A power transmission line structure health state intelligent perception and evaluation system and method

Abstract

The application discloses a kind of transmission line structure health state intelligent perception and evaluation system and method, system includes: transmission tower structure health state intelligent perception module, transmission tower disaster inversion module and transmission tower intelligent evaluation and patrol positioning module, structure health state intelligent perception module includes line response detection unit, data processing unit, data storage unit and data transmission unit;Disaster inversion module includes structural dynamics analysis unit, tower mechanics performance calculation unit, disaster inversion calculation unit;Intelligent evaluation and patrol positioning module includes health degree calculation unit, health state evaluation unit, patrol positioning unit.Based on system, the application can be slightly deformed, bolt loosening, structure weakening and other hidden danger evaluation method and perception to transmission tower, realize in-service transmission tower intelligent evaluation and patrol key positioning, promptly find hidden danger, avoid accident.

Description

Technical Field

[0001] This invention relates to the field of power engineering, and in particular to an intelligent sensing and evaluation system and method for the structural health status of transmission lines. Background Technology

[0002] As of the end of May 2019, the State Grid Corporation of China had more than 50,000 overhead transmission lines of 110 (66) kV and above, totaling 992,600 kilometers, and this number was growing at a rate of about 10% per year. How to ensure the safety of such a large-scale power transmission and distribution network is a core issue in the construction and development of the power system.

[0003] Transmission towers are a crucial component of power transmission lines. As supports for overhead conductors, their load-bearing capacity plays a vital role in the normal operation of the transmission lines. Because overhead transmission lines are exposed to the atmosphere, they are susceptible to the effects of temperature fluctuations, strong winds, icing, and other meteorological conditions. Transmission towers are constantly subjected to various static and dynamic loads, as well as salt spray corrosion, which can lead to problems such as loose bolt connections, node corrosion, and component deformation. This weakens the tower's load-bearing capacity and can easily induce serious transmission line accidents such as tower deformation or even collapse.

[0004] Against the backdrop of rapid development of power transmission lines, traditional manual inspection methods are inefficient and lack accurate evaluation methods and perception means for potential hazards such as minor deformation of towers, loose bolts, and structural weakening. If traditional management methods and maintenance strategies are not changed, the existing maintenance personnel will be unable to support the ever-growing scale of power transmission line operation and maintenance work, nor will they be able to meet the power system's requirements for efficiency and intelligence. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent sensing and evaluation system and method for the structural health status of power transmission lines, aiming to achieve intelligent evaluation and key point location of in-service power transmission towers during inspections, promptly identify potential hazards, and prevent accidents. To achieve the above objective, this invention provides the following technical solution:

[0006] A smart sensing and evaluation system for the structural health status of transmission lines includes: a smart sensing module for the structural health status of transmission towers, a disaster inversion module for transmission towers, and a smart evaluation and patrol positioning module for transmission towers. The smart sensing module for structural health status includes a line response detection unit, a data processing unit, a data storage unit, and a data transmission unit. The disaster inversion module includes an information retrieval unit, a structural dynamics analysis unit, a tower mechanical performance calculation unit, and a disaster inversion calculation unit. The smart evaluation and patrol positioning module includes a health degree calculation unit, a health status evaluation unit, and a patrol positioning unit.

[0007] In a further embodiment, the line response monitoring unit has functions of monitoring the tilt angle of the entire tower, monitoring the conductor tension, monitoring the stress of the tower components, and monitoring meteorological information.

[0008] In a further embodiment, the data processing unit has an abnormal data removal function.

[0009] In a further embodiment, the data storage unit has the function of temporarily storing monitoring data.

[0010] In a further embodiment, the data transmission unit has the function of transmitting monitoring data over long distances.

[0011] In a further embodiment, the tower mechanical performance calculation unit can calculate the tower bearing capacity as the basis for health status calculation.

[0012] In a further embodiment, the structural dynamics analysis unit has the function of solving and calculating the dynamic response of the transmission line using a finite element model of the tower-line system. The resulting data is then transmitted to the disaster inversion calculation unit.

