阅读说明：本技术 一种基于可达域的激光增材制造装备人机界面布局优化方法 (Reachable domain-based man-machine interface layout optimization method for laser additive manufacturing equipment ) 是由 刘丹 王旭 杨国哲 赵文鹏 侯志权 赵琛 刘新昊 刘伟军 姜兴宇 于 2021-08-31 设计创作，主要内容包括：本发明提出一种基于可达域的激光增材制造装备人机界面布局优化方法,属于制造装备界面工效学设计领域。本发明依据双手垂直可达域舒适性区域划分人机交互界面可达域等级。在此基础上,综合考虑界面操作功能模块的重要性、关联性与安全操作要求,构建基于可达域的人机界面布局优化模型。本发明还提出一种基于狼群-粒子群混合智能算法的激光增材制造装备界面布局求解方法,解决传统粒子群算法求解多维域模型易陷入局部最优的问题。本发明的有益效果为：很好的满足了操作者对激光增材制造装备界面交互的高舒适性和高安全性的操作需要,为激光增材制造装备的人机界面优化设计提供非常理想的设计依据。(The invention provides a reachable domain-based optimization method for a human-computer interface layout of laser additive manufacturing equipment, and belongs to the field of ergonomic design of interfaces of manufacturing equipment. The reachable domain grade of the human-computer interaction interface is divided according to the comfortable region of the vertical reachable domain of the hands. On the basis, importance, relevance and safety operation requirements of the interface operation function module are comprehensively considered, and a human-computer interface layout optimization model based on the reachable domain is constructed. The invention further provides a wolf pack-particle swarm hybrid intelligent algorithm-based laser additive manufacturing equipment interface layout solving method, and the problem that the traditional particle swarm algorithm for solving the multidimensional domain model is prone to falling into local optimization is solved. The invention has the beneficial effects that: the operating requirements of operators on high comfort and high safety of interface interaction of the laser additive manufacturing equipment are well met, and ideal design basis is provided for the human-computer interface optimization design of the laser additive manufacturing equipment.)

1. A reachable domain-based laser additive manufacturing equipment human-machine interface layout optimization method is characterized by comprising the following steps:

s1, modularization of a human-computer interaction interface and division of reachable domains,

s2, determining the use relationship, the operation relationship and the coordination relationship of each functional module of the human-computer interaction interface,

and S3, constructing a human-computer interface layout model of the laser additive manufacturing equipment.

2. The reach-based laser additive manufacturing equipment human-machine interface layout optimization method of claim 1, wherein the human-machine interface layout design principle is as follows:

(1) the cognitive requirements of operators are met, the experience and the cognitive characteristics of personnel are unified, the quick identification and quick response of important key information are ensured, the cognitive rules of the personnel and the importance, the use frequency and the relevance of the display control function module are fully considered, and the interface layout space is reasonably arranged;

(2) the comfort of the operation task is met, and the display and control function modules are arranged in a comfortable operation area of a person in a centralized and orderly manner according to the use frequency, the operation sequence and the operation relevance so as to accelerate the processing of operation information and realize the effective improvement of the human-computer interaction efficiency and the operation comfort;

(3) the safety requirement is met, the influence of safety factors in the cognitive process, the operation process and the interface design of an operator is fully considered, and the safety factor is used as a key layout influence factor to be integrated into the optimization of the human-computer interface layout.

3. The reachable domain-based laser additive manufacturing equipment human-machine interface layout optimization method of claim 1, wherein the modularization of the human-machine interaction interface and the division of the reachable domain in step S1 are specifically performed by:

(1) the interface modularization divides the functional area into a plurality of rectangular regular modules according to the use function of the human-computer interaction interface and the shape and size, and simultaneously does not consider the complex shape of the functional area and the layout condition in the area;

(2) drawing a CAD graph of an operator reachable area by using a reachable area analysis module of Jack simulation software and combining with a vertical reachable area range of a human coronal plane, setting that the right side is higher than the left side by taking the midline of the human coronal plane as a boundary in consideration of the fact that the operator generally operates with the right hand in normal operation, and dividing a reachable area containing 6 levels;

(3) the comfort and stability of each module used by an operator are related to the grade of the reachable region where each functional module is located and the area of each reachable region, and in order to simplify the calculation process of the module area, unit rasterization processing is carried out by taking the center line of the reachable region as a reference; the reachable area of each functional module is divided by taking 10mm as a basic unit.

