Helicopter cockpit control panel arrangement method

Abstract

The invention belongs to the technical field of man-machine work efficiency design, and discloses a helicopter cockpit control panel arrangement method. The method comprises the following steps of: 1, establishing a multi-objective optimization mathematical model by taking the minimum panel control muscle feeling load, the minimum panel visual load and the minimum driving operation stroke load as optimization objectives; 2, according to constraints of a console loading space, a panel arrangement element and a control activity space, determining an arrangement constraint condition of a control panel; and 3, solving the whole flight process-oriented unit driving control load control optimization model by adopting a genetic algorithm.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of man-machine ergonomics design, and particularly relates to a method for arranging a control panel in a helicopter cockpit. BACKGROUND

[0002] The console is an important interface for the pilot to manipulate and control the helicopter, and power, power supply, environmental control, task, etc. control panels are usually configured thereon. The rationality of the control panel arrangement is directly related to the pilot's flight mental load and control physiological load, and directly affects the helicopter control efficiency, driving comfort and safety. The control panel arrangement needs to consider multiple design objectives and engineering constraint conditions, including device installation space limitation, structure installation gap requirement, limb movement space, operation visibility and accessibility, task low load control, etc. These constraint factors are not isolated, but are interrelated and have inherent connections, which inevitably brings difficulties to the control panel arrangement.

[0003] At present, the cockpit control panel arrangement mainly relies on mapping imitation or personal experience, and is realized through repeated coordination, comprehensive balance and multiple iterations of various professionals, with long design cycle, low efficiency, and the arrangement scheme formed generally has problems of heavy task control load and long driving operation distance. SUMMARY

[0004] The purpose of the present application is to provide a method for arranging a control panel in a helicopter cockpit, which can reduce the task control load, shorten the driving operation distance, improve the crew driving control efficiency, and at the same time reduce the number of arrangement coordination and iteration, shorten the development cycle, and effectively improve the reliability and optimization efficiency of the arrangement scheme.

[0005] The present application provides a method for arranging a control panel in a helicopter cockpit, which comprises: Step 1: Establishing a multi-objective optimization mathematical model with the minimum muscle sense load of the panel control, the minimum visual load of the panel, and the minimum driving operation distance load as the optimization objectives; Step 2: Determining the control panel arrangement constraint conditions according to the console loading space, panel arrangement elements, and control activity space constraints; Step 3: Solving the crew driving control load control optimization model for the whole flight process by using a genetic algorithm.

[0006] Further, in step 1, the objective function of the minimum muscle sense load of the panel control is specifically:

[0007] Wherein, is the muscle sense load of the crew control panel; represents the pilot serial number, represents the pilot identification, represents the pilot identification, , represents the number of pilots equipped with the helicopter; represents the panel serial number, represents the panel identification, , , is the total number of panels; represents the frequency of the pilot's manipulation of the panel during the process of executing the normal flight operation program; represents the frequency of the pilot's manipulation of the panel during the process of executing the emergency flight operation program; represents the frequency of the pilot's manipulation of the panel during the process of executing the emergency flight operation program; represents the muscle sensation load of the pilot's single manipulation of the panel ;

[0008] wherein, represents the muscle sensation load coefficient, represents the arrangement number of the panel relative to the pilot, , , is the total number of panel arrangement columns.

[0009] Further, in step one, the target function of the minimum visual load of the panel is specific to:

[0010] wherein, is the visual load of the crew's manipulation of the panel; represents the visual load of the pilot's single manipulation of the panel ;

[0011] wherein, is the visual load system, represents the panel arrangement source point coordinate; represents the center coordinate of the panel ; represents the design eye point coordinate of the pilot .

[0012] Further, in step one, the target function of the minimum driving operation stroke load is specific to:

[0013] wherein, represents the driving operation stroke load; ​​Indicates driver During normal flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver During the execution of emergency flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver right , The operating load per unit distance between panels is expressed as:

[0014] at the same time express , The distance between panels is expressed as: .

[0015] Furthermore, in step one, the overall objective function is constructed as follows:

[0016] in, This represents the overall optimization objective; , , For multi-objective weights.

