A method and device for controlling the attitude adjustment force of screws in aerospace equipment

Abstract

The present invention discloses a force control method and device for adjusting the screw posture of aerospace equipment, which belongs to the technical field of screw tightening of aerospace equipment. It includes: obtaining the current position and current posture information of the robot; calculating the current joint rotation angles, current posture matrix, and current joint stiffness performance index of the robot based on the current position and current posture information; setting the predetermined angle of rotation of the robot around the processing axis; after the robot rotates, obtaining the new position and posture information of the robot; calculating the new joint rotation angles, new posture matrix, and new joint stiffness performance index of the robot; judging whether the new posture matrix and new joint stiffness performance index meet the evaluation criteria. In the present invention, force sensors and torque sensors are arranged at the end of the robot to realize real-time collection and online perception of process parameters; the screw posture adjustment force control method is adopted to determine the optimal target area of ​​the process parameters of the robot's automatic tightening process.

Description

Technical Field

[0001] The invention belongs to the technical field of screw tightening for aerospace equipment, and in particular relates to a method and device for force control of screw posture adjustment for aerospace equipment. Background Art

[0002] As the new generation of aerospace products develop towards precision, high speed, space-air integration, long life, and ultra-long range, their structural complexity has increased significantly and their service environment has become increasingly harsh. The connection of aerospace square core components represented by integrated measurement and control devices is mainly based on screw connection. The quality of the connection is directly related to the reliability and performance of the measurement and control device, so higher requirements are placed on the quality of assembly connection.

[0003] At present, there are three main ways to connect fasteners on aviation products: manual assembly, semi-automatic assembly, and automated assembly. Manual assembly is labor-intensive and may cause harm to assembly workers in special environments. It is not suitable for the agile production model of aerospace products with multiple varieties and small batches. Product consistency is difficult to ensure, and it is not convenient to collect and manage information such as tightening torque. Although semi-automatic assembly has improved the efficiency of screw tightening to a certain extent, manual intervention is still required during the connection process, and the degree of automation is not high. Compared with manual assembly and semi-automatic assembly, automatic screw assembly has the advantages of high connection efficiency, stable assembly quality, low assembly cost, measurable assembly process data, and easy to achieve high flexibility, intelligent, and information-based assembly. However, the domestic automatic picking and tightening technology of multi-specification screws is mainly used in the field of electronic assembly and the automotive industry, and lacks corresponding technical support and equipment application in the fields of weapons and equipment and aerospace. Summary of the invention

[0004] Purpose of the invention: In order to solve the above problems, the present invention provides a method and device for force control of screw attitude adjustment in aerospace equipment.

[0005] Technical solution: A force control method for adjusting the screw attitude of aerospace equipment, comprising the following steps:

[0006] S1, obtaining the current position and current posture information of the robot; based on the current position and current posture information, calculating the current joint rotation angles, current posture matrix, and current joint stiffness performance index of the robot;

[0007] S2, setting a predetermined angle for the robot to rotate around the machining axis; after the robot rotates, obtaining the new position and posture information of the robot; based on the new position and posture information, calculating the new joint rotation angles, new posture matrix, and new joint stiffness performance index of the robot;

[0008] S3, judging whether the new posture matrix and the new joint stiffness performance index meet the evaluation criteria, if not, repeating S2; if yes, recording the new joint stiffness performance index, and executing the following steps:

[0009] S4, obtaining a pressure signal and a torque signal, and converting them into corresponding tightening pressure and tightening torque;

[0010] S5, adding the new joint stiffness performance index recorded in S3, and the tightening pressure and tightening torque in S4 into the set P;

[0011] S6, determining whether the predetermined angle satisfies the predetermined value, if not, repeating steps S2, S3, S4, and S5 in sequence; if yes, executing the following steps:

[0012] S7, based on the set P, calculate the optimal processing posture, tightening pressure and tightening torque parameters.

[0013] In a further embodiment, the S1 includes the following process:

[0014] Define the current position information as N, and the current posture information as M; based on N and M, use the Paul inverse transform method to find the inverse solution of the robot kinematics to obtain the current joint angle w r (r=1,2,3,4,5,6), the current pose matrix Y=[w 1 , w 2 , w 3 , w 4 , w 5 , w 6 ] T , and the current joint stiffness performance index k.