4. The reachable domain based layout optimization method for the human-machine interface of the laser additive manufacturing equipment according to claim 1, wherein the step S2 is to determine the usage relationship, the operation relationship, and the matching relationship of each functional module of the human-machine interface, and the specific determination method is to:

(1) determination using relational parameters

The use relation refers to the use condition of each functional module in the human-computer interface operation interaction process of the laser additive manufacturing equipment, the use relation is formed by the importance degree and the use frequency of the functional modules of the interface, the modules with stronger use relation are reasonably arranged in the reachable area of rapid, comfortable and safe operation of the operator as much as possible,

the importance degree and the use frequency of the interface function module are determined by expert scoring, corresponding importance scores and use degree scores are determined, then a gray entropy weight method is adopted to be converted into importance indexes and use frequency indexes to represent the importance and use frequency conditions of a certain interface function module, an importance scoring matrix of the interface function module is set as I, and a number of experts score I modules (I is 17), then:

considering that the experience of each expert is different, the self-evaluation weight of each expert is set as alpha

α＝[α₁ α₂ ... α_a]^T (2)

The importance score ω of the interface function is then

ω＝Iα (3)

In the importance scoring process of the interface function module, considering the influence of safety operation, the importance scoring of the interface function module is based on the following indexes: the importance level in the subsystem, the importance level in the whole system, the error-proof design level, the safe color and display design level, the safe coding condition,

if the use frequency scoring matrix of the interface function module is K, b working states are set in total in consideration of the working conditions of different states of the laser additive manufacturing equipment in the operation process, and the use frequency matrix K can be expressed as:

let the probability of each condition occurring be beta

β＝[β₁ β₂ ... β_b]^T (5)

The interface function module uses the frequency score θ of

θ＝Kβ (6)

Combining the importance degree and the use frequency to form a use relation parameter of the human-computer interface equipment component, and if the use relation parameter is C, then

C＝Aω+Bθ (7)

Wherein: a and B are weight coefficients between the importance parameter and the usage relation parameter, and a + B is 1.

(2) Determination of operational relationship parameters

The operation relation refers to the operation sequence relation of each functional module executing tasks under each working condition in the operation interaction process of an operator and a human-computer interface of the laser additive manufacturing equipment, and an operation sequence matrix is set to be F

In order to consider the influence of the safety of the equipment in the operation process, a parameter, namely a safety operation coefficient, is introduced, and represents the safety degree of the module in the operation process, and if the coefficient is e, the operation relation parameter is as follows:

wherein: f_ipRepresents the operation sequence of the functional module i in the working condition p.

(3) Fitting relation parameter

The cooperation relationship mainly refers to the degree of closeness of the two functional modules in the operation function; namely, in the operation interaction process of the man-machine interface of the laser additive manufacturing equipment, in order to realize a certain task, whether the functional modules of the certain two interfaces have task correlation or not, the matching relation matrix is set as O

Wherein, O_idShowing the matching relationship between the ith functional module and the d-th functional module, and [ AEIOU ] when building the matching relationship]Expressing the strong and weak relationship of cooperation, the cooperation relationship between a certain device and other devices can be expressed as

Wherein l_idThe distance between the equipment i and the equipment d is represented, the closer the distance is, the stronger the matching relation is, the distance l is considered in the processing mode of rasterization of the interface unit_idExpressed as the number of units spaced between the two interface modules.

5. The reachable domain-based human-machine interface layout optimization method for laser additive manufacturing equipment according to claim 1, wherein step S3 is to construct a human-machine interface layout model of the laser additive manufacturing equipment by:

(1) problem description: according to the principle of optimization of the human-computer interface layout of the laser additive manufacturing equipment, the human-computer interface layout of the laser additive manufacturing equipment needs to meet a certain ergonomic principle, the display and control device with higher importance and frequency characteristics is arranged in the range with comfortable and convenient operation, and the logicality of operation and association among the devices is noticed; the quick cognition, the quick operation and the safe and comfortable operation in the interaction process are ensured, and the goal of optimizing the model is to ensure that the total important degree of each functional module is expected to occupy the maximum reachable domain grade;

(2) the condition is assumed as follows: the following assumptions are made herein for equipment human interface layout optimization: the sizes, the number and the internal composition forms of all the display and control devices provided with the human-computer interaction interface are unchanged, no overlapping area exists among the display and control devices, and the layout range does not exceed the total range of the interface;

(3) variable definition: the main variables of the equipment interface layout optimization model are

W-total degree of weight, wherein W_i＝C_i+O_i+f_i

X-intensity classes of different achievable ranges, X_ijFor the intensity level of the ith device in the jth reachable domain,

q-number of units occupied by different levels of reachable domains, Q_ijThe number of units occupied by the ith module in the jth reachable domain,

z-human-computer interface layout optimization comprehensive strength;

(4) model and constraint conditions: the laser additive manufacturing equipment human-computer interaction interface layout optimization model can be expressed as

The constraint conditions are as follows:

wherein, formula (14) represents that the number of units occupied by the ith functional module in the reachable domains of different levels is equal to the total number of the units, and formula (15) represents that the number of units occupied by all the unit functional modules in the reachable domains is equal to the sum of the areas of all the modules.

