CN116910667B

CN116910667B - Communication tower abnormal state analysis method and system based on decision algorithm

Info

Publication number: CN116910667B
Application number: CN202311154939.9A
Authority: CN
Inventors: 赵斌; 韩秀娟; 金吉龙; 王彦超
Original assignee: China Tower Co ltd Jilin Branch
Current assignee: China Tower Co ltd Jilin Branch
Priority date: 2023-09-08
Filing date: 2023-09-08
Publication date: 2023-11-21
Anticipated expiration: 2043-09-08
Also published as: CN116910667A

Abstract

The invention provides a communication tower abnormal state analysis method and system based on a decision algorithm, and relates to the technical field of artificial intelligence. According to the method, a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data is obtained, the target iron tower environment data corresponding to a target communication iron tower is analyzed by using the target abnormality analysis model, and a communication iron tower prediction state corresponding to the target communication iron tower is output; reflecting the condition that the state of the target communication tower is abnormal in the communication tower prediction state, and acquiring a target decision algorithm model; and extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing a target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower. Based on the above, the cost of analysis of the abnormal state of the communication tower can be reduced to a certain extent.

Description

Communication tower abnormal state analysis method and system based on decision algorithm

Technical Field

The invention relates to the technical field of artificial intelligence, in particular to a communication tower abnormal state analysis method and system based on a decision algorithm.

Background

The communication iron tower is generally composed of steel components such as a tower body, a platform, a lightning rod, a ladder stand, an antenna support and the like, is subjected to hot galvanizing corrosion prevention treatment, and is mainly used for transmission and emission of microwaves, ultrashort waves and wireless network signals. Because the state of the communication tower directly influences whether communication can be effectively performed, the state of the communication tower needs to be analyzed to determine whether the communication tower is abnormal or not and the type of the abnormality is provided so as to perform reliable maintenance in time, however, in the prior art, the analysis of the state of the communication tower has the problem of relatively high cost.

Disclosure of Invention

Therefore, the invention aims to provide a method and a system for analyzing the abnormal state of the communication tower based on a decision algorithm, so as to reduce the cost of the analysis of the abnormal state of the communication tower to a certain extent.

In order to achieve the above purpose, the embodiment of the present invention adopts the following technical scheme:

a communication tower abnormal state analysis method based on a decision algorithm comprises the following steps:

acquiring a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data, analyzing the target iron tower environment data corresponding to the target communication iron tower by utilizing the target abnormality analysis model, and outputting a communication iron tower prediction state corresponding to the target communication iron tower, wherein the historical iron tower environment data is used for describing the environment where the communication iron tower is located, and the historical communication iron tower abnormality data is used for reflecting whether the state of the communication iron tower is abnormal or not;

The method comprises the steps that the condition that the state of a target communication tower is abnormal is reflected in the predicted state of the communication tower, a target decision algorithm model is obtained, the target decision algorithm model is formed by constructing a decision tree based on historical tower attribute data and corresponding historical tower fault data, and the historical tower attribute data is used for reflecting the dynamic attribute of the communication tower;

extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing the target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower, wherein the target iron tower fault data is used for reflecting abnormal type information of the target communication iron tower in dynamic attribute dimension.

In some preferred embodiments, in the above method for analyzing abnormal states of communication towers based on decision algorithm, the steps of obtaining a target abnormal analysis model trained based on historical tower environment data and corresponding historical communication tower abnormal data, analyzing target tower environment data corresponding to a target communication tower by using the target abnormal analysis model, and outputting a predicted state of the communication tower corresponding to the target communication tower include:

Determining a training iron tower construction data cluster, a training iron tower environment data cluster and suitability data between each training iron tower construction data in the training iron tower construction data cluster and each training iron tower environment data in the training iron tower environment data cluster, wherein the training iron tower construction data are used for reflecting self static attribute information of a training communication iron tower, and the static attribute information at least comprises iron tower coordinate information, iron tower type information and iron tower material information of the training communication iron tower;

the training iron tower construction data and the training iron tower environment data are subjected to key information mining, corresponding iron tower data vectors are output, and based on the suitability data, the training iron tower construction data and the training iron tower environment data are subjected to mapping processing to form corresponding iron tower environment adaptation maps;

in the iron tower environment adaptation map, transmitting and updating the iron tower data vector, and analyzing iron tower environment data differences between training iron tower environment data in the training iron tower environment data cluster;

according to the transmitted iron tower data vector and the iron tower environment data difference, determining adaptive training iron tower environment data corresponding to each training iron tower construction data from the training iron tower environment data cluster;

Optimizing and adjusting the iron tower environment adaptation map based on the adaptation training iron tower environment data to form a corresponding optimized and adjusted iron tower environment adaptation map, expanding the target communication iron tower with the optimized and adjusted iron tower environment adaptation map, and outputting expanded iron tower environment data corresponding to the target communication iron tower;

acquiring a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data, analyzing the target iron tower environment data corresponding to the target communication iron tower and the expanded iron tower environment data by utilizing the target abnormality analysis model, and outputting a communication iron tower prediction state corresponding to the target communication iron tower, wherein the training iron tower construction data cluster comprises target iron tower construction data corresponding to the target communication iron tower, the training iron tower environment data cluster comprises the target iron tower environment data, and the acquisition time of other training iron tower environment data in the training iron tower environment data cluster and the acquisition time of the target iron tower environment data have synchronism.