[0013] In a further embodiment, the disaster inversion calculation unit has the functions of retrieving historical disaster information and disaster simulation.

[0014] In a further embodiment, the health calculation unit has the function of calculating the health of the component.

[0015] In a further embodiment, the health status evaluation unit uses the proposed power transmission tower structure health evaluation system to evaluate the health status of the components.

[0016] In a further embodiment, the patrol positioning unit has the function of locating and marking the weak points of the tower.

[0017] A smart sensing and evaluation system for the structural health status of power transmission lines includes the following steps:

[0018] Step 1: The system uses a line response detection unit composed of various pre-deployed sensors to collect data on tower tilt, conductor tension, tower component stress, and meteorological information, and transmits the real-time sensing data to the database.

[0019] Step 2: The system reads the structural model data and real-time sensing data of the transmission lines and transmission towers from the database, then performs local wind field simulation calculations on the geographical location of the transmission lines, further performs structural dynamics simulation calculations and tower member bearing capacity calculations, performs disaster inversion calculations on this basis, and saves the calculation results to the database.

[0020] Step 3: The system reads the component bearing capacity calculation results and line and tower information from the database, and uses the data to calculate the health status of the transmission tower. Based on this, it performs an intelligent evaluation of the structural health status, compares the evaluation results with the threshold, and if the threshold is exceeded, it locates the weak parts of the structure.

[0021] This system aims to intelligently perceive the structural health status of transmission towers. Research is conducted from four aspects: theoretical analysis, experimental research, device development, and field application. It employs a combination of field surveys, simulation experiments, and finite element simulation, considering the weakening of in-service transmission tower structures, components, and nodes, and providing a method for assessing their load-bearing capacity. A comprehensive perception technology for the status of transmission towers is constructed, deeply integrated with digital simulation models based on real-time measurements of overhead conductor loads, tower structural tilt angles, and stress states. A disaster inversion method for in-service transmission towers based on status perception data is proposed. A quantitative evaluation method for the health status of transmission towers is provided, enabling the location of weak points in the line's health status. An edge-based intelligent perception and evaluation system for the structural health status of transmission towers is developed. This system will provide important theoretical support, technical assurance, and practical basis for enhancing the perception capabilities of important transmission line corridors and strengthening power grid construction. Temperature, wind speed, and icing thickness are the three key meteorological conditions. Meteorological conditions affect the safe and stable operation of transmission lines; altering the operating environment of transmission lines will affect their operating status. To achieve efficient online monitoring of transmission lines, the design and development of an online monitoring management platform were undertaken. Sensors were installed within the circuit equipment to intelligently monitor the transmission lines. An online monitoring system was constructed at the transmission line tower level, and the online monitoring management platform was designed. Currently, some regions in China have established transmission line operation status monitoring systems and conducted pilot applications, improving the level of lean operation, maintenance, and production management. The information collected by the transmission line monitoring devices and the data generated by the system are integrated and stored to improve the operational status of the transmission line information data platform, thereby enabling the monitoring of transmission line operation status and environment, and fault analysis.

[0022] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention solves the problems of low efficiency and lack of accurate evaluation methods and sensing means for potential hazards such as minor tower deformation, loose bolts, and structural weakening by setting up a transmission tower structural health status intelligent sensing module, transmission tower disaster inversion module, transmission tower intelligent evaluation and patrol positioning module, line response detection unit, data processing unit, data storage unit, data transmission unit, structural dynamics analysis unit, tower mechanical performance calculation unit, disaster inversion calculation unit, health calculation unit, health status evaluation unit, and patrol positioning unit. Relying on modern communication technology and intelligent sensing technology, combined with disaster information and power grid information, it achieves information integration and visualization. The proposed real-time sensing method for the structural health status of in-service transmission towers can realize intelligent evaluation and patrol focus positioning functions for in-service transmission towers. Referring to the relevant provisions in the "Guidelines for Status Evaluation of Overhead Transmission Lines" regarding the division of weight levels of status quantities in the evaluated items and how to define the degree of deterioration of status quantities, a scoring standard for transmission tower health evaluation indicators is designed, facilitating the evaluation of the overall operating status of transmission lines. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the computing system structure in this invention;