6. A laser additive manufacturing equipment interface layout solving method based on a wolf colony-particle swarm hybrid intelligent algorithm used in the reachable domain-based laser additive manufacturing equipment human-computer interface layout optimization method is characterized by comprising the following steps of:

step 1: setting parameters, namely randomly initializing parameters such as the quantity of wolf colony groups, the attack running step length and the like;

step 2: calculating the fitness value of the single wolf, finding out the global historical optimal position, and determining the wolf;

step 3: according to the formula

x_ij(t+1)＝x_ij(t)+rand×step×[x_Lj(t)-x_ij(t)] (15)

Carrying out running behavior, and replacing the wolf if a better fitness value is found in the way;

step 4: according to the formula

Determining a critical value, and entering the critical value according to a formula

x_ij(t+1)＝x_ij(t)+rand×step_b (17)

Turning to attack enclosing behavior;

step 5: recording the current optimal position and the global optimal position of the particles according to a particle swarm algorithm formula;

step 6: calculating the fitness value of a single particle, and updating the individual historical optimal position and the global historical optimal position;

step 7: eliminating q particles with the worst individual historical optimal position fitness value, and generating q particles again at random;

step 8: judging whether a termination condition is met (the maximum iteration number is reached), otherwise, jumping to Step 3; if yes, outputting the global optimal position is ended.

7. The method for solving the interface layout of the laser additive manufacturing equipment based on the wolf pack-particle swarm hybrid intelligent algorithm according to claim 6, wherein each formula in the solving step is derived from a basic wolf pack algorithm, and the specific operation principle is as follows:

in the process of searching, running and attacking a wolf pack, if other wolfs find a better solution than the solution of the wolf pack, the wolf pack replaces the position of the wolf pack to reinitiate the running attack activity, after one iteration is finished, the wolf pack can update the wolf pack through a knockout mechanism, so that the wolf pack always keeps stronger optimizing capability, the group running mechanism is shown as a formula (15), wherein rand is a random number between 0 and 1, step represents the running step length of the wolf pack, and x is x_Lj(t) represents the position of the wolf of the head at the t-th iteration,

in the running behavior, if the fitness value of the objective function of the position of the trailing wolf is better than the fitness value of the objective function of the current position, the position of the trailing wolf is updated to be the position of the trailing wolf, otherwise, the position of the trailing wolf is the position before the trailing wolf, the wolf cluster is switched from the running state to the precision searching trailing state by taking a set critical value as a boundary, and the critical value is set as S_nThe calculation formula is shown in formula (16) wherein,andrepresenting the upper limit and the lower limit of the feasible solution jth dimension in the solution space, D is the dimension of the solution space, eta is a distance judgment factor,

the attack behavior of attack wolf is a local precise search, and the attack behavior formula is shown as formula (17), wherein rand is a random number from-1 to 1, and step_bRepresenting the attack step length, wherein the attack step length is the same as the running behavior, and when the fitness value of the target function of the position after the attack of the attack wolf is superior to the fitness value of the target function of the current position, the position of the attack wolf is updated to the position after the attack, otherwise, the position of the attack wolf is the position before the attack; if the position searched by the attack-enclosing wolf is better than the position of the head wolf, the head wolf becomes a new head wolf.

Technical Field

The invention relates to a reachable domain-based optimization method for a human-computer interface layout of laser additive manufacturing equipment, and belongs to the field of ergonomic design of interfaces of manufacturing equipment.

Background

The laser additive manufacturing technology is a key technology for competitive development of all countries in the world at present, and is mainly a direct deposition forming process based on high-energy laser beam rapid cladding metal powder. In the laser additive manufacturing process, an operator needs to perform man-machine interaction operation with a plurality of subsystems such as a laser generation system, a powder feeding system, a water cooling system, a numerical control system and a monitoring system to complete the forming and processing of a workpiece. Therefore, the man-machine interaction process of the laser additive manufacturing device has the characteristics of multi-dimensional information, multi-flow, multi-function, multi-object and the like, so that the man-machine interaction efficiency is low, the comfort and safety are poor in the operation process, and the stability of the forming quality of the laser additive manufactured part is restricted. Therefore, development of optimization design research on the layout of the human-computer interaction interface of the additive manufacturing equipment is a key for effectively improving the comfort and safety of human-computer interaction operation and the human-computer interaction efficiency in the laser additive manufacturing process.

