CN111967093A - Balance layout method and device for excavator, electronic equipment and storage medium - Google Patents

Balance layout method and device for excavator, electronic equipment and storage medium Download PDF

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CN111967093A
CN111967093A CN202010826369.3A CN202010826369A CN111967093A CN 111967093 A CN111967093 A CN 111967093A CN 202010826369 A CN202010826369 A CN 202010826369A CN 111967093 A CN111967093 A CN 111967093A
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CN111967093B (en
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刘硕杨
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Shanghai Sany Heavy Machinery Co Ltd
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Abstract

The invention provides a balance layout method and device of an excavator, electronic equipment and a storage medium, and relates to the field of excavators. The method randomly generates an initial population, each vector in the initial population comprises a centroid coordinate value and a counterweight weight corresponding to each of a plurality of components, selecting, cross calculating and mutation calculating the initial group according to the coordinate value of the center of mass corresponding to each of the plurality of components, the weight of each of the plurality of components and the position of the center of rotation of the excavator to obtain a new generation group, carrying out selection operation, cross calculation and variation operation on the new generation group cycle until the obtained fitness mean error and the fitness maximum error of a plurality of new generation groups are all smaller than a first preset value, and then selecting an optimal vector from the last generation group, and obtaining the optimal coordinate distribution value and the optimal weight distribution value of the counterweight corresponding to each of the plurality of components according to the optimal vector, so that the optimal balance layout design of the excavator is realized, and the balance calculation efficiency of the excavator is improved.

Description

Balance layout method and device for excavator, electronic equipment and storage medium
Technical Field
The invention relates to the field of excavators, in particular to a balance layout method and device of an excavator, electronic equipment and a storage medium.
Background
At present, the implementation mode of the balance layout of the excavator is mainly to manually calculate the layout balance of each component after each component of the excavator is preliminarily laid out, and if the balance is found to be unbalanced, the balance weight needs to be finely adjusted and the balance is recalculated. The layout design mode is quite heavy in work, the positions of the obtained parts are not necessarily the optimal positions, and meanwhile, the balance requirements of the front and back and the left and right of the excavator cannot be met simultaneously only by adjusting the balance weight.
Disclosure of Invention
In view of the above, the present invention provides a balance layout method and apparatus for an excavator, an electronic device, and a storage medium, which are capable of obtaining an optimal position of each component of the excavator and an optimal weight of a counterweight, and implementing an optimal balance layout design for the excavator.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a balance layout method for an excavator, which is applied to an electronic device, where mass center position adjustment ranges corresponding to a plurality of components of the excavator, weights of the components except for a counterweight in the plurality of components, and a rotation center position of the excavator are stored in advance in the electronic device; the method comprises the following steps:
randomly generating an initial population, the initial population comprising a first preset number of vectors, each vector comprising a centroid coordinate value and a counterweight weight corresponding to each of the plurality of components; the coordinate value of the center of mass of each part is in the corresponding adjustment range of the position of the center of mass;
selecting the initial population according to the coordinate values of the center of mass corresponding to each of the plurality of components, the weight of each of the plurality of components and the position of the gyration center of the excavator so as to select a first target vector from the initial population;
performing cross calculation and mutation operation on the other vectors except the first target vector in the initial population to obtain a second target vector;
obtaining a new generation group according to the first target vector and the second target vector, and circularly performing selection operation, cross calculation and variation operation on the obtained new generation group until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are smaller than a first preset value;
and selecting an optimal vector from the last generation group of the plurality of new generation groups, and obtaining the optimal coordinate distribution value corresponding to each of the plurality of components and the optimal weight distribution value of the balance weight according to the optimal vector.
In an alternative embodiment, the selecting the initial population according to the coordinate values of the center of mass corresponding to each of the plurality of components, the weight of each of the plurality of components, and the position of the center of gyration of the excavator to select the first target vector from the initial population includes:
respectively calculating the probability value of each vector inherited to the next generation group according to the mass center coordinate values corresponding to the components, the weights of the components and the rotation center position of the excavator;
selecting a first target vector from the initial population according to the probability value of each vector inherited to the next generation population.
In an alternative embodiment, the selecting a first target vector from the initial population according to the probability value of each vector being inherited to the next generation population comprises:
determining a probability interval corresponding to each vector according to the probability value of each vector inherited to the next generation group;
randomly generating a random number between 0 and 1, and determining the number of times each vector is selected according to the number of times the random number appears in each probability interval;
and selecting a second preset number of vectors as the first target vector according to the number of times of selecting each vector.
In an alternative embodiment, each component has a corresponding reference number, the centroid coordinate values include a centroid abscissa and a centroid ordinate, the swing center position includes a swing center abscissa and a swing center ordinate, and the calculating the probability value of each vector being inherited to the next generation group according to the centroid coordinate values corresponding to each of the plurality of components, the respective weights of the plurality of components, and the swing center position of the excavator respectively includes:
according to the formula F ═ 1/(aP)X|+|PYmin|+|PYmaxI) calculating the fitness of each vector, and calculating the sum of the fitness of all vectors in the initial population according to the fitness of each vector; wherein a is a preset balance coefficient, PX=∑9.8×Gi×(Xi-X0),PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],GiDenotes the weight of the part denoted by i, XiThe abscissa of the mass of the part denoted by i, X0Representing the abscissa, Y, of the centre of rotation0Representing the ordinate, G, of the centre of revolutionmRepresenting the weight, Y, of the working device in said plurality of partsmA centroid ordinate, f (Y), representing the fully retracted state of the working devicem) Ordinate of mass, G, representing the working device in a fully extended statejDenotes the weight of a part denoted by j, Y, of the plurality of parts excluding the working devicejA centroid ordinate representing a part of the plurality of parts, denoted by reference numeral j, other than the working device;
according to formula FkCalculating the probability value of each vector inherited to the next generation group; wherein FkAnd F is the fitness of the kth vector, and is the sum of the fitness of all vectors in the initial population.