[0017] Furthermore, in step two, the constraints for the layout of the control panel are determined, specifically as follows: (1) Panels in the same column do not collide or overlap.

[0018] in, , Representing the panels , Length dimension; (2) The panel of any column shall not collide with the front and rear wall panels of the control panel structure.

[0019] in, Indicates the first Coordinates of the front wall panel of the train control console. Indicates the first The coordinates of the rear wall panel of the train control console.

[0020] Furthermore, in step three, a genetic algorithm is used to solve the crew pilot control load optimization model for the entire flight process, specifically as follows: (1) Panel layout optimization identification: The fitness function and constraints of the problem model are identified as layout optimization. (2) Population initialization: N random arrangements of all panels are generated, and for each arrangement, the center coordinates of the panel arrangement are solved according to the constraints to form N chromosomes as the initial population. (3) Fitness calculation: The panel layout optimization function is transformed into a fitness function. For panels that exceed the control panel layout constraints, a penalty term is introduced. The fitness function is then expressed as:

[0021] (5) Genetic selection operation: Calculate the fitness value of all chromosomes in the population, arrange them in descending order, retain the first 10% of chromosomes to enter the next generation population, without crossover and mutation operations, and use the roulette wheel method to perform crossover and mutation operations on the remaining 90% of chromosomes that are inferior to the population. (6) Genetic crossover operation: Adaptive crossover operation is performed on the arrangement of chromosomes of the inferior population according to the crossover probability; according to the arrangement scheme after crossover, the center coordinates of the equipment arrangement are solved in combination with the constraints to form a new chromosome; calculate the fitness value of the new chromosome. If the value is greater than the fitness value of the original chromosome, crossover repair is performed; otherwise, the original chromosome is retained. (7) Genetic mutation operation: Adaptive mutation operation is performed on the arrangement of chromosomes of the inferior population according to the mutation probability; according to the arrangement scheme after mutation, the center coordinates of the panel arrangement are solved in combination with the constraints to form a new chromosome and complete the mutation operation. (8) Replace unqualified chromosomes: If any panel in the population exceeds the control panel layout constraints, the chromosome with the highest fitness value in the population shall be used for replacement, which is convenient for genetic optimization. (9) Termination condition judgment: Determine whether the maximum number of iterations has been reached. If so, output the optimal panel layout scheme; otherwise, proceed to step (5) for iterative optimization.

[0022] In summary, the beneficial effects of the present invention are as follows: This invention proposes a method for arranging control panels in a helicopter cockpit. It fully considers the optimization of crew control load throughout the entire helicopter flight process, effectively avoiding problems such as heavy mission control load and long pilot operation strokes inherent in conventional arrangements. Furthermore, it employs a genetic algorithm to solve the control panel arrangement optimization problem, enabling rapid and efficient acquisition of optimized helicopter cockpit control panel layout schemes. This method has been successfully applied to a certain type of helicopter and can be applied to other helicopters or fixed-wing aircraft in the future, demonstrating significant engineering application value. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the fitness function curve of the method of the present invention; Figure 2 This is a schematic diagram of the optimal control panel layout scheme determined by the method of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0025] A method for arranging control panels in a helicopter cockpit is proposed. A mathematical model for optimizing crew control load is established for the entire flight process. Based on the optimization objectives of minimizing tactile load, visual load, and travel load of panel operation, a weighted value is introduced to transform it into a single optimization model. Meanwhile, constraints such as structural loading space, panel arrangement, and control activity space are considered. A genetic algorithm is used to solve the optimization model to quickly obtain the helicopter cockpit control panel arrangement scheme.

[0026] A method for arranging control panels in a helicopter cockpit includes the following steps: Step 1: Establish a multi-objective optimization mathematical model with the optimization objectives of minimizing the tactile load of panel operation, the visual load of panel operation, and the driving operation travel load.

[0027] (1) Objective function for minimizing the tactile load of panel control The placement of the control panel directly affects the tactile load on the generator set's operation. Considering the issue of controlling the tactile load on the generator set's control panel, the primary goal is to minimize the tactile load on the control panel.