In some preferred embodiments, in the method for analyzing abnormal states of communication towers based on decision algorithm, the step of determining adaptive training tower environmental data corresponding to each training tower construction data from the training tower environmental data clusters according to the transmitted tower data vector and the tower environmental data difference includes:

Based on the transmitted iron tower data vector, adjusting the iron tower environment adaptation map to form a corresponding preliminary optimized and adjusted iron tower environment adaptation map;

in the preliminary optimized and adjusted iron tower environment adaptation map, transmitting and updating the iron tower data vector to form a corresponding preliminary transmitted iron tower data vector;

and determining the adaptive training iron tower environment data corresponding to each training iron tower construction data from the training iron tower environment data cluster according to the primarily transmitted iron tower data vector and the iron tower environment data difference.

In some preferred embodiments, in the method for analyzing abnormal states of a communication tower based on the decision algorithm, the step of adjusting the tower environment adaptation map based on the transmitted tower data vector to form a corresponding preliminary optimized adjusted tower environment adaptation map includes:

based on the transmitted iron tower data vector, analyzing a data matching index between each training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster; determining a training error index corresponding to the iron tower environment adaptation map based on the data matching index; updating and adjusting the iron tower environment adaptation map according to the training error index to form a corresponding preliminary optimized and adjusted iron tower environment adaptation map;

The step of determining the training error index corresponding to the iron tower environment adaptation map based on the data matching index comprises the following steps:

determining a data matching index of training iron tower environment data with a suitability relation with the training iron tower construction data from the data matching indexes, and marking the data matching index as a first data matching index; and determining a data matching index corresponding to the training iron tower environment data which does not have the suitability relation with the training iron tower construction data from the data matching indexes, and marking the data matching index as a second data matching index; and analyzing index difference coefficients between the first data matching index and the second data matching index, merging the index difference coefficients, and outputting training error indexes corresponding to the iron tower environment adaptation map.

In some preferred embodiments, in the method for analyzing abnormal states of communication towers based on decision algorithm, the step of determining adaptive training tower environmental data corresponding to each training tower construction data from the training tower environmental data clusters according to the difference between the primarily transferred tower data vector and the tower environmental data includes:

Based on the suitability data, determining a training iron tower environment data cluster with suitability related to the training iron tower construction data and a training iron tower environment data cluster with non-suitability related to the training iron tower construction data from the training iron tower environment data clusters;

analyzing the data matching initial index between each training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster according to the primarily transmitted iron tower data vector;

determining the initial difference of iron tower environment data between each training iron tower environment data in the non-adaptive training iron tower environment data cluster and each training iron tower environment data in the adaptive training iron tower environment data cluster from the iron tower environment data difference;

and determining adaptive training iron tower environment data corresponding to each training iron tower construction data from the non-adaptive training iron tower environment data clusters based on the initial data matching index and the initial difference of the iron tower environment data.

In some preferred embodiments, in the method for analyzing abnormal states of communication towers based on the decision algorithm, the step of determining adaptive training tower environmental data corresponding to each training tower construction data from the non-adaptive training tower environmental data clusters based on the initial data matching index and the initial difference of the tower environmental data includes:

Determining the initial difference of target iron tower environment data corresponding to each training iron tower environment data in the non-adaptive training iron tower environment data cluster from the initial difference of iron tower environment data;

based on a predetermined index fusion coefficient, fusing the initial difference of the target iron tower environment data and the data matching initial index, and outputting target adaptation parameters of each training iron tower environment data in the training iron tower construction data and the corresponding non-adaptive training iron tower environment data cluster;

and based on the target adaptation parameters, determining the adaptation training iron tower environment data corresponding to the training iron tower construction data from the non-adaptive training iron tower environment data cluster.

In some preferred embodiments, in the above method for analyzing abnormal states of a communication tower based on a decision algorithm, the steps of optimizing and adjusting the tower environment adaptation map based on the adaptation training tower environment data to form a corresponding optimized and adjusted tower environment adaptation map, expanding the target communication tower with the target communication tower environment data by using the optimized and adjusted tower environment adaptation map, and outputting the expanded tower environment data corresponding to the target communication tower include:

Based on the adaptive training iron tower environment data, adjusting the adaptive data to form corresponding adjusted adaptive data;

optimizing and adjusting the iron tower environment adaptation map according to the adjusted suitability data to form a corresponding candidate adjusted iron tower environment adaptation map;

optimizing and adjusting the candidate adjusted iron tower environment adaptation map to form a corresponding optimized and adjusted iron tower environment adaptation map;

and expanding the target communication iron tower by using the optimized and adjusted iron tower environment adaptation map, and outputting expanded iron tower environment data corresponding to the target communication iron tower, wherein the expanded iron tower environment data comprises at least one other training iron tower environment data with an adaptation relation with target iron tower construction data corresponding to the target communication iron tower in the optimized and adjusted iron tower environment adaptation map.

