CN113504763B - Method, device and equipment for controlling load weight of workbench and storage medium - Google Patents
Method, device and equipment for controlling load weight of workbench and storage medium Download PDFInfo
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- CN113504763B CN113504763B CN202110786985.5A CN202110786985A CN113504763B CN 113504763 B CN113504763 B CN 113504763B CN 202110786985 A CN202110786985 A CN 202110786985A CN 113504763 B CN113504763 B CN 113504763B
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- 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
- G05B19/406—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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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23F—MAKING GEARS OR TOOTHED RACKS
- B23F23/00—Accessories or equipment combined with or arranged in, or specially designed to form part of, gear-cutting machines
- B23F23/12—Other devices, e.g. tool holders; Checking devices for controlling workpieces in machines for manufacturing gear teeth
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- 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
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- G05B2219/37616—Use same monitoring tools to monitor tool and workpiece
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to the technical field of machinery, and discloses a method, a device, equipment and a storage medium for controlling the load weight of a workbench, wherein the method comprises the following steps: acquiring current running state information of a target workbench, and determining corresponding current load weight information according to the current running state information; acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is more than or equal to the preset load weight information; reducing the load of a target workbench according to a target unloading strategy to obtain target flow information and target pressure information; determining a target load capacity of the target workbench according to the target flow information and the target pressure information; when the current load weight information is larger than the preset load weight information, the load of the target workbench is reduced through the target unloading strategy, the load weight of the target workbench is controlled, and compared with the load weight of a lifting device control workbench in the prior art, the accuracy of controlling the load weight can be effectively improved.
Description
Technical Field
The invention relates to the technical field of machinery, in particular to a method, a device, equipment and a storage medium for controlling the load weight of a workbench.
Background
The gear hobbing machine is a special machine tool for processing gears, and is divided into a vertical gear hobbing machine and a horizontal gear hobbing machine. The vertical hobbing machine has the advantages that because a horizontal upright column guide rail and a vertical upright column are different from a horizontal hobbing machine working shaft, the two working tables are different, because the working tables are bridges between users and the hobbing machine and play a vital role in the operation of the hobbing machine, the load weight of the working tables is related to the performance of the hobbing machine, and when the load weight of the working tables exceeds a set threshold value, the hobbing machine is damaged, so the load weight of the working tables needs to be monitored in real time and controlled in the operation process of the hobbing machine, the load weight of the working tables is monitored by a weight sensor arranged on the working tables in a commonly used control mode at present, when the load weight is more than the threshold value, the load weight of the working tables is controlled by manually adjusting lifting equipment, but the control accuracy of the working tables is low by using the control mode, the production requirements cannot be met.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for controlling the load weight of a workbench, and aims to solve the technical problem that the precision of controlling the load weight cannot be effectively improved in the prior art.
In order to achieve the above object, the present invention provides a method for controlling a table load weight, comprising the steps of:
acquiring current running state information of a target workbench, and determining corresponding current load weight information according to the current running state information;
acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information;
reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information;
and determining the target load capacity of the target workbench according to the target flow information and the target pressure information so as to realize the control of the load weight of the target workbench.
Optionally, the obtaining current operation state information of the target workbench, and determining corresponding current load weight information according to the current operation state information includes:
acquiring current running state information of a target workbench, and acquiring left load weight information and right load weight information of the target workbench according to the current running state information;
respectively extracting characteristic information of the left load weight information and the right load weight information;
and obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information.
Optionally, the obtaining historical load weight information and searching for corresponding current load weight information in the historical load weight information according to the characteristic information includes:
acquiring a preset linear algorithm, and performing curve fitting on the characteristic information according to the preset linear algorithm to obtain a corresponding characteristic curve graph;
selecting the characteristic curve graph according to the current running state information to obtain target characteristic information;
and acquiring historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the target characteristic information.
Optionally, the reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information includes:
acquiring current parameter information of a hydraulic pump arranged on the target workbench, and acquiring corresponding current flow information and current pressure information according to the current parameter information;
and reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information.