In an alternative embodiment, the performing the cross-computing and mutation operations on the remaining vectors in the initial population except for the first target vector to obtain a second target vector includes:
carrying out pairwise random pairing on the other vectors except the first target vector in the initial population;
performing cross calculation on the paired vectors to obtain a first intermediate vector;
performing variation operation on the first intermediate vector to randomly select a new centroid coordinate value and a new counterweight weight from the peripheries of the centroid coordinate value and the counterweight weight of each component in the first intermediate vector respectively, and updating the centroid coordinate value and the counterweight weight of each component in the first intermediate vector into the new centroid coordinate value and the new counterweight weight to obtain a second intermediate vector;
and when the mass center coordinate value and the counterweight weight of each component in the second intermediate vector meet a second preset condition, determining the second intermediate vector as a second target vector.
In an alternative embodiment, when the coordinate value of the center of mass and the weight of the counterweight of each component in the second intermediate vector meet a second preset condition, determining the second intermediate vector as a second target vector includes:
when the coordinate values of the mass centers of all the components in the second intermediate vector are all in the corresponding mass center position adjusting range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmaxI) when the second intermediate vector is smaller than a second preset value, determining the second intermediate vector as a second target vector; wherein, PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],Y0Representing the ordinate of the centre of rotation, GmRepresenting the weight, Y, of the working device in said plurality of partsmA centroid ordinate, f (Y), representing the fully retracted state of the working devicem) Ordinate of mass, G, representing the working device in a fully extended statejDenotes the weight of a part denoted by j, Y, of the plurality of parts excluding the working devicejRepresents the ordinate of the mass center of the part, denoted by the reference j, of the plurality of parts, excluding the working device.
In an alternative embodiment, the selecting the optimal vector from the last generation population of the plurality of new generation populations comprises:
calculating the probability value of each vector inherited from the last generation group to the next generation group;
and determining the vector with the maximum probability value as the optimal vector.
In a second aspect, an embodiment of the present invention provides a balance layout device for an excavator, which is applied to an electronic device, where the electronic device stores, in advance, a center-of-mass position adjustment range corresponding to each of a plurality of components of the excavator, a weight of each of the other components except for a counterweight in the plurality of components, and a swing center position of the excavator; the device comprises:
an initial population generating module for randomly generating an initial population, wherein the initial population comprises a first preset number of vectors, and each vector comprises a centroid coordinate value and a counterweight weight corresponding to each of the plurality of components; the coordinate value of the center of mass of each part is in the corresponding adjustment range of the position of the center of mass;
the calculation module is used for selecting the initial population according to the mass center coordinate values corresponding to the components, the weights of the components and the rotation center position of the excavator so as to select a first target vector from the initial population; performing cross calculation and mutation operation on the other vectors except the first target vector in the initial population to obtain a second target vector;
the calculation module is further used for obtaining a new generation group according to the first target vector and the second target vector, and performing selection operation, cross calculation and variation operation on the obtained new generation group in a circulating manner until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are smaller than a first preset value;
and the acquisition module is used for selecting an optimal vector from the last generation group of the plurality of new generation groups and obtaining the optimal coordinate distribution value corresponding to each of the plurality of components and the optimal weight distribution value of the counterweight according to the optimal vector.
In a third aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory, where the memory stores a computer program capable of being executed by the processor, and when the computer program is executed by the processor, the electronic device implements the method according to any one of the foregoing embodiments.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method according to any one of the foregoing embodiments.
The balance layout method, the balance layout device, the electronic equipment and the storage medium for the excavator provided by the embodiment of the invention generate an initial population at random, wherein the initial population comprises a first preset number of vectors, each vector comprises a mass center coordinate value and a counterweight weight which correspond to a plurality of components, the mass center coordinate value of each component is in a corresponding mass center position adjusting range, the initial population is selected according to the mass center coordinate value, the weight and the rotation center position of the excavator, which correspond to the components, so that a first target vector is selected from the initial population, the other vectors except the first target vector in the initial population are subjected to cross calculation and variation operation to obtain a second target vector, a new generation population is obtained according to the first target vector and the second target vector, and the obtained new generation population is circularly subjected to the selection operation, And performing cross calculation and variation operation until the obtained fitness mean error and the fitness maximum error of the plurality of new generation groups are smaller than a first preset value, selecting an optimal vector from the last generation group of the plurality of new generation groups, and obtaining optimal coordinate distribution values and optimal weight distribution values of the balance weights corresponding to the plurality of parts according to the optimal vector. Therefore, the optimal coordinate distribution value of each component of the excavator and the optimal weight distribution value of the balance weight can be obtained only by determining the mass center position adjusting range, the weight and the rotation center position of each component of the excavator, so that the optimal balance layout design of the excavator is realized; meanwhile, the whole balance calculation process does not need human participation, so that the balance calculation efficiency of the excavator is improved.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a block diagram of an electronic device provided by an embodiment of the invention;
FIG. 2 is a flow chart illustrating a balancing layout method of an excavator according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating the sub-steps of step S202 in FIG. 2;
FIG. 4 is a flow chart illustrating the sub-steps of step S203 in FIG. 2;
fig. 5 is a functional block diagram of a balancing layout apparatus of an excavator according to an embodiment of the present invention.
Icon: 100-an electronic device; 110-a memory; 120-a processor; 130-a communication module; 500-balanced layout of excavator; 510-initial population generation module; 520-a calculation module; 530-obtaining module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Fig. 1 is a block diagram of an electronic device 100 according to an embodiment of the invention. The electronic device 100 may be a Personal Computer (PC) device, and the electronic device 100 may obtain an optimal coordinate distribution value of each component of the excavator and an optimal weight distribution value of the counterweight according to a given rotation center position of the excavator, a center of mass position adjustment range of each component, a weight, and other parameters, thereby implementing an optimal balance layout design of the excavator and improving a balance calculation efficiency of the excavator. The electronic device 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, the processor 120, and the communication module 130 are electrically connected to each other directly or indirectly to enable data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
The memory 110 is used to store programs or data. The Memory 110 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor 120 is used to read/write data or programs stored in the memory 110 and perform corresponding functions. For example, the processor 120 may implement the balanced layout method of the excavator disclosed by the embodiment of the present invention by executing the computer program stored in the memory 110.
The communication module 130 is used for establishing a communication connection between the electronic device 100 and another communication terminal through a network, and for transceiving data through the network.
It should be understood that the configuration shown in fig. 1 is merely a schematic diagram of the configuration of the electronic device 100, and that the electronic device 100 may include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor 120, the method for balancing and arranging the excavator disclosed by the embodiment of the present invention can be implemented.