[0024] Figure 2 This is a schematic diagram of the main calculation process in this invention;

[0025] Figure 3 This is a schematic diagram of the quantitative algorithm for the structural health of transmission lines in this invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0027] The technical solutions in the embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] Please refer to 1-3. This embodiment is a system and method for intelligent sensing and evaluation of the structural health status of transmission lines. The system includes: an intelligent sensing module for the structural health status of transmission towers, a disaster inversion module for transmission towers, and an intelligent evaluation and patrol positioning module for transmission towers. The intelligent sensing module for structural health status is composed of a line response detection unit, a data processing unit, a data storage unit, and a data transmission unit. The disaster inversion module is composed of a structural dynamics analysis unit, a tower mechanical performance calculation unit, and a disaster inversion calculation unit. The intelligent evaluation and patrol positioning module is composed of a health degree calculation unit, a health status evaluation unit, and a patrol positioning unit.

[0029] like Figure 1 As shown, the output terminal of the line response monitoring unit is unidirectionally electrically connected to the input terminal of the data processing unit, the output terminal of the data processing unit is unidirectionally electrically connected to the input terminal of the data storage unit, and the output terminal of the data storage unit is unidirectionally electrically connected to the input terminal of the data transmission unit.

[0030] The output terminal of the data transmission unit is unidirectionally electrically connected to the input terminal of the tower mechanical performance calculation unit and the input terminal of the structural dynamics analysis unit, respectively. The input terminal of the disaster inversion calculation unit of the disaster inversion module is unidirectionally electrically connected to the output terminal of the structural dynamics analysis unit.

[0031] The output of the tower mechanical performance calculation unit of the disaster inversion module is unidirectionally electrically connected to the input of the health calculation unit of the intelligent evaluation and patrol positioning modules, respectively. The output of the health calculation unit is unidirectionally electrically connected to the input of the health status evaluation unit, and the output of the health status evaluation unit is unidirectionally electrically connected to the input of the patrol positioning unit. The line response monitoring unit has functions of monitoring the entire tower tilt angle, conductor tension, tower component stress, and meteorological information.

[0032] The data processing unit has an abnormal data removal function;

[0033] The data storage unit has the function of temporarily storing monitoring data;

[0034] The data transmission unit has the function of transmitting monitoring data over long distances;

[0035] The tower mechanical performance calculation unit can calculate the tower bearing capacity, serving as the basis for health assessment.

[0036] The structural dynamics analysis unit has the function of solving and calculating the dynamic response of transmission lines using the finite element model of the tower-line system. The results are then transmitted to the disaster inversion calculation unit.

[0037] The disaster inversion calculation unit has the functions of retrieving historical disaster information and disaster simulation;

[0038] The health calculation unit has the function of calculating the health of components;

[0039] The health status assessment unit uses the proposed structural health assessment system for power transmission towers to evaluate the health status of components.

[0040] The patrol positioning unit has the function of locating and marking the weak points of the tower;

[0041] Based on real-time data obtained by the intelligent sensing module for the structural health status of transmission towers, the system's various functions are centered on the database. By querying information such as the structure of the transmission tower, disaster path, calculation results of the mechanical properties of the transmission tower, and disaster risk assessment results of the tower, combined with the proposed method for reproducing the continuous collapse process of transmission lines, and applying the finite element method to reasonably simulate the failure mechanism of the structure, the system can intuitively and accurately provide the collapse form and path of the structure.