Optionally, the reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information includes:
reducing the current flow information according to the target unloading strategy to obtain target flow information;
and acquiring a preset flow threshold, and if the flow in the target flow information is greater than the preset flow threshold, decompressing the current pressure information according to the target unloading strategy to obtain target pressure information.
Optionally, the determining a target load capacity of the target workbench according to the target traffic information and the target pressure information includes:
acquiring a preset neural network model, and extracting node information and function information in the preset neural network model;
modifying the node information according to the target flow information and the target pressure information to obtain target node information;
adjusting the function information according to the target flow information and the target pressure information to obtain target function information;
acquiring a preset neural network strategy, and training the target node information and the target function information according to the preset neural network strategy to obtain a target neural network model;
and predicting the target flow information and the target pressure information according to the target neural network model to obtain the target load capacity of the target workbench.
Optionally, after predicting the target flow information and the target pressure information according to the target neural network model, the method further includes:
acquiring a preset load threshold, and if the target load is larger than the preset load threshold, extracting flow information and pressure information of the preset load;
and predicting the extracted flow information and pressure information according to the target neural network model to obtain the predicted load capacity of the target workbench.
In order to achieve the above object, the present invention provides a control device for a table load weight, comprising:
the determining module is used for acquiring the current running state information of the target workbench and determining corresponding current load weight information according to the current running state information;
the acquisition module is used for acquiring preset load weight information and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information;
the reduction module is used for reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information;
and the control module is used for determining the target load capacity of the target workbench according to the target flow information and the target pressure information so as to realize the control of the load weight of the target workbench.
In addition, in order to achieve the above object, the present invention further provides a control apparatus for a table load weight, including: a memory, a processor, and a control program of a table load weight stored on the memory and executable on the processor, the control program of a table load weight being configured to implement the control method of a table load weight as described above.
In addition, in order to achieve the above object, the present invention further provides a storage medium having a table load weight control program stored thereon, wherein the table load weight control program, when executed by a processor, implements the table load weight control method as described above.
The method for controlling the load weight of the workbench comprises the steps of obtaining current running state information of a target workbench, and determining corresponding current load weight information according to the current running state information; acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information; reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information; determining the target load capacity of the target workbench according to the target flow information and the target pressure information; when the current load weight information is larger than the preset load weight information, the load of the target workbench is reduced through the target unloading strategy, so that the load weight of the target workbench can be controlled, and compared with the prior art that the load weight of the workbench is controlled by adjusting the lifting device, the accuracy of controlling the load weight can be effectively improved.
Drawings
FIG. 1 is a schematic structural diagram of a control device for a table load weight in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a method for controlling a load weight of a work table according to a first embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating a method for controlling the weight of a work table according to a second embodiment of the present invention;
FIG. 4 is a schematic flow chart illustrating a third embodiment of a method for controlling a table load weight according to the present invention;
fig. 5 is a functional block diagram of the control device for the load weight of the workbench according to the first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a control device for a table load weight in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the apparatus for controlling the weight of the load on the work table may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the control device for the table load weight and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of storage medium, may include therein an operating system, a network communication module, a user interface module, and a control program of a work table load weight.
In the control apparatus of the table load weight shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the control apparatus of the table load weight of the present invention may be provided in the control apparatus of the table load weight, which calls the control program of the table load weight stored in the memory 1005 through the processor 1001 and executes the control method of the table load weight provided by the embodiment of the present invention.
Based on the hardware structure, the embodiment of the method for controlling the load weight of the workbench is provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a method for controlling a load weight of a workbench according to a first embodiment of the present invention.
In a first embodiment, the method for controlling the load weight of the workbench comprises the following steps:
and step S10, acquiring the current running state information of the target workbench, and determining the corresponding current load weight information according to the current running state information.
It should be noted that the execution subject of the present embodiment is a control device for the load weight of the workbench, and may also be other devices that can achieve the same or similar functions, such as a load weight controller, for example, which is not limited in this embodiment.