In some preferred embodiments, in the method for analyzing abnormal states of a communication tower based on the decision algorithm, the step of adjusting the suitability data based on the adaptive training tower environment data to form corresponding adjusted suitability data includes:

Reassigning the adaptive training tower environment data to be distributed into the adaptive training tower environment data clusters to form target adaptive training tower environment data clusters corresponding to the training tower construction data; analyzing suitability characterization information of the training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster based on the target suitability training iron tower environment data cluster; and adjusting the suitability data according to the suitability characterization information to form corresponding adjusted suitability data;

and the step of optimizing and adjusting the iron tower environment adaptation map according to the adjusted suitability data to form a corresponding candidate adjusted iron tower environment adaptation map comprises the following steps:

carrying out key information mining on the adjusted adaptability data, and outputting a corresponding adjusted adaptability data vector; based on the adjusted adaptability data vector, analyzing a target transmission update index of the iron tower environment adaptation map; and adjusting the current transmission update index in the iron tower environment adaptation map to the target transmission update index to form a corresponding candidate adjusted iron tower environment adaptation map;

And the step of optimizing and adjusting the candidate adjusted iron tower environment adaptation map to form a corresponding optimized and adjusted iron tower environment adaptation map comprises the following steps:

analyzing the transmission update data of the iron tower data vector in the candidate adjusted iron tower environment adaptation map under the target transmission update quantity based on the target transmission update index; and performing aggregation processing on the transmission update data and the iron tower data vector to form a corresponding iron tower data vector after target transmission; and optimizing and adjusting the candidate adjusted iron tower environment adaptation map according to the iron tower data vector transmitted by the target to form a corresponding optimized and adjusted iron tower environment adaptation map.

In some preferred embodiments, in the method for analyzing abnormal states of communication towers based on a decision algorithm, the step of extracting target tower attribute data of the target communication tower, analyzing the target tower attribute data by using the target decision algorithm model, and outputting target tower fault data corresponding to the target communication tower includes:

extracting the galvanized rust degree, the vertical deviation degree, the settlement amount of the tower foundation, the grounding resistance value, the antenna feeder, the lightning rod anomaly monitoring result, the foreign matter monitoring result and the fire point monitoring result of the tower body serving as the target iron tower attribute data of the target communication iron tower;

And the target decision algorithm model is used for analyzing the galvanization corrosion degree of the tower body, the vertical deviation degree of the tower body, the settlement amount of the tower foundation, the grounding resistance value, the antenna feeder and lightning rod abnormal monitoring result, the foreign matter monitoring result and the fire point monitoring result and outputting target iron tower fault data corresponding to the target communication iron tower.

The embodiment of the invention also provides a communication tower abnormal state analysis system based on the decision algorithm, which comprises a processor and a memory, wherein the memory is used for storing a computer program, and the processor is used for executing the computer program so as to realize the communication tower abnormal state analysis method based on the decision algorithm.

According to the communication tower abnormal state analysis method and system based on the decision algorithm, a target abnormal analysis model trained based on historical iron tower environment data and corresponding historical communication tower abnormal data can be obtained first, the target abnormal analysis model is utilized to analyze the target iron tower environment data corresponding to the target communication tower, and the communication tower prediction state corresponding to the target communication tower is output; reflecting the condition that the state of the target communication tower is abnormal in the communication tower prediction state, and acquiring a target decision algorithm model; and extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing a target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower. Based on the foregoing, before the analysis of the fault data by using the target decision algorithm model, the analysis is performed based on the iron tower environmental data, and the fault data analysis is performed based on the extracted target iron tower attribute data only under the condition of abnormal analysis, so that the extraction frequency of the iron tower attribute data and the frequency of the fault data analysis can be reduced to a certain extent, the cost of the analysis of the abnormal state of the communication iron tower can be effectively reduced, and the problem of higher analysis cost in the prior art is solved.

In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

Fig. 1 is a block diagram of a communication tower abnormal state analysis system based on a decision algorithm according to an embodiment of the present invention.

Fig. 2 is a schematic flow chart of steps included in the method for analyzing abnormal states of a communication tower based on a decision algorithm according to an embodiment of the present invention.

Fig. 3 is a schematic diagram of each module included in the communication tower abnormal state analysis device based on the decision algorithm according to the embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of 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, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

As shown in fig. 1, the embodiment of the invention provides a communication tower abnormal state analysis system based on a decision algorithm. The communication tower abnormal state analysis system based on the decision algorithm can comprise a memory and a processor.

In detail, the memory and the processor are electrically connected directly or indirectly to realize transmission or interaction of data. For example, electrical connection may be made to each other via one or more communication buses or signal lines. The memory may store at least one software functional module (computer program) that may exist in the form of software or firmware. The processor may be configured to execute the executable computer program stored in the memory, so as to implement the method for analyzing abnormal states of the communication tower based on the decision algorithm provided by the embodiment of the present invention.

For example, in one embodiment, the Memory may be, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), and the like.

For example, in one embodiment, the processor may be a general purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), a System on Chip (SoC), etc.; but also Digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

For example, in one embodiment, the decision algorithm-based communication tower abnormal state analysis system may be a server with data processing capability.

With reference to fig. 2, the embodiment of the invention also provides a communication tower abnormal state analysis method based on a decision algorithm, which can be applied to the communication tower abnormal state analysis system based on the decision algorithm. The method steps defined by the flow related to the communication tower abnormal state analysis method based on the decision algorithm can be realized by the communication tower abnormal state analysis system based on the decision algorithm.

The specific flow shown in fig. 2 will be described in detail.

Step S110, a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data is obtained, the target iron tower environment data corresponding to a target communication iron tower is analyzed by using the target abnormality analysis model, and a communication iron tower prediction state corresponding to the target communication iron tower is output.

