High-efficiency inspecting method for mobile robots based on task planning for heat transfer tubes in a steam generator

doi:10.1007/s11465-022-0741-z

Frontiers of Mechanical Engineering

2023, Vol. 18

Issue (2): 25 https://doi.org/10.1007/s11465-022-0741-z

本期目录

High-efficiency inspecting method for mobile robots based on task planning for heat transfer tubes in a steam generator

Biying XU, Xuehe ZHANG, Yue OU, Kuan ZHANG, Zhenming XING, Hegao CAI, Jie ZHAO, Jizhuang FAN(

)

State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China

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Abstract：

Many heat transfer tubes are distributed on the tube plates of a steam generator that requires periodic inspection by robots. Existing inspection robots are usually involved in issues: Robots with manipulators need complicated installation due to their fixed base; tube mobile robots suffer from low running efficiency because of their structural restricts. Since there are thousands of tubes to be checked, task planning is essential to guarantee the precise, orderly, and efficient inspection process. Most in-service robots check the task tubes using row-by-row and column-by-column planning. This leads to unnecessary inspections, resulting in a long shutdown and affecting the regular operation of a nuclear power plant. Therefore, this paper introduces the structure and control system of a dexterous robot and proposes a task planning method. This method proceeds into three steps: task allocation, base position search, and sequence planning. To allocate the task regions, this method calculates the tool work matrix and proposes a criterion to evaluate a sub-region. And then all tasks contained in the sub-region are considered globally to search the base positions. Lastly, we apply an improved ant colony algorithm for base sequence planning and determine the inspection orders according to the planned path. We validated the optimized algorithm by conducting task planning experiments using our robot on a tube sheet. The results show that the proposed method can accomplish full task coverage with few repetitive or redundant inspections and it increases the efficiency by 33.31% compared to the traditional planning algorithms.

Key words： steam generator transfer tubes mobile robot dexterous structure task planning efficient inspection

收稿日期: 2022-05-06 出版日期: 2023-05-17

Corresponding Author(s): Jizhuang FAN

引用本文:

. [J]. Frontiers of Mechanical Engineering, 2023, 18(2): 25.
Biying XU, Xuehe ZHANG, Yue OU, Kuan ZHANG, Zhenming XING, Hegao CAI, Jie ZHAO, Jizhuang FAN. High-efficiency inspecting method for mobile robots based on task planning for heat transfer tubes in a steam generator. Front. Mech. Eng., 2023, 18(2): 25.

链接本文:

https://academic.hep.com.cn/fme/CN/10.1007/s11465-022-0741-z
https://academic.hep.com.cn/fme/CN/Y2023/V18/I2/25

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Tab.1

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Fig.5

No.	Parameters	Symbol	Influence
1	Distribution of the tube holes	${H o l e (x, y)}$	Robot moving direction
2	Distribution of the plugging holes	${P l u g (x, y)}$	Planned path
3	Distribution of the task holes	${T a s k (x, y)}$	Task planning results
4	Robot maximum translation distance	$S m a x = 6$	Motion speed and accuracy
5	Distribution of the base toes	$L O u t e r$	Robot reachable position
6	Distance between the foot toes	${B a s e (x, y)}$	Tool working space
7	Distance between the tools	$L OutertoTool$	Task planning results
8	Distance from the foot toe to the tool	$k$	Tool working space
9	Robot rotation speed	$C$	Action cost
10	Robot translation speed	$V Rot$	Action cost
11	Robot grasping time	$V Trans$	Action cost
12	Robot releasing time	$T Grasp$	Action cost

Tab.2

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Tab.3

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Abbreviations
ABC	Artificial bee colony optimization
ACO	Ant colony optimization
D?H	Denavit?Hertenbeg
DoF	Degree-of-freedom
IK	Inverse kinematics
NPP	Nuclear power plant
PSO	Particle swarm optimization
SG	Steam generator
TSP	Traveling salesman problem
Variables
a	Rectangular region of width/length
B_Best	Best base position for the current searching region
B_Current	Current base position
Base(x, y)	Distance between the foot toes
C	Robot rotation speed
C_r	Turning cost
C_w	Translation cost
d	Distance between two tube holes
d(cur, next, t)	Heuristic cost function
f (w_j, l_j, k)	Minimum number of tasks to be completed of $V j$
$F D (B)$	Number of different elements in $B$
Hole(x, y)	Distribution of the tube holes
k	Distance from the foot toe to the tool
$l ˉ$	Length of the unassigned work row
$l j$	Length of $V j$
$l max$	Maximum length of the region according to the work matrix
$l s$	Length of the search row
$L Ant (B)$	Total distance of the points in the set $B$
$L Outer$	Distribution of the base toes
$L OutertoTool$	Distance between the tools
$N (w)$	Number of completed tasks
$P l u g (x, y)$	Distribution of the plugging holes
$[q h 1 q h 2 q h 3]$	Robot joint configuration solution
$R m$	Maximum size of the optimal region
$R p$	Configuration matrix
$R p ′$	Intermediate variable to obtain $R p ∗$
$R p ∗$	All matrices that minimize the number of base positions
$S max$	Robot maximum translation distance
$t$	Number of turns
$T Grasp$	Robot releasing time
$T i$	Task tube hole
$T pb$	Optimal work matrix
$T pl$	Length work matrix
$T ps$	Suboptimal work matrix
Task(x, y)	Distribution of the task holes
$V Rot$	Robot translation speed
$V Trans$	Robot grasping time
$V (w)$	Evaluation function of the main working direction
$w j$	Width of $V j$
$(x h, y h)$	Robot base position solution
$? x ?$	Downward rounding function
$α ˉ$	Factor along the length direction
$α 2 k$	Factor along the width direction
$α 2 k ? 1, α 2 k ? 2, . . ., α k + 1$	Factor of the compound direction
$B$	Point set containing n base positions
$T$	Task set
$V j$	Sub-region

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