CN112287564A - Electrode array optimization method based on goblet sea squirt group algorithm - Google Patents

Electrode array optimization method based on goblet sea squirt group algorithm Download PDF

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CN112287564A
CN112287564A CN202011311093.1A CN202011311093A CN112287564A CN 112287564 A CN112287564 A CN 112287564A CN 202011311093 A CN202011311093 A CN 202011311093A CN 112287564 A CN112287564 A CN 112287564A
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蒋毅
许源
梁运华
刘功能
郭奉仁
李泽文
王梓糠
尹骏刚
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State Grid Corp of China SGCC
State Grid Hunan Electric Power Co Ltd
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Abstract

The invention discloses an electrode array optimization method based on a goblet sea squirt group algorithm, which comprises the steps of taking the set number of electrodes as the dimension of a search space of the goblet sea squirt group, taking the arrangement space of the electrode array as the set search space of the goblet sea squirt group, utilizing iteration of the goblet sea squirt group algorithm until the set target is met or the iteration reaches the set times, outputting the final food position of the goblet sea squirt group, and taking the final food position as the arrangement position of the electrode array to complete optimization. The electrode array optimization method based on the goblet sea squirt group algorithm has the advantages of simplicity, practicability, small calculated amount, high optimization speed, high efficiency and the like.

