An Unmanned Aerial Vehicle Trajectory Planning Method and System for Distribution Network Inspection

Abstract

The present invention provides a method and system for unmanned aerial vehicle (UAV) trajectory planning for distribution network inspection, including: S1 inputting the parameters of the airport, UAV, and tower poles; S2 initializing the inspection duration, duration iteration times, inspection trajectory, inspection record vector, and trajectory iteration times; S3 selecting the next inspection tower pole; S4 calculating the estimated inspection duration of the UAV to the next inspection tower pole and determining whether it meets the power limit. If so, proceed to S5; otherwise, proceed to S6; S5 the UAV returns to the airport for charging, updates the inspection trajectory, restores the inspection duration, and returns to S3; S6 updates the inspection trajectory, inspection duration, and inspection record vector; S7 calculates the sum of the inspection record vectors and determines whether it is equal to 0. If so, proceed to S8; otherwise, return to S3; S8 outputs the inspection trajectory. The present invention maximally considers the power limit on the premise of meeting the minimum inspection requirements of the distribution network, and at the same time achieves the purpose of minimizing the single inspection task cycle of the UAV.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) inspection, and particularly to a UAV trajectory planning method and system for distribution network inspection. Background Art

[0002] UAVs are widely used in the industrial field due to their advantages. Inspection is an essential project for distribution networks, which has the characteristics of long inspection distance, wide coverage area, and remote locations. Traditional manual inspection requires a huge amount of manpower and material resources, and has a high potential risk. To reduce risks and improve inspection efficiency, using UAVs for distribution network inspection has become a feasible solution, which can not only avoid the risk factors of manual inspection but also greatly improve the inspection efficiency through the high mobility of UAVs. For UAVs, the biggest factor affecting their inspection efficiency lies in their trajectories. By planning efficient UAV trajectories, the inspection efficiency of distribution networks can be further improved.

[0003] However, the current hardware conditions of UAVs are not sufficient to support long-term flight. One solution is to cooperate with an additional UAV platform and return to the platform for charging multiple times during the inspection process. This charging process will bring additional time costs to the UAV. Therefore, how to reasonably plan its trajectory considering the UAV's power limit has become a difficulty and focus. Summary of the Invention

[0004] The purpose of the present invention is to propose a UAV trajectory planning method and system for distribution network inspection, and reasonably plan its trajectory considering the UAV's power limit.

[0005] To achieve the above object, the technical solution of the method of the present invention is as follows:

[0006] A UAV trajectory planning method for distribution network inspection includes the following steps:

[0007] Step S1: Input the airport coordinates (ω x , ω y ), the number of poles K, the coordinates of each pole (x k , y k ), the UAV speed V, and the UAV endurance time T;

[0008] Step S2: Initialize the inspection duration and the duration iteration count, initialize the inspection trajectory, initialize the inspection record vector, and initialize the trajectory iteration count;

[0009] Step S3: Calculate the effective distance vector between the current position of the UAV and each pole, and select the position i where the smallest numerical element in the effective distance vector is located as the next inspection pole number;

[0010] Step S4: Calculate the estimated inspection duration from the current position of the UAV to the next inspection tower Determine whether the power limit is met If so, proceed to step S5; otherwise, proceed to step S6

[0011] Step S5: The UAV returns to the airport for charging, updates the inspection trajectory, updates the trajectory iteration count, restores the inspection duration, and then returns to step S3

[0012] Step S6: Update the inspection trajectory and inspection duration, update the trajectory iteration count, update the duration iteration count, and update the inspection record vector

[0013] Step S7: Calculate the inspection record vector and N, and determine whether it is equal to 0. If so, proceed to step S8; otherwise, return to step S3

[0014] Step S8: Output the inspection trajectory

[0015] Furthermore, the tower coordinate matrix in S1 is as follows

[0016] M = [x 1 , y 1 ; x 2 , y 2 ;..; x k , y k ;..,; x K , y K

[0017] where M is the tower coordinate matrix, (x k , y k ) is the coordinate of the kth tower, and K is the number of towers