Fig. 2 is a schematic flow chart of a balanced layout method of an excavator according to an embodiment of the present invention. It should be noted that, the balancing layout method of the excavator according to the embodiment of the present invention is not limited by fig. 2 and the following specific sequence, and it should be understood that, in other embodiments, the sequence of some steps in the balancing layout method of the excavator according to the embodiment of the present invention may be interchanged according to actual needs, or some steps in the balancing layout method of the excavator may be omitted or deleted. The balance layout method of the excavator can be applied to the electronic device 100 shown in fig. 1, and the center-of-mass position adjustment ranges corresponding to each of the plurality of components of the excavator, the respective weights of the other components except the counterweight in the plurality of components, and the rotation center position of the excavator are stored in advance in the electronic device 100, and the specific process shown in fig. 2 will be described in detail below.
Step S201, randomly generating an initial population, wherein the initial population comprises a first preset number of vectors, and each vector comprises a mass center coordinate value and a counterweight weight which correspond to a plurality of components; the mass center coordinate value of each part is in the corresponding mass center position adjusting range.
Taking an electric hydraulic excavator as an example, only the changed parts are considered, considering that only the positions or weights of some parts of the electric hydraulic excavator change, and some parts do not change. Wherein, in the part that changes, the position all can change, and except that the weight of counter weight is adjustable, the weight of other parts is all certain. Therefore, in the present embodiment, the center-of-mass position adjustment range corresponding to each of the plurality of components of the excavator, the weight of each of the remaining components of the plurality of components excluding the counterweight, and the swing center position of the excavator may be determined in advance, and these data may be stored in the electronic apparatus 100.
When the electronic device 100 randomly generates the initial population, the centroid coordinate values corresponding to the components in each vector should be within the corresponding centroid position adjustment range, and in order to obtain the result as soon as possible, a range may be set in advance for the weight of the counterweight in the electronic device 100, so that the weight of the counterweight in each randomly generated vector is also within the set counterweight weight range.
In the present embodiment, it is assumed that each component has a corresponding reference numeral, and the centroid coordinate value corresponding to each component includes a centroid abscissa and a centroid ordinate, and the vector may be expressed as M ═ X (X)1,X2,……,Xi,Y1,Y2,……,YiG), wherein XiThe abscissa of the mass of the part denoted by i, YiThe vertical axis of the center of mass of the part denoted by the reference character i, and G the counterweight weight. It should be noted that, since the working device of the excavator has two states of contraction and expansion, when the working device is included in the plurality of components, the centroid ordinate of the working device may be the centroid ordinate in the fully contracted state or the fully expanded state, and there is a certain functional relationship between the centroid ordinate in the fully contracted state and the centroid ordinate in the fully expanded state. In this embodiment, the centroid ordinate of the working device is taken as the centroid ordinate in the fully retracted state for explanation, and the working device is in the fully retracted stateThe centroid ordinate of the contracted state may be represented as YmThe centroid ordinate of the fully retracted working device may be represented as f (Y)m)。
In the present embodiment, the weight of the component denoted by reference numeral i may be denoted as GiThe adjustment range of the center of mass position corresponding to the component marked with the reference number i can be expressed as the maximum allowable X-axis distance X of the center of massimaxMinimum allowable X-axis distance X of center of massiminCenter of mass allowed maximum Y-axis distance YimaxPermissible minimum Y-axis distance Y of center of massimin. The center of mass position adjusting range corresponding to the working device of the excavator comprises a center of mass position adjusting range in a full-contraction state and a center of mass position adjusting range in a full-extension state. Wherein, the adjustment range of the center of mass position in the fully contracted state can be expressed as the maximum allowable X-axis distance X of the center of mass1 imaxMinimum allowable X-axis distance X of center of mass1 iminCenter of mass allowed maximum Y-axis distance Y1 imaxPermissible minimum Y-axis distance Y of center of mass1 imin(ii) a The adjustment range of the center of mass position in the fully extended state can be expressed as the allowable maximum X-axis distance X of the center of mass2 imaxMinimum allowable X-axis distance X of center of mass2 iminCenter of mass allowed maximum Y-axis distance Y2 imaxPermissible minimum Y-axis distance Y of center of mass2 imin
In one example, assuming that the plurality of components include 8 components including a heat sink, a motor and a main pump, a hydraulic oil tank, a battery pack, a counterweight, a PDU (Power Distribution Unit), an AFE (Active Front End Unit), and a working device, and that the corresponding reference numeral of the heat sink is 1, the corresponding reference numeral of the motor and the main pump is 2, the corresponding reference numeral of the hydraulic oil tank is 3, the corresponding reference numeral of the battery pack is 4, the corresponding reference numeral of the counterweight is 5, the corresponding reference numeral of the PDU is 6, the corresponding reference numeral of the AFE is 7, and the corresponding reference numeral of the working device is 8, the centroid coordinate value of the heat sink may be represented as (X is an X-coordinate value of the centroid of the heat sink)1,Y1) The centroid coordinate values of the motor and the main pump may be expressed as (X)2,Y2) The centroid coordinate value of the hydraulic oil tank can be expressed as (X)3,Y3),The centroid coordinate value of the battery pack may be expressed as (X)4,Y4) The mass center coordinate value of the weight can be expressed as (X)5,Y5) The centroid coordinate value of the PDU can be expressed as (X)6,Y6) The centroid coordinate value of the AFE can be expressed as (X)7,Y7) The centroid coordinate value of the working device may be expressed as (X)8,Y8) Wherein Y is8The ordinate of the center of mass representing the working device in the fully retracted state may be represented as f (Y)8). Assuming that the first preset number is 10, that is, 10 vectors are included in the initial population randomly generated by the electronic device 100, the 10 vectors may be respectively represented as M1、M2、M3、M4、M5、M6、M7、M8、M9、M10
Step S202, selecting the initial population according to the coordinate values of the mass center corresponding to the components, the weights of the components and the rotation center position of the excavator, so as to select a first target vector from the initial population.
In this embodiment, by performing a selection operation on the initial population, a first target vector can be selected from the initial population for direct placement into the next generation population.