[0028] (1) In formula (1), To reduce the tactile stress on the unit's control panel; Indicates the driver's serial number. Indicates the first Driver identification, , Indicates the number of pilots on board the helicopter; Indicates the panel number. Indicates the first Each panel label, , Total number of panels; Indicates driver During the execution of normal flight operation procedures, the panel The frequency of operation; Indicates driver During the execution of emergency flight operation procedures, the panel The frequency of operation; Indicates driver For the panel Single manipulation muscle load: (2) In formula (2), Indicates the muscle sensation load coefficient. Display panel relative driver The number of permutations arranged, , Set the total number of columns for the panel.

[0029] (2) Objective function for minimizing visual load on the panel The control panel on the control console is equipped with various control devices, which are numerous, have diverse operations and functions. Improper operation can easily cause helicopter malfunctions and even endanger the flight safety of the helicopter. Therefore, the pilot needs to operate the control panel visually to avoid flight misoperation. Thus, minimizing the visual load on the panel is an optimization goal.

[0030] (3) In formula (3), To reduce the visual load on the unit's control panel; Indicates driver For the panel Visual load during a single operation: (4) In formula (4), For visual load systems, Indicates the coordinates of the source point for panel layout; Display panel The center coordinates; Indicates driver The coordinates of the eye point in the design.

[0031] (3) Objective function for minimizing driving operation stroke load The crew mainly follows the flight operation procedures to achieve helicopter take-off, landing, flight and complete various tasks. This requires planning the flight operation journey through the control panel in stages to form a control interconnection network. Considering that the quality of the flight operation journey design will directly affect the crew's flight quality and mission efficiency, the crew's flight operation journey should be simplified as much as possible when planning the layout of the control panel. Therefore, minimizing the flight operation journey load is taken as an optimization goal.

[0032] (5) In formula (5), Indicates the driving operation stroke load; Indicates driver During normal flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver During the execution of emergency flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver right , The operating load per unit distance between panels can be expressed as: (6) at the same time express , The distance between panels can be expressed as: (7) (4) Construct the overall objective function By assigning appropriate weights to the above objective function values, an objective function for equipment layout optimization is constructed: (8) In formula (8), This represents the overall optimization objective; , , For multi-objective weights.

[0033] Step 2: Taking into account constraints such as the loading space of the control panel, panel layout elements, and operating space, determine the constraints for the layout of the control panel.

[0034] (1) Panels in the same column do not collide or overlap. (9) In formula (9), , Representing the panels , The length dimension.

[0035] (2) The panel of any column shall not collide with the front and rear wall panels of the control panel structure. (10) In formula (10), Indicates the first Coordinates of the front wall panel of the train control console. Indicates the first The coordinates of the rear wall panel of the train control console.

[0036] Step 3: Use a genetic algorithm to solve the crew pilot control load optimization model for the entire flight process.

[0037] (1) Panel layout optimization identification: The fitness function and constraints of the problem model are identified as layout optimization. (2) Population initialization. N random arrangements of all panels are generated, and for each arrangement, the center coordinates of the panel arrangement are solved according to the constraints to form N chromosomes as the initial population.

[0038] (3) Fitness calculation. The panel layout optimization function is transformed into a fitness function. For panels that exceed the control panel layout constraints, a penalty term is introduced. The fitness function can then be expressed as: (11) (5) Genetic selection operation. Calculate the fitness values ​​of all chromosomes in the population, arrange them in descending order, retain the top 10% of chromosomes to enter the next generation population without crossover and mutation operations, and use the roulette wheel method to perform crossover and mutation operations on the remaining 90% of chromosomes (called the inferior population).

[0039] (6) Genetic crossover operation. Adaptive crossover operation is performed on the arrangement of chromosomes in the inferior population according to the crossover probability. That is, for each chromosome in the inferior population, the chromosome to be crossed and the crossover node are randomly generated. The genes of the two chromosomes to be crossed are exchanged at the crossover node, and the duplicate genes on other nodes of the chromosome are corrected to replace the genes. According to the arrangement scheme after crossover, the center coordinates of the equipment arrangement are solved in combination with the constraints to form a new chromosome. The fitness value of the new chromosome is calculated. If the value is greater than the fitness value of the original chromosome, crossover repair is performed. Otherwise, the original chromosome is retained.

