CN117371639B - Torpedo tank motion optimization method, electronic equipment and readable storage medium - Google Patents
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
Abstract
The invention relates to the field of building intellectualization, in particular to a torpedo tank motion optimization method, which comprises the following steps: s1, determining the travelling track of a torpedo ladle along a track; s2, taking the energy consumed by the torpedo tank for advancing a set time value under a set advancing track as a time energy value; s3, performing iterative optimization on the set time value until the time energy value corresponding to the time value after iteration reaches the minimum; s4, controlling the driving motor to drive the torpedo tank to move at a constant rotating speed, so that the torpedo tank finishes the travel of the set travel track at a time value corresponding to the lowest time energy value. The invention ensures that the energy consumed by the torpedo tank when moving along the set track reaches the optimal balance point in time, thereby greatly improving the transportation efficiency of the torpedo tank.
Description
Technical Field
The invention relates to the field of building intellectualization, in particular to a torpedo tank motion optimization method, electronic equipment and a readable storage medium.
Background
The fabricated building refers to a building assembled from prefabricated parts on a construction site. The assembled building is mainly divided into three forms, namely an assembled wood structure, an assembled steel structure building and an assembled concrete structure. As a matching link of an assembled concrete building, the construction of a PC component factory is also focused by various enterprises, the construction management operation of the PC component factory becomes a major subject to be put in front of a constructor, which functions the PC component factory needs to meet, how the capacity design and the equipment configuration match, how the component yard and the capacity match, and whether the effect of factory construction can reach the design requirement can be influenced.
In a PC construction factory, an important transportation tool, namely a torpedo tank, is mainly responsible for transporting stirred concrete to a corresponding pouring station, and in the process of driving the torpedo tank to travel along a track through a driving motor, the time consumed by the movement of the torpedo tank on the track and the energy consumed by the movement are not optimally considered, so that the total amount of the consumed energy is possibly increased in the actual production process due to overlong and excessively short transportation, the time consumed by the movement of the torpedo tank along the set track and the consumed energy cannot reach an optimal balance point, and the transportation efficiency is low, so that the problem is to be solved.
Disclosure of Invention
In order to avoid and overcome the technical problems in the prior art, the invention provides a torpedo tank motion optimization method. The invention ensures that the energy consumed by the torpedo tank when moving along the set track reaches the optimal balance point in time, thereby greatly improving the transportation efficiency of the torpedo tank.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a torpedo tank motion optimizing method comprises the following steps:
s1, determining the travelling track of a torpedo ladle along a track;
s2, taking the energy consumed by the torpedo tank for advancing a set time value under a set advancing track as a time energy value;
s3, performing iterative optimization on the set time value until the time energy value corresponding to the time value after iteration reaches the minimum;
s4, controlling the driving motor to drive the torpedo tank to move at a constant rotating speed, so that the torpedo tank finishes the travel of the set travel track at a time value corresponding to the lowest time energy value.
As a further scheme of the invention: in step S1, the torpedo tank is used at the starting point of the trackIs M 0 On-orbit with torpedo tank The end point of the track is M j ，M 1 、M 2 、…、M j－1 Indicating the common between the start and end of the trackj－1 key point; the torpedo tank moves along each key point and formsjGroup time sequences, each group time sequence havingnEach time value represents a different time spent by adjacent key points, and the optimal time value in each group of time series is calculated through step S3.
As still further aspects of the invention: in step S3:
s31, calculate the firstjCurrent optimum discrimination factor for group time seriesES；
S32, select the firstjTime values in group time seriesX i As a start-up time value, calculateX i Is a discrimination factor of (2)ES i ；
S33, pairX i Performing an iteration, comprising:
s331, whenX i Is a discrimination factor of (2)ES i Greater thanESIn the time-course of which the first and second contact surfaces,
；
wherein,X i New representation pairX i Performing a new time value after iteration;
ris [0,1]Random numbers within a range;
s332, whenX i Is a discrimination factor of (2)ES i Less thanESIn the time-course of which the first and second contact surfaces,
；
X BS representing the first in the iterative processjA current optimal time value of the group time series;
X CP representing the first in the iterative processjThe average time of all current time values of the group time series;
SL i for time valueX i Stability level of (2);
r 1 andr 2 Are all [0,1 ]]Random numbers within a range;
s34, generating new time value by iterationX i New Add the firstjIn the group time sequence, and update the firstjCurrent optimum discrimination factor for group time seriesESThe method comprises the steps of carrying out a first treatment on the surface of the Calculation ofX i New Is a discrimination factor of (2)ES i New Repeating the step S33 pairX i New Performing iteration;
s35, in step S33, whenX i Is a discrimination factor of (2)ES i Equal toESWhen the iteration is stopped, the methodX i Outputting the optimal time value;
or, in step S34, whenX i New Is a discrimination factor of (2)ES i New Equal toESWhen the iteration is stopped, the methodX i New The output is the optimal time value.