Due to the characteristics of high integration, complexity and the like of the laser additive manufacturing equipment, the information capacity of a human-computer interface is large, the structural relationship is complicated, human errors are easily caused, and the efficient operation and the personnel safety of a human-computer system are seriously influenced; therefore, the ergonomic optimization design is carried out on the layout of the human-computer interaction interface, and the problem of imbalance between the cognition of personnel and the information coding of the interface layout is particularly important to solve. At present, scholars at home and abroad mainly develop human-computer interface layout optimization research aiming at traditional manufacturing equipment around a human-computer interaction cognitive model and a human-computer interface optimization method, and obtain certain effect. Because laser vibration material disk equipment all has apparent difference with traditional manufacturing equipment in aspects such as system architecture, processing technology, control form, traditional man-machine interface layout optimization method is difficult to be suitable for the laser vibration material disk equipment that high travelling comfort and high security operation need, and the man-machine interface layout optimization research to laser vibration material disk equipment is also rarely reported. Therefore, the following problems mainly exist in the research of optimizing the layout of the human-computer interface of the laser additive manufacturing equipment to be solved:

(1) aiming at the problem of optimizing the layout of a human-computer interface of laser additive manufacturing equipment, the conventional method focuses on factors such as the importance of personnel cognition and interface modules in the operation process, can meet the basic requirement of operation cognition in the human-computer interaction process, but ignores the relevance of each module in the human-computer interface in the use process, so that the layout effect of the human-computer interface of the laser additive manufacturing equipment is difficult to achieve an ideal state.

(2) Aiming at the problem of severe requirements of high operation comfort and safety of laser additive manufacturing equipment, a traditional manufacturing equipment human-computer interface layout model is heavily used for carrying out layout optimization on human cognition and interface functions based on experience, is difficult to systematically consider comfort factors and safety factors of an equipment interface, is easily influenced by subjective factors, and causes low human-computer interaction efficiency.

(3) Aiming at the problem of solving the layout model of the laser additive manufacturing equipment with multiple decision variables, the traditional single algorithm is complex in parameter composition and setting when the layout model is solved, the search direction of the optimal solution is difficult to be accurately determined within the maximum iteration times, the solving quality is low, and the optimal layout scheme of the human-computer interface of the laser additive manufacturing equipment cannot be determined.

Disclosure of Invention

The invention aims to provide a reachable domain-based optimization method for the human-computer interface layout of laser additive manufacturing equipment, and provides an effective way for the human-computer interaction optimization design of the laser additive manufacturing equipment.

In order to achieve the above object, the present invention is realized by the following steps:

s1, modularization of a human-computer interaction interface and division of reachable domains,

s2, determining the use relationship, the operation relationship and the coordination relationship of each functional module of the human-computer interaction interface,

and S3, constructing a reachable domain-based man-machine interface layout model of the laser additive manufacturing equipment.

Further, according to the method for optimizing the human-computer interface layout of the laser additive manufacturing equipment based on the reachable domain, the design principle of the human-computer interface layout is as follows:

(1) the cognitive requirements of operators are met, the experience of personnel and the cognitive characteristics are unified, and the quick identification and quick response of important key information are guaranteed. The cognitive rules of the personnel and the importance, the use frequency and the relevance of the display control function module are fully considered, and the interface layout space is reasonably arranged;

(2) the comfort of the operation task is met, and the display and control function modules are arranged in a comfortable operation area of a person in a centralized and orderly manner according to the use frequency, the operation sequence and the operation relevance so as to accelerate the processing of operation information and realize the effective improvement of the human-computer interaction efficiency and the operation comfort;

(3) the safety requirement is met, the influence of safety factors in the cognitive process, the operation process and the interface design of an operator is fully considered, and the safety factor is used as a key layout influence factor to be integrated into the optimization of the human-computer interface layout.

Further, in the reachable domain-based laser additive manufacturing equipment human-machine interface layout optimization method, the modularization of the human-machine interaction interface and the division of the reachable domain in the step S1 are specifically performed by:

(1) the interface modularization divides the functional area into a plurality of rectangular rule modules according to the use function of the human-computer interaction interface and the shape and the size. And simultaneously, the complex shape of the functional area and the layout condition inside the area are not considered.

(2) And drawing a CAD graph of the reachable region of the operator by using a reachable region analysis module of Jack simulation software and combining the range of the vertical reachable region of the coronal plane of the human body. Considering that the operator generally operates with the right hand in normal operation, the right side is set to be higher than the left side by taking the midline of the coronal plane of the human body as a boundary, and an reachable domain containing 6 levels is divided.

(3) The comfort and stability of the operator using each module is related to the level of the accessible area in which each functional module is located and the area in each accessible area. In order to simplify the calculation process of the module area, unit rasterization processing is carried out by taking the center line of the reachable domain as a reference; the reachable area of each functional module is divided by taking 10mm as a basic unit.