[0040] (7) Genetic mutation operation. Adaptive mutation operation is performed on the arrangement of chromosomes in the inferior population according to the mutation probability. That is, two different mutation nodes are randomly generated, and the genes of the chromosomes to be mutated in the inferior population are interchanged at the two mutation nodes. According to the arrangement scheme after mutation, the center coordinates of the panel arrangement are solved in combination with the constraints to form a new chromosome and complete the mutation operation.

[0041] (8) Replace unqualified chromosomes. If any panel in the population exceeds the control panel layout constraints, the chromosome with the highest fitness value in the population shall be used for replacement to facilitate genetic optimization.

[0042] (9) Termination condition judgment: Determine whether the maximum number of iterations has been reached. If so, output the optimal panel layout scheme; otherwise, proceed to step (5) for iterative optimization.

[0043] Example illustration: The specific details of the central control panel design for the side-by-side two-seat helicopter cockpit in this example are as follows: The helicopter cockpit crew consists of two pilots who share a central control panel. The central control panel is divided into three rows, each 146mm wide. The middle row has a length ranging from 0 to 550mm, while the two side rows have lengths ranging from 86mm to 550mm. Based on the control panel layout plan, 11 panels with different functions are prepared for the control panel arrangement. Control panel information (dimensions, frequency of operation by the two pilots during normal / emergency flight procedures) is shown in Table 1; the control panel travel distance during normal / emergency flight is shown in Table 2; assuming the panel placement origin point is located on the left front wall of the control panel, the pilot's designed eye position relative to the placement origin point in the X direction is 300mm, the muscle feel load factor is 3, and the visual load factor is 2.

[0044] Table 1 Control Panel Information Table

[0045] Table 2. Trip Schedule for Unit Control Panel

[0046] The proposed unit driving operation load control optimization model was solved using a genetic algorithm. The relevant parameters were set as follows: population size of 100, crossover probability of 0.3, mutation probability of 0.2, and maximum iteration termination count of 100. The weights of the objective function were set as follows: , , The penalty value is The layout of the cockpit control panel is as follows: Table 3 Optimal Solution for Cockpit Control Panel Layout

[0047] from Figure 1 It can be seen that the helicopter cockpit control panel layout method based on genetic algorithm proposed in this invention fully considers the optimization of crew pilot control load, and can quickly and efficiently obtain the optimized layout scheme of helicopter cockpit control panels, such as... Figure 2 As shown.

[0048] The key point of this invention is a helicopter cockpit control panel layout optimization method based on genetic algorithms. It is applicable to multiple panel layouts with multiple constraints and complex control interconnections, and can quickly and efficiently obtain helicopter cockpit control panel layout optimization schemes.

[0049] The cockpit configuration can be a side-by-side two-seat configuration, a tandem two-seat configuration, a single-seat configuration, or a multi-seat configuration.

[0050] The genetic operations described can be performed by first crossing over and then mutation, or by first mutation and then crossing over.

Claims

1. A method for arranging control panels in a helicopter cockpit, characterized in that, The method includes: Step 1: Establish a multi-objective optimization mathematical model with the optimization objectives of minimizing the tactile load of panel operation, minimizing the visual load of panel operation, and minimizing the travel load of driving operation. Step 2: Determine the control panel layout constraints based on the constraints of the control panel loading space, panel layout elements, and control activity space. Step 3: Use a genetic algorithm to solve the crew pilot control load optimization model for the entire flight process.

2. The method for arranging a helicopter cockpit control panel according to claim 1, characterized in that, In step one, the objective function that minimizes the tactile load on the panel controls is specifically: in, To reduce the tactile stress on the unit's control panel; Indicates the driver's serial number. Indicates the first Driver identification, , Indicates the number of pilots on board the helicopter; Indicates the panel number. Indicates the first Each panel label, , Total number of panels; Indicates driver During the execution of normal flight operation procedures, the panel The frequency of operation; Indicates driver During the execution of emergency flight operation procedures, the panel The frequency of operation; Indicates driver For the panel Single manipulation muscle load: in, Indicates the muscle sensation load coefficient. Display panel relative driver The number of permutations arranged, , Set the total number of columns for the panel.