Optionally, referring to fig. 3, the step S202 may include the following sub-steps:
and a substep S2021 of calculating probability values of each vector inherited to the next generation group according to the coordinate values of the mass centers corresponding to the components, the weights of the components and the rotation center position of the excavator respectively.
In the present embodiment, the position of the center of gyration can be set to include the abscissa X of the center of gyration0And the ordinate Y of the centre of rotation0The electronic device 100 may set 1/(a | P) according to the formula FX|+|PYmin|+|PYmax|) calculating the fitness of each vector, calculating the sum of the fitness of all vectors in the initial population according to the fitness of each vector, and calculating the fitness of all vectors in the initial population according to a formula FkSigma F calculates the probability of each vector being inherited to the next generation groupA value of the rate; wherein a is a preset balance coefficient, PX=∑9.8×Gi×(Xi-X0),PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],GiDenotes the weight of the part denoted by i, XiThe abscissa of the mass of the part denoted by i, X0Denotes the abscissa of the center of rotation, Y0Representing the ordinate of the centre of rotation, GmIndicating the weight of the working device in a plurality of parts, YmOrdinate of mass, f (Y), representing the working device in a fully retracted statem) Ordinate of mass, G, representing the working device in the fully extended statejDenotes the weight, Y, of a part denoted by j of the plurality of parts excluding the working devicejDenotes the centroid ordinate, F, of a part of the plurality of parts, denoted by the reference number j, with the exception of the working devicekThe fitness of the kth vector is obtained, and sigma F is the sum of the fitness of all vectors in the initial population.
Taking the multiple components as a radiator (reference numeral 1), a motor and a main pump (reference numeral 2), a hydraulic oil tank (reference numeral 3), a battery pack (reference numeral 4), a counterweight (reference numeral 5), a PDU (reference numeral 6), an AFE (reference numeral 7), and a working device (reference numeral 8), respectively, as an example, the formula PX=∑9.8×Gi×(Xi-X0) The value of i in (1) - (8) is shown in the formula PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0) And PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0]Wherein j is 1-7 and m is 8.
In the embodiment, considering that the deviation of the actual gravity center and the centre of gyration of each component in the left-right direction is generally small, and in order to prevent neglect in the calculation process, a balance coefficient a is introduced, and the balance optimization objective function of the excavator is defined as P ═ a | PX|+|PYmin|+|PYmaxI), then the followingF=1/(a|PX|+|PYmin|+|PYmax|) calculating the fitness F of each vector in the initial population as the fitnesskFinally, the fitness summation sigma F of all vectors is obtained, and then the corresponding fitness F of each vector is calculatedkAnd (E) obtaining probability values of the vector inherited to the next generation group, wherein the sum of the probabilities is 1. It should be noted that the value of the balance coefficient a may be set according to an actual situation, which is not limited in this embodiment. For example, a may take 15.
With 10 vectors (M) in the initial population1、M2、M3、M4、M5、M6、M7、M8、M9、M10) For example, after the calculation process of the sub-step S2021, the vector M can be obtained1The probability value of inheritance to the next generation group is F1V. F, vector M2The probability value of inheritance to the next generation group is F2V. F, vector M3The probability value of inheritance to the next generation group is F3V. F, vector M4The probability value of inheritance to the next generation group is F4V. F, vector M5The probability value of inheritance to the next generation group is F5V. F, vector M6The probability value of inheritance to the next generation group is F6V. F, vector M7The probability value of inheritance to the next generation group is F7V. F, vector M8The probability value of inheritance to the next generation group is F8V. F, vector M9The probability value of inheritance to the next generation group is F9V. F, vector M10The probability value of inheritance to the next generation group is F10/∑F。
Substep S2022 selects a first target vector from the initial population based on the probability value that each vector is inherited to the next generation population.
In this embodiment, after calculating the probability value of each vector being inherited to the next-generation group, the electronic device 100 may determine a probability interval corresponding to each vector according to the probability value of each vector being inherited to the next-generation group, randomly generate a random number between 0 and 1, determine the number of times each vector is selected according to the number of times the random number appears in each probability interval, and select a second preset number of vectors as the first target vector according to the number of times each vector is selected.
Wherein, the probability interval corresponding to each vector can be determined by calculating the cumulative probability of each vector. For example, assume vector M1、M2、M3、M4、M5、M6、M7、M8、M9、M10The probability values of inheritance to the next generation groups are 0.1, 0.15, 0.05, 0.3, 0.14, 0.1, 0.01, 0.04, 0.1 and 0.01 respectively, and then the vector M is1The cumulative probability of (2) is 0.1, and the corresponding probability interval is 0-0.1; vector M2The cumulative probability of (2) is 0.25, and the corresponding probability interval is 0.1-0.25; vector M3The cumulative probability of (2) is 0.3, and the corresponding probability interval is 0.25-0.3; vector M4The cumulative probability of (2) is 0.6, and the corresponding probability interval is 0.3-0.6; vector M5The cumulative probability of (2) is 0.74, and the corresponding probability interval is 0.6-0.74; vector M6The cumulative probability of (2) is 0.84, and the corresponding probability interval is 0.74-0.84; vector M7The cumulative probability of (2) is 0.85, and the corresponding probability interval is 0.84-0.85; vector M8The cumulative probability of (2) is 0.89, and the corresponding probability interval is 0.85-0.89; vector M9The cumulative probability of (2) is 0.99, and the corresponding probability interval is 0.89-0.99; vector M10The cumulative probability of (2) is 1, and the corresponding probability interval is 0.99-1. After the electronic device 100 generates the random number, it can be determined whether the vector is selected by determining which vector the random number is in the probability interval corresponding to, for example, if the random number is 0.57, the vector M is4If it is selected, the random number is 0.8, then the vector M6And (6) selecting. In this way, the electronic device 100 can determine the number of times each vector is selected by generating a plurality of random numbers, and according to the number of times selected, a second predetermined number (for example, 2) of vectors with the largest number of times are selected as the first target vector and directly put into the next generation group.
Step S203, performing cross calculation and mutation operation on the remaining vectors in the initial population except the first target vector to obtain a second target vector.
In this embodiment, a new vector can be obtained by performing cross calculation and mutation operation on the remaining vectors except the first target vector, so as to obtain a second target vector.
Optionally, referring to fig. 4, the step S203 may include the following sub-steps:
and a substep S2031 of randomly pairing the vectors except the first target vector in the initial population pairwise.