Description

Electrode array optimization method based on goblet sea squirt group algorithm
Technical Field
The invention relates to the technical field of electrode detection, in particular to an electrode array optimization method based on a goblet sea squirt group algorithm.
Background
Personnel such as overhaul, pretest of electric power trade work in the high-voltage field, often meet the situation of operation scope peripheral equipment live working, have the hidden danger that safe distance is not enough. The common near-electricity alarm device is difficult to accurately alarm in a complex electromagnetic environment. The near-electricity alarm device based on the multiple electrodes has the advantages of high spatial resolution of electric field signals, strong anti-interference capability and the like, and can directionally detect whether equipment is electrified or not through the electrode array, so that the problems of high false alarm rate and the like of a common near-electricity alarm device are solved.
The multi-electrode spatial distribution and excitation mode is the technical key of the near-electricity alarm device, and the near-electricity alarm device is preferably optimally designed by adopting an intelligent algorithm. Intelligent algorithms are widely used in the engineering field for the solution of optimization problems, in particular non-linear optimization problems. In recent years, intelligent algorithms are applied to various sensor array designs due to the efficiency advantage of solving the nonlinear optimization problem, and genetic algorithms, particle swarm algorithms and the like are widely applied. However, the optimization process for a complex electrode array model may take several hours or even longer, and the computational cost is extremely large.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art and provide an electrode array optimization method based on the goblet sea squirt group algorithm, which is simple and practical, has small calculated amount, high optimization speed and high efficiency.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
an electrode array optimization method based on a goblet sea squirt group algorithm is characterized in that a set electrode number is used as a dimension of a goblet sea squirt group search space, an electrode array arrangement space is used as a set search space of the goblet sea squirt group, iteration is performed by using the goblet sea squirt group algorithm until a set target is met or the iteration reaches a set number of times, a final food position of the goblet sea squirt group is output and is used as an arrangement position of an electrode array, and optimization is completed.
The process of utilizing the goblet sea squirt group algorithm to iterate until the set target is met comprises the following steps:
s1: initializing the individual number N of the goblet sea squirt group as 3N +1, wherein N is a natural number, taking the electrode number as the dimension number D of the search space, and setting the iteration number Tmax(ii) a Initializing a population to
Figure BDA0002789862080000011
S2: calculating the fitness of each individual of the goblet sea squirt group, taking the individual with the highest fitness as food, and dividing the rest individuals into n pilots, n trackers and n backers;
s3: updating the pilot position as follows:
Figure BDA0002789862080000021
wherein,
Figure BDA0002789862080000022
the position of the ith navigator goblet ascidian individual in the jth dimension, ubjAnd lbjRespectively representing a search upper limit and a search lower limit in a j-dimension search space; fjIs the position of the food in the j-dimensional space, c2And c3Is the interval [0,1]Internally generated random numbers; parameter c1Is defined as:
Figure BDA0002789862080000023
t is the current iteration number, TmaxIs the maximum iteration number;
s4: updating the tracker position as follows:
Figure BDA0002789862080000024
in the formula,
Figure BDA0002789862080000025
for the ith tracker to track the position of the individual of ascidians of goblet in the jth dimension,
Figure BDA0002789862080000026
is the symbiotic quantity; b is a benefit parameter, and 1 or 2 is randomly selected; r is [0,1 ]]A random number of intervals;
s5: the rescuer location update is:
Figure BDA0002789862080000027
Figure BDA0002789862080000028
in the formula,
Figure BDA0002789862080000029
the position of the ith person of the eschewed sea squirt in the jth dimension space is represented by t, which is the current iteration number; t ismaxIs the maximum iteration number;
s6: repeating the steps S2-S5 until the iteration number reaches TmaxOr the food suitability value reaches a set termination threshold.
When updating the position of the ith tracker goblet ascidian individual in the jth dimension space, the position of the ith tracker goblet ascidian individual before updating in the jth dimension space is stored as
Figure BDA00027898620800000210
And determine
Figure BDA00027898620800000211
And
Figure BDA00027898620800000212
the degree of adaptability is good or bad
Figure BDA00027898620800000213
Is superior to
Figure BDA00027898620800000214
Then, the position of the ith tracker goblet individual in the jth dimension space is updated again to
Figure BDA00027898620800000215
The goblet sea squirt group individual also comprises a plurality of rescuers, and the position of the rescuers is updated as follows:
Figure BDA00027898620800000216
Figure BDA00027898620800000217
in the formula,
Figure BDA0002789862080000031
the position of the ith person of the eschewed sea squirt in the jth dimension space is represented by t, which is the current iteration number; t ismaxIs the maximum number of iterations.
The arrangement space of the target electrode array is a concentric electrode array, the target is set to be the minimum peak sidelobe level, and the individual fitness of each goblet ascidian is obtained by the following operation:
Figure BDA0002789862080000032
Figure BDA0002789862080000033
where theta is the angle from the normal,
Figure BDA0002789862080000034
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure BDA0002789862080000035
the feeding amplitude is that the electrodes I (n, m) are excited simultaneously, and psi (n, m) is the included angle of the electrodes and the x axis.
The target electrode array arrangement space is a rectangular electrode array, the target is set to be the minimum peak sidelobe level, and the individual fitness of each goblet ascidian is obtained by the following operation:
Figure BDA0002789862080000036
Figure BDA0002789862080000037
where theta is the angle from the normal,
Figure BDA0002789862080000038
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure BDA0002789862080000039
pmxas position of the electrode in the x-direction, pmyThe position of the electrode in the y direction, and the feeding amplitude is I (n, m), and the electrodes are excited simultaneously.
Compared with the prior art, the invention has the advantages that:
the invention discloses an electrode array optimization method based on a goblet sea squirt group algorithm, which is characterized in that the set electrode number is used as the dimension of a search space of the goblet sea squirt group, the electrode array arrangement space is used as the set search space of the goblet sea squirt group, iteration is carried out by utilizing the goblet sea squirt group algorithm until the set target is met or the iteration reaches the set times, the final food position of the goblet sea squirt group is output and is used as the arrangement position of an electrode array, and the optimization is completed. The optimization method has simple steps and is easy to realize, the solving precision can meet the requirement, the convergence speed is high, and the exploration range cannot fall into the local optimal solution, so that the required calculated amount is greatly reduced, the time required by the optimization process is shortened, and the time and the cost are saved while the performance of the electrode array is improved.