As still further aspects of the invention: first, thejCurrent optimum discrimination factor for group time seriesESThe method comprises the following steps:
；
wherein,c 1 andc 2 Are all discrimination constants;
EBrepresent the firstjAverage time energy value of the group time series;
SLrepresent the firstjAverage stability level of group time series;
in the step S34 of the process of the present invention,X i New add the firstjAfter group time series, pairSLAndEBUpdating to output new current optimal discrimination factorES。
As still further aspects of the invention: first, thejAverage time energy value of group time seriesEBThe method comprises the following steps:
；
NEL i representation ofX i The corresponding time energy value;
；
representing torque of a torpedo tank driving motor;
qthe angular acceleration of the torpedo tank driving motor is represented;
dtrepresenting time differentiation;
representing a learning factor;
representing a temporal weight factor;
representing energy expenditure weighting factors, < >>。
As still further aspects of the invention: first, thejAverage stability level of group time seriesSLThe method comprises the following steps:
。
as still further aspects of the invention: time valueX i Stability level of (2)SL i The method comprises the following steps:
；
wherein,BSis the firstjIn the group time sequence, the time energy value corresponding to the time value with the highest current stability level;
WSis the firstjIn the group time series, the time energy value corresponding to the time value with the lowest current stability level.
The electronic device is characterized by comprising a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are sequentially connected, the memory is used for storing a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions and execute the torpedo tank motion optimization method.
A readable storage medium, characterized in that the storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform a method of fish tank motion optimization.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the optimal passing time of the torpedo tank when the movement path is set is calculated based on the time energy value, so that the torpedo tank can be transported for a short time under the condition of smaller energy consumption, the energy consumed by the torpedo tank when moving along the set track reaches the optimal balance point, the transportation efficiency of the torpedo tank is greatly improved, the movement control of the torpedo tank is dynamically optimized, the optimal balance of time and energy is realized, and the transportation time is reduced.
2. According to the invention, the motion of the torpedo tank is controlled through an optimization algorithm, so that the motion of the torpedo tank under various tracks can be processed, the robustness is realized on the interference of some uncertainties in the torpedo tank, and the labor cost in the process of transporting the torpedo tank can be reduced.
3. The invention introduces continuously updated discrimination factors, and updates the formula according to the discrimination factors, thereby improving the accuracy of the algorithm; the concept of stability level is introduced, so that the algorithm has the characteristic of rapid convergence and relatively low function iteration times.
4. The time energy value is introduced, the energy consumption and the time cost are comprehensively considered, so that a balance point is found in the movement process of the torpedo tank, the situation that only one side is focused and the other side is ignored can be avoided, and the energy utilization rate is improved: the time energy value can help optimize the path, so that the energy consumption of the torpedo tank is reduced as much as possible in the walking process, the torpedo tank can more effectively utilize energy, the use time is prolonged or the energy consumption is reduced, and the minimum walking time of the torpedo tank is found; the time energy value can be adjusted and optimized according to actual requirements. In a particular design, the weights of energy and time may be adjusted to meet specific requirements and constraints according to different constraints and optimization objectives.
Drawings
FIG. 1 is a graph showing the relationship between the number of algorithm iterations and the time energy value in the present invention.
FIG. 2 is a schematic diagram of the relationship between the number of iterations and the optimal time point in the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, in an embodiment of the invention, a method for optimizing the motion of a torpedo tank includes the following steps:
s1, determining the travelling track of a torpedo ladle along a track; with torpedo tanks at the start of the trackIs M 0 With torpedo tanks on the track The end point of (C) is M j ，M 1 、M 2 、…、M j－1 Indicating the common between the start and end of the trackj－1 key point; the torpedo tank moves along each key point and formsjGroup time sequences, each group time sequence havingnEach time value representing a different time spent by passing adjacent keypoints.
S2, taking the energy consumed by the torpedo tank for advancing a set time value under a set advancing track as a time energy value; the lower the time energy value, the better the corresponding time value. In the calculation process, the limit that the maximum moment, the angular acceleration and the angular speed cannot be exceeded by the driving motor of the torpedo tank is taken as a constraint condition.
In time valuesX i For example, time valueX i Corresponding time energy valueNEL i The method comprises the following steps:
；
representing torque of a torpedo tank driving motor;
qthe angular acceleration of the torpedo tank driving motor is represented;
dtrepresenting time differentiation;
representing a learning factor for ensuring that the total time and total energy dissipation of the torpedo tank operation are in the same order of magnitude;
representing a temporal weight factor;
represents an energy expenditure weighting factor, and +.>The method comprises the steps of carrying out a first treatment on the surface of the The time and energy dissipation can be balanced by adjusting the time weight factor and the energy consumption weight factor.