[0015] In a further embodiment, S2 includes the following process:

[0016] Define θ = i × Δθ, where i is the number of times the angle step is increased, and Δθ is the angle step. After the robot rotates around the machining axis by an angle θ, the new position N′ and new posture information M′ are obtained; based on N′ and M′, the new joint angle w′ is calculated. r (r=1, 2, 3, 4, 5, 6), the new pose matrix Y′=w′ 1 , w′ 2 , w′ 3 , w′ 4 , w′ 5 , w′ 6 ] T , and a new joint stiffness performance index k′.

[0017] In a further embodiment, the specific process of determining whether the evaluation criteria are met in S3 is as follows:

[0018] Determine whether the new posture matrix and the new joint stiffness performance index have the best stiffness corresponding to the extreme posture and singular posture when far away from the joint.

[0019] In a further embodiment, S4 includes the following process:

[0020] The pressure signal and torque signal output by the pressure sensor and torque sensor are obtained, and median filtering, mean filtering and singular point removal are performed on them; the processed pressure signal and torque signal are converted into corresponding tightening pressure and tightening torque.

[0021] In a further embodiment, the step of determining whether the predetermined angle satisfies a predetermined value in S6 includes the following process:

[0022] Determine whether θ≥180. If yes, execute S7. If no, repeat steps S2, S3, S4 and S5.

[0023] In a further embodiment, the S7 includes the following process:

[0024] S71, encode the set P to generate the current primary population; define the current primary population as the parent population;

[0025] S72, performing fast non-dominated sorting on the parent population, using its Pareto level as the fitness value, and using the basic operator of the genetic algorithm to generate the first generation of offspring population;

[0026] S73, merging the parent population with the first generation offspring population to generate a pre-population;

[0027] S74, calculating the terminal vibration response amplitude and posture error in each posture in the population according to the objective function K(θ) and Δ(θ);

[0028]

[0029] Among them, θ 1 ,θ 2 ,θ 3 ,θ 4 ,θ 5 ,θ 6 is the rotation angle of each joint of the robot;

[0030] δ x ,δ y ,δ z ,δ A ,δ B ,δ C are the errors between the center position and posture of the screwdriver head of the end effector and the target point to be processed, δ Fis the error between the actual torque collected by the end sensor and the target torque; δ θ is the error between the actual tightening number of turns and the target tightening number of turns; θ imin ,θ imax are the upper and lower limits of each variable respectively; a, b, c are the weights of each variable in the error calculation respectively;

[0031] S75, performing fast non-dominated sorting and crowding calculation on the terminal vibration response amplitude and posture error under each posture;

[0032] S76, select the better solution according to the individual Pareto level and crowding degree to form a new parent population, and use the three basic operators of genetic algorithm, selection, crossover and mutation, to generate a new generation of offspring population;

[0033] S77, repeat steps S73, S74, S75, and S76 until the number of population iterations reaches a preset value n, and obtain the final optimal processing posture, tightening pressure, and tightening torque parameters.

[0034] In another technical solution, a screw tightening device for aerospace equipment is provided to execute the above-mentioned force control method for adjusting the screw posture of aerospace equipment. The device includes: a six-degree-of-freedom industrial robot, and a screw tightening machine arranged at the output end of the six-degree-of-freedom industrial robot.

[0035] In a further embodiment, a pressure sensor and a torque sensor are provided at the end of the six-degree-of-freedom industrial robot.

[0036] Beneficial effects: Combining industrial robots with automatic picking and tightening technology for screws of various specifications can improve assembly efficiency; force sensors and torque sensors are arranged at the end of the robot to realize real-time collection and online perception of process parameters; a force control method for adjusting the screw posture by integrating force and torque is used to determine the optimal target area for the process parameters of the robot's automatic tightening process. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is the flowchart of the method

[0038] Figure 2 This is a schematic diagram of the structure of the device.

[0039] Figure 3 This is a schematic diagram of the structure of a screw tightening machine.

