the lubricating oil corresponding to the machine tool is absent, and sending the alarm reminding to the client side corresponding to the operator.
5. The intelligent integrated control system based on liquid materials according to claim 4, wherein: the server side further comprises:
the task progress real-time recording module is used for recording the processing progress of the current processing information corresponding to each machine tool in real time and generating corresponding real-time task progress information;
the processing efficiency calculation module is used for calculating the processing average efficiency corresponding to each machine tool according to the historical task list corresponding to each machine tool;
and the dynamic adjustment module is used for dynamically adjusting the preset minimum liquid level threshold value corresponding to the current moment according to the real-time task progress information and the processing average efficiency.
6. The intelligent integrated control system based on liquid materials according to claim 5, wherein: the server side further comprises: the server side further comprises:
the real-time comparison module is used for calculating the actual oil-reducing speed of the lubricating oil at the current moment according to the real-time total amount of the lubricating oil at the previous moment and the real-time total amount of the lubricating oil at the current moment, and judging that the current machine tool is an abnormal machine tool if the corresponding actual oil-reducing speed is greater than a preset oil-reducing threshold;
the alarm module is also used for sending alarm information to the client of the operator when judging that the current machine tool is an abnormal machine tool;
the position information acquisition module is used for acquiring the position information of the client side receiving the alarm information;
and the path planning module is used for planning a path of an operator to the position where the current machine tool is located according to the acquired client position information and the position information of the current machine tool, generating a corresponding maintenance path and sending the maintenance path to the client.
7. The intelligent integrated control system based on liquid materials according to claim 2, wherein: the mathematical model module includes:
the first screening module is used for randomly generating an initial population with the scale of N, wherein the individuals of the initial population are oil supply paths of other selected machine tools to the current machine tool, and judging and screening the individuals of the initial population through constraint conditions, wherein the constraint conditions comprise a total supply quantity constraint condition and a single maximum oil supply quantity constraint condition, if the constraint conditions are met, the corresponding oil supply paths become feasible solutions, and if the constraint conditions are not met, the corresponding oil supply paths become infeasible solutions;
the fitness calculation module is used for respectively carrying out first fitness calculation and second fitness calculation on the screened population, and the first fitness calculation is as follows:
the method comprises the steps that D1 is the sum of oil transportation distances in an initial population, xi is the distance from a machine tool i to the current machine tool, and f1 is a first fitness;
the second fitness is calculated as follows:
f2＝D2
wherein D2 is the influence value of each individual in the initial population on the next processing, and Y is j The influence value of the lubricating oil delivery of the machine tool j on the next machining is f2, which is the second adaptability；
The selection module is used for selecting a population with the first fitness being greater than or equal to a first fitness threshold value according to the first fitness corresponding to the population in the first preset iteration times, selecting the first three populations with the second lowest fitness from the populations rejected at the moment, and storing the first three populations in the standby library;
when the number of iterations exceeds the first preset number of iterations, combining the current population with the population in the standby library to form a new population, and selecting the population with the second fitness smaller than the preset second fitness corresponding to the current population;
the cross mutation module is used for obtaining a offspring population through hybridization and mutation of the selected population through a genetic algorithm;
the circulation module is used for continuing to execute the fitness calculation module after the offspring population is obtained until the preset iteration number is met;
and the output module is used for outputting the child population as an optimal solution set of the multi-objective optimization.
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