Drawings
FIG. 1 is a diagram of a concentric electrode array obtained by the electrode array optimization method based on the goblet sea squirt group algorithm according to the present invention;
fig. 2 is a diagram of the detection obtained by the electrode array shown in fig. 1.
Detailed Description
In order to facilitate an understanding of the invention, the invention will be described more fully and in detail below with reference to the accompanying drawings and preferred embodiments, but the scope of the invention is not limited to the specific embodiments below.
Example (b):
in the method for optimizing the electrode array based on the goblet ascidian group algorithm of this embodiment, the set number of electrodes is used as the dimension of the search space of the goblet ascidian group, the arrangement space of the electrode array is used as the set search space of the goblet ascidian group, iteration is performed by using the goblet ascidian group algorithm until the set target is met or the iteration reaches the set number of times, the final food position of the goblet ascidian group is output and used as the arrangement position of the electrode array, and the optimization is completed. The optimization method has simple steps and is easy to realize, the solving precision can meet the requirement, the convergence speed is high, and the exploration range cannot fall into the local optimal solution, so that the required calculated amount is greatly reduced, the time required by the optimization process is shortened, and the time and the cost are saved while the performance of the electrode array is improved.
In this embodiment, the concentric electrode array is optimized, and the main lobe area of the directional diagram is constrained to be
Figure BDA0002789862080000041
The target is set to minimize the peak sidelobe level, the initial target value is set to-15 dB, and if the set target value is met before the maximum number of iterations is reached, the target value is lowered by 0.5 dB.
The process of utilizing the goblet sea squirt group algorithm to iterate until the set target is met comprises the following steps:
s1: the number N of initialized goblet sea squirt groups is 3N +1, N is a natural number, N generally ranges from 50 to 100, 61 in the present embodiment, the number of electrodes is used as the dimension number D of the search space, 24 in the present embodiment, and the iteration number T is setmax500; initializing a population to
Figure BDA0002789862080000042
Initializing coordinates of each electrode in population individuals
Figure BDA0002789862080000043
Wherein theta is [0,2 pi ]]And a plurality of electrodes are arranged along the three concentric circular ring arrays, and the sub-distance between adjacent electrodes on the same ring is larger than a set distance.
S2: calculating the fitness of each individual of the goblet sea squirt group:
Figure BDA0002789862080000044
Figure BDA0002789862080000045
where theta is the angle from the normal,
Figure BDA0002789862080000051
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure BDA0002789862080000052
the feeding amplitude is that all electrodes I (n, m) are excited simultaneously, psi (n, m) is the included angle between the electrode and the x axis;
taking the individual with the maximum fitness as food, and dividing the rest individuals into n pilots, n trackers and n backers;
s3: updating the pilot position as follows:
Figure BDA0002789862080000053
wherein,
Figure BDA0002789862080000054
the position of the ith navigator goblet ascidian individual in the jth dimension, ubjAnd lbjRespectively the upper limit and the lower limit of the search in the j-th dimension of the search space, and the coordinates of the search space can be determined according to
Figure BDA0002789862080000055
When the upper limit is obtained, m is 3, and the lower limit is obtained, m is 1; fjIs the position of the food in the j-dimensional space, c2And c3Is the interval [0,1]Internally generated random numbers; parameter c1Is defined as:
Figure BDA0002789862080000056
t is the current iteration number, TmaxIs the maximum iteration number;
s4: updating the tracker position as follows:
Figure BDA0002789862080000057
in the formula,
Figure BDA0002789862080000058
for the ith tracker to track the position of the individual of ascidians of goblet in the jth dimension,
Figure BDA0002789862080000059
is the symbiotic quantity; b is a benefit parameter, and 1 or 2 is randomly selected; r is [0,1 ]]A random number of intervals; when updating the position of the ith tracker goblet ascidian individual in the jth dimension space, the position of the ith tracker goblet ascidian individual before updating in the jth dimension space is stored as
Figure BDA00027898620800000510
And determine
Figure BDA00027898620800000511
And
Figure BDA00027898620800000512
the degree of adaptability is good or bad
Figure BDA00027898620800000513
Is superior to
Figure BDA00027898620800000514
Then, the position of the ith tracker goblet individual in the jth dimension space is updated again to
Figure BDA00027898620800000515
S5: the rescuer location update is:
Figure BDA00027898620800000516
Figure BDA0002789862080000061
in the formula,
Figure BDA0002789862080000062
for ith person of rescue goblet in jth dimensionThe position of the space, t is the current iteration number; t ismaxIs the maximum number of iterations. The method has the advantages that the cosine function is introduced by the backers, so that the updating mode of the backers is more flexible, the position updating distance is totally increased by adding 1, and the distance is not too large due to the fact that the maximum value of the cosine function is 1, so that the global search and the local search of a group of the backers are balanced. The pilot, the follower and the back-up person are beneficial to improving the exploration performance of the algorithm and the ability of jumping out of local optimum in the later period to a certain extent.
S6: repeating the steps S2-S5 until the iteration number reaches TmaxOr the food suitability value reaches a set termination threshold.
And then, the food position can be output as an electrode arrangement position, and the electrode array can meet the target requirement by arranging the electrodes according to the position. Fig. 1 is the optimized electrode array pattern, from which the detection map shown in fig. 2 is obtained, with a peak side lobe level of-17.3 dB and a narrower main lobe.
In this embodiment, when the target electrode array arrangement space is a rectangular electrode array, the target is set to minimize the peak sidelobe level, and the fitness of each individual ascidian is obtained by the following operation:
Figure BDA0002789862080000063
Figure BDA0002789862080000064
where theta is the angle from the normal,
Figure BDA0002789862080000065
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure BDA0002789862080000066
pmxas position of the electrode in the x-direction, pmyThe position of the electrode in the y direction, and the feeding amplitude is I (n, m), and the electrodes are excited simultaneously.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-described embodiments. It should be apparent to those skilled in the art that modifications and variations can be made without departing from the technical spirit of the present invention.

