CN109960871B - Single-station testing modeling scheduling method for performance of precision speed reducer of industrial robot - Google Patents

Single-station testing modeling scheduling method for performance of precision speed reducer of industrial robot Download PDF

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CN109960871B
CN109960871B CN201910220955.0A CN201910220955A CN109960871B CN 109960871 B CN109960871 B CN 109960871B CN 201910220955 A CN201910220955 A CN 201910220955A CN 109960871 B CN109960871 B CN 109960871B
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刘桂雄
林志宇
汤少敏
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South China University of Technology SCUT
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Abstract

The invention discloses a single-station test modeling scheduling method for the performance of a precision speed reducer of an industrial robot, which comprises the following steps: selecting a performance test item required by the precision speed reducer of the tested industrial robot; establishing a selected project test operation execution flow program list set, and solving an optimization relation among the execution sequences of the projects; constructing a test item sequence optimization matrix, and degenerating complete optimization items in the test item sequence optimization matrix; constructing a test path matrix, solving an optimal test path by using a genetic algorithm, and calculating a shortest test sequence and test time; and testing the precision speed reducer of the industrial robot in sequence according to the shortest test sequence. According to the invention, by scheduling a plurality of performance test items of the industrial robot precision reducer in a single station, multi-task comprehensive test is realized, the test cost is greatly saved, and the test efficiency is improved.

Description

Single-station testing modeling scheduling method for performance of precision speed reducer of industrial robot
Technical Field
The invention belongs to the technical field of reducer performance testing, and particularly relates to a single-station testing, modeling and scheduling method for the performance of a precision reducer of an industrial robot.
Background
The precision speed reducer is one of the core components of the industrial robot, the quality of the precision speed reducer directly influences the precision and the service life of the industrial robot, and how to accurately, quickly and reliably test the performance of the precision speed reducer has important significance. The performance test is the most important part in the quality detection link of the industrial robot speed reducer, according to relevant national and industrial standards, the robot precision speed reducer test items mainly comprise 10 types of no-load experiments, overload experiments, transmission efficiency, starting torque, torsional rigidity, idle stroke and backlash, transmission errors, service life experiments and the like, the test conditions of all items are different, the test procedures are complex, and the test environment of a tested piece needs to be frequently switched in the test process. The current mainstream test method is that after a test item and a test sequence are selected, a test flow is sequentially clamped and loaded for testing the precision speed reducer according to the requirement of the item, a large amount of waiting time exists in the test process, the overall test time is long, and the efficiency is low.
The invention discloses a single-station test modeling scheduling method for the performance of a precision speed reducer of an industrial robot, which models the speed reducer test process, constructs a corresponding scheduling model, solves the optimal test path under the currently selected test item by adopting a scheduling algorithm, further executes a test task, greatly saves the test time, and improves the test efficiency
The specific patent references and related documents mentioned above are:
1) and "a test system for robot decelerator", patent application No. 201811284065.8. The invention discloses a test system of a robot speed reducer, which comprises a bottom plate, a support platform, a vertical plate, a servo motor and a rotating rod, wherein the speed reducer is fixed on the vertical plate and connected with the rotating rod during testing. The test system can only realize the comprehensive test of the temperature change, the angle value and the torque value of the speed reducer, and can not carry out scheduling optimization on the test process.
2) The Wangchang Zhang Hui, Wutai and Boyu of northern industry university provide a dynamic measurement and control system for detecting the transmission precision, back clearance, torsional rigidity, return stroke error, mechanical efficiency, start-stop torque and friction torque of a RV reducer of a robot in the measurement and control system design of the comprehensive performance parameter detection of the RV reducer in the 2 nd journal of northern industry university in 2018. The hardware part selects test components such as an industrial personal computer, a frequency converter, an angle and torque sensor, a collection card and the like; the software part carries out test interface design based on LabVIEW graphical programming language, and can carry out real-time control and monitoring on the whole test process. The system can complete multiple testing tasks of the RV reducer for the industrial robot, is improved in measurement precision and working efficiency compared with the traditional testing system, cannot realize optimized scheduling of a testing process, and is limited in improvement of testing efficiency.