Further, in the reachable domain-based laser additive manufacturing equipment human-machine interface layout optimization method, in step S2, a use relationship, an operation relationship, and a cooperation relationship of each functional module of a human-machine interface are determined. The specific determination method comprises the following steps:

(1) determination using relational parameters

The use relation refers to the use condition of each functional module in the human-computer interface operation interaction process of the laser additive manufacturing equipment. The use relationship is composed of the importance degree of the function module of the interface and the use frequency. For the module with stronger use relationship, the module should be reasonably arranged in the reachable area of the operator for quick, comfortable and safe operation.

The importance degree and the use frequency of the interface function module are determined by expert scoring, and then converted into importance indexes and use frequency indexes by adopting a gray entropy weight method to represent the importance and use frequency conditions of a certain interface function module. If the importance scoring matrix of the interface function module is I, and a experts score I modules (I is 17), then:

considering that the experience of each expert is different, the self-evaluation weight of each expert is set as alpha

α＝[α₁ α₂ ... α_a]^T (2)

The importance score ω of the interface function is then

ω＝Iα (3)

In the importance scoring process of the interface function module, considering the influence of safety operation, the importance scoring of the interface function module is based on the following indexes: the importance degree in the subsystem, the importance degree in the whole system, the error-proof design degree, the safe color and display design degree and the safe coding condition.

If the use frequency scoring matrix of the interface function module is K, b working states are set in total in consideration of the working conditions of different states of the laser additive manufacturing equipment in the operation process, and the use frequency matrix K can be expressed as:

let the probability of each condition occurring be beta

β＝[β₁ β₂ ... β_b]^T (5)

The interface function module uses the frequency score θ of

θ＝Kβ (6)

Combining the importance degree and the use frequency to form a use relation parameter of the human-computer interface equipment component, and if the use relation parameter is C, then

C＝Aω+Bθ (7)

Wherein: a and B are weight coefficients between the importance parameter and the usage relation parameter, and a + B is 1.

(2) Determination of operational relationship parameters

The operation relation refers to the operation sequence relation of each functional module when an operator performs a task under each working condition in the operation interaction process of the laser additive manufacturing equipment human-computer interface. Let the operation order matrix be F

In order to consider the influence of the safety of the equipment in the operation process, a parameter, namely a safety operation coefficient, is introduced, and represents the safety degree of the module in the operation process, and if the coefficient is e, the operation relation parameter is as follows:

wherein: f_ipRepresents the operation sequence of the functional module i in the working condition p.

(3) Fitting relation parameter

The cooperation relationship mainly refers to the degree of closeness of the two functional modules in the operation function; namely, in the operation interaction process of the man-machine interface of the laser additive manufacturing equipment, an operator aims to realize whether task correlation exists between certain two interface functional modules of a certain task. Setting the matching relation matrix as O

Wherein, O_idShowing the matching relationship between the ith functional module and the d-th functional module. When constructing the mating relationship with [ AE IO U]Expressing the strength relationship of the coordination. The cooperative relationship between a certain device and other devices can be expressed as

Wherein l_idThe distance between the device i and the device d is represented, and the closer the distance is, the stronger the matching relationship is. Distance l considering the way the interface elements are rasterized_idExpressed as the number of units spaced between the two interface modules.

Further, the laser additive manufacturing equipment comprehensive test analysis method based on user operation experience is characterized in that the step S3 is implemented to construct a human-computer interface layout model of the laser additive manufacturing equipment, and the specific method is as follows:

(1) problem description: according to the principle of optimization of the human-computer interface layout of the laser additive manufacturing equipment, the human-computer interface layout of the laser additive manufacturing equipment needs to meet a certain ergonomic principle, the display and control device with higher importance and frequency characteristics is arranged in the range with comfortable and convenient operation, and the logicality of operation and association among the devices is noticed; and the quick cognition, the quick operation and the safe and comfortable operation in the interaction process are ensured. The goal of optimizing the model should be to ensure that the total important degree of each functional module is expected to occupy the maximum reachable domain level.

(2) The condition is assumed as follows: the following assumptions are made herein for equipment human interface layout optimization: the sizes, the number and the internal composition forms of all the display and control devices provided with the human-computer interaction interface are unchanged. There is no overlapping area between the display and control devices, and the layout range must not exceed the total range of the interface.

(3) Variable definition: the main variables of the equipment interface layout optimization model are

W-total degree of weight, wherein W_i＝C_i+O_i+f_i

X-intensity classes of different achievable ranges, X_ijThe intensity level for the ith device in the jth reachable domain.

Q-number of units occupied by different levels of reachable domains, Q_ijThe number of units occupied by the ith module in the jth reachable domain.