Claims (5)

1. An electrode array optimization method based on a goblet sea squirt group algorithm is characterized in that: and (3) taking the set number of electrodes as the dimension of the search space of the goblet sea squirt group, taking the electrode array arrangement space as the set search space of the goblet sea squirt group, iterating by using the goblet sea squirt group algorithm until the set target is met or the iteration reaches the set times, outputting the final food position of the goblet sea squirt group, and taking the final food position as the arrangement position of the electrode array to complete optimization.
2. The method of claim 1, wherein the method comprises: the process of utilizing the goblet sea squirt group algorithm to iterate until the set target is met comprises the following steps:
s1: initializing the individual number N of the goblet sea squirt group as 3N +1, wherein N is a natural number, taking the electrode number as the dimension number D of the search space, and setting the iteration number Tmax(ii) a Initializing a population to
Figure FDA0002789862070000011
S2: calculating the fitness of each individual of the goblet sea squirt group, taking the individual with the highest fitness as food, and dividing the rest individuals into n pilots, n trackers and n backers;
s3: updating the pilot position as follows:
Figure FDA0002789862070000012
wherein,
Figure FDA0002789862070000013
the position of the ith navigator goblet ascidian individual in the jth dimension, ubjAnd lbjRespectively representing a search upper limit and a search lower limit in a j-dimension search space; fjIs the position of the food in the j-dimensional space, c2And c3Is the interval [0,1]Internally generated random numbers; parameter c1Is defined as:
Figure FDA0002789862070000014
t is the current iteration number, TmaxIs the maximum iteration number;
s4: updating the tracker position as follows:
Figure FDA0002789862070000015
in the formula,
Figure FDA0002789862070000016
for the ith tracker to track the position of the individual of ascidians of goblet in the jth dimension,
Figure FDA0002789862070000017
is the symbiotic quantity; b is a benefit parameter, and 1 or 2 is randomly selected; r is [0,1 ]]A random number of intervals;
s5: the rescuer location update is:
Figure FDA0002789862070000018
Figure FDA0002789862070000019
in the formula,
Figure FDA00027898620700000110
the position of the ith person of the eschewed sea squirt in the jth dimension space is represented by t, which is the current iteration number; t ismaxIs the maximum iteration number;
s6: repeating the steps S2-S5 until the iteration number reaches TmaxOr the food suitability value reaches a set termination threshold.
3. The method of claim 2, wherein the method comprises: when updating the position of the ith tracker goblet ascidian individual in the jth dimension space, the position of the ith tracker goblet ascidian individual before updating in the jth dimension space is stored as
Figure FDA0002789862070000021
And determine
Figure FDA0002789862070000022
And
Figure FDA0002789862070000023
the degree of adaptability is good or bad
Figure FDA0002789862070000024
Is superior to
Figure FDA0002789862070000025
Then, the position of the ith tracker goblet individual in the jth dimension space is updated again to
Figure FDA0002789862070000026
4. The method of claim 2, wherein the method comprises: the arrangement space of the target electrode array is a concentric electrode array, the target is set to be the minimum peak sidelobe level, and the individual fitness of each goblet ascidian is obtained by the following operation:
Figure FDA0002789862070000027
Figure FDA0002789862070000028
where theta is the angle from the normal,
Figure FDA0002789862070000029
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure FDA00027898620700000210
the feeding amplitude is that the electrodes I (n, m) are excited simultaneously, and psi (n, m) is the included angle of the electrodes and the x axis.
5. The method of claim 2, wherein the method comprises: the target electrode array arrangement space is a rectangular electrode array, the target is set to be the minimum peak sidelobe level, and the individual fitness of each goblet ascidian is obtained by the following operation:
Figure FDA00027898620700000211
Figure FDA00027898620700000212
where theta is the angle from the normal,
Figure FDA00027898620700000213
is the phase shift of the electrode, j is the imaginary symbol, FmaxIs the main lobe peak value of the concentric circle electrode array, NyNumber of rings arranged for electrodes, NxIs the number of electrodes on the ring, rmRefers to the radius of the nth electrode (n, m) on the mth ring,
Figure FDA00027898620700000214
pmxas position of the electrode in the x-direction, pmyThe position of the electrode in the y direction, and the feeding amplitude is I (n, m), and the electrodes are excited simultaneously.
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KR20180065472A (en) * 2016-12-08 2018-06-18 한국항공우주연구원 Apparatus and method for pattern synthesis of antenna array
CN109873810A (en) * 2019-01-14 2019-06-11 湖北工业大学 A kind of phishing detectin method based on cup ascidian group's algorithm support vector machines
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