[0040] Figures 1 to 3 The labels are: six-degree-of-freedom industrial robot 1, tightening machine 2, head assembly 3, chuck assembly 4, tightening gun 5, pneumatic moving assembly 6, pressure sensor 7, torque sensor 8. DETAILED DESCRIPTION

[0041] Embodiment 1

[0042] This embodiment provides a method for force control of attitude adjustment of screws for aerospace equipment, including the following steps:

[0043] S1. Obtain the current position and current attitude information of the robot; calculate the current joint angles, current pose matrix, and current joint stiffness performance index of the robot based on the current position and current attitude information;

[0044] Specifically, it is described as follows: Define the current position information as N and the current attitude information as M; based on N and M, use the Paul inverse transformation method to solve the inverse kinematics of the robot to obtain the current joint angles w r (r = 1, 2, 3, 4, 5, 6), the current pose matrix Y = [w 1 , w 2 , w 3 , w 4 , w 5 , w 6 T , and the current joint stiffness performance index k.

[0045] S2. Set a predetermined angle for the robot to rotate around the machining axis; after the robot rotates, obtain the new position and attitude information of the robot; calculate the new joint angles, new pose matrix, and new joint stiffness performance index of the robot based on the new position and attitude information;

[0046] Specifically, it is described as follows: Define θ = i × Δθ, where i is the number of times of increasing the rotation angle step and Δθ is the rotation angle step. After the robot rotates around the machining axis by an angle θ, obtain the new position N' and new attitude information M'; based on N' and M', calculate the new joint angles w' r (r = 1, 2, 3, 4, 5, 6), the new pose matrix Y' = w' 1 , w' 2 , w' 3 , w' 4 , w' 5 , w' 6 T , and the new joint stiffness performance index k'.

[0047] S3. Judge whether the new pose matrix and the new joint stiffness performance index meet the evaluation criteria. The specific judgment process is as follows:

[0048] Judge whether the stiffness of the corresponding extreme pose and singular pose of Y' and k' reaches the best in the state away from the joints. The best degree is limited according to different actual working conditions.

[0049] If not, repeat S2; ​​

[0050] If yes, then record the new joint stiffness performance index and perform the following steps:

[0051] S4, obtaining a pressure signal and a torque signal, and converting them into corresponding tightening pressure and tightening torque;

[0052] The pressure signal and torque signal output by the pressure sensor and torque sensor are obtained, and median filtering, mean filtering and singular point removal are performed on them; the processed pressure signal and torque signal are converted into corresponding tightening pressure and tightening torque.

[0053] S5, adding the new joint stiffness performance index recorded in S3, and the tightening pressure and tightening torque in S4 into the set P;

[0054] S6, judging whether the predetermined angle satisfies the predetermined value: judging whether θ≥180,

[0055] If not, repeat steps S2, S3, S4, and S5 in sequence.

[0056] If yes, execute S7.

[0057] S7, based on the set P, calculate the optimal processing posture, tightening pressure and tightening torque parameters.

[0058] The S7 includes the following process:

[0059] S71, encode the set P to generate the current primary population; define the current primary population as the parent population;

[0060] S72, performing fast non-dominated sorting on the parent population, using its Pareto level as the fitness value, and using the basic operator of the genetic algorithm to generate the first generation of offspring population;

[0061] S73, merging the parent population with the first generation offspring population to generate a pre-population;

[0062] S74, calculating the terminal vibration response amplitude and posture error in each posture in the population according to the objective function K(θ) and Δ(θ);

[0063]

[0064] Among them, θ 1 ,θ 2 ,θ 3 ,θ 4 ,θ 5 ,θ 6 is the rotation angle of each joint of the robot;

[0065] δ x , δ y , δz ,δ A ,δ B ,δ C are the position and posture errors of the center point of the screwdriver head of the end effector and the target point to be processed (position and posture error), δ F is the error between the actual torque collected by the end sensor and the target torque; δ θ is the error between the actual tightening number of turns and the target tightening number of turns; θ imin ,θ imax are the upper and lower limits of the constraints for each variable; a, b, and c are the weights of each variable in the error calculation. The vibration response amplitude is the maximum value of the six joint angles within the range of their respective joint variables.

