Intelligent control method for climbing control of overhead line inspection robot

Abstract

This invention provides an intelligent control method for the climbing control of a rail-mounted inspection robot. When the rail-mounted inspection robot is climbing a slope, it uses an intelligent algorithm to determine the clamping force value to be applied to the front and rear wheels based on the current slope information, and then applies this clamping force to the front and rear wheels. This achieves optimized distribution of the clamping force between the front and rear wheels, improving climbing efficiency, reducing energy loss, and extending the service life of the drive wheels.

Description

Technical Field

[0001] This invention relates to the field of inspection robot control, and specifically to an intelligent control method for the climbing control of a rail-mounted inspection robot. Background Technology

[0002] Inspection is an essential part of industries such as power, coal, steel, and sewage treatment. It is usually done manually. However, most of the equipment in these industries works in harsh environments or in environments that are difficult for humans to reach. This poses a great challenge to manual inspection. Therefore, inspection robots are gradually replacing manual inspection and becoming the main means of inspection.

[0003] Rail-mounted inspection robots offer advantages such as precise control, simple mechanism, and high safety, making them ideal for situations with simple routes and complex environments. When a rail-mounted inspection robot is climbing a slope, the clamping mechanism provides clamping force to prevent slippage. Most clamping mechanisms provide the same clamping force to both the front and rear wheels. This presents a problem: when climbing, the front wheels bear a greater component of the gravity, and the clamping force applied to the front wheels is too high for the rear wheels. This can lead to the robot failing to climb, wasting energy, and increasing wear on the drive wheels. Summary of the Invention

[0004] The main objective of this invention is to provide an intelligent control method for the climbing control of a rail-mounted inspection robot, thereby solving the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an intelligent control method for the climbing control of a rail-mounted inspection robot, comprising the following steps: the rail-mounted robot determines the clamping force value applied to the front and rear wheels based on the current slope information using an intelligent algorithm, and applies the clamping force of the value to the front and rear wheels.

[0006] Furthermore, the intelligent algorithm is an adaptive algorithm that uses slope information as an input variable to adaptively adjust the value of the clamping force applied to the front and rear wheels.

[0007] Furthermore, the intelligent control method for the ramp control of the rail-mounted inspection robot includes the following adaptive algorithm implementation steps:

[0008] S1. Based on the slope information, and combined with the fixed parameters such as the center of gravity height, weight, and track friction coefficient of the rail-mounted inspection robot, the force balance and torque of the rail-mounted inspection robot are analyzed, and the range of values ​​of the front and rear wheel clamping forces under the slope is calculated.

[0009] S2. Multiply the minimum value of the corresponding front and rear wheel clamping forces by the redundancy coefficient to obtain the value of the actual clamping force applied to the front and rear wheels;

[0010] S3. Compare the minimum value of the corresponding front and rear wheel clamping force obtained in real time in S1 with the actual value of the front and rear wheel clamping force. When the minimum value of the corresponding front wheel clamping force is greater than the actual value of the front wheel clamping force, multiply the minimum value of the corresponding front wheel clamping force by a redundancy coefficient to obtain the value of the actual clamping force applied to the front wheel. When the minimum value of the corresponding rear wheel clamping force is greater than the actual value of the rear wheel clamping force, multiply the minimum value of the corresponding rear wheel clamping force by a redundancy coefficient to obtain the value of the actual clamping force applied to the rear wheel.

[0011] S4. Repeat S3;

[0012] The above steps enable precise clamping force control.

[0013] Furthermore, in the intelligent control method for the ramp control of the rail-mounted inspection robot, the redundancy coefficient is 1.05~1.4.

[0014] Preferably, in the intelligent control method for the ramp control of the rail-mounted inspection robot, the redundancy coefficient is 1.1.

[0015] Furthermore, in the intelligent control method for the climbing control of the rail-mounted inspection robot, in step S1, the force analysis of the rail-mounted inspection robot during climbing is as follows, listing the balance equation of the robot's gravity components at the front and rear wheels:

[0016] ;

[0017] in, G For the weight of the robot, F GF , F GR These are the components of the force exerted by the ground wire on the front and rear wheels as it overcomes the robot's gravity. LF , LR These are the distances from the center of gravity along the line connecting the front and rear wheels to the front and rear wheels, respectively. H It is the height of the center of gravity. To account for the track slope, the balance formula for the front and rear wheel components can be obtained as follows:

[0018] ;

[0019] Therefore, we can obtain:

[0020] ;

[0021] To apply a clamping force to prevent slippage of both the front and rear drive wheels, the following conditions must be met:

[0022] ;

[0023] in, The coefficient of friction of the track. F NF , F NR These are the clamping forces corresponding to the front and rear wheels, respectively.