3) The article provides a hybrid genetic simulated annealing algorithm for solving the workshop operation scheduling problem on a small-sized microcomputer system in the 2 nd stage of 2015, which combines the advantages of the genetic algorithm and the simulated annealing algorithm, can solve the workshop operation scheduling problem and make the maximum completion time of workshop operation shortest. The scheduling model provided by the article is suitable for multi-machine and multi-process operation scheduling, but the testing process of the industrial robot precision speed reducer belongs to single-station multi-task scheduling, the establishment of the scheduling model is obviously different from the method described in the paper, and the method is not suitable for scheduling of the testing task of the industrial robot precision speed reducer.
4) The invention discloses a test task scheduling method, which is characterized in that a certain number of test task queues are arranged, the priority range of test tasks which can be listed is appointed for each test task queue, and the test tasks are added into the corresponding test task queues according to the priority of each test task during testing. The invention only carries out redistribution arrangement according to the item priority in the test, and can not substantially shorten the test time and improve the test efficiency.
5) And "serial scheduling method and apparatus for multitasking", patent application No. 201610130066.1, which discloses a serial scheduling method and apparatus for multitasking. Wherein, the method comprises the following steps: receiving a multi-task serial scheduling request, determining current serial scheduling configuration information according to a batch identifier of the current serial scheduling, and scheduling tasks in the configuration information according to an execution sequence number and an identifier of a system to which the tasks belong. The method only ensures the scheduling and execution of the task change, and cannot realize the effect of optimized execution of the test task of the precision speed reducer of the industrial robot for the input of the test task.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a single-station test modeling scheduling method for the performance of a precision speed reducer of an industrial robot.
The purpose of the invention is realized by the following technical scheme:
a single-station test modeling scheduling method for performance of a precision speed reducer of an industrial robot comprises the following steps:
step A, decomposing all testable projects according to project execution operation, and establishing a test sequence set of all projects;
b, selecting the industrial robot precision reducer test items to be tested, and setting the test sequence relation of part of the items;
step C, establishing a sequence set of the selected items, solving an optimization relation among the items according to the sequence set, filling and determining an optimization relation matrix by combining the set item sequence relation, and further cutting the matrix according to the element values in the matrix;
d, according to the cut optimization relation matrix, obtaining an optimal path matrix by using a genetic algorithm, and restoring a corresponding optimal test sequence;
and E, sequentially carrying out performance test on the industrial robot precision speed reducer according to the obtained optimal test sequence.
One or more embodiments of the present invention may have the following advantages over the prior art:
the testing process is scheduled and modeled, the genetic algorithm is used for solving to obtain the optimal testing path, and finally the single-station multi-task test is carried out according to the testing sequence of the obtained optimal path, so that the testing time is greatly shortened, and the testing efficiency is improved.
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FIG. 1 is a flow chart of a single-station test modeling and scheduling method for the performance of a precision reducer of an industrial robot;
FIG. 2 is a detailed flow chart of the implementation process of the single-station testing, modeling and scheduling method for the performance of the precision reducer of the industrial robot.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings.