Z-human-machine interface layout optimization comprehensive strength

S-total number of interface units

(4) Model and constraint conditions: the laser additive manufacturing equipment human-computer interaction interface layout optimization model can be expressed as

The constraint conditions are as follows:

wherein, the formula (14) represents that the number of units occupied by the ith functional module in the reachable domains of different levels is equal to the total number of the units. The formula (15) shows that the number of units occupied by all the unit function modules in each reachable domain is equal to the sum of the areas of all the modules.

The invention also provides a wolf pack-particle swarm hybrid intelligent algorithm-based laser additive manufacturing equipment interface layout solving method, so as to solve the problem that the traditional particle swarm algorithm for solving the multidimensional domain model is easy to fall into local optimization.

In order to achieve the above object, the present invention is realized by the following steps:

step 1: setting parameters, namely randomly initializing parameters such as the quantity of wolf colony groups, the attack running step length and the like;

step 2: calculating the fitness value of the single wolf, finding out the global historical optimal position, and determining the wolf;

step 3: according to the formula

x_ij(t+1)＝x_ij(t)+rand×step×[x_Lj(t)-x_ij(t)] (15)

Carrying out running behavior, and replacing the wolf if a better fitness value is found in the way;

step 4: according to the formula

Determining a critical value, and entering the critical value according to a formula

x_ij(t+1)＝x_ij(t)+rand×step_b (17)

Turning to attack enclosing behavior;

step 5: recording the current optimal position and the global optimal position of the particles according to a particle swarm algorithm formula;

step 6: calculating the fitness value of a single particle, and updating the individual historical optimal position and the global historical optimal position;

step 7: eliminating q particles with the worst individual historical optimal position fitness value, and generating q particles again at random;

step 8: judging whether a termination condition is met (the maximum iteration number is reached), otherwise, jumping to Step 3; if yes, outputting the global optimal position is ended.

Further, the laser additive manufacturing equipment interface layout solving method based on the wolf pack-particle swarm hybrid intelligent algorithm is characterized in that in the solving step, all formulas are derived from a basic wolf pack algorithm, and the specific operation principle is as follows:

in the process of searching, running and attacking the wolf group, if other wolfs find a better solution than the head wolf, the wolf replaces the position of the head wolf to initiate the running attack activity again. After one iteration is finished, the wolf pack can be updated through a elimination mechanism, so that the wolf pack always keeps strong optimizing capacity. The wolf cluster running mechanism is shown in formula (15). Wherein rand is a random number between 0 and 1, step represents the step length of the wolf of attack, x_Lj(t) represents the position of the wolf of the head at the t-th iteration.

In the running behavior, if the fitness value of the objective function of the position after the attack wolf runs is better than the fitness value of the objective function of the current position, the position of the attack wolf is updated to be the position after the running, otherwise, the position of the attack wolf is the position before the running. The wolf group is transferred from the running state to the attack state of the precise search by taking a set critical value as a boundary, and the critical value is set as S_nThe calculation formula is shown in formula (16) wherein,andthe upper limit and the lower limit of the feasible solution jth dimension in the solution space are shown, D is the dimension of the solution space, and eta is a distance judgment factor.

The attack of the attack wolf is a local precise search, and the attack formula is shown as formula (17). Wherein rand is a random number of-1 to 1, step_bRepresenting the attack step size. As with the running behavior, when the fitness value of the objective function of the position after the attack of the attack wolf is superior to the fitness value of the objective function of the current position, the position of the attack wolf is updated to the position after the attack, otherwise, the position of the attack wolf is the position before the attack; if the position searched by the attack-enclosing wolf is better than the position of the head wolf, the head wolf becomes a new head wolf.

The invention has the beneficial effects that: the operation requirements of an operator on quick, stable, safe and comfortable interaction of the laser additive manufacturing equipment interface are well met, and an ideal design basis is provided for the design of a human-computer interface of the laser additive manufacturing equipment.

Drawings

FIG. 1 is a schematic diagram of interface functional areas according to an embodiment of the present invention.

Fig. 2 is a functional area modularization result according to an embodiment of the present invention.

Fig. 3 is the operator reachable domain modularization result of the present invention.

FIG. 4 shows the result of interface rasterization processing in accordance with an embodiment of the present invention.

FIG. 5 is a flow chart of the hybrid intelligence algorithm of the present invention.

FIG. 6 is a diagram of the hybrid algorithm solution iteration result according to an embodiment of the present invention.

FIG. 7 is an optimized design scheme of the embodiment of the invention.

FIG. 8 is a verification experiment scenario in accordance with an embodiment of the present invention.

Fig. 9 is a comparison graph of the first fixation time of a validation experiment according to an embodiment of the present invention.

Fig. 10(1) and 10(2) are comparison graphs of eye movement hotspots of the optimization effect of the verification experiment of the embodiment of the present invention, where fig. 10(1) is a hotspot graph of the original scheme, and fig. 10(2) is a hotspot graph of the optimization scheme.