[0024] Furthermore, the intelligent control method for the climbing control of the rail-mounted inspection robot calculates and processes the non-slipping conditions to obtain the value range of the corresponding front and rear wheel clamping forces:

[0025] .

[0026] Furthermore, in the intelligent control method for the climbing control of the rail-mounted inspection robot, in step S2, the actual clamping force applied to the front and rear wheels is determined based on the range of clamping forces of the front and rear wheels as follows:

[0027] ;

[0028] As can be seen from the above formula, apart from the slope, the other parameters are inherent to the robot or the track itself.

[0029] Furthermore, in the intelligent control method for the slope control of the rail-mounted inspection robot, in step S3, the slope at the current moment is set as... The minimum value of the corresponding front wheel clamping force is F NF1 The corresponding minimum value of the rear wheel clamping force is F NR1 Compare the corresponding front wheel clamping force value with the actual front wheel clamping force value. When the corresponding front wheel clamping force value is greater than or equal to the actual front wheel clamping force value, that is:

[0030] ;

[0031] Update the actual clamping force value of the front wheels:

[0032] ;

[0033] Furthermore, in the intelligent control method for the slope control of the rail-mounted inspection robot, in step S3, the slope at the current moment is set as... The minimum value of the corresponding front wheel clamping force is F NF1 The corresponding minimum value of the rear wheel clamping force is F NR1 Compare the corresponding rear wheel clamping force value with the actual rear wheel clamping force value. When the corresponding rear wheel clamping force value is greater than or equal to the actual rear wheel clamping force value, that is:

[0034] (9);

[0035] Update the actual clamping force value of the rear wheels:

[0036] (10). Attached Figure Description

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0038] Figure 1 This is a flowchart of the control algorithm of the present invention;

[0039] Figure 2 This is a force analysis diagram of the rail-mounted inspection robot of the present invention when climbing a slope. Detailed Implementation

[0040] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0041] like Figure 1 As shown, the intelligent control method for the slope control of the rail-mounted inspection robot includes the following steps: the rail-mounted robot uses an intelligent algorithm to determine the clamping force value applied to the front and rear wheels based on the current slope information, and applies the clamping force of that value to the front and rear wheels.

[0042] The intelligent algorithm is an adaptive algorithm with slope as the independent variable. The adaptive algorithm can adaptively adjust the value of the clamping force applied to the front and rear wheels.

[0043] The steps of the adaptive algorithm are as follows:

[0044] S1. As Figure 2 As shown, the force analysis of the rail-mounted inspection robot when climbing a slope is as follows, and the balance equation of the robot's gravity components at the front and rear wheels is listed:

[0045] ;

[0046] in, G For the weight of the robot, F GF , F GR These are the components of the force exerted by the ground wire on the front and rear wheels as it overcomes the robot's gravity. L F , L R These are the distances from the center of gravity along the line connecting the front and rear wheels to the front and rear wheels, respectively. Let be the track slope. By processing the balance equations for the front and rear wheel components, we obtain:

[0047] ;

[0048] Therefore, we can obtain:

[0049] ;

[0050] To apply a clamping force to prevent slippage of both the front and rear drive wheels, the following conditions must be met:

[0051] ;

[0052] in, The coefficient of friction of the track. F NF , F NR These are the clamping forces corresponding to the front and rear wheels, respectively.

[0053] By calculating the above non-slip conditions, the range of values ​​for the clamping forces of the front and rear wheels can be obtained:

[0054] ;

[0055] S2. Based on the range of clamping forces for the front and rear wheels obtained in Step 1, multiply the minimum value by a redundancy coefficient. The redundancy coefficient ranges from 1.05 to 1.4, with a value of 1.1 yielding better results. The actual clamping force applied to the front and rear wheels is then determined as follows:

[0056] ;

[0057] As can be seen from the above formula, except for the slope, the other parameters are fixed parameters of the robot or the track itself.

[0058] S3. Let the slope at the current moment be... The minimum value of the corresponding front wheel clamping force is F NF1 The corresponding minimum value of the rear wheel clamping force is F NR1 Compare the corresponding front wheel clamping force value with the actual front wheel clamping force value. When the corresponding front wheel clamping force value is greater than or equal to the actual front wheel clamping force value, that is:

[0059] ;

[0060] Update the actual clamping force value of the front wheels:

[0061] ;

[0062] When the corresponding rear wheel clamping force value is greater than or equal to the actual rear wheel clamping force value, that is:

[0063] ;

[0064] Update the actual clamping force value of the rear wheels:

[0065] .