S3, performing iterative optimization on the set time value until the time energy value corresponding to the time value after iteration reaches the minimum;
s31, calculate the firstjCurrent optimum discrimination factor for group time seriesES；
First, thejCurrent optimum discrimination factor for group time seriesESThe method comprises the following steps:
；
wherein,c 1 andc 2 Are all discrimination constants;
EBrepresent the firstjAverage time energy value of the group time series;
SLrepresent the firstjAverage stability level of group time series;
first, thejAverage time energy value of group time seriesEBThe method comprises the following steps:
；
first, thejAverage stability level of group time seriesSLThe method comprises the following steps:
；
nis the firstjThe total number of time values in the set time series dynamically varies as the iterative process time value increases.
S32, select the firstjTime values in group time seriesX i As a start-up time value, calculateX i Is a discrimination factor of (2)ES i ；X i Can be from the firstjOf group time seriesnRandomly selected from, or from, time valuesnA time value is randomly selected outside the time values.
Time valueX i Stability level of (2)SL i The method comprises the following steps:
；
wherein,BSis the firstjOf group time seriesnThe time energy value corresponding to the time value with the highest stability level among the time values; first, thejThere is no pre-iteration initial existence in the group time sequencenA time value, a first iteration,BSis initialnThe time energy value corresponding to the time value with the highest stability in the time values is the following iterationjThe time values in the group time series are updated continuously,BSthe values vary with this.
WSIs the firstjOf group time seriesnThe time energy value corresponding to the time value with the lowest stability level among the time values; first, thejThere is no pre-iteration initial existence in the group time sequencenA time value, a first iteration,WSis initialnThe time energy value corresponding to the time value with the highest stability in the time values is the following iterationjThe time values in the group time series are updated continuously,WSthe values vary with this.
S33, pairX i Performing an iteration, comprising:
s331, whenX i Is a discrimination factor of (2)ES i Greater thanESIn the time-course of which the first and second contact surfaces,
；
wherein,X i New representation pairX i Performing a new time value after iteration;
ris [0,1]Random numbers in the range are used to determine the amplitude of the time value.
S332, whenX i Is a discrimination factor of (2)ES i Less thanESIn the time-course of which the first and second contact surfaces,
；
X BS representing the first in the iterative processjA current optimal time value of the group time series;
X CP representing the first in the iterative processjThe average time of all current time values of the group time series;
SL i for time valueX i Stability level of (2);
r 1 andr 2 Are all [0,1 ]]Random numbers in the range are used to determine the amplitude of the time value.
X i Is a discrimination factor of (2)ES i The following is shown:
；
c 1 andc 2 Are all discrimination constants;
s34, will iterateThe new time value generatedX i New Add the firstjIn the group time sequence, and update the firstjCurrent optimum discrimination factor for group time seriesESThe method comprises the steps of carrying out a first treatment on the surface of the Calculation ofX i New Is a discrimination factor of (2)ES i New Repeating the step S33 pairX i New Performing iteration;
s35, in step S33, whenX i Is a discrimination factor of (2)ES i Equal toESWhen the iteration is stopped, the methodX i Outputting the optimal time value;
or, in step S34, whenX i New Is a discrimination factor of (2)ES i New Equal toESWhen the iteration is stopped, the methodX i New The output is the optimal time value.
S4, controlling the driving motor to drive the torpedo tank to move at a constant rotating speed, so that the torpedo tank finishes the travel of the set travel track at a time value corresponding to the lowest time energy value.
As shown in fig. 1, the invention optimizes the objective function (time energy value), and the objective function is converged to the minimum value within 5 iterations. As shown in FIG. 2, corresponding to FIG. 1, the fish tank operation has reached the optimal time in a shorter iteration number, and it can be seen that the optimization method of the invention has extremely high convergence speed and higher accuracy.
Another embodiment of the present application is an electronic device.
The electronic device may be the mobile device itself, or a stand-alone device independent thereof, which may communicate with the mobile device to receive the acquired input signals from them and to send the selected target decision-making actions thereto.
The electronic device includes one or more processors and memory.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform the desired functions.
The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by a processor to implement a method of torpedo motion optimization as described above for various embodiments of the present application.
In one example, the electronic device may further include: input devices and output devices, which are interconnected by a bus system and/or other forms of connection mechanisms. For example, the input device may include various devices such as an on-board diagnostic system (OBD), a video camera, an industrial camera, and the like. The input device may also include, for example, a keyboard, mouse, etc. The output means may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
In addition, the electronic device may include any other suitable components depending on the particular application.