As shown in FIG. 1, the single-station testing, modeling and scheduling method for the performance of the precision speed reducer of the industrial robot comprises the following steps:
step 10, decomposing all testable items according to item execution operation, and establishing a test sequence set of all items;
step 20, selecting the precision reducer test items of the industrial robot to be tested, and setting the test sequence relation of part of the items;
step 30, establishing a sequence set of the selected items, solving an optimization relation among the items according to the sequence set, filling and determining an optimization relation matrix by combining the set item sequence relation, and further cutting the matrix according to the element values in the matrix;
step 40, according to the cut optimization relation matrix, utilizing a genetic algorithm to obtain an optimal path matrix, and restoring a corresponding optimal test sequence;
step 50, sequentially carrying out performance test on the industrial robot precision speed reducer according to the obtained optimal test sequence;
1. in step 10, as shown in fig. 2, the execution operation of the precision retarder in all the test items can be regarded as being composed of basic test units, the type of each basic test unit is determined by 4 parts of execution rotation speed, execution steering, execution load and execution time, and the set of the execution units of all the items in step 10 is set as X, XiThe i-th execution unit in the m-type execution units under test is represented by:
X＝{xi|xi＝(xsi,xli,xdi,xti)，i∈(1,m)}
let Y be the set of all item sequences, and any item sequence Y in YjConsisting of elements of X, t (y)j) Test time required for a sequence of items, kiIs a sequence yjIn (a) contains xiA number of elements that satisfies:
Figure BDA0002003594520000041
2. in step 20, selecting test items according to different test requirements, and setting the sequence of partial test items according to the requirements;
3. in step 30, taking out the corresponding item sequence from Y according to the selected item, wherein the calculation formula of the optimization relationship among the items is as follows:
cij＝r(yi→yj)＝t(yj)-t(yi∩yj)
wherein: c. CijTo execute yiRear yjExecution time of r (y)i→yj) For selecting the ith item yiPoint to the jth item yjIf there is an order in which the items are set to be executed in step 20, the operation that does not satisfy the execution order is regarded as that the execution process is not optimized, and corresponds to cijThe value is + ∞, and all optimized sequence values are solved to obtain a matrix C which meets the following conditions:
Figure BDA0002003594520000051
supplementing an initial node in the matrix C, namely supplementing the length value of the sequence of each corresponding item into the first row, and filling 0 element in the first column to enable the first row to meet the square matrix, so that a selected item optimization relation matrix C' can be obtained, which meets the following requirements:
Figure BDA0002003594520000052
Figure BDA0002003594520000053
if the non-diagonal and non-first row elements in the optimization matrix C 'are 0, deleting the rows and columns of the test items corresponding to the elements in the optimization matrix C', and cutting to obtain a matrix D:
Figure BDA0002003594520000054
wherein:
dij≠0,i≠j&j≠1
4. in step 40, the path matrix R represents an optimized connection sequence between the items in the clipped optimized matrix D, which satisfies:
Figure BDA0002003594520000061
rijrepresenting node yjTo node yiThe value of (a) is:
Figure BDA0002003594520000062
the testing time after the corresponding optimization of the different path matrixes meets the following relational expression:
t＝tr(R·D)
randomly generating an initial generation optimized path matrix set by using a genetic algorithm, calculating respective corresponding test time, selecting excellent individuals for cross variation, and generating a filial generation optimized path set; enabling the filial generation optimized path set to serve as a new generation genetic algorithm parent, and repeatedly executing the operation; and after the multi-generation development and evolution, taking the optimal individual in the final filial generation as a global optimal solution, namely an optimal path matrix corresponding to the shortest test time.
And (3) restoring the optimal test sequence according to the project sequence set and the interactive calculation process in the steps 10 and 30 according to the optimal path matrix.
5. In step 50, according to the optimal test sequence obtained in step 40, restoring the corresponding test operation and installing the test, so as to complete the optimal scheduling test process of the selected item.