[0018] Furthermore, in step S2, the inspection duration is initialized as follows

[0019]

[0020] where is the inspection duration for the 0th duration iteration

[0021] The duration iteration count is initialized as follows

[0022] m = 0

[0023] where m is the duration iteration count

[0024] The inspection trajectory is initialized as follows

[0025] Traj 0 = [ω x , ω y ​​

[0026] Among them, Traj 0 is the inspection trajectory of the 0th trajectory iteration, (ω x , ω y ) is the airport coordinate;

[0027] The trajectory iteration count is initialized as:

[0028] j = 0

[0029] Among them, j is the trajectory iteration count.

[0030] The inspection record vector is initialized as:

[0031] L = [1, 2,..L(i).., K]

[0032] Among them, L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and K is the number of tower poles.

[0033] Furthermore, step S3 includes the following sub-steps:

[0034] Step 3.1: Calculate the distance vector D

[0035]

[0036] Among them, D is the distance vector, Traj j is the inspection trajectory of the j-th trajectory iteration, Traj j (end, 1:2) is the coordinate composed of the first to second column elements of the last row of the inspection trajectory of the j-th trajectory iteration, j is the trajectory iteration count, |||| 2 is the two-norm operation of the vector;

[0037] Step 3.2: Calculate the effective distance vector

[0038]

[0039] Among them, is the effective distance vector, D is the distance vector, L is the inspection record vector, == is the operation to extract the positions where the element values are equal, L == 0 is to extract the positions where the elements in the inspection record vector L are equal to 0, and D(L == 0) is to correct the distances at the positions corresponding to the elements in the inspection record vector L that are equal to 0 in the distance vector D to 10 9 ;

[0040] The position i of the element with the minimum value in the effective distance vector is the next inspection tower pole number.

[0041] Furthermore, the estimated inspection duration in step S4 is:

[0042]

[0043] Among them, is the estimated inspection duration, is the inspection duration of the m-th duration iteration, m is the number of duration iterations, τ is the inspection time for each tower pole, (ω x , ω y ) is the airport coordinate, (x i , y i ) is the coordinate of the i-th tower pole, and i is the number of the next inspection tower pole.

[0044] Furthermore, the updated inspection trajectory in step S5 is:

[0045] Traj j+1 = [Traj j ; ω x , ω k

[0046] Among them, Traj j is the inspection trajectory of the j-th trajectory iteration, j is the number of trajectory iterations, [] is the vector combination operation;

[0047] The updated number of trajectory iterations in step S5 is:

[0048] j = j + 1

[0049] Among them, j is the number of trajectory iterations.

[0050] The restored inspection duration in step 5 is:

[0051]

[0052] Among them, is the inspection duration, and m is the number of duration iterations.

[0053] Furthermore, the updated inspection trajectory in step S6 is:

[0054] Traj j+1 = [Traj j ; x i , y i

[0055] Among them, Traj j is the inspection trajectory of the j-th trajectory iteration, j is the number of trajectory iterations, (x i , y i ) is the coordinate of the i-th tower pole, i is the number of the next inspection tower pole, and [] is the vector combination operation;

[0056] The updated number of trajectory iterations in step S6 is:​​

[0057] j = j + 1

[0058] Where j is the number of trajectory iterations.

[0059] The updated inspection duration is:

[0060]

[0061] Where is the inspection duration of the m-th duration iteration, m is the number of duration iterations, τ is the inspection time of the tower pole, V is the UAV speed, Traj j is the inspection trajectory of the j-th trajectory iteration, Traj j (end,1:2) is the coordinate composed of the first to second column elements of the last row of the inspection trajectory of the j-th trajectory iteration, j is the number of trajectory iterations, |||| 2 is the two-norm operation of the vector, (x i , y i ) is the coordinate of the i-th tower pole, i is the number of the next tower pole to be inspected;

[0062] The updated number of duration iterations is:

[0063] m = m + 1

[0064] Where m is the number of duration iterations.