It should be understood that the current operation state information of the target workbench refers to the operation state information of the workbench at the time of collection, and the target workbench refers to the workbench of which the load weight needs to be controlled, if the load weight needs to be controlled by all the multiple workbenches in the production process, all the multiple workbenches are the target workbench, after the current operation state information of the target workbench is obtained, because multiple production lines corresponding to the target workbench exist, the load weight of the target workbench is determined according to the number of the production lines, for example, the production lines of the workbench are divided into two production lines, respectively a left production line and a right production line, the load weight of the target workbench is determined by the load weight of the left production line and the load weight of the right production line, but because the actual value of the load weight is different from the value read by the pressure sensor arranged on the target workbench, therefore, if the read numerical value is directly used as the actual load weight of the target table, a large error is caused, and at this time, the current load weight information of the target table needs to be calculated together by using the characteristic information of the left load weight and the right load weight.
It can be understood that, since the load weight of the target workbench refers to the whole load amount, but the different positions of the same workpiece may cause weight differences, in order to increase the accuracy of obtaining the current load weight information, the whole target workbench is divided into a left part and a right part, where the left part of the workbench obtains the load weight as the left load weight and the right part of the workbench obtains the right load weight, and thus the current load weight information of the target workbench is calculated according to the characteristic information of the left load weight information and the right load weight information.
In specific implementation, the load weight controller acquires current operation state information of the target workbench, and determines corresponding current load weight information according to the current operation state information.
Step S20, acquiring preset load weight information, and if the current load weight information is greater than or equal to the preset load weight information, acquiring a target unloading strategy.
It should be understood that the preset load weight information refers to the maximum load weight information that the target workbench can bear, and when the load weight corresponding to the preset load weight information is exceeded, the performance of the production line is reduced and the workbench is damaged, therefore, the load weight information of the target workbench needs to be monitored in real time in the process of starting production, when the current load weight information is wirelessly approached to the preset load weight information, the time that the current load weight is wirelessly approached to the preset load weight needs to be predicted according to the current production state of the production line, and when the current load weight is greater than the preset load weight, the load weight of the target workbench is controlled through the obtained target unloading strategy, so as to effectively reduce the load weight of the target workbench.
It can be understood that, since the measures for reducing the load weight of the target platform are divided into two measures, one is flow unloading and the other is pressure unloading, and the target unloading strategy refers to a strategy for reducing the flow and reducing the pressure, the load weight of the target platform can be reduced by the strategies for reducing the flow and reducing the pressure, wherein when the load weight of the target platform is reduced according to the strategies for reducing the flow and reducing the pressure, the two strategies need to be used in cooperation with each other, namely when the flow is reduced, the pressure needs to be synchronously reduced, and the variable displacement pump is prevented from being damaged due to excessive reduction or excessive reduction.
In specific implementation, the load weight controller acquires preset load weight information, and if the current load weight information is greater than or equal to the preset load weight information, acquires a target unloading strategy.
And step S30, reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information.
It should be understood that the load of the target workbench is formed by combining the current flow information and the current pressure information when the target workbench operates, and therefore, the essence of load reduction on the target workbench is to reduce the current flow information and the current pressure information, and since the target unloading strategy is a strategy for reducing flow and reducing pressure, the corresponding current flow in the current flow information or the corresponding pressure value in the current pressure information is reduced through the target unloading strategy to obtain the target flow information and the target pressure information.
In specific implementation, the load weight controller reduces the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information.
Step S40, determining a target load capacity of the target workbench according to the target flow information and the target pressure information, so as to control the load weight of the target workbench.
It should be understood that, after obtaining the target flow information and the target pressure information, obtaining a preset neural network model, extracting node information and function information in the preset neural network model, modifying the node information and the function information according to the target flow information and the target pressure information, respectively, obtaining target node information and target function information, obtaining a preset neural network policy, training the target node information and the target function information according to the preset neural network policy, obtaining a target neural network model, predicting the target flow information and the target pressure information according to the target neural network model, so as to obtain a target load capacity of the target workbench, where the preset neural network model may be a convolutional neural network model or another neural network model, and this embodiment is not limited thereto and takes the convolutional neural network model as an example for explanation, the node information and the function information are constituent elements of a preset network model, and because the number of nodes and the function parameters of the preset neural network model are incompatible with the target flow information and the target pressure information, the node information and the function information need to be modified according to the target flow information and the target pressure information to obtain the target node information and the target function information, the preset neural network strategy refers to a strategy for training the parameter information or data into the neural network model, and the same type of neural network model corresponding to the parameter information or data is obtained through training of the preset neural network strategy.