For example, assume vector M1And M2The two vectors with the most number of times of selection are selected, the vector M can be selected1And M2Determined as a first target vector M1 1And M1 2And directly put into the next generation group. At this point M remains in the initial population3、M4、M5、M6、M7、M8、M9、M10And 4 pairs of paired vectors can be obtained by randomly pairing the 8 vectors in pairs.
And a substep S2032 of performing cross calculation on the paired vectors to obtain a first intermediate vector.
Vector M paired with one of the pairs3And M4For example, assume M3=(X31,X32,……,X3i,Y31,Y32,……,Y3i,G3),M4=(X41,X42,……,X4i,Y41,Y42,……,Y4i,G4) Then the following cross-over calculation can be performed: x'31=λX31+(1-λ)X41,X'3i=λX3i+(1-λ)X4i,Y'31=λY31+(1-λ)Y41,Y'3i=λY3i+(1-λ)Y4i,G'3=λG3+(1-λ)G4,X'41=λX41+(1-λ)X31,X'4i=λX4i+(1-λ)X3i,Y'41=λY41+(1-λ)Y31,Y'4i=λY4i+(1-λ)Y3i,G'4=λG4+(1-λ)G3Wherein λ can be a random value between 0 and 1, and then a corresponding first intermediate vector M 'can be obtained'3=(X'31,X'32,……,X'3i,Y'31,Y'32,……,Y'3i,G'3),M'4=(X'41,X'42,……,X'4i,Y'41,Y'42,……,Y'4i,G'4). Similarly, after the vectors after other pairs are subjected to cross calculation, the corresponding first intermediate vector M 'can also be obtained'5、M'6、M'7、M'8、M'9、M'10
And a substep S2033 of performing a variation operation on the first intermediate vector to randomly select a new centroid coordinate value and a new counterweight weight from the peripheries of the centroid coordinate values and the counterweight weights of the components in the first intermediate vector, respectively, and updating the centroid coordinate values and the counterweight weights of the components in the first intermediate vector into the new centroid coordinate values and the new counterweight weights to obtain a second intermediate vector.
In this embodiment, gaussian variation is performed on each first intermediate vector obtained after the cross calculation, a new centroid coordinate value and a new counterweight weight can be respectively selected at random from the peripheries of the centroid coordinate value and the counterweight weight of each component in the first intermediate vector based on gaussian distribution, and the new centroid coordinate value and the new counterweight weight replace the old centroid coordinate value and the old counterweight weight to obtain a corresponding second intermediate vector. With a first intermediate vector M'3=(X'31,X'32,……,X'3i,Y'31,Y'32,……,Y'3i,G'3) For example, after Gaussian mutation, X 'may be added'31、X'32、……、X'3i、Y'31、Y'32、……、Y'3i、G'3Randomly selects a new value to replace, thereby obtaining a corresponding second intermediate vector M "3=(X”31,X”32,……,X”3i,Y”31,Y”32,……,Y”3i,G”3)。
And a substep S2034 of determining the second intermediate vector as a second target vector when the coordinate values of the center of mass of each component in the second intermediate vector and the weight of the counterweight meet a second preset condition.
Optionally, after performing variation operation to obtain corresponding second intermediate vectors, the electronic device 100 needs to determine, for each second intermediate vector, whether the centroid coordinate values of each component are all within the corresponding centroid position adjustment range, and if the centroid coordinate values of each component are all within the corresponding centroid position adjustment range, determine 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmaxIf is less than the second preset value, when the coordinate values of the mass centers of all the components in the second middle vector are all in the corresponding mass center position adjusting range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmax|) is less than a second preset value, the second intermediate vector is determined as a second target vector. When the mass center coordinate values of all the components of the second intermediate vector do not satisfy the mass center coordinate values, the mass center coordinate values are all in the corresponding mass center position adjusting range or do not satisfy 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmaxIf | is less than the second preset value, the cross calculation needs to be performed again in the sub-step S2032 until the centroid coordinate values of the components in the second intermediate vectors are all within the corresponding centroid position adjustment range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmax|) is less than a second preset value. Wherein, PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],Y0Representing the ordinate of the centre of rotation, GmIndicating the weight of the working device in a plurality of parts, YmOrdinate of mass, f (Y), representing the working device in a fully retracted statem) Ordinate of mass, G, representing the working device in the fully extended statejDenotes the weight, Y, of a part denoted by j of the plurality of parts excluding the working devicejIndicating division of a plurality of partsThe centroid of the part labeled j outside the device is ordinate.
For example, when the second intermediate vector M "3=(X”31,X”32,……,X”3i,Y”31,Y”32,……,Y”3i,G”3) Satisfy that the mass center coordinate value of each part is all in the corresponding mass center position adjusting range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmax|) is less than a second preset value, the second intermediate vector M "3Determined as a second target vector M1 3(ii) a In the same way, the second intermediate vector M "4、M”5、M”6、M”7、M”8、M”9、M”10Satisfy that the mass center coordinate value of each part is all in the corresponding mass center position adjusting range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmax|) is less than a second preset value, the second intermediate vector M "4、M”5、M”6、M”7、M”8、M”9、M”10Determined as a second target vector M1 4、M1 5、M1 6、M1 7、M1 8、M1 9、M110
And step S204, obtaining a new generation group according to the first target vector and the second target vector, and circularly performing selection operation, cross calculation and variation operation on the obtained new generation group until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are smaller than a first preset value.
In this embodiment, the first target vector M is obtained1 1And M1 2And a second target vector M1 3、M1 4、M1 5、M1 6、M1 7、M1 8、M1 9、M110Then, M1 1、M1 2、M1 3、M1 4、M1 5、M1 6、M1 7、M1 8、M1 9、M110And (3) forming a new generation group, taking the new generation group as a new initial group, returning to the steps S202-S203 to perform selection operation, cross calculation and mutation operation in a circulating way, and obtaining a new generation group after calculation in each circulating way. For each new generation population, 1/(a | P) according to the formula FX|+|PYmin|+|PYmax|) can obtain the fitness of each vector, and then can obtain the fitness mean value corresponding to the new generation group and the fitness maximum value corresponding to the new generation group, and based on the fitness mean value and the fitness maximum value corresponding to each new generation group, the fitness mean value error and the fitness maximum value error can be calculated, and then whether the requirements are both smaller than the first preset value is judged.