[0042] According to the appendix Figure 3 The specific steps of the quantitative algorithm for the structural health of transmission lines are as follows: First, based on the survey questionnaire results, a judgment matrix is ​​formed. A programming language is used to read the judgment matrix of transmission tower health stored in an Excel spreadsheet. The pre-written analytic hierarchy process (AHP) subroutine is then called to form the subjective weight vector wa of the transmission tower health evaluation system. The entropy weight method and standard deviation method are used to analyze and process each indicator, obtaining the corresponding objective weight vectors ws and wd. Based on the game theory inheritance model, the weights formed by the above three schemes are calculated and synthesized to form the scheme evaluation matrix B. The pre-written game theory-based combined weight calculation program is called to obtain the combined weights of the three evaluation schemes. The scoring tables for each indicator are read in to form a scoring matrix. The comprehensive health score Q of the transmission tower is calculated. Finally, based on the above-mentioned transmission tower health level classification standards, the health level of the transmission tower is output.

[0043] The basic steps for calculating weights using the analytic hierarchy process (AHP) in the above algorithm are as follows:

[0044] Step 1: Identify the key criteria for making decisions regarding the system's final goals.

[0045] Step 2: Divide the various influencing factors in the system into the target layer, the criterion layer, and the solution layer. The higher-level elements can be regarded as the criteria of the lower-level elements and play a certain dominant role in the lower-level elements.

[0046] Step 3: Construct a judgment matrix based on the relative importance of elements, and calculate the relative importance of all sub-factors under a given criterion relative to the higher-level criterion. Based on the correlations between influencing factors in the target layer and criterion layer, and between the criterion layer and indicator layer, perform pairwise comparisons of sub-factors under each criterion. Construct judgment matrices according to their relative importance, separately constructing judgment matrices between risk factors in the target layer and criterion layer, and between risk factors in the criterion layer and indicator layer. The expression for the judgment matrix is ​​as follows:

[0047]

[0048] For the three-scale hierarchical analysis method:

[0049] Step 4: Calculate the weight of each sub-risk factor relative to the parent risk factor, and the relative weights among the sub-risk factors. The formula for calculating the weights of a sub-risk factor relative to its parent risk factor is as follows:

[0050]

[0051] In the formula, i and j are sub-risk factors; x is the parent risk factor of sub-risk factors i and j; n is the number of sub-risk factors; q is the relative importance of factor i relative to factor j; and y is the weight of sub-risk factor i relative to parent risk factor x.

[0052] The formula for calculating the relative weights between the sub-risk factors is as follows:

[0053] w ij =w ix -w jx +0.5 (3)

[0054] In the formula w ij This represents the weight of risk factor i relative to risk factor j.

[0055] Step 5: Analyze the final weights of each factor in each layer relative to the final target, working from the top down. The overall weight calculation expression for the risk factors in the target layer and indicator layer is as follows:

[0056] w ix =w yx ·w iy (4)

[0057] w yx w represents the weight of the risk factor y in the criterion layer with respect to its parent risk factor, i.e., the target layer x. iy This represents the weight of indicator-level risk factor i relative to its parent risk factor y in the criterion layer above it; it also represents the overall weight of indicator-level risk factor i relative to the target x.

[0058] Step 6: Perform feasibility calculations and assessments on the judgment matrices established between the target layer and the criterion layer, and between the criterion layer and the risk factors in the indicator layer, and verify the feasibility of the matrices. The general calculation formula is:

[0059]

[0060] If Z is the feasibility ratio, then the judgment matrix satisfies the feasibility requirement.

[0061] For the nine-scale hierarchical analytic hierarchy process:

[0062] Step 4: Find the positive reciprocal matrix (also called the judgment matrix) Ts = (a ij ) n×n The weights are determined by solving for the eigenvalues ​​of matrix A. The corresponding eigenvectors are obtained, and after normalization, they become the weights W. The elements of W represent the ranking weights of factors at the same level relative to a factor at the next higher level; this process is called hierarchical single ranking. To confirm whether hierarchical single ranking is valid, a consistency test is required. The consistency test determines the acceptable range of inconsistencies in A. Specifically, the unique non-zero eigenvalue of an n-order consistent matrix is ​​n; the largest eigenvalue λ of an n-order positive reciprocal matrix A is ≥ n, and A is a consistent matrix if and only if λ = n.