In the embodiment of the invention, the communication tower abnormal state analysis system based on the decision algorithm can acquire a target abnormal analysis model trained based on historical iron tower environment data and corresponding historical communication tower abnormal data, analyze the target iron tower environment data corresponding to the target communication tower by using the target abnormal analysis model, and output the communication tower prediction state corresponding to the target communication tower. The historical iron tower environment data are used for describing the environment where the communication iron tower is located, such as weather data including humidity, temperature and illumination, air quality data, earthquake occurrence conditions and the like, and the historical communication iron tower abnormal data are used for reflecting whether the state of the communication iron tower is abnormal or not. That is, the historical iron tower environment data and the corresponding historical communication iron tower abnormal data (serving as a label) can be acquired first, and the candidate abnormal analysis model (which can be a neural network) is trained to learn the mapping relationship between the historical iron tower environment data and the historical communication iron tower abnormal data, so that in the application process, the communication iron tower prediction state corresponding to the target iron tower environment data, namely whether the state is abnormal, can be mapped based on the mapping relationship.

And step S120, reflecting the condition that the state of the target communication tower is abnormal in the communication tower prediction state, and acquiring a target decision algorithm model.

In the embodiment of the invention, the communication tower abnormal state analysis system based on the decision algorithm can obtain a target decision algorithm model when the communication tower prediction state reflects that the state of the target communication tower is abnormal. The target decision algorithm model is formed by constructing a decision tree based on historical iron tower attribute data and corresponding historical iron tower fault data, wherein the historical iron tower attribute data is used for reflecting the dynamic attribute of the communication iron tower, namely, the dynamic attribute of the communication iron tower possibly changes along with the change of time in application. The decision tree algorithm is a method for approaching discrete function values, and is a typical classification method, such as ID3, C4.5, CART, etc., firstly, data is processed, readable rules and decision trees are generated by using a generalization algorithm, then new data is analyzed by using decisions, and the decision tree is essentially a process for classifying the data through a series of rules. Specifically, the input to the decision tree structure is a set of examples with class labels (e.g., historical tower fault data is used as class labels, historical tower attribute data is used as input data), and the result of the structure is a binary tree or a multi-fork tree. The internal nodes (non-leaf nodes) of a binary tree are generally represented as a logical predicate, e.g., a logical predicate of the form a=aj, where a is an attribute and aj is all values of the attribute: the edges of the tree are the branch results of the logical decision. Wherein the internal nodes of the multi-way tree (such as ID 3) are attributes, the edges are all values of the attributes, and the edges are provided with a plurality of attribute values. In addition, the training process of the target decision algorithm model may refer to the related prior art, and is not specifically limited herein.

And step S130, extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing the target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower.

In the embodiment of the invention, the communication tower abnormal state analysis system based on the decision algorithm can extract the target tower attribute data of the target communication tower (for example, the target tower attribute data is formed by monitoring the monitoring equipment configured for the target communication tower), analyze the target tower attribute data by using the target decision algorithm model, and output the target tower fault data corresponding to the target communication tower. The target iron tower fault data are used for reflecting abnormal type information of the target communication iron tower in a dynamic attribute dimension, such as abnormal grounding resistance value (such as more than 30 ohms) and the like.

Based on the foregoing, before the analysis of the fault data is performed by using the target decision algorithm model, the analysis is performed based on the iron tower environmental data, and the fault data analysis is performed based on the extracted target iron tower attribute data only under the condition that the analysis is abnormal, so that the extraction frequency of the iron tower attribute data and the frequency of the fault data analysis can be reduced to a certain extent, the cost of the analysis of the abnormal state of the communication iron tower (such as the cost of data acquisition and the calculation cost of the data analysis) can be effectively reduced, and the problem of higher analysis cost in the prior art is solved.

For example, in one embodiment, step S110 may include:

determining a training iron tower construction data cluster, a training iron tower environment data cluster and suitability data between each training iron tower construction data in the training iron tower construction data cluster and each training iron tower environment data in the training iron tower environment data cluster, wherein the suitability data can be used for indicating whether the training iron tower environment data is matched with the training iron tower construction data or not, if the position of a communication iron tower corresponding to the training iron tower construction data has an environment reflected by the training iron tower environment data or not, in the initial stage, the suitability data can be determined based on whether environment data acquisition is carried out at the corresponding position or not, the training iron tower construction data is used for reflecting static attribute information of the training communication iron tower, and the static attribute information at least comprises iron tower coordinate information, iron tower information and iron tower material information of the training communication iron tower, and can also comprise other information, and is not particularly limited;

the training iron tower construction data and the training iron tower environment data are subjected to key information mining, corresponding iron tower data vectors are output, and based on the suitability data, the training iron tower construction data and the training iron tower environment data are subjected to mapping processing to form corresponding iron tower environment adaptation maps; for example, the training iron tower construction data and the training iron tower environment data may be encoded by an encoding neural network to form a corresponding iron tower data vector, where the iron tower environment adaptation map may include a knowledge map and a neural network for processing the knowledge map, the neural network may include the encoding neural network, in the knowledge map, the training iron tower construction data and the training iron tower environment data may be respectively used as knowledge map members, for example, the corresponding training iron tower environment data and the training iron tower construction data may be connected by a connection line (may be represented by a first numerical value in a matrix), the corresponding training iron tower environment data and the training iron tower construction data may not be adapted, and the knowledge map members may not be connected by a connection line (may be represented by a second numerical value in a matrix), where the second numerical value may be different from the first numerical value, for example, the first numerical value is 1, and the second numerical value is 0);