Although the embodiments of the present invention have been described above, the above descriptions are only for the convenience of understanding the present invention, and are not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (5)

1. A single-station test modeling scheduling method for performance of a precision speed reducer of an industrial robot is characterized by comprising the following steps:
step A, decomposing all testable projects according to project execution operation, and establishing a test sequence set of all projects;
b, selecting the industrial robot precision reducer test items to be tested, and setting the test sequence relation of part of the items;
step C, establishing a sequence set of the selected items, solving an optimization relation among the items according to the sequence set, filling and determining an optimization relation matrix by combining the set item sequence relation, and further cutting the matrix according to the element values in the matrix;
d, according to the cut optimization relation matrix, obtaining an optimal path matrix by using a genetic algorithm, and restoring a corresponding optimal test sequence;
step E, sequentially carrying out performance test on the industrial robot precision speed reducer according to the obtained optimal test sequence;
setting the execution unit set of all the items in the step A as X, XiThe i-th execution unit in the m-type execution units under test is represented by:
X＝{xi|xi＝(xsi,xli,xdi,xti)，i∈(1,m)}
let Y be the set of all item sequences, and any item sequence Y in YjConsisting of elements of X, t (y)j) Test time required for a sequence of items, kiIs a sequence yjIn (a) contains xiA number of elements that satisfies:
Figure FDA0002767643680000011
in the step B, test items are selected according to different test requirements, and the sequence of partial test items can be set according to the requirements;
in the step C: the optimization relationship among the projects refers to the minimum time required for executing one project sequence and then executing the other project sequence;
the optimized relation matrix refers to a matrix corresponding to pairwise relations among the items after the initial nodes are added;
the cutting process refers to deleting rows and columns of the item sequence corresponding to the non-first-row and non-diagonal 0-value elements in the matrix;
taking out the corresponding item sequence from Y according to the selected item, wherein the calculation formula of the optimization relationship among the items is as follows:
cij＝r(yi→yj)＝t(yj)-t(yi∩yj)
wherein: c. CijTo execute yiRear yjExecution time of r (y)i→yj) For selecting the ith item yiPoint to the jth item yjIf the sequence value after optimization in step B has the sequence of setting the execution of the items, the operation which does not meet the execution sequence is regarded as that the execution process is not optimized, and the operation corresponds to cijThe value is + ∞, and all optimized sequence values are solved to obtain a matrix C which meets the following conditions:
Figure FDA0002767643680000021
supplementing an initial node in the matrix C, namely supplementing the length value of the sequence of each corresponding item into the first row, and filling 0 element in the first column to enable the first row to meet the square matrix, so that a selected item optimization relation matrix C' can be obtained, which meets the following requirements:
Figure FDA0002767643680000022
Figure FDA0002767643680000023
if the non-diagonal and non-first row elements in the optimization matrix C 'are 0, deleting the rows and columns of the test items corresponding to the elements in the optimization matrix C', and cutting to obtain a matrix D:
Figure FDA0002767643680000024
wherein:
dij≠0,i≠j&j≠1
in step D, the path matrix R represents an optimized connection order between the items in the clipped optimized matrix D, which satisfies:
Figure FDA0002767643680000025
wherein r isijRepresenting node yjTo node yiConnection relation of (a), yj→yiRepresenting the execution of the item sequence i after the execution of the item sequence j;
the testing time after the corresponding optimization of the different path matrixes meets the following relational expression:
t＝tr(R·D)
randomly generating an initial generation optimized path matrix set by using a genetic algorithm, calculating respective corresponding test time, selecting excellent individuals for cross variation, and generating a filial generation optimized path set; enabling the filial generation optimized path set to serve as a new generation genetic algorithm parent, and repeatedly executing excellent individual selection and cross mutation operations; and after the multi-generation development and evolution, taking the optimal individual in the final filial generation as a global optimal solution, namely an optimal path matrix corresponding to the shortest test time.
2. The single-station testing, modeling and scheduling method for the performance of the industrial robot precision reducer according to claim 1 is characterized in that the robot precision reducer is a harmonic reducer or an RV reducer for a robot.
3. The method for single-station test modeling scheduling of the performance of the industrial robot precision reducer according to claim 1, wherein the single-station test modeling scheduling refers to scheduling optimization when only one industrial robot precision reducer to be tested exists.
4. The industrial robot precision reducer performance single-station test modeling and scheduling method according to claim 1, wherein in the step B, the setting of the precedence relationship of the partial items means that the execution sequence of the partial items is subjected to relevant test standard specifications.
5. The single-station test modeling and scheduling method for the performance of the precision reducer of the industrial robot according to claim 1 is characterized in that in the step D: the optimal test sequence refers to the test sequence with the shortest solved time.
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