[0063] Step 5: Consistency check. Since λ continuously depends on a... ij The greater the difference between λ and n, the more severe the inconsistency of A. The consistency index is calculated using CI; the smaller the CI, the greater the consistency. The eigenvector corresponding to the largest eigenvalue is used as the weight vector for the degree of influence of the compared factor on a higher-level factor. The greater the degree of inconsistency, the greater the judgment error. Therefore, the magnitude of λ-n can be used to measure the degree of inconsistency of A. The consistency index is defined as:

[0064]

[0065] CI = 0 indicates perfect consistency; CI close to 0 indicates satisfactory consistency; the larger the CI, the more severe the inconsistency.

[0066] To measure the magnitude of CI, the random consistency metric RI is introduced:

[0067]

[0068] Considering that deviations in consistency may be due to random causes, when verifying whether the judgment matrix has satisfactory consistency, it is also necessary to compare CI with the random consistency index RI to obtain the test coefficient CR, as shown in the following formula:

[0069]

[0070] If CR < 0.1, the judgment matrix is ​​considered to have passed the consistency test; otherwise, it does not have satisfactory consistency.

[0071] Step 6: If the judgment matrix passes the consistency test, then the eigenvector corresponding to its largest eigenvalue is the importance ranking ω of the indicator relative to the previous level indicator.

[0072] In the above algorithm, the calculation steps of the entropy weight method are as follows:

[0073] Step 1: Determine the evaluation object, establish the evaluation index system, and construct the index level matrix R′

[0074]

[0075] Where r ij Let be the evaluation value of the i-th item under the j-th indicator.

[0076] Step 2: Standardize the evaluation matrix R to obtain matrix R = (r ij ) n×n .

[0077] j is a positive indicator:

[0078] j is a negative indicator:

[0079] Step 3: Calculate the entropy of the j-th index.

[0080]

[0081] in This represents the proportion of the i-th item indicator value under the j-th indicator; k = 1 / lnm.

[0082] Step 4: Calculate the entropy weight w of the j-th index. j :

[0083]

[0084] Step 5: Calculate the comprehensive weight λ of the indicators. j :

[0085] Assume the evaluator determines the importance weight of the indicators as λ based on their own objectives and requirements. j Let ', j = 1, 2, ..., n, and combine the entropy weight w of the index. j This allows us to obtain the overall weight of index j:

[0086]

[0087] In the above algorithm, the steps for calculating the objective weights using the standard deviation method are as follows:

[0088] Step 1: Statistically analyze the tower accidents that have occurred in the area where the target tower is located over the past five years to obtain the number of accidents caused by each assessment item.

[0089] Step 2: Calculate the mean of the j-th evaluation indicator:

[0090]

[0091] Step 3: Obtain the standard deviation of each evaluation item from the sample data. The formula is:

[0092]

[0093] In the formula, δ j S is the standard deviation of the j-th evaluation indicator; ij For the sample data of the j-th evaluation indicator in the nth year, is the sample mean of the j-th evaluation indicator.

[0094] Step 4: Calculate the corresponding standard deviation weights from the standard deviations of each evaluation item. The formula is:

[0095]

[0096] In the formula, is the standard deviation weight of the j-th evaluation index on the safety status of the tower; is the standard deviation of the j-th evaluation index.

[0097] Based on the above operational methods, the main process of the intelligent sensing and evaluation method is shown in the appendix. Figure 2 As shown, the process includes the following steps: Step 1: The system uses a line response detection unit composed of various pre-deployed sensors to collect data on the overall tower tilt angle, conductor tension, tower component stress, and meteorological information, and transmits the real-time sensing data to the database; Step 2: The system reads the structural model data of the transmission line and transmission tower and the real-time sensing data from the database, then performs local wind field simulation calculations on the geographical location of the transmission line, calculates the wind load on the transmission line, further performs structural dynamics simulation calculations and tower member bearing capacity calculations on