In the iron tower environment adaptation map, transmitting and updating the iron tower data vector, namely, performing associated updating on the iron tower data vector to form a transmitted iron tower data vector, and analyzing iron tower environment data differences between training iron tower environment data in the training iron tower environment data cluster, wherein the iron tower environment data differences can be used for reflecting differences between the training iron tower environment data in the training iron tower environment data cluster, such as vector distances between corresponding data vectors; in addition, the transmission updating of the iron tower data vector and the analysis of the iron tower environment data difference can be performed in any order or in parallel;

according to the transmitted iron tower data vector and the iron tower environment data difference, determining adaptive training iron tower environment data corresponding to each training iron tower construction data from the training iron tower environment data cluster, for example, in the unmatched training iron tower environment data determined based on the adaptive data, further determining adaptive training iron tower environment data corresponding to each training iron tower construction data according to the transmitted iron tower data vector and the iron tower environment data difference;

Optimizing and adjusting the iron tower environment adaptation map based on the adaptation training iron tower environment data to form a corresponding optimized and adjusted iron tower environment adaptation map, expanding the target communication iron tower with the optimized and adjusted iron tower environment adaptation map, and outputting expanded iron tower environment data corresponding to the target communication iron tower; for example, other training tower environment data with the connecting line corresponding to the training tower construction data of the target communication tower and the target tower environment data can be determined directly in the optimized and adjusted tower environment adaptation map;

the method comprises the steps of obtaining a target anomaly analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower anomaly data, analyzing the target iron tower environment data and the expansion iron tower environment data corresponding to a target communication iron tower by utilizing the target anomaly analysis model (by way of example, key information mining can be firstly carried out on the target iron tower environment data and the expansion iron tower environment data respectively, then a target vector and an expansion vector are obtained, then a attention mechanism can be utilized, the target vector is subjected to associated mining based on the expansion vector, a corresponding attention vector is output, a corresponding communication iron tower prediction state is analyzed based on the attention vector, such as full connection processing is firstly carried out, and then processing is carried out based on functions such as softmax, and the like), a communication iron tower prediction state corresponding to the target communication iron tower is output, a training iron tower construction data cluster comprises target iron tower construction data corresponding to the target communication iron tower, the training environment data cluster comprises the target iron tower environment data, and acquisition time of other training environment data in the training iron tower environment data cluster has synchronism with time of acquisition of the target iron tower environment data, and the time of the target environment data is formed within the same time interval.

For example, in one embodiment, the step of mining the training tower construction data and the training tower environment data for key information, outputting corresponding tower data vectors, and performing mapping processing on the training tower construction data and the training tower environment data based on the suitability data to form corresponding tower environment adaptation maps may include:

respectively carrying out vectorization processing on the training iron tower construction data and the training iron tower environment data, outputting a first vector corresponding to the training iron tower construction data, outputting a second vector corresponding to the training iron tower environment data, and carrying out cascade combination on the first vector and the second vector to output corresponding iron tower data vectors such as { first vector, second vector };

performing suitability matrixing processing on the training iron tower construction data and the training iron tower environment data based on the suitability data, and outputting a corresponding suitability characterization matrix, wherein the suitability characterization matrix can be formed based on the first numerical value and the second numerical value and is used for judging whether the training iron tower construction data and the training iron tower environment data are matched or not;

Based on the suitability characterization matrix, determining an intermediate vector, wherein elements of the intermediate vector on one diagonal (such as a main diagonal) are respectively the suitability characterization matrix and a transpose matrix of the suitability characterization matrix, and elements on the other diagonal (such as a secondary diagonal) are configuration values, such as the second numerical value;

based on the intermediate vectors, a transfer update vector is analyzed, each vector element included in the transfer update vector is taken as a corresponding transfer update parameter, illustratively, vector elements and values of each row (or column) in the intermediate vector can be calculated respectively, and for each vector element in the intermediate vector, whether the vector element belongs to a main diagonal is determined, when the vector element does not belong to the main diagonal, the vector element is determined as a configuration value, such as the second numerical value, and when the vector element belongs to the main diagonal, the vector element is determined as vector elements and values of the row (or column) in which the vector element belongs, so that a correlation matrix (vector), namely an adaptation matrix, can be formed; then, the correlation matrix and the intermediate vector may be multiplied to obtain a corresponding transfer update vector, for example, the 0.5 power of the correlation matrix, the intermediate vector and the 0.5 power of the correlation matrix may be multiplied;

And carrying out mapping treatment on the training iron tower construction data and the training iron tower environment data to form a corresponding iron tower environment adaptation map, wherein the iron tower environment adaptation map comprises the transmission updating parameters, and the training iron tower construction data and the training iron tower environment data are used as map members.

For example, in one embodiment, the step of transferring and updating the iron tower data vector in the iron tower environment adaptation map and analyzing the iron tower environment data difference between the training iron tower environment data in the training iron tower environment data cluster may include:

multiplying the transmission updating parameters included in the iron tower environment adaptation map by the iron tower data vector to form a transmitted iron tower data vector; and calculating a first vector (or a corresponding linear mapping result) corresponding to the training iron tower construction data and a first vector (or a corresponding linear mapping result) corresponding to other training iron tower construction data to obtain iron tower environment data differences between the training iron tower environment data in the training iron tower environment data cluster.