[0065] The updated inspection record vector described in step 6 is:

[0066] L(i) = 0

[0067] Where L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and i is the number of the next tower pole to be inspected.

[0068] Furthermore, the calculation of the inspection record vector sum described in step S7:

[0069] N = sum(L)

[0070] Where N is the inspection record vector sum, L is the inspection record vector, and sum() is the operation of summing all elements.

[0071] On the other hand, the present invention provides a UAV trajectory planning system for distribution network inspection, including:

[0072] Module 1, which is used to input the airport coordinates (ω x , ω y ), the number of tower poles K, the coordinates of each tower pole (x k , y k ), the UAV speed V, and the UAV endurance time T;

[0073] Module 2, which is used to initialize the trajectory iteration times according to the inspection duration, initialize the inspection trajectory, initialize the inspection record vector, and initialize the trajectory iteration times;

[0074] Module 3, which is used to calculate the effective distance vector between the current position of the UAV and each tower pole, and select the position i where the minimum numerical element in the effective distance vector is located as the next inspection tower pole number;

[0075] Module 4, which is used to calculate the estimated inspection duration from the current position of the UAV to the next inspection tower pole Judge whether the power limit is satisfied If so, enter Module 5; otherwise, enter Module 6;

[0076] Module 5, which is used for the UAV to return to the airport for charging, update the inspection trajectory, update the trajectory iteration times, restore the inspection duration, and then return to step S3;

[0077] Module 6, which is used to update the inspection trajectory and inspection duration, update the trajectory iteration times, update the duration iteration times, and update the inspection record vector;

[0078] Module 7, which is used to calculate the inspection record vector and N, and judge whether it is equal to 0. If so, enter Module 8; otherwise, return to Module 3;

[0079] Module 8, which is used to output the inspection trajectory.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] Aiming at the deficiencies of the existing large-scale distribution network inspection strategy and the on-demand inspection requirements of the distribution network based on UAVs, the present invention provides a UAV trajectory planning method for distribution network inspection, aiming to reduce the manual inspection cost and improve the distribution network inspection efficiency. On the premise of meeting the distribution network inspection requirements, the invention designs the UAV trajectory by using an improved greedy algorithm and a corresponding trajectory solution scheme, and tries to minimize the single inspection task cycle of the inspection UAV on the premise of meeting the distribution network inspection requirements.

[0082] The present invention proposes a method for unmanned aerial vehicle (UAV) trajectory planning for distribution network inspection. This trajectory planning strategy enables the inspection UAV to perform on-demand inspections of the distribution network based on inspection requirements and obtain the system parameters of the distribution network and the inspection UAV. A model is built for the distribution network composed of towers, and a motion plan for the inspection UAV is designed by improving the greedy algorithm to achieve on-demand inspections of the distribution network. This problem is solved with the inspection requirements of distribution towers as the constraint and the goal of minimizing the single inspection mission cycle of the inspection UAV, and finally an efficient mission trajectory for the single inspection mission of the UAV is obtained. The mission trajectory of the inspection UAV maximally considers the power limit on the premise of meeting the minimum inspection requirements of the distribution network, and at the same time achieves the goal of minimizing the single inspection mission cycle of the UAV. Description of the Drawings

[0083] Figure 1 It is the algorithm flowchart of the embodiment of the present invention;

[0084] Figure 2 It is a schematic diagram of the distribution network, UAV and airport in the embodiment of the present invention; Detailed Embodiments

[0085] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0086] Embodiment 1

[0087] Combined with the attached Figure 1 The technical solution of the method of the present invention is a method for UAV trajectory planning for distribution network inspection, and the specific steps are as follows:

[0088] Step S1: Input the airport coordinates (ω x , ω y ) = (0, 0), the number of towers K = 9, the coordinates of each tower (x k , y k ), the UAV speed V = 1 m / s, and the UAV endurance time T = 70 s;