Detailed Description

The present invention will be described in further detail with reference to the following drawings and examples, but it should be understood that the examples are illustrative of the present invention and are not intended to limit the present invention.

The embodiment provides a reachable domain-based laser additive manufacturing equipment human-machine interface layout optimization method, which comprises the following steps:

s1, modularization of a human-computer interaction interface and division of reachable domains,

s2, determining the use relationship, the operation relationship and the coordination relationship of each functional module of the human-computer interaction interface,

and S3, constructing a human-computer interface layout model of the laser additive manufacturing equipment.

Referring to fig. 1, 2, and 3, the step S1 of dividing the modularization and reachable domain of the human-computer interaction interface specifically includes:

(1) the interface modularization divides the functional area into a plurality of rectangular rule modules according to the use function of the human-computer interaction interface and the shape and the size. And simultaneously, the complex shape of the functional area and the layout condition inside the area are not considered.

(2) And drawing a CAD graph of the reachable region of the operator by using a reachable region analysis module of Jack simulation software and combining the range of the vertical reachable region of the coronal plane of the human body. Considering that the operator generally operates with the right hand in normal operation, the right side is set to be higher than the left side by taking the midline of the coronal plane of the human body as a boundary, and an reachable domain containing 6 levels is divided.

(3) The comfort and rapidity of the operator using each module are related to the level of the reachable region where each functional module is located and the area in each reachable region. In order to simplify the calculation process of the module area, unit rasterization processing is carried out by taking the center line of the reachable domain as a reference; the reachable area of each functional module is divided by taking 10mm as a basic unit.

Referring to fig. 4, in the embodiment, the interface modularization result is overlapped with the reachable domain to form a unit rasterization processing result of the human-computer interaction interface of the embodiment. And counting the unit number of each reachable domain and the unit number of each module in each reachable domain according to the result. The statistical results of the number of the modular units after the rasterization processing are shown in table 1.

TABLE 1 statistical results of the number of each module unit

Note: no. 10 module-handwheel is movable module, does not occupy any interface space

According to the step S2, in this embodiment, six experts are selected to perform expert interview on the importance degree, the use frequency, and the occurrence probability of each working condition of each function module in the human-computer interface, so as to construct an expert scoring matrix of importance and use frequency. The importance and the use frequency weight index of each interface function module are calculated by adopting a gray entropy weight method, and the result is shown in table 2.

TABLE 2 importance index and use frequency weight index

According to step S2, according to the operation conditions of the function module under different conditions of LDM4030, the operation sequence weight index of the function module under multiple conditions is calculated (as shown in table 3). Meanwhile, the matching relation between the functional modules is determined, and the [ AE IO U ] is represented by 1, 3, 5, 7 and 9 to represent the correlation between the functional modules and other modules. The fitting relationship between the functional modules is shown in table 4.

TABLE 3 importance index and usage frequency weighting index

TABLE 4 coordination relationships between functional modules

According to step S3, the usage relationship parameters, the operation relationship parameters, and the coordination relationship parameters of the interface function module are integrated (as shown in table 5) and substituted into the interface layout model.

Referring to fig. 5, the invention also provides a laser additive manufacturing equipment interface layout solving method based on a wolf pack-particle swarm hybrid intelligent algorithm, so as to solve the problem that the solving of a multidimensional domain model by a traditional particle swarm algorithm is easy to fall into local optimization.

In order to achieve the above object, the present invention is realized by the following steps:

step 1: setting parameters, namely randomly initializing parameters such as the quantity of wolf colony groups, the attack running step length and the like;

step 2: calculating the fitness value of the single wolf, finding out the global historical optimal position, and determining the wolf;

step 3: according to the formula

x_ij(t+1)＝x_ij(t)+rand×step×[x_Lj(t)-x_ij(t)] (15)

Carrying out running behavior, and replacing the wolf if a better fitness value is found in the way;

step 4: according to the formula

Determining a critical value, and entering the critical value according to a formula

x_ij(t+1)＝x_ij(t)+rand×step_b (17)

Turning to attack enclosing behavior;

step 5: recording the current optimal position and the global optimal position of the particles according to a particle swarm algorithm formula;

step 6: calculating the fitness value of a single particle, and updating the individual historical optimal position and the global historical optimal position;

step 7: eliminating q particles with the worst individual historical optimal position fitness value, and generating q particles again at random;

step 8: judging whether a termination condition is met (the maximum iteration number is reached), otherwise, jumping to Step 3; if yes, outputting the global optimal position is ended.