Further, in order to improve the accuracy of obtaining the load capacity of the target workbench, after predicting the target flow information and the target pressure information according to the target neural network model, the method further includes:
acquiring a preset load threshold, and if the target load is larger than the preset load threshold, extracting flow information and pressure information of the preset load; and predicting the extracted flow information and pressure information according to the target neural network model to obtain the predicted load capacity of the target workbench.
It can be understood that the preset load threshold refers to a load between the maximum load and the qualified load that can be borne by the target workbench, and since the preset load threshold is not within the safety range, if the predicted target load is greater than the preset load, the flow information and the pressure information of the preset load need to be extracted again, and the target load is predicted again in the target neural network model to obtain the predicted load of the target workbench, where the predicted load is the load of the controlled target workbench.
In specific implementation, the load weight controller determines the target load capacity of the target workbench according to the target flow information and the target pressure information, so as to realize control on the load weight of the target workbench.
The method comprises the steps of determining corresponding current load weight information according to current running state information by obtaining the current running state information of a target workbench; acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information; reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information; determining the target load capacity of the target workbench according to the target flow information and the target pressure information; when the current load weight information is larger than the preset load weight information, the load of the target workbench is reduced through the target unloading strategy, so that the load weight of the target workbench can be controlled, and compared with the prior art that the load weight of the workbench is controlled by adjusting the lifting device, the accuracy of controlling the load weight can be effectively improved.
In an embodiment, as shown in fig. 3, a second embodiment of the method for controlling a load weight of a workbench according to the present invention is proposed based on the first embodiment, and the step S10 includes:
step S101, obtaining current running state information of a target workbench, and obtaining left load weight information and right load weight information of the target workbench according to the current running state information.
It should be understood that, after obtaining the current operation state information of the target workbench, in order to increase the accuracy of obtaining the current load weight information, the whole target workbench is divided into a left part and a right part, and left load weight information and right load weight information of the target workbench are respectively obtained according to the current operation state information, wherein the left load weight information refers to weight information borne by the left side of the target workbench, and the right load weight information refers to weight information borne by the right side of the target workbench.
In specific implementation, the load weight controller acquires current operation state information of a target workbench, and obtains left load weight information and right load weight information of the target workbench according to the current operation state information.
Step S102, respectively extracting feature information of the left load weight information and the right load weight information.
It can be understood that the feature information refers to feature information of left load weight information and right load weight information, if the production line corresponding to the target workbench is one, the feature information of the left load weight information is consistent with the feature information of the right load weight information, if the production lines corresponding to the left and right parts of the target workbench are different, the feature information of the left load weight information is inconsistent with the feature information of the right load weight information, the feature information of the left load weight information and the feature information of the right load weight information depend on the types of products produced on the production line, the feature information of the left load weight information and the feature information of the right load weight information are determined according to the types of the products, and after the types of the products are determined, the feature information of the left load weight information and the feature information of the right load weight information are extracted respectively.
In a specific implementation, the load weight controller extracts feature information of the left load weight information and the right load weight information, respectively.
Step S103, obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information.
It should be understood that the historical load weight information refers to all load weight information of the target workbench when different products are processed on the production line, and due to different types of the products processed on the production line, the historical load weight information is also different, so the historical load weight information is a set of load weight information of the target workbench, after the characteristic information is obtained, corresponding load weight information is found in the historical load weight information according to the characteristic information, and the found load weight information is used as the current load weight information of the target workbench.
Further, in order to effectively improve the accuracy of obtaining the current load weight information, historical load weight information is obtained, and corresponding current load weight information is searched for in the historical load weight information according to the characteristic information, including:
acquiring a preset linear algorithm, and performing curve fitting on the characteristic information according to the preset linear algorithm to obtain a corresponding characteristic curve graph; selecting the characteristic curve graph according to the current running state information to obtain target characteristic information; and acquiring historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the target characteristic information.