[0089] Step S2: Initialize the inspection duration and the number of duration iterations, initialize the inspection trajectory, initialize the inspection record vector, and initialize the number of trajectory iterations;

[0090] Step S3: Calculate the effective distance vectors between the current position of the UAV and each tower pole, and select the position i where the smallest numerical element in the effective distance vectors is located as the number of the next inspection tower pole;

[0091] Step S4: Calculate the estimated inspection duration from the current position of the UAV to the next inspection tower pole Judge whether the power limit is satisfied If so, go to Step S5; otherwise, go to Step S6;

[0092] Step S5: The UAV returns to the airport for charging, updates the inspection trajectory, updates the trajectory iteration count, restores the inspection duration, and then returns to Step S3;

[0093] Step S6: Update the inspection trajectory and inspection duration, update the trajectory iteration count, update the duration iteration count, and update the inspection record vector;

[0094] Step S7: Calculate the inspection record vector and N, and judge whether it is equal to 0. If so, go to Step S8; otherwise, return to Step S3;

[0095] Step S8: Output the inspection trajectory.

[0096] Furthermore, the tower pole coordinate matrix in S1 is:

[0097] M = [x 1 , y 1 ; x 2 , y 2 ;..; x k , y k ;..,; x K , y K

[0098] = [-20, -30; 30, -10; -10, -20; 20, 10; -10, -10; -10, 20; -10, 30; 10, 0; -15, 35]

[0099] where M is the tower pole coordinate matrix, (x k , y k ) is the coordinate of the k-th tower pole, and K = 9 is the number of tower poles.

[0100] Furthermore, the inspection duration is initialized in Step S2 as:

[0101]

[0102] where is the inspection duration of the 0th duration iteration.

[0103] The duration iteration count is initialized as: ​

[0104] m = 0

[0105] Wherein, m is the duration iteration count.

[0106] Initialize the inspection trajectory as:

[0107] Traj 0 = [ω x , ω y

[0108] Wherein, Traj 0 is the inspection trajectory of the 0th trajectory iteration, (ω x , ω y ) is the airport coordinate;

[0109] Initialize the trajectory iteration count as:

[0110] j = 0

[0111] Wherein, j is the trajectory iteration count.

[0112] Initialize the inspection record vector as:

[0113] L = [1, 2,..L(i).., K]

[0114] Wherein, L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and K is the number of tower poles.

[0115] Furthermore, step S3 includes the following sub-steps:

[0116] Step 3.1: Calculate the distance vector D

[0117]

[0118] Wherein, D is the distance vector, Traj j is the inspection trajectory of the j-th trajectory iteration, Traj j (end, 1:2) is the coordinate composed of the first to second column elements of the last row of the inspection trajectory of the j-th trajectory iteration, j is the trajectory iteration count, |||| 2 is the two-norm operation of the vector;

[0119] Step 3.2: Calculate the effective distance vector

[0120]

[0121] Wherein, ​Let the effective distance vector be \(V\), the distance vector be \(D\), and the inspection record vector be \(L\). The operation of extracting the positions where the element values are equal is denoted as \(==\). \(L == 0\) extracts the positions of the elements in the inspection record vector \(L\) that are equal to 0. \(D(L == 0)\) modifies the distances at the positions in the distance vector \(D\) corresponding to the positions of the elements in the inspection record vector \(L\) that are equal to 0 to 10. 9 ;

[0122] Step 3.3: The position \(i\) of the element with the minimum value in the effective distance vector is the number of the next inspection tower pole.

[0123] Furthermore, the estimated inspection duration in step S4 is:

[0124]

[0125] where, is the estimated inspection duration, is the inspection duration of the \(m\)-th duration iteration, \(m\) is the number of duration iterations, \(\tau = 10s\) is the inspection time for each tower pole, \(V = 1m / s\) is the UAV speed, \((\omega x ,\omega y ) is the airport coordinate, \((x i ,y i ) is the coordinate of the \(i\)-th tower pole, and \(i\) is the number of the next inspection tower pole.