Yet another embodiment of the present application is a computer program product, which comprises computer program instructions, which when being executed by a processor, cause the processor to perform the optimization steps according to the various embodiments of the present application described in the above-mentioned torpedo tank motion optimization method part of the present specification.
The computer program product may write program code for performing the operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present application may also be a computer-readable storage medium, having stored thereon computer program instructions, which when executed by a processor, cause the processor to perform a torpedo tank motion optimization method as described in the present specification.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present application have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present application. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, as the application is not intended to be limited to the details disclosed herein as such.
The block diagrams of the devices, apparatuses, devices, systems referred to in this application are only illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
Claims (3)
1. The method for optimizing the movement of the torpedo tank is characterized by comprising the following steps of:
s1, determining the travelling track of a torpedo ladle along a track;
s2, taking the energy consumed by the torpedo tank for advancing a set time value under a set advancing track as a time energy value;
s3, performing iterative optimization on the set time value until the time energy value corresponding to the time value after iteration reaches the minimum;
s4, controlling a driving motor to drive the torpedo tank to move at a constant rotating speed, so that the torpedo tank finishes the travel of the set travel track at a time value corresponding to the lowest time energy value;
in step S1, the torpedo tank is used at the starting point of the trackIs M 0 The end point of the torpedo tank on the track is M j ，M 1 、M 2 、…、M j－1 Indicating the common between the start and end of the trackj－1 key point; the torpedo tank moves along each key point and formsjGroup time sequences, each group time sequence havingnTime values, each time value representing a different time spent by adjacent key points, respectively calculating an optimal time value in each group of time sequences through step S3;
in step S3:
s31, calculate the firstjCurrent optimum discrimination factor for group time seriesES；
S32, select the firstjTime values in group time seriesX i As a start-up time value, calculateX i Is a discrimination factor of (2)ES i ；
S33, pairX i Performing an iteration, comprising:
s331, whenX i Is a discrimination factor of (2)ES i Greater thanESIn the time-course of which the first and second contact surfaces,
wherein,X i New representation pairX i Performing a new time value after iteration;
ris [0,1]Random numbers within a range;
s332, whenX i Is a discrimination factor of (2)ES i Less thanESIn the time-course of which the first and second contact surfaces,
X BS representing the first in the iterative processjA current optimal time value of the group time series;
X CP representing the first in the iterative processjThe average time of all current time values of the group time series;
SL i for time valueX i Stability level of (2);
r 1 andr 2 Are all [0,1 ]]Random numbers within a range;
s34, generating new time value by iterationX i New Add the firstjIn the group time sequence, and update the firstjCurrent optimum discrimination factor for group time seriesESThe method comprises the steps of carrying out a first treatment on the surface of the Calculation ofX i New Is a discrimination factor of (2)ES i New Repeating the step S33 pairX i New Performing iteration;
s35, in step S33, whenX i Is a discrimination factor of (2)ES i Equal toESWhen the iteration is stopped, the methodX i Outputting the optimal time value;
or, in step S34, whenX i New Is a discrimination factor of (2)ES i New Equal toESWhen the iteration is stopped, the methodX i New Outputting the optimal time value;
first, thejCurrent optimum discrimination factor for group time seriesESThe method comprises the following steps:
wherein,c 1 andc 2 Are all discrimination constants;
EBrepresent the firstjAverage time energy value of the group time series;
SLrepresent the firstjAverage stability level of group time series;
in the step S34 of the process of the present invention,X i New add the firstjAfter group time series, pairSLAndEBUpdating to output new current optimal discrimination factorES；
First, thejAverage time energy value of group time seriesEBThe method comprises the following steps:
NEL i representation ofX i The corresponding time energy value;
representing torque of a torpedo tank driving motor;
qthe angular acceleration of the torpedo tank driving motor is represented;
dtrepresenting time differentiation;
representing a learning factor;
representing a temporal weight factor;
representing energy expenditure weighting factors, < >>First, thejAverage stability level of group time seriesSLThe method comprises the following steps:
time valueX i Stability level of (2)SL i The method comprises the following steps:
wherein,BSis the firstjIn the group time sequence, the time energy value corresponding to the time value with the highest current stability level;
WSis the firstjIn the group time series, the time energy value corresponding to the time value with the lowest current stability level.
2. An electronic device comprising a processor, an input device, an output device, and a memory, the processor, the input device, the output device, and the memory being connected in sequence, the memory being configured to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform a method of optimizing the motion of a torpedo tank according to claim 1.
3. A readable storage medium, characterized in that the storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform a torpedo tank motion optimization method according to claim 1.
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