In an example, after a preset number of times (e.g., 5 times) of loop calculation may be set, it is determined whether or not the fitness mean error and the fitness maximum error of the obtained multiple new-generation groups within 5 generations are both within 1% (that is, less than a first preset value), and if not, the steps S202 to S203 need to be returned to perform the selection operation, the cross calculation, and the mutation operation again; if yes, stopping calculation.
Step S205 selects an optimal vector from the last generation group of the plurality of new generation groups, and obtains an optimal coordinate distribution value and an optimal weight distribution value of the counterweight corresponding to each of the plurality of components according to the optimal vector.
Alternatively, the step S205 may include: and calculating the probability value of each vector inherited from the last generation group to the next generation group, and determining the vector with the maximum probability value as the optimal vector.
In this embodiment, after determining that the fitness mean error and the fitness maximum error of the plurality of new-generation groups are both smaller than the first preset value, the electronic device 100 passes through the formula FkCalculating the probability value of each vector in the last generation group being inherited to the next generation group, determining the vector with the maximum probability value, and further determining the probability value of each vectorAnd obtaining an optimal vector in the last generation group, converting the optimal vector into a centroid coordinate value and a counterweight weight of each part, and finally outputting an excavator balance optimization result (namely, an optimal coordinate distribution value and an optimal counterweight distribution value corresponding to each of the parts).
For example, assume that the optimal vector in the last generation population is M6 2=(X1p,X2p,……,Xip,Y1p,Y2p,……,Yip,Gp) Then, the optimal coordinate distribution value corresponding to each component can be obtained as (X)1p,Y1p)、(X2p,Y2p)、……、(Xip,Yip) The optimum weight distribution value of the counterweight is Gp
In order to execute the corresponding steps in the above embodiments and various possible manners, an implementation manner of the balancing layout device of the excavator is given below. Referring to fig. 5, a functional block diagram of a balance layout apparatus 500 of an excavator according to an embodiment of the present invention is shown. It should be noted that the basic principle and the generated technical effects of the balance layout device 500 of the excavator provided in the present embodiment are the same as those of the above embodiments, and for the sake of brief description, no part of the present embodiment is mentioned, and reference may be made to the corresponding contents in the above embodiments. The balance layout device 500 of the excavator comprises an initial group generation module 510, a calculation module 520 and an acquisition module 530.
Alternatively, the modules may be stored in the memory 110 shown in fig. 1 in the form of software or Firmware (Firmware) or be fixed in an Operating System (OS) of the electronic device 100, and may be executed by the processor 120 in fig. 1. Meanwhile, data, codes of programs, and the like required to execute the above-described modules may be stored in the memory 110.
The initial population generating module 510 is configured to randomly generate an initial population, where the initial population includes a first preset number of vectors, each vector includes a centroid coordinate value and a counterweight weight corresponding to each of the plurality of components; the mass center coordinate value of each part is in the corresponding mass center position adjusting range.
It is understood that the initial population generating module 510 may perform the step S201.
The calculating module 520 is configured to perform a selecting operation on an initial population according to the coordinate values of the center of mass corresponding to each of the plurality of components, the weight of each of the plurality of components, and the position of the center of rotation of the excavator, so as to select a first target vector from the initial population; and performing cross calculation and mutation operation on the other vectors except the first target vector in the initial population to obtain a second target vector.
Optionally, the calculating module 520 is configured to calculate a probability value of each vector being inherited to the next generation group according to the centroid coordinate values corresponding to the components, the weights of the components, and the rotation center position of the excavator, and select the first target vector from the initial group according to the probability value of each vector being inherited to the next generation group.
Optionally, the calculating module 520 is specifically configured to determine a probability interval corresponding to each vector according to a probability value that each vector is inherited to a next generation group, randomly generate a random number between 0 and 1, determine the number of times each vector is selected according to the number of times that the random number appears in each probability interval, and select a second preset number of vectors as the first target vector according to the number of times each vector is selected.
Optionally, each component has a corresponding label, the coordinates of the center of mass include a center of mass abscissa and a center of mass ordinate, the position of the centre of revolution includes a center of revolution abscissa and a center of revolution ordinate, the calculation module 520 being particularly configured to calculate the value of 1/(a | P) according to the formula FX|+|PYmin|+|PYmaxI) calculating the fitness of each vector, and calculating the sum of the fitness of all vectors in the initial population according to the fitness of each vector; wherein a is a preset balance coefficient, PX=∑9.8×Gi×(Xi-X0),PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],GiDenotes the weight of the part denoted by i, XiIs indicated by a reference numerali center of mass abscissa, X of the component0Denotes the abscissa of the center of rotation, Y0Representing the ordinate of the centre of rotation, GmIndicating the weight of the working device in a plurality of parts, YmOrdinate of mass, f (Y), representing the working device in a fully retracted statem) Ordinate of mass, G, representing the working device in the fully extended statejDenotes the weight, Y, of a part denoted by j of the plurality of parts excluding the working devicejA centroid ordinate representing a part of the plurality of parts, denoted by reference numeral j, other than the working device; and according to formula FkCalculating the probability value of each vector inherited to the next generation group; wherein FkThe fitness of the kth vector is obtained, and sigma F is the sum of the fitness of all vectors in the initial population.
Optionally, the calculating module 520 is configured to pair the other vectors in the initial population except for the first target vector at random two by two, cross-calculate the paired vectors to obtain a first intermediate vector, perform a variation operation on the first intermediate vector to randomly select a new centroid coordinate value and a new counterweight weight from the peripheries of the centroid coordinate value and the counterweight weight of each component in the first intermediate vector, update the centroid coordinate value and the counterweight weight of each component in the first intermediate vector to the new centroid coordinate value and the new counterweight weight to obtain a second intermediate vector, and determine the second intermediate vector as the second target vector when the centroid coordinate value and the counterweight weight of each component in the second intermediate vector meet a second preset condition.