For example, in one embodiment, the step of determining, from the training tower environmental data cluster, the adapted training tower environmental data corresponding to each of the training tower construction data according to the transmitted tower data vector and the tower environmental data difference may include:

Based on the transmitted iron tower data vector, the iron tower environment adapting map is adjusted to form a corresponding preliminary optimized and adjusted iron tower environment adapting map, and the preliminary related description map actually comprises a knowledge map and a neural network, such as the transmission update of the iron tower data vector and the actual aiming at the knowledge map, so that the neural network can be adjusted based on the transmitted iron tower data vector, such as the adjustment of network parameters, such as parameters in the coding neural network, so that the corresponding error index can be reduced to a target value;

in the preliminary optimization adjusted iron tower environment adaptation map, transmitting and updating the iron tower data vector to form a corresponding preliminary transmitted iron tower data vector, wherein the process of transmitting and updating to form a corresponding preliminary transmitted iron tower data vector can be described in the previous related description;

and determining the adaptive training iron tower environment data corresponding to the training iron tower construction data from the training iron tower environment data clusters according to the primarily transmitted iron tower data vector and the iron tower environment data difference, wherein the adaptive training iron tower environment data corresponds to the training iron tower construction data, and the adaptive training iron tower environment data meets a certain adaptability relation.

For example, in one embodiment, the step of adjusting the iron tower environment adaptation map based on the transferred iron tower data vector to form a corresponding preliminary optimized adjusted iron tower environment adaptation map may include:

based on the transmitted iron tower data vector, analyzing a data matching index between each training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster; for example, cosine similarity may be calculated for a first vector corresponding to training tower construction data and a second vector corresponding to training tower environment data to obtain a data matching index, or a number product may also be calculated for a transposed vector of the first vector and the second vector;

determining a training error index corresponding to the iron tower environment adaptation map based on the data matching index;

according to the training error index, updating and adjusting the iron tower environment adaptation map to form a corresponding preliminary optimized and adjusted iron tower environment adaptation map, and illustratively, adjusting network parameters of a neural network in the iron tower environment adaptation map along the direction of reducing the training error index to reduce the training error index to a target value.

For example, in one embodiment, the step of determining, based on the data matching index, a training error index corresponding to the iron tower environment adaptation map may include:

determining a data matching index of training iron tower environment data with a suitability relation with the training iron tower construction data from the data matching indexes, and marking the data matching index as a first data matching index;

determining a data matching index corresponding to training iron tower environment data which does not have an adaptability relation with the training iron tower construction data from the data matching indexes, and marking the data matching index as a second data matching index;

analyzing index difference coefficients (such as difference calculation) between the first data matching index and the second data matching index, merging the index difference coefficients, and outputting a training error index corresponding to the iron tower environment adaptation map; for example, the normalization process may be performed on each index difference coefficient, then the logarithm operation may be performed on the normalization result, and the summation calculation may be performed on each result of the logarithm operation, and finally, the negative correlation coefficient determination may be performed on the result of the summation calculation, so as to obtain a training error index, for example, calculate a difference between a fixed parameter (such as the aforementioned second value) and the summation calculation result, and obtain the training error index.

For example, in one embodiment, the step of determining, from the training tower environmental data cluster, the adapted training tower environmental data corresponding to each of the training tower construction data according to the preliminary transmitted tower data vector and the tower environmental data difference may include:

determining an adaptive training tower environment data cluster with an adaptive relation with the training tower construction data and an unadapted training tower environment data cluster without an adaptive relation with the training tower construction data from the training tower environment data clusters based on the adaptive data, wherein the adaptive training tower environment data cluster comprises all training tower environment data with the adaptive relation (i.e. adaptive) with the training tower construction data, and the unadapted training tower environment data cluster comprises all training environment data without the adaptive relation (i.e. unadapted) with the training tower construction data;

according to the primarily transferred iron tower data vector, analyzing that data between each training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster matches an initial index, wherein a calculation mode is as described above, for example, calculation is performed based on a sub-vector corresponding to the training iron tower construction data and a sub-vector corresponding to the training iron tower environment data in the primarily transferred iron tower data vector;

Determining the initial difference of iron tower environmental data between each training iron tower environmental data in the non-adaptive training iron tower environmental data cluster and each training iron tower environmental data in the adaptive training iron tower environmental data cluster from the iron tower environmental data differences, namely determining the initial difference of iron tower environmental data between each training iron tower environmental data in the non-adaptive training iron tower environmental data cluster and each training iron tower environmental data in the adaptive training iron tower environmental data cluster, and marking the initial difference as the initial difference of iron tower environmental data;

For example, in one embodiment, the step of determining, from the non-adaptive training tower environment data cluster, the adaptive training tower environment data corresponding to each of the training tower construction data based on the initial data matching index and the initial difference between the tower environment data may include:

Determining a target iron tower environment data initial difference corresponding to each training iron tower environment data in the non-adaptive training iron tower environment data cluster from the iron tower environment data initial differences, wherein the minimum iron tower environment data initial difference corresponding to each training iron tower environment data in the training iron tower environment data cluster can be determined as the target iron tower environment data initial difference in the iron tower environment data initial differences;

based on a predetermined index fusion coefficient (which can be configured according to actual requirements, such as 0.6), fusing the initial difference of the target iron tower environment data and the data matching initial index, outputting target adaptation parameters of each training iron tower environment data in the training iron tower construction data and the corresponding non-adaptive training iron tower environment data cluster, and for example, weighting and summing the target iron tower environment data initial difference and the data matching initial index to obtain target adaptation parameters, wherein the sum value of the index fusion coefficient and the negative correlation coefficient of the index fusion coefficient is a fixed value, such as the first value;

Based on the target adaptation parameters, determining adaptation training iron tower environment data corresponding to the training iron tower construction data from the non-adaptive training iron tower environment data clusters; for example, training iron tower environment data corresponding to the maximum one or more target adaptation parameters can be used as adaptation training iron tower environment data corresponding to the training iron tower construction data.