[0066] The rotation angle of each joint of the industrial robot 1 ,θ 2 ,θ 3 ,θ 4 ,θ 5 ,θ 6 , and the torque θ collected by the tightening end effector 7 and tightening turns (angle)θ 8 , the value ranges are shown in the following table:

[0067]

[0068] S75, performing fast non-dominated sorting and crowding calculation on the terminal vibration response amplitude and posture error under each posture;

[0069] S76, select the better solution according to the individual Pareto level and crowding degree to form a new parent population, and use the three basic operators of genetic algorithm, selection, crossover and mutation, to generate a new generation of offspring population;

[0070] S77, repeat steps S73, S74, S75, and S76 until the number of population iterations reaches a preset value n, and obtain the final optimal processing posture, tightening pressure, and tightening torque parameters.

[0071] The specific process in S7 is as follows:

[0072] S71, perform chromosome decimal encoding on set P to generate the initial population P j ;

[0073] S72, for the primary population P j Perform fast non-dominated sorting, use its Pareto level as the fitness value, and use the basic operator of the genetic algorithm to generate the first generation of offspring population Q j ;

[0074] S73, define the initial population P jis the parent population; the parent population P i With offspring Q j Individuals are merged to generate a pre-population R j ;

[0075] S74, calculate the pre-population R according to the objective function j The terminal vibration response amplitude and posture error in each posture;

[0076] S75, fast non-dominated sorting and crowding calculation of the terminal vibration response amplitude and posture error;

[0077] S76, select the better solution according to the individual Pareto level and crowding degree to form a new parent population P j+1 , using the three basic operators of genetic algorithms: selection, crossover, and mutation to generate a new generation of offspring population Q j+1 ;

[0078] S77, repeat steps S73, S74, S75, and S76 until the number of population iterations reaches a preset value n, and obtain the final optimal processing posture and process parameter set (the set includes tightening pressure and tightening torque).

[0079] Example 2

[0080] This embodiment provides a screw tightening device for aerospace equipment, which adopts a force control method for adjusting the screw posture of aerospace equipment described in Example 1, and the device includes: a six-degree-of-freedom industrial robot 1, and a tightening machine 2 arranged at the output end of the six-degree-of-freedom industrial robot 1. A pressure sensor 7 and a torque sensor 8 are arranged at the end of the six-degree-of-freedom industrial robot 1.

[0081] A multi-specification screw tightening system for a box of aerospace equipment, such as Figures 1 to 2 As shown, it includes a KUKA six-degree-of-freedom industrial robot 1 and a tightening machine 2, wherein the tightening machine 2 is a multi-specification screw tightening machine 2. The tightening machine 2 is installed at the end of the industrial robot. The industrial robot completes the positioning of the process of replacing the head assembly 3 and the chuck assembly 4 in the end tightening machine 2. The overall system composed of the tightening machine 2 and the industrial robot realizes the tightening of screws of different specifications.

[0082] A multi-specification screw tightening system for a box of aerospace equipment. The screw tightening process of the system is as follows:

[0083] (1) Adjust the posture of the industrial robot for the first time, and replace the tightening head assembly 3 and the chuck assembly 4 of the tightening machine 2 with a suitable one;

[0084] (2) Adjust the posture of the industrial robot for the second time and position the end of the robot to the assembly position;

[0085] (3) The tightening gun 5 in the tightening machine 2 picks up a single screw from the cartridge assembly 4 and moves it to the assembly position through the pneumatic moving assembly 6 to tighten it. After tightening at this position, the tightening gun 5 returns to the cartridge assembly 4 to pick up the next screw until all the screws in the cartridge are assembled;

[0086] (4) After all the screws in one chuck tray are assembled, repeat steps (1) to (3) until the screws of one workpiece are tightened.