It can be understood that the preset linear algorithm refers to an algorithm for arranging and connecting the feature information into a fitting curve, and the mutual relationship of the feature information can be displayed through the preset linear algorithm to obtain a corresponding feature curve graph, at this time, the feature curve graph includes a plurality of feature information, and the operating state information corresponding to each feature information is different, so that the target feature information needs to be selected from the feature curve graph according to the current operating information of the target workbench, and the corresponding current load weight information needs to be searched in the historical load weight information through the target feature information.
In specific implementation, the load weight controller acquires historical load weight information, and searches corresponding current load weight information in the historical load weight information according to the characteristic information.
In the embodiment, the current running state information of a target workbench is obtained, and the left load weight information and the right load weight information of the target workbench are obtained according to the current running state information; respectively extracting characteristic information of the left load weight information and the right load weight information; obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information; the characteristic information of the left load weight information and the characteristic information of the right load weight information obtained through the current running state information are respectively extracted, and the current load weight information is searched in the historical load weight information based on the characteristic information, so that the accuracy of obtaining the current load weight information is effectively improved.
In an embodiment, as shown in fig. 4, a third embodiment of the method for controlling a load weight of a workbench according to the present invention is proposed based on the first embodiment, and the step S30 includes:
step S301, obtaining current parameter information of a hydraulic pump arranged on the target workbench, and obtaining corresponding current flow information and current pressure information according to the current parameter information.
It can be understood that the current parameter information refers to the parameter information of the hydraulic pump when the operation state information of the workbench is acquired instantly, the performance state of the hydraulic pump can be obtained through the current parameter information, the performance of the target workbench is determined by the performance state of the hydraulic pump, the current parameter information and the current pressure information of the hydraulic pump are calculated according to the current parameter information, wherein the target workbench is positively correlated, namely the performance state of the hydraulic pump is better, and the performance of the target workbench is better.
In specific implementation, the load weight controller acquires current parameter information of a hydraulic pump arranged on the target workbench, and obtains corresponding current flow information and current pressure information according to the current parameter information.
Step S302, reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information.
It can be understood that after the target unloading strategy is obtained, the current flow information and the current pressure information are respectively reduced through the target unloading strategy, and the current flow information and the current pressure information need to be synchronously reduced in the unloading process, that is, when the current flow is reduced, the current pressure value also needs to be reduced, the current flow cannot be directly reduced to the lowest value, and then the current pressure value is reduced, so that the target workbench and the production line are damaged through the operation, and after the current flow information and the current pressure information are reduced, the target flow information and the target pressure information can be obtained.
Further, in order to effectively control and reduce the accuracy of the current flow information and the current pressure information, the method for reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information includes:
reducing the current flow information according to the target unloading strategy to obtain target flow information; and acquiring a preset flow threshold, and if the flow in the target flow information is larger than the preset flow threshold, decompressing the current pressure information according to the target unloading strategy to obtain target pressure information.
It should be understood that, when the current flow information and the current pressure information are reduced through the target unloading strategy, there needs to be a sequence, first, the corresponding current flow in the current flow information is reduced, whether the reduced target flow information is greater than a preset flow threshold value is judged, the target workbench is prevented from being damaged due to excessive reduction through judgment of the preset flow threshold value, and then, when the flow in the target flow information is greater than the preset flow threshold value, the pressure value in the current pressure information is reduced to obtain the target pressure information.
In specific implementation, the load weight controller reduces the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information.
In the embodiment, the current parameter information of the hydraulic pump arranged on the target workbench is acquired, and the corresponding current flow information and the current pressure information are obtained according to the current parameter information; reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information; and reducing the flow in the current flow information and reducing the pressure value in the current pressure information by a target unloading strategy to obtain target flow information and target pressure information, thereby effectively controlling and reducing the accuracy of the current flow information and the current pressure information.
Furthermore, an embodiment of the present invention further provides a storage medium, where a control program of the table load weight is stored, and the control program of the table load weight, when executed by a processor, implements the steps of the control method of the table load weight as described above.
Since the storage medium adopts all technical solutions of all the embodiments, at least all the beneficial effects brought by the technical solutions of the embodiments are achieved, and no further description is given here.