For example, in one embodiment, the step of optimizing and adjusting the iron tower environment adaptation map based on the adaptation training iron tower environment data to form a corresponding optimized and adjusted iron tower environment adaptation map, and expanding the target communication iron tower with the optimized and adjusted iron tower environment adaptation map to output the expanded iron tower environment data corresponding to the target communication iron tower may include:

adjusting the suitability data based on the adaptation training tower environment data to form corresponding adjusted suitability data, for example, supplementing new suitability data based on the adaptation training tower environment data;

according to the adjusted suitability data, the iron tower environment adaptation map is optimized and adjusted to form a corresponding candidate adjusted iron tower environment adaptation map, the adjusted suitability data is subjected to feature extraction to obtain an adjusted suitability data vector, key information mining can be carried out on the adjusted suitability data to obtain an adjusted suitability data vector (such as the suitability characterization matrix represented by the first numerical value and the second numerical value), a target transmission update index of the iron tower environment adaptation map is determined based on the adjusted suitability data vector, and the current transmission update index in the iron tower environment adaptation map is replaced by a target transmission update index (such as the transmission update parameter) to obtain the candidate adjusted iron tower environment adaptation map;

Optimizing and adjusting the candidate adjusted iron tower environment adaptation map to form a corresponding optimized and adjusted iron tower environment adaptation map, namely, after updating the knowledge map included in the iron tower environment adaptation map based on the steps, further updating the network parameters of the included neural network to form an optimized and adjusted iron tower environment adaptation map;

and expanding the target communication iron tower by using the optimized and adjusted iron tower environment adaptation map, and outputting expanded iron tower environment data corresponding to the target communication iron tower, wherein the expanded iron tower environment data comprises at least one other training iron tower environment data, such as one or each of the most suitable training iron tower environment data and the target iron tower construction data corresponding to the target communication iron tower, in the optimized and adjusted iron tower environment adaptation map.

For example, in one embodiment, the step of adjusting the suitability data based on the adaptive training tower environment data to form corresponding adjusted suitability data may include:

reassigning the adaptive training iron tower environment data to be distributed into the adaptive training iron tower environment data clusters to form target adaptive training iron tower environment data clusters corresponding to the training iron tower construction data, namely supplementing the adaptive training iron tower environment data;

Analyzing suitability characterization information of the training iron tower construction data and each training iron tower environment data in the training iron tower environment data cluster based on the target suitability training iron tower environment data cluster, and adjusting the suitability data according to the suitability characterization information to form corresponding adjusted suitability data; for example, the suitability characterization information in the suitability data may be replaced by the currently determined suitability characterization information, so as to obtain adjusted suitability data, and if the suitability characterization information of the training iron tower construction data 1 and the training iron tower environment data 1 in the suitability data is not adapted, the suitability characterization information determined by the training iron tower construction data 1 and the training iron tower environment data 1 is adapted, the not-adapted in the suitability data may be updated to be adapted, so as to obtain adjusted suitability data.

For example, in one embodiment, the step of optimally adjusting the iron tower environment adaptation map according to the adjusted suitability data to form a corresponding candidate adjusted iron tower environment adaptation map may include:

The adjusted adaptability data are subjected to key information mining, and corresponding adjusted adaptability data vectors (as described in the previous related description) are output; and, based on the adjusted suitability data vector, analyzing a target transfer update index of the iron tower environment adaptation map (as described in the foregoing related description); and adjusting the current transmission update index in the iron tower environment adaptation map to the target transmission update index to form a corresponding candidate adjusted iron tower environment adaptation map.

For example, in one embodiment, the step of optimally adjusting the candidate adjusted iron tower environment adaptation map to form a corresponding optimally adjusted iron tower environment adaptation map may include:

based on the target transmission update index, analyzing transmission update data of the iron tower data vector in the candidate adjusted iron tower environment adaptation map under the target transmission update quantity, wherein the target transmission update quantity can refer to the number of times of transmission update, and thus, the target transmission update index can be a transmission update vector, and each vector element is included as corresponding transmission update data;

Performing aggregation processing on the transmission update data and the iron tower data vector to form a corresponding iron tower data vector after target transmission; illustratively, the transmission update data and the iron tower data vector may be multiplied to obtain an iron tower data vector after target transmission;

according to the iron tower data vector transmitted by the target, optimizing and adjusting the candidate adjusted iron tower environment adaptation map to form a corresponding optimized and adjusted iron tower environment adaptation map; in a specific implementation process, the iron tower environment adaptation map may be adjusted according to the transmitted iron tower data vector, so as to form a corresponding relevant description of the step of primarily optimizing the adjusted iron tower environment adaptation map, which is not described in detail herein.

The galvanized rust degree, the vertical deviation degree, the settlement amount of the tower foundation, the grounding resistance value, the antenna feeder, the lightning rod abnormal monitoring result, the foreign matter monitoring result and the fire point monitoring result of the tower body, which are the target iron tower attribute data of the target communication iron tower, are extracted, and can be monitored based on corresponding monitoring equipment;

and the target decision algorithm model is used for analyzing the galvanization corrosion degree of the tower body, the vertical deviation degree of the tower body, the settlement amount of the tower foundation, the grounding resistance value, the antenna feeder (the antenna feeder can be composed of an antenna and a transmission connecting line (also called a feeder)), an abnormal lightning rod monitoring result, the foreign matter monitoring result and the fire point monitoring result, and outputting target iron tower fault data corresponding to the target communication iron tower, such as the vertical tower body, the abnormal grounding resistance and the like.