[0066] By repeating the above steps, precise adaptive control of the clamping force can be achieved.

[0067] The beneficial effects of this invention are: it provides different clamping forces to the front and rear wheels according to the changes in slope, making the distribution of clamping forces between the front and rear wheels more reasonable, improving climbing efficiency, reducing energy loss, and extending the service life of the drive wheels.

Claims

1. An intelligent control method for climbing control of a hanging rail inspection robot, applied to the hanging rail inspection robot, characterized in that: The process includes the following steps: The rail-mounted robot uses an intelligent algorithm to determine the clamping force value to be applied to the front and rear wheels based on the current slope information, and then applies the clamping force of that value to the front and rear wheels; The intelligent algorithm is an adaptive algorithm that uses slope information as an input variable to adaptively adjust the value of the clamping force applied to the front and rear wheels. The implementation steps of the adaptive algorithm are as follows: S1. Based on the slope information, and combined with the center of gravity height, weight and track friction coefficient of the rail-mounted inspection robot, the force balance and torque of the rail-mounted inspection robot are analyzed, and the range of values ​​of the front and rear wheel clamping forces under the slope is calculated. In step S1, when climbing a slope, the force analysis of the rail-mounted inspection robot is as follows, and the balance equation of the robot's gravity components at the front and rear wheels is listed: （1）； wherein, G is the weight of the robot, F GF , F GR are the components of the ground wire acting on the front and rear wheels to overcome the robot's gravity, respectively, LF , LR are the distances from the center of gravity to the front and rear wheels in the direction of the line connecting the front and rear wheels, respectively, H is the height of the center of gravity, is the slope of the track, and the balance equation for the front and rear wheel components is given by: （2）； Therefore, we can obtain: （3）； To apply a clamping force to prevent slippage of both the front and rear drive wheels, the following conditions must be met: （4）； in, The coefficient of friction of the track. F NF , F NR These are the clamping forces corresponding to the front and rear wheels, respectively. S2. Multiply the minimum value of the corresponding front and rear wheel clamping forces by the redundancy coefficient to obtain the value of the actual clamping force applied to the front and rear wheels; S3. Compare the minimum value of the corresponding front and rear wheel clamping force obtained in real time in S1 with the actual value of the front and rear wheel clamping force. When the minimum value of the corresponding front wheel clamping force is greater than the actual value of the front wheel clamping force, multiply the minimum value of the corresponding front wheel clamping force by a redundancy coefficient to obtain the value of the actual clamping force applied to the front wheel. When the minimum value of the corresponding rear wheel clamping force is greater than the actual value of the rear wheel clamping force, multiply the minimum value of the corresponding rear wheel clamping force by a redundancy coefficient to obtain the value of the actual clamping force applied to the rear wheel. S4. Repeat S3; The above steps enable precise clamping force control.

2. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 1, characterized in that: The redundancy coefficient is 1.05 to 1.

4.

3. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 1, characterized in that: The redundancy coefficient is 1.

1.

4. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 1, characterized in that: The non-slip condition is calculated to obtain the corresponding range of clamping forces for the front and rear wheels: （5）。 5. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 4, characterized in that: In step S2, based on the range of clamping forces for the front and rear wheels, the actual clamping force applied to the front and rear wheels is determined as follows: （6）； As can be seen from the above formula, apart from the slope, the other parameters are inherent to the robot or the track itself.

6. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 5, characterized in that: In step S3, let the slope at the current moment be... The minimum value of the corresponding front wheel clamping force is F NF1 The corresponding minimum value of the rear wheel clamping force is F NR1 Compare the corresponding front wheel clamping force value with the actual front wheel clamping force value. When the corresponding front wheel clamping force value is greater than or equal to the actual front wheel clamping force value, that is: （7）； Update the actual clamping force value of the front wheels: （8）。 7. The intelligent control method for slope climbing control of the rail-mounted inspection robot according to claim 5, characterized in that: In step S3, let the slope at the current moment be... The minimum value of the corresponding front wheel clamping force is F NF1 The corresponding minimum value of the rear wheel clamping force is F NR1 Compare the corresponding rear wheel clamping force value with the actual rear wheel clamping force value. When the corresponding rear wheel clamping force value is greater than or equal to the actual rear wheel clamping force value, that is: （9）； Update the actual clamping force value of the rear wheel: （10）。

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