And compiling an algorithm statement on Matlab according to the wolf pack-particle swarm hybrid intelligent algorithm flow according to the steps. Assuming that the total number of iterations is 35, the population scale is 100, c1 is c2 is 2.0, the scale of the wolf colony is 50, and the number of rejected wolfs after each iteration is 5. The optimal layout scheme value obtained after optimization calculation is 13427, and the obtained layout scheme is shown in table 6. The layout scheme value obtained by calculating the layout scheme before optimization is 10551.

TABLE 5 human-machine interface function Module parameters

TABLE 6 optimized layout scheme

Through the model solution and the calculated layout scheme, the number of units occupied by each optimized functional module in the I-th reachable domain and the II-th reachable domain is increased by 351 units compared with the number of units occupied by each optimized functional module in the I-th reachable domain and the II-th reachable domain compared with the layout before optimization, and the number of units in the V-th reachable domain and the VI-th reachable domain is obviously reduced.

Referring to fig. 6, the gray wolf pack algorithm is applied at the same time, the genetic algorithm is used for solving the same model, and the results are compared with the solving quality of the wolf pack-particle swarm hybrid algorithm respectively. The gray wolf group algorithm has a solution result of 12766, and converges when iteration is performed for about 20 times; the solving result of the genetic algorithm is 11327, and the genetic algorithm converges when the iteration is carried out for about 23 times; the wolf pack-particle swarm algorithm converges on the left and right of iteration 16.

Referring to fig. 7, an optimization scheme design effect diagram is formed according to a mixed intelligent algorithm solution result, compared with a layout situation before optimization, a new layout scheme concentrates main operation function areas and a total emergency stop button on the right side and the right lower corner, and arranges main display interfaces on the left side and the central axis, so that the operator can operate quickly and safely and the cognitive characteristics of the operator are met.

Referring to fig. 8, in order to prove that the optimization scheme of the embodiment of the present invention improves human-computer interaction efficiency of an operator and satisfies the safety and comfort operation, the embodiment of the present invention performs example verification by using an eye movement experiment. The hardware of the ErgoLAB man-machine interaction experimental platform used in the experiment comprises one Tobii Fusion-250 eye tracker (the sampling frequency is 250Hz) and one external display screen (the size is 960mm multiplied by 800 mm). The software is combined into ErgoLAB V3.0 human-computer environment test analysis software. 4 old users with abundant operation experience, 4 new users with certain experience and 8 operators who are 26 years old are selected in the experiment and voluntarily participate in the experiment. The specific tasks of the experiment are as follows: an operator completes interface interaction tasks on an original scheme interface and an optimization scheme interface according to the whole process operation sequence from starting to stopping according to the operation process of the LDM4030 in the normal machining state, and the completion time of a single experiment is about 3 minutes.

Referring to fig. 9, the degree of the design solution before and after optimization meeting the requirement of the operator for quick operation is judged by analyzing and comparing the search time of the operator for the specified interest area before and after optimization. Table 7 shows the comparison of the first fixation time before and after optimization.

TABLE 7 comparison of first fixation time before and after optimization

Compared with the original scheme, the optimization scheme can effectively shorten the time for operators to identify the operation information, and further can quickly execute the operation task. And performing two-factor variance analysis on the first fixation time before and after optimization, wherein the interest area and the design scheme are used as independent variables, and the first fixation time is used as a dependent variable. The two-way anova results are shown in table 8.

TABLE 8 first fixation time two-factor analysis of variance results

Note: 626 (485. R after adjustment)

The value of the F statistic of the region of interest is 2.415, and p is 0.151>0.05, which indicates that the influence of the region of interest on the first fixation time is not obvious; the value of the F statistic for the optimization was 8.545, p 0.019 < 0.05, indicating that the optimization had a significant impact on the time-to-first-fixation. It is demonstrated that the post-optimization scheme does have the effect of improving the ability to operate faster than before optimization.

Referring to fig. 10(1) and 10(2), from the hotspot graphs before and after optimization, the hot spot distribution of the original scheme and the optimized scheme is almost different from the line-of-sight concentration range of the core operation area, but the area of the red hot spot area of the original scheme is larger than that of the optimized scheme, which indicates that the original scheme has longer line-of-sight residence time in the core operation area, and the operation time is relatively longer than that of the optimized scheme. It is further demonstrated that the optimized solution can better meet the needs of operators for fast and comfortable operation.

In summary, the optimized human-computer interface layout has certain improvement in the aspects of interface rationality, operation comfort and safety compared with that before optimization, and the laser additive manufacturing equipment human-computer interaction interface after layout optimization is more suitable for the operation requirements of operators on high comfort and high safety of the equipment interface.

The above description is a preferred embodiment of the present invention, and is not intended to limit the present invention, and those skilled in the art may modify the above technical solutions or substitute some technical features of the above technical solutions. 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.