[0126] Furthermore, the updated inspection trajectory in step S5 is:

[0127] Traj j+1 = [Traj j ; \omega x ,\omega k

[0128] where, Traj j is the inspection trajectory of the \(j\)-th trajectory iteration, \(j\) is the number of trajectory iterations, and [] is the vector combination operation;

[0129] The updated number of trajectory iterations in step S5 is:

[0130] j = j + 1

[0131] where, \(j\) is the number of trajectory iterations.

[0132] The restored inspection duration in step 5 is:

[0133]

[0134] where, is the inspection duration, and \(m\) is the number of duration iterations.

[0135] Furthermore, the updated inspection trajectory in step S6 is:​

[0136] Traj j+1 = [Traj j ; x i , y i

[0137] where Traj j is the inspection trajectory of the j-th trajectory iteration, j is the number of trajectory iterations, (x i , y i ) is the coordinate of the i-th tower pole, i is the number of the next inspection tower pole, and [] represents vector combination operation;

[0138] In the step S6, the updated number of trajectory iterations is:

[0139] j = j + 1

[0140] where j is the number of trajectory iterations.

[0141] The updated inspection duration is:

[0142]

[0143] where is the inspection duration of the m-th duration iteration, m is the number of duration iterations, τ = 10s is the tower pole inspection time, V = 1m / s is the UAV speed, Traj j is the inspection trajectory of the j-th trajectory iteration, Traj j (end, 1:2) is the coordinate composed of the first to second column elements of the last row of the inspection trajectory of the j-th trajectory iteration, j is the number of trajectory iterations, |||| 2 is the two-norm operation of the vector, (x i , y i ) is the coordinate of the i-th tower pole, i is the number of the next inspection tower pole;

[0144] The updated number of duration iterations is:

[0145] m = m + 1

[0146] where m is the number of duration iterations.

[0147] The updated inspection record vector in step 6 is:

[0148] L(i) = 0

[0149] where L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and i is the number of the next inspection tower pole.

[0150] Furthermore, the calculation of the sum of the inspection record vectors in step S7:

[0151] ​N = sum(L)

[0152] Wherein, N is the sum of the inspection record vectors, L is the inspection record vector, and sum() is the summation operation of all elements.

[0153] The final output inspection trajectory is:

[0154] Traj = [0,0; 10,0; 20,10; 30,-10; 0,0; -10,-10; -10,-20; -20,-30; 0,0; -10,20; -10,30; -15,35]

[0155] On the other hand, the present invention provides an unmanned aerial vehicle trajectory planning system for distribution network inspection, including:

[0156] Module 1, which is used to input the airport coordinates (ω x , ω y ), the number of poles K, the coordinates of each pole (x k , y k ), the speed V of the unmanned aerial vehicle, and the endurance time T of the unmanned aerial vehicle;

[0157] Module 2, which is used to initialize the trajectory iteration times according to the inspection duration, initialize the inspection trajectory, initialize the inspection record vector, and initialize the trajectory iteration times;

[0158] Module 3, which is used to calculate the effective distance vector between the current position of the unmanned aerial vehicle and each pole, and select the position i where the smallest numerical element in the effective distance vector is located as the next inspection pole number;

[0159] Module 4, which is used to calculate the estimated inspection duration from the current position of the unmanned aerial vehicle to the next inspection pole Judge whether the power limit is satisfied If so, enter Module 5, otherwise enter Module 6;

[0160] Module 5, which is used for the unmanned aerial vehicle to return to the airport for charging, update the inspection trajectory, update the trajectory iteration times, restore the inspection duration, and then return to step S3;

[0161] Module 6, which is used to update the inspection trajectory and inspection duration, update the trajectory iteration times, update the duration iteration times, and update the inspection record vector;

[0162] Module 7, which is used to calculate the sum N of the inspection record vectors and judge whether it is equal to 0. If so, enter Module 8, otherwise return to Module 3;

[0163] Module 8, which is used to output the inspection trajectory.