In addition, referring to fig. 5, an embodiment of the present invention further provides a control device for a table load weight, where the control device for a table load weight includes:
the determining module 10 is configured to obtain current operation state information of the target workbench, and determine corresponding current load weight information according to the current operation state information.
It should be understood that the current operation state information of the target workbench refers to the operation state information of the workbench at the time of collection, and the target workbench refers to the workbench of which the load weight needs to be controlled, if the load weight needs to be controlled by all the multiple workbenches in the production process, all the multiple workbenches are the target workbench, after the current operation state information of the target workbench is obtained, because multiple production lines corresponding to the target workbench exist, the load weight of the target workbench is determined according to the number of the production lines, for example, the production lines of the workbench are divided into two production lines, respectively a left production line and a right production line, the load weight of the target workbench is determined by the load weight of the left production line and the load weight of the right production line, but because the actual value of the load weight is different from the value read by the pressure sensor arranged on the target workbench, therefore, if the read numerical value is directly used as the actual load weight of the target table, a large error is caused, and at this time, the current load weight information of the target table needs to be calculated together by using the characteristic information of the left load weight and the right load weight.
It can be understood that, since the load weight of the target workbench refers to the whole load amount, but different positions of the same workpiece may cause weight differences, in order to increase the accuracy of obtaining the current load weight information, the whole target workbench is divided into a left part and a right part, where the load weight obtained by the left part of the workbench is the left load weight, and the load weight obtained by the right part of the workbench is the right load weight, and thus the current load weight information of the target workbench is calculated according to the characteristic information of the left load weight information and the right load weight information.
In specific implementation, the load weight controller acquires current operation state information of the target workbench, and determines corresponding current load weight information according to the current operation state information.
An obtaining module 20, configured to obtain preset load weight information, and if the current load weight information is greater than or equal to the preset load weight information, obtain a target unloading strategy.
It should be understood that the preset load weight information refers to the maximum load weight information that the target workbench can bear, and when the load weight corresponding to the preset load weight information is exceeded, the performance of the production line is reduced and the workbench is damaged, therefore, the load weight information of the target workbench needs to be monitored in real time in the process of starting production, when the current load weight information is wirelessly approached to the preset load weight information, the time that the current load weight is wirelessly approached to the preset load weight needs to be predicted according to the current production state of the production line, and when the current load weight is greater than the preset load weight, the load weight of the target workbench is controlled through the obtained target unloading strategy, so as to effectively reduce the load weight of the target workbench.
It can be understood that, since the measures for reducing the load weight of the target platform are divided into two measures, one is flow unloading and the other is pressure unloading, and the target unloading strategy refers to a strategy for reducing the flow and reducing the pressure, the load weight of the target platform can be reduced by the strategies for reducing the flow and reducing the pressure, wherein when the load weight of the target platform is reduced according to the strategies for reducing the flow and reducing the pressure, the two strategies need to be used in cooperation with each other, namely when the flow is reduced, the pressure needs to be synchronously reduced, and the variable displacement pump is prevented from being damaged due to excessive reduction or excessive reduction.
In specific implementation, the load weight controller obtains preset load weight information, and if the current load weight information is greater than or equal to the preset load weight information, a target unloading strategy is obtained.
And the reducing module 30 is configured to reduce the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information.
It should be understood that the load of the target workbench is formed by combining the current flow information and the current pressure information when the target workbench operates, and therefore, the essence of load reduction on the target workbench is to reduce the current flow information and the current pressure information, and since the target unloading strategy is a strategy for reducing flow and reducing pressure, the corresponding current flow in the current flow information or the corresponding pressure value in the current pressure information is reduced through the target unloading strategy to obtain the target flow information and the target pressure information.
In specific implementation, the load weight controller reduces the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information.
And the control module 40 is configured to determine a target load capacity of the target workbench according to the target flow information and the target pressure information, so as to control the load weight of the target workbench.