Claims

1. A force control method for adjusting the screw attitude of aerospace equipment. It is characterized in that The following steps are involved: S1, obtain the current position and current posture information of the robot; Based on the current position and current posture information, the current joint rotation angles, current posture matrix, and current joint stiffness performance indicators of the robot are calculated; S2, setting a predetermined angle for the robot to rotate around the machining axis; after the robot rotates, obtaining the new position and posture information of the robot; based on the new position and posture information, calculating the new joint rotation angles, new posture matrix, and new joint stiffness performance index of the robot; S3, judging whether the new posture matrix and the new joint stiffness performance index meet the evaluation criteria, if not, repeating S2; if yes, recording the new joint stiffness performance index, and executing the following steps: S4, obtaining a pressure signal and a torque signal, and converting them into corresponding tightening pressure and tightening torque; S5, adding the new joint stiffness performance index recorded in S3, and the tightening pressure and tightening torque in S4 into the set P; S6, determining whether the predetermined angle satisfies the predetermined value, if not, repeating steps S2, S3, S4, and S5 in sequence; if yes, executing the following steps: S7, based on the set P, calculating the optimal processing posture, tightening pressure and tightening torque parameters; S71, encode the set P to generate the current primary population; define the current primary population as the parent population; S72, performing fast non-dominated sorting on the parent population, using its Pareto level as the fitness value, and using the basic operator of the genetic algorithm to generate the first generation of offspring population; S73, merging the parent population with the first generation offspring population to generate a pre-population; S74, according to the objective function and , calculate the terminal vibration response amplitude and posture error under each posture in the population; ； in, is the rotation angle of each joint of the robot; is the collected torque; is the number of tightening turns; They are the errors between the position and posture of the center point of the screwdriver bit of the end effector and the target point to be processed; It is the error between the actual torque collected by the end sensor and the target torque; It is the error between the actual number of tightening turns and the target number of tightening turns; are the upper and lower limits of each variable respectively; a, b, c are the weights of each variable in the error calculation respectively; S75, performing fast non-dominated sorting and crowding calculation on the terminal vibration response amplitude and posture error under each posture; S76, select the better solution according to the individual Pareto level and crowding degree to form a new parent population, and use the three basic operators of genetic algorithm, selection, crossover and mutation, to generate a new generation of offspring population; S77, repeat steps S73, S74, S75, and S76 until the number of population iterations reaches a preset value n, and obtain the final optimal processing posture, tightening pressure, and tightening torque parameters.

2. A method for controlling the attitude adjustment of screws in aerospace equipment according to claim 1, It is characterized in that The S1 includes the following processes: Define the current position information as N, and the current posture information as M; based on N and M, use the Paul inverse transform method to find the inverse solution of the robot kinematics to obtain the current joint angles , the current pose matrix , and the current joint stiffness performance index k.

3. A method for controlling the attitude adjustment of screws in aerospace equipment according to claim 1, It is characterized in that The S2 includes the following process: definition , Increase the number of times for the corner step size, is the angle step length, the robot rotates around the machining axis After that, get the new position , new posture information ;based on , , calculate the new rotation angles of each joint , the new pose matrix , and new joint stiffness performance indicators .

4. A method for controlling the attitude adjustment force of a screw in aerospace equipment according to claim 1, It is characterized in that The specific process of determining whether the evaluation criteria are met in S3 is as follows: Determine whether the new posture matrix and the new joint stiffness performance index have the best stiffness for the corresponding extreme posture and singular posture when far away from the joint.

5. A method for controlling the attitude adjustment force of a screw in aerospace equipment according to claim 1, It is characterized in that The S4 includes the following process: The pressure signal and torque signal output by the pressure sensor and torque sensor are obtained, and median filtering, mean filtering and singular point removal are performed on them; the processed pressure signal and torque signal are converted into corresponding tightening pressure and tightening torque.

6. A method for controlling the attitude adjustment force of a screw in aerospace equipment as claimed in claim 1, It is characterized in that The determination in S6 whether the predetermined angle satisfies the predetermined value includes the following process: judge If yes, execute S7, if no, repeat steps S2, S3, S4, and S5.

7. A screw tightening device for aerospace equipment, It is characterized in that A force control method for adjusting the screw posture of aerospace equipment is adopted as described in any one of claims 1 to 6, and the equipment includes: a six-degree-of-freedom industrial robot, and a screw tightening machine arranged at the output end of the six-degree-of-freedom industrial robot.

8. The aerospace equipment screw tightening device according to claim 7, It is characterized in that The end of the six-degree-of-freedom industrial robot is provided with a pressure sensor and a torque sensor.

Images