With reference to fig. 3, the embodiment of the invention also provides a communication tower abnormal state analysis device based on a decision algorithm, which can be applied to the communication tower abnormal state analysis system based on the decision algorithm. The communication tower abnormal state analysis device based on the decision algorithm can comprise:

the system comprises a first analysis module, a second analysis module and a third analysis module, wherein the first analysis module is used for acquiring a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical iron tower abnormality data, analyzing the target iron tower environment data corresponding to a target iron tower by utilizing the target abnormality analysis model, and outputting a communication tower prediction state corresponding to the target iron tower, the historical iron tower environment data is used for describing the environment where the communication tower is located, and the historical iron tower abnormality data is used for reflecting whether the state of the communication tower is abnormal or not;

the decision model acquisition module is used for acquiring a target decision algorithm model when the predicted state of the communication tower reflects that the state of the target communication tower is abnormal, and the target decision algorithm model is formed by constructing a decision tree based on historical tower attribute data and corresponding historical tower fault data, wherein the historical tower attribute data is used for reflecting the dynamic attribute of the communication tower;

The second analysis module is used for extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing the target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower, wherein the target iron tower fault data is used for reflecting abnormal type information of the target communication iron tower in a dynamic attribute dimension.

In summary, the method and the system for analyzing the abnormal state of the communication tower based on the decision algorithm provided by the invention can firstly obtain the target abnormal analysis model trained based on the historical iron tower environment data and the corresponding historical communication tower abnormal data, analyze the target iron tower environment data corresponding to the target communication tower by utilizing the target abnormal analysis model, and output the communication tower prediction state corresponding to the target communication tower; reflecting the condition that the state of the target communication tower is abnormal in the communication tower prediction state, and acquiring a target decision algorithm model; and extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing a target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower. Based on the foregoing, before the analysis of the fault data by using the target decision algorithm model, the analysis is performed based on the iron tower environmental data, and the fault data analysis is performed based on the extracted target iron tower attribute data only under the condition of abnormal analysis, so that the extraction frequency of the iron tower attribute data and the frequency of the fault data analysis can be reduced to a certain extent, the cost of the analysis of the abnormal state of the communication iron tower can be effectively reduced, and the problem of higher analysis cost in the prior art is solved.

The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. The communication tower abnormal state analysis method based on the decision algorithm is characterized by comprising the following steps of:

Extracting target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing the target decision algorithm model, and outputting target iron tower fault data corresponding to the target communication iron tower, wherein the target iron tower fault data is used for reflecting abnormal type information of the target communication iron tower in dynamic attribute dimension;

the step of obtaining a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data, analyzing the target iron tower environment data corresponding to a target communication iron tower by using the target abnormality analysis model, and outputting a communication iron tower prediction state corresponding to the target communication iron tower comprises the following steps:

Acquiring a target abnormality analysis model trained based on historical iron tower environment data and corresponding historical communication iron tower abnormality data, analyzing the target iron tower environment data corresponding to a target communication iron tower and the expanded iron tower environment data by using the target abnormality analysis model, and outputting a communication iron tower prediction state corresponding to the target communication iron tower, wherein a training iron tower construction data cluster comprises target iron tower construction data corresponding to the target communication iron tower, the training iron tower environment data cluster comprises the target iron tower environment data, and the acquisition time of other training iron tower environment data in the training iron tower environment data cluster and the acquisition time of the target iron tower environment data have synchronism; the adaptability data is used for indicating whether the training iron tower environment data is matched with the training iron tower construction data or not;

the step of extracting the target iron tower attribute data of the target communication iron tower, analyzing the target iron tower attribute data by utilizing the target decision algorithm model and outputting target iron tower fault data corresponding to the target communication iron tower comprises the following steps:

2. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 1, wherein the step of determining the adaptive training tower environment data corresponding to each training tower construction data from the training tower environment data clusters according to the transmitted tower data vector and the tower environment data difference comprises the following steps:

3. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 2, wherein the step of adjusting the tower environment adaptation map based on the transmitted tower data vector to form a corresponding preliminary optimized adjusted tower environment adaptation map comprises the following steps:

4. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 2, wherein the step of determining the adaptive training tower environment data corresponding to each training tower construction data from the training tower environment data clusters according to the primarily transmitted tower data vector and the tower environment data difference comprises the steps of:

5. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 4, wherein the step of determining the adapted training tower environment data corresponding to each training tower construction data from the non-adapted training tower environment data clusters based on the initial data matching index and the initial difference of the tower environment data comprises:

6. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 4, wherein the steps of optimizing and adjusting the tower environment adaptation map based on the adaptation training tower environment data to form a corresponding optimized and adjusted tower environment adaptation map, expanding the target communication tower with the target communication tower environment data by using the optimized and adjusted tower environment adaptation map, and outputting the expanded tower environment data corresponding to the target communication tower comprise:

7. The method for analyzing abnormal states of communication towers based on decision algorithm as claimed in claim 6, wherein the step of adjusting the suitability data based on the adaptive training tower environment data to form corresponding adjusted suitability data comprises:

8. A system for analyzing abnormal states of a communication tower based on a decision algorithm, comprising a processor and a memory, wherein the memory is used for storing a computer program, and the processor is used for executing the computer program to realize the method for analyzing abnormal states of the communication tower based on the decision algorithm according to any one of claims 1 to 7.