It should be understood that, after obtaining the target flow information and the target pressure information, obtaining a preset neural network model, extracting node information and function information in the preset neural network model, modifying the node information and the function information according to the target flow information and the target pressure information, respectively, obtaining target node information and target function information, obtaining a preset neural network policy, training the target node information and the target function information according to the preset neural network policy, obtaining a target neural network model, predicting the target flow information and the target pressure information according to the target neural network model, so as to obtain a target load capacity of the target workbench, where the preset neural network model may be a convolutional neural network model or another neural network model, and this embodiment is not limited thereto and takes the convolutional neural network model as an example for explanation, the node information and the function information are constituent elements of a preset network model, and because the number of nodes and the function parameters of the preset neural network model are incompatible with the target flow information and the target pressure information, the node information and the function information need to be modified according to the target flow information and the target pressure information to obtain the target node information and the target function information, the preset neural network strategy refers to a strategy for training the parameter information or data into the neural network model, and the same type of neural network model corresponding to the parameter information or data is obtained through training of the preset neural network strategy.
Further, in order to improve the accuracy of obtaining the load capacity of the target workbench, after predicting the target flow information and the target pressure information according to the target neural network model, the method further includes:
acquiring a preset load threshold, and if the target load is larger than the preset load threshold, extracting flow information and pressure information of the preset load; and predicting the extracted flow information and pressure information according to the target neural network model to obtain the predicted load capacity of the target workbench.
It can be understood that the preset load threshold refers to a load between the maximum load and the qualified load that can be borne by the target workbench, and since the preset load threshold is not within the safety range, if the predicted target load is greater than the preset load, the flow information and the pressure information of the preset load need to be extracted again, and the target load is predicted again in the target neural network model to obtain the predicted load of the target workbench, where the predicted load is the load of the controlled target workbench.
In specific implementation, the load weight controller determines the target load capacity of the target workbench according to the target flow information and the target pressure information, so as to realize control on the load weight of the target workbench.
The method comprises the steps of determining corresponding current load weight information according to current running state information by obtaining the current running state information of a target workbench; acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information; reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information; determining the target load capacity of the target workbench according to the target flow information and the target pressure information; when the current load weight information is larger than the preset load weight information, the load of the target workbench is reduced through the target unloading strategy, so that the load weight of the target workbench can be controlled, and compared with the prior art that the load weight of the workbench is controlled by adjusting the lifting device, the accuracy of controlling the load weight can be effectively improved.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may refer to the method for controlling the load weight of the workbench according to any embodiment of the present invention, and are not described herein again.
In an embodiment, the determining module 10 is further configured to obtain current operation state information of a target workbench, and obtain left load weight information and right load weight information of the target workbench according to the current operation state information; respectively extracting characteristic information of the left load weight information and the right load weight information; and obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information.
In an embodiment, the determining module 10 is further configured to obtain a preset linear algorithm, and perform curve fitting on the feature information according to the preset linear algorithm to obtain a corresponding feature curve graph; selecting the characteristic curve graph according to the current running state information to obtain target characteristic information; and acquiring historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the target characteristic information.
In an embodiment, the reducing module 30 is further configured to obtain current parameter information of a hydraulic pump disposed on the target workbench, and obtain corresponding current flow information and current pressure information according to the current parameter information; and reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information.
In an embodiment, the reducing module 30 is further configured to reduce the current traffic information according to the target unloading policy to obtain target traffic information; and acquiring a preset flow threshold, and if the flow in the target flow information is larger than the preset flow threshold, decompressing the current pressure information according to the target unloading strategy to obtain target pressure information.
In an embodiment, the control module 40 is further configured to obtain a preset neural network model, and extract node information and function information in the preset neural network model; modifying the node information according to the target flow information and the target pressure information to obtain target node information; adjusting the function information according to the target flow information and the target pressure information to obtain target function information; acquiring a preset neural network strategy, and training the target node information and the target function information according to the preset neural network strategy to obtain a target neural network model; and predicting the target flow information and the target pressure information according to the target neural network model to obtain the target load capacity of the target workbench.
In an embodiment, the control module 40 is further configured to obtain a preset load threshold, and if the target load is greater than the preset load threshold, extract flow information and pressure information of the preset load; and predicting the extracted flow information and pressure information according to the target neural network model to obtain the predicted load capacity of the target workbench.