3. The method for arranging a helicopter cockpit control panel according to claim 2, characterized in that, In step one, the objective function that minimizes the visual load on the panel is specifically: in, To reduce the visual load on the unit's control panel; Indicates driver For the panel Visual load during a single operation: in, For visual load systems, Indicates the coordinates of the source point for panel layout; Display panel The center coordinates; Indicates driver The coordinates of the eye point in the design.

4. The method for arranging a helicopter cockpit control panel according to claim 3, characterized in that, In step one, the objective function for minimizing the driving operation stroke load is as follows: in, Indicates the load of driving operation stroke; Indicates driver During normal flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver During the execution of emergency flight procedures, the operating procedures are controlled from the panel. To panel The number of times; Indicates driver right , The operating load per unit distance between panels is expressed as: at the same time express , The distance between panels is expressed as: 。 5. A method for arranging control panels in a helicopter cockpit according to claim 4, characterized in that, In step one, the overall objective function is constructed as follows: in, This represents the overall optimization objective; , , For multi-objective weights.

6. A method for arranging control panels in a helicopter cockpit according to claim 5, characterized in that, In step two, the constraints for the layout of the control panel are determined, specifically as follows: (1) Panels in the same column do not collide or overlap. in, , Representing the panels , Length dimension; (2) The panel of any column shall not collide with the front and rear wall panels of the control panel structure. in, Indicates the first Coordinates of the front wall panel of the train control console. Indicates the first The coordinates of the rear wall panel of the train control console.

7. A method for arranging control panels in a helicopter cockpit according to claim 6, characterized in that, In step three, a genetic algorithm is used to solve the crew piloting load control optimization model for the entire flight process, specifically as follows: (1) Panel layout optimization identification: The fitness function and constraints of the problem model are identified as layout optimization. (2) Population initialization: N random arrangements of all panels are generated, and for each arrangement, the center coordinates of the panel arrangement are solved according to the constraints to form N chromosomes as the initial population. (3) Fitness calculation: The panel layout optimization function is transformed into a fitness function. For panels that exceed the control panel layout constraints, a penalty term is introduced. The fitness function is then expressed as: (5) Genetic selection operation: Calculate the fitness value of all chromosomes in the population, arrange them in descending order, retain the first 10% of chromosomes to enter the next generation population, without crossover and mutation operations, and use the roulette wheel method to perform crossover and mutation operations on the remaining 90% of chromosomes that are inferior to the population. (6) Genetic crossover operation: Adaptive crossover operation is performed on the arrangement of chromosomes of the inferior population according to the crossover probability; according to the arrangement scheme after crossover, the center coordinates of the equipment arrangement are solved in combination with the constraints to form a new chromosome; calculate the fitness value of the new chromosome. If the value is greater than the fitness value of the original chromosome, crossover repair is performed; otherwise, the original chromosome is retained. (7) Genetic mutation operation: Adaptive mutation operation is performed on the arrangement of chromosomes of the inferior population according to the mutation probability; according to the arrangement scheme after mutation, the center coordinates of the panel arrangement are solved in combination with the constraints to form a new chromosome and complete the mutation operation. (8) Replace unqualified chromosomes: If any panel in the population exceeds the control panel layout constraints, the chromosome with the highest fitness value in the population shall be used for replacement, which is convenient for genetic optimization. (9) Termination condition judgment: Determine whether the maximum number of iterations has been reached. If so, output the optimal panel layout scheme; otherwise, proceed to step (5) for iterative optimization.

8. A helicopter cockpit control panel layout system, characterized in that, The system is used to perform the method as described in any one of claims 1-7.

9. A helicopter cockpit control panel, characterized in that, The control panel is a panel arranged using the method described in any one of claims 1-7.

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