[0164] Embodiment 2

[0165] This embodiment provides a UAV trajectory planning system for power distribution network inspection, including:

[0166] Module 1, which is used to input the airport coordinates (ω x , ω y ), the number of poles K, the coordinates of each pole (x k , y k ), the UAV speed V, and the UAV endurance time T;

[0167] Module 2, which is used to initialize the inspection duration, initialize the inspection trajectory, and initialize the inspection record vector;

[0168] Module 3, which is used to calculate the effective distance vector between the current position of the UAV and each pole, and select the position i where the minimum numerical element in the effective distance vector is located as the next inspection pole number;

[0169] Module 4, which is used to calculate the estimated inspection duration from the current position of the UAV to the next inspection pole Judge whether the power limit is satisfied If so, enter Module 5, otherwise enter Module 6;

[0170] Module 5, which is used for the UAV to return to the airport for charging, update the inspection trajectory, restore the inspection duration, and then return to step S3;

[0171] Module 6, which is used to update the inspection trajectory and inspection duration, and update the inspection record vector;

[0172] Module 7, which is used to calculate the sum N of the inspection record vector, and judge whether it is equal to 0. If so, enter Module 8, otherwise return to Module 3;

[0173] Module 8, which is used to output the inspection trajectory.

[0174] Although the preferred examples of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be interpreted to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0175] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

[0176] Other parts not described in detail are all prior arts.

Claims

1. A UAV trajectory planning method for power distribution network inspection, characterized in that: The steps include: Step S1, input airport coordinates (ω x ,ω y ), the number of towers K, the coordinates of each tower (x k ,y k ), UAV speed V and UAV endurance time T; Step S2, initializing the inspection duration and the number of duration iterations, initializing the inspection trajectory, initializing the inspection record vector, and initializing the number of trajectory iterations; Step S3, calculating the effective distance vector between the current position of the drone and each tower, and selecting the position i where the minimum numerical element in the effective distance vector is located as the next inspection tower number; The step S3 includes the following sub-steps: Step 3.1: Calculate the distance vector D Where D is the distance vector, Traj j is the inspection trajectory of the jth trajectory iteration, Traj j (end,1:2) is the coordinates of the first to second columns of the last row of the inspection trajectory of the jth trajectory iteration, j is the number of trajectory iterations, and ||||2 is the vector bi-norm operation; Step 3.2: Calculate the effective distance vector D(L==0)=10 9 , in, is the effective distance vector, D is the distance vector, L is the inspection record vector, == is the operation of extracting the position of the element with equal value, L == 0 is to extract the position of the element equal to 0 in the inspection record vector L, D(L == 0) is to correct the distance in the distance vector D corresponding to the position of the element equal to 0 in the inspection record vector L to 10 9 ; Step 3.3: The position i where the minimum numerical element in the effective distance vector is located is the number of the next inspection tower; Step S4: Calculate the estimated inspection time from the current position of the drone to the next inspection tower Determine whether the power limit is met If yes, go to step S5, otherwise go to step S6; Step S5: The drone returns to the airport to charge, updates the inspection track, updates the number of track iterations, restores the inspection time, and then returns to step S3; Step S6, update the inspection trajectory and inspection duration, update the trajectory iteration number, update the duration iteration number, and update the inspection record vector; Step S7, calculate the inspection record vector and N, and determine whether it is equal to 0. If so, proceed to step S8, otherwise return to step S3; Step S8: Output the inspection trajectory.

2. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The tower coordinate matrix in S1 is: M=[x1,y1;x2,y2;..;x k ,y k ;..,;x K ,y K ] Where M is the tower coordinate matrix, (x k ,y k ) is the coordinate of the kth tower, and K is the number of towers.

3. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The initial inspection duration in step S2 is: Initialize the inspection trajectory as: Traj0=[ω x ,oh k ] Among them, Traj0 is the inspection trajectory of the 0th trajectory iteration, (ω x ,ω y ) are the airport coordinates; The number of trajectory iterations is initialized to: j＝0 Where, j is the number of trajectory iterations; The inspection record vector is initialized as: L=[1,2,..L(i)..,K] Wherein, L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and K is the number of towers.

4. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The estimated inspection time in step S4 for: in, is the inspection time of the mth time iteration, m is the number of time iterations, τ is the inspection time of each tower, (ω x ,ω y ) is the airport coordinate, (x i ,y i ) is the coordinate of the ith tower, i is the number of the next inspection tower, Traj j is the inspection trajectory of the jth trajectory iteration, Traj j (end,1:2) is the coordinates of the first to second column elements of the last row of the inspection trajectory of the jth trajectory iteration, and j is the number of trajectory iterations.

5. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The inspection trajectory updated in step S5 is: Through j+1 =[Through j ;ω x ,ω y ] Among them, Traj j The jth trajectory iteration is the inspection trajectory, j is the number of trajectory iterations, and [] is the vector combination operation; The restoration inspection duration in step 5 is: in, is the inspection duration; The number of iterations of updating the trajectory in step S5 is: j=j+1 Where j is the number of trajectory iterations.

6. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The step S6 updates the inspection trajectory as follows: Through j+1 =[Through j ;x i ,y i ] Among them, Traj j The jth trajectory iteration is the inspection trajectory, j is the number of trajectory iterations, (x i ,y i ) is the coordinate of the ith tower, i is the number of the next inspection tower, and [] is a vector combination operation; The number of trajectory iterations updated in step S6 is: j=j+1 Where, j is the number of trajectory iterations; The update inspection duration is: in, is the inspection time of the mth time iteration, m is the number of time iterations, τ is the tower inspection time, V is the UAV speed, Traj j is the inspection trajectory of the jth trajectory iteration, Traj j (end,1:2) is the coordinates of the first to second columns of the last row of the inspection trajectory of the jth trajectory iteration, j is the number of trajectory iterations, ||||2 is the vector bi-norm operation, (x i ,y i ) is the coordinate of the ith tower, and i is the number of the next inspection tower; The update duration iteration number is: m=m+1 Among them, m is the number of time iterations; The update inspection record vector described in step 6 is: L(i)=0 Wherein, L is the inspection record vector, L(i) is the i-th element in the inspection record vector, and i is the number of the next inspection tower.

7. The method for UAV trajectory planning for power distribution network inspection according to claim 1 is characterized in that: The step S7 calculates the inspection record vector and: N = sum(L) Wherein, N is the inspection record vector sum, L is the inspection record vector, and sum() is the sum operation of all elements.

8. A UAV trajectory planning system for power distribution network inspection, characterized in that: include: Module 1, which is used to input airport coordinates (ω x ,ω y ), the number of towers K, the coordinates of each tower (x k ,y k ), UAV speed V and UAV endurance time T; Module 2 is used to initialize the inspection time, the number of trajectory iterations, the inspection trajectory, the inspection record vector, and the number of trajectory iterations; Module three is used to calculate the effective distance vector between the current position of the drone and each tower, and select the position i where the minimum numerical element in the effective distance vector is located as the number of the next inspection tower; Module 4 is used to calculate the estimated inspection time from the current position of the drone to the next inspection tower. Determine whether the power limit is met If yes, go to module five, otherwise go to module six; Module 5, which is used for the drone to return to the airport for charging, update the inspection track, update the number of track iterations, restore the inspection time, and then return to step S3; Module six is ​​used to update the inspection trajectory and inspection duration, update the trajectory iteration number, update the duration iteration number, and update the inspection record vector; Module seven is used to calculate the inspection record vector and N, and determine whether it is equal to 0. If so, enter step module eight, otherwise return to module three; Module eight, which is used to output the inspection trajectory; The drone trajectory planning system for power distribution network inspection is used to execute the steps in the drone trajectory planning method for power distribution network inspection described in any one of claims 1-7.

Images