Optionally, the calculating module 520 is specifically configured to, when the coordinate values of the centroid of each component in the second intermediate vector are all within the corresponding adjustment range of the centroid position, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmax|) when less than the second preset value, determining the second intermediate vector as a second target vector; wherein, PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],Y0In the representation revolutionOrdinate of the heart, GmIndicating the weight of the working device in a plurality of parts, YmOrdinate of mass, f (Y), representing the working device in a fully retracted statem) Ordinate of mass, G, representing the working device in the fully extended statejDenotes the weight, Y, of a part denoted by j of the plurality of parts excluding the working devicejThe ordinate of the mass center of the part denoted by the reference j of the plurality of parts, excluding the working device, is indicated.
The calculating module 520 is further configured to obtain a new generation group according to the first target vector and the second target vector, and perform selection operation, cross calculation, and mutation operation on the obtained new generation group in a circulating manner until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are both smaller than a first preset value.
Optionally, the calculating module 520 is specifically configured to calculate a probability value of each vector in the last-generation group being inherited to the next-generation group, and determine the vector with the largest probability value as the optimal vector.
It is understood that the calculating module 520 can execute the steps S202, S021 to S2022, S203, S2031 to S2034, and S204.
The obtaining module 530 is configured to select an optimal vector from a last generation group of the plurality of new generation groups, and obtain an optimal coordinate distribution value and an optimal weight distribution value of the counterweight corresponding to each of the plurality of components according to the optimal vector.
It is understood that the obtaining module 530 can execute the step S205.
To sum up, the balance layout method, the balance layout device, the electronic device, and the storage medium for the excavator according to the embodiments of the present invention randomly generate an initial population, where the initial population includes a first preset number of vectors, each vector includes a centroid coordinate value and a counterweight weight corresponding to each of a plurality of components, the centroid coordinate value of each component is within a corresponding centroid position adjustment range, select the initial population according to the centroid coordinate value corresponding to each of the plurality of components, the weight of each of the plurality of components, and a rotation center position of the excavator, to select a first target vector from the initial population, perform cross calculation and mutation operation on the remaining vectors except the first target vector in the initial population to obtain a second target vector, obtain a new generation population according to the first target vector and the second target vector, and perform the above-mentioned selection operation on the obtained new generation population cyclically, And performing cross calculation and variation operation until the obtained fitness mean error and the fitness maximum error of the plurality of new generation groups are smaller than a first preset value, selecting an optimal vector from the last generation group of the plurality of new generation groups, and obtaining optimal coordinate distribution values and optimal weight distribution values of the balance weights corresponding to the plurality of parts according to the optimal vector. Therefore, the optimal coordinate distribution value of each component of the excavator and the optimal weight distribution value of the balance weight can be obtained only by determining the mass center position adjusting range, the weight and the rotation center position of each component of the excavator, so that the optimal balance layout design of the excavator is realized; meanwhile, the whole balance calculation process does not need human participation, so that the balance calculation efficiency of the excavator is improved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The balance layout method of the excavator is characterized by being applied to electronic equipment, wherein the electronic equipment stores mass center position adjusting ranges corresponding to a plurality of parts of the excavator, weights of the parts except a balance weight in the parts and a rotation center position of the excavator in advance; the method comprises the following steps:
randomly generating an initial population, the initial population comprising a first preset number of vectors, each vector comprising a centroid coordinate value and a counterweight weight corresponding to each of the plurality of components; the coordinate value of the center of mass of each part is in the corresponding adjustment range of the position of the center of mass;
selecting the initial population according to the coordinate values of the center of mass corresponding to each of the plurality of components, the weight of each of the plurality of components and the position of the gyration center of the excavator so as to select a first target vector from the initial population;
performing cross calculation and mutation operation on the other vectors except the first target vector in the initial population to obtain a second target vector;
obtaining a new generation group according to the first target vector and the second target vector, and circularly performing selection operation, cross calculation and variation operation on the obtained new generation group until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are smaller than a first preset value;
and selecting an optimal vector from the last generation group of the plurality of new generation groups, and obtaining the optimal coordinate distribution value corresponding to each of the plurality of components and the optimal weight distribution value of the balance weight according to the optimal vector.
2. The method of claim 1, wherein said selecting the initial population based on the centroid coordinate values of each of the plurality of components, the weight of each of the plurality of components, and the center of gyration position of the excavator to select a first target vector from the initial population comprises:
respectively calculating the probability value of each vector inherited to the next generation group according to the mass center coordinate values corresponding to the components, the weights of the components and the rotation center position of the excavator;
selecting a first target vector from the initial population according to the probability value of each vector inherited to the next generation population.
3. The method of claim 2, wherein selecting a first target vector from the initial population based on the probability value that each vector is inherited to the next generation population comprises:
determining a probability interval corresponding to each vector according to the probability value of each vector inherited to the next generation group;
randomly generating a random number between 0 and 1, and determining the number of times each vector is selected according to the number of times the random number appears in each probability interval;
and selecting a second preset number of vectors as the first target vector according to the number of times of selecting each vector.
4. The method of claim 2, wherein each component has a corresponding label, the centroid coordinate values comprise a centroid abscissa and a centroid ordinate, the swing center position comprises a swing center abscissa and a swing center ordinate, and the calculating the probability value of each vector inheritance to the next generation population based on the respective centroid coordinate values of the plurality of components, the respective weights of the plurality of components, and the swing center position of the excavator comprises:
according to the formula F ═ 1/(aP)X|+|PYmin|+|PYmaxI) calculating the fitness of each vector, and calculating the sum of the fitness of all vectors in the initial population according to the fitness of each vector; wherein a is a preset balance coefficient, PX=∑9.8×Gi×(Xi-X0),PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],GiDenotes the weight of the part denoted by i, XiThe abscissa of the mass of the part denoted by i, X0Representing the abscissa, Y, of the centre of rotation0Representing the ordinate, G, of the centre of revolutionmRepresenting the weight, Y, of the working device in said plurality of partsmA centroid ordinate, f (Y), representing the fully retracted state of the working devicem) Ordinate of mass, G, representing the working device in a fully extended statejDenotes the weight of a part denoted by j, Y, of the plurality of parts excluding the working devicejA centroid ordinate representing a part of the plurality of parts, denoted by reference numeral j, other than the working device;
according to formula FkCalculating the probability value of each vector inherited to the next generation group; wherein FkAnd F is the fitness of the kth vector, and is the sum of the fitness of all vectors in the initial population.