Other embodiments or methods of implementing the apparatus for controlling the table load weight according to the present invention are described with reference to the method embodiments described above, and are not intended to be exhaustive.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A method for controlling the load weight of a workbench is characterized by comprising the following steps:
acquiring current running state information of a target workbench, and determining corresponding current load weight information according to the current running state information;
acquiring preset load weight information, and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information;
reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information;
determining a target load capacity of the target workbench according to the target flow information and the target pressure information so as to realize control of the load weight of the target workbench;
the obtaining of the current operation state information of the target workbench and the determining of the corresponding current load weight information according to the current operation state information include:
acquiring current running state information of a target workbench, and acquiring left load weight information and right load weight information of the target workbench according to the current running state information;
respectively extracting characteristic information of the left load weight information and the right load weight information;
and obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information.
2. The method for controlling the load weight of the workbench according to claim 1, wherein the obtaining of the historical load weight information and the searching of the corresponding current load weight information in the historical load weight information according to the characteristic information comprises:
acquiring a preset linear algorithm, and performing curve fitting on the characteristic information according to the preset linear algorithm to obtain a corresponding characteristic curve graph;
selecting the characteristic curve graph according to the current running state information to obtain target characteristic information;
and acquiring historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the target characteristic information.
3. The method for controlling the loading weight of the workbench according to claim 1, wherein the reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information comprises:
acquiring current parameter information of a hydraulic pump arranged on the target workbench, and acquiring corresponding current flow information and current pressure information according to the current parameter information;
and reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information.
4. The method for controlling the load weight of the workbench according to claim 3, wherein the reducing the current flow information and the current pressure information according to the target unloading strategy to obtain target flow information and target pressure information comprises:
reducing the current flow information according to the target unloading strategy to obtain target flow information;
and acquiring a preset flow threshold, and if the flow in the target flow information is larger than the preset flow threshold, decompressing the current pressure information according to the target unloading strategy to obtain target pressure information.
5. The method for controlling the load weight of the workbench according to any one of claims 1 to 4, wherein the determining the target load capacity of the target workbench according to the target flow information and the target pressure information comprises:
acquiring a preset neural network model, and extracting node information and function information in the preset neural network model;
modifying the node information according to the target flow information and the target pressure information to obtain target node information;
adjusting the function information according to the target flow information and the target pressure information to obtain target function information;
acquiring a preset neural network strategy, and training the target node information and the target function information according to the preset neural network strategy to obtain a target neural network model;
and predicting the target flow information and the target pressure information according to the target neural network model to obtain the target load capacity of the target workbench.
6. The method of controlling the table load weight according to claim 5, wherein after predicting the target flow information and the target pressure information according to the target neural network model, further comprising:
acquiring a preset load threshold, and if the target load is larger than the preset load threshold, extracting flow information and pressure information of the preset load;
and predicting the extracted flow information and pressure information according to the target neural network model to obtain the predicted load capacity of the target workbench.
7. A control device for a table load weight, comprising:
the determining module is used for acquiring the current running state information of the target workbench and determining corresponding current load weight information according to the current running state information;
the acquisition module is used for acquiring preset load weight information and acquiring a target unloading strategy if the current load weight information is greater than or equal to the preset load weight information;
the reduction module is used for reducing the load of the target workbench according to the target unloading strategy to obtain target flow information and target pressure information;
the control module is used for determining the target load capacity of the target workbench according to the target flow information and the target pressure information so as to control the load weight of the target workbench;
the determining module is further configured to obtain current operation state information of a target workbench, and obtain left load weight information and right load weight information of the target workbench according to the current operation state information; respectively extracting characteristic information of the left load weight information and the right load weight information; and obtaining historical load weight information, and searching corresponding current load weight information in the historical load weight information according to the characteristic information.
8. A control apparatus for a table load weight, the control apparatus comprising: a memory, a processor, and a control program of a table load weight stored on the memory and executable on the processor, the control program of a table load weight being configured with a control method of implementing a table load weight according to any one of claims 1 to 6.
9. A storage medium having a table load weight control program stored thereon, the table load weight control program, when executed by a processor, implementing the table load weight control method according to any one of claims 1 to 6.
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