5. The method of claim 1, wherein the performing cross-computing and mutation operations on remaining vectors of the initial population except for the first target vector to obtain a second target vector comprises:
carrying out pairwise random pairing on the other vectors except the first target vector in the initial population;
performing cross calculation on the paired vectors to obtain a first intermediate vector;
performing variation operation on the first intermediate vector to randomly select a new centroid coordinate value and a new counterweight weight from the peripheries of the centroid coordinate value and the counterweight weight of each component in the first intermediate vector respectively, and updating the centroid coordinate value and the counterweight weight of each component in the first intermediate vector into the new centroid coordinate value and the new counterweight weight to obtain a second intermediate vector;
and when the mass center coordinate value and the counterweight weight of each component in the second intermediate vector meet a second preset condition, determining the second intermediate vector as a second target vector.
6. The method according to claim 5, wherein the determining the second intermediate vector as a second target vector when the centroid coordinate value and the counterweight weight of each component in the second intermediate vector meet a second preset condition comprises:
when the coordinate values of the mass centers of all the components in the second intermediate vector are all in the corresponding mass center position adjusting range, and 2(| P)Ymin|-|PYmax|)/(|PYmin|+|PYmaxI) when the second intermediate vector is smaller than a second preset value, determining the second intermediate vector as a second target vector; wherein, PYmin=∑9.8×Gj×(Yj-Y0)+9.8×Gm×(Ym-Y0),PYmax=∑9.8×Gj×(Yj-Y0)+9.8×Gm×[f(Ym)-Y0],Y0Representing the ordinate of the centre of rotation, GmRepresenting the weight, Y, of the working device in said plurality of partsmA centroid ordinate, f (Y), representing the fully retracted state of the working devicem) Ordinate of mass, G, representing the working device in a fully extended statejDenotes the weight of a part denoted by j, Y, of the plurality of parts excluding the working devicejRepresents the ordinate of the mass center of the part, denoted by the reference j, of the plurality of parts, excluding the working device.
7. The method of claim 1, wherein selecting the optimal vector from the last generation population of the plurality of new generation populations comprises:
calculating the probability value of each vector inherited from the last generation group to the next generation group;
and determining the vector with the maximum probability value as the optimal vector.
8. The balance layout device of the excavator is characterized by being applied to electronic equipment, wherein the electronic equipment stores mass center position adjusting ranges corresponding to a plurality of parts of the excavator, weights of the parts except a balance weight in the parts and a rotation center position of the excavator in advance; the device comprises:
an initial population generating module for randomly generating an initial population, wherein the initial population comprises a first preset number of vectors, and each vector comprises a centroid coordinate value and a counterweight weight corresponding to each of the plurality of components; the coordinate value of the center of mass of each part is in the corresponding adjustment range of the position of the center of mass;
the calculation module is used for selecting the initial population according to the mass center coordinate values corresponding to the components, the weights of the components and the rotation center position of the excavator so as to select a first target vector from the initial population; performing cross calculation and mutation operation on the other vectors except the first target vector in the initial population to obtain a second target vector;
the calculation module is further used for obtaining a new generation group according to the first target vector and the second target vector, and performing selection operation, cross calculation and variation operation on the obtained new generation group in a circulating manner until the fitness mean error and the fitness maximum error of the obtained multiple new generation groups are smaller than a first preset value;
and the acquisition module is used for selecting an optimal vector from the last generation group of the plurality of new generation groups and obtaining the optimal coordinate distribution value corresponding to each of the plurality of components and the optimal weight distribution value of the counterweight according to the optimal vector.
9. An electronic device, comprising a processor and a memory, the memory storing a computer program executable by the processor, the computer program, when executed by the processor, implementing the method according to any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103046606A (en) * 2012-12-21 2013-04-17 中联重科股份有限公司 Engineering mechanical equipment, movable counterweight system and control method
CN103226740A (en) * 2013-04-27 2013-07-31 中南大学 Load distribution optimization method of double-crane collaborative operation
US20150376869A1 (en) * 2014-06-25 2015-12-31 Topcon Positioning Systems, Inc. Method and Apparatus for Machine Synchronization
US20160169413A1 (en) * 2014-12-16 2016-06-16 Caterpillar Inc. Counterweight System and Method
CN109165778A (en) * 2018-08-10 2019-01-08 南通大学 Beam type stereo storage location distribution method applied to long material storage
US20190196854A1 (en) * 2017-12-21 2019-06-27 Caterpillar Inc. System and method for using virtual machine operator model
CN110795836A (en) * 2019-10-17 2020-02-14 浙江大学 Mechanical arm robust optimization design method based on mixed uncertainty of interval and bounded probability
CN110851962A (en) * 2019-10-23 2020-02-28 上海船舶工艺研究所(中国船舶工业集团公司第十一研究所) Digital workshop layout optimization method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103046606A (en) * 2012-12-21 2013-04-17 中联重科股份有限公司 Engineering mechanical equipment, movable counterweight system and control method
CN103226740A (en) * 2013-04-27 2013-07-31 中南大学 Load distribution optimization method of double-crane collaborative operation
US20150376869A1 (en) * 2014-06-25 2015-12-31 Topcon Positioning Systems, Inc. Method and Apparatus for Machine Synchronization
US20160169413A1 (en) * 2014-12-16 2016-06-16 Caterpillar Inc. Counterweight System and Method
US20190196854A1 (en) * 2017-12-21 2019-06-27 Caterpillar Inc. System and method for using virtual machine operator model
CN109165778A (en) * 2018-08-10 2019-01-08 南通大学 Beam type stereo storage location distribution method applied to long material storage
CN110795836A (en) * 2019-10-17 2020-02-14 浙江大学 Mechanical arm robust optimization design method based on mixed uncertainty of interval and bounded probability
CN110851962A (en) * 2019-10-23 2020-02-28 上海船舶工艺研究所(中国船舶工业集团公司第十一研究所) Digital workshop layout optimization method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
GONGYUE XU等: "Optimal Design of Hydraulic Excavator Shovel Attachment Based on Multiobjective Evolutionary Algorithm", 《PUBLISHED IN: IEEE/ASME TRANSACTIONS ON MECHATRONICS 》 *
万宇阳等: "基于响应面法的挖掘机三油缸结构动臂轻量化设计", 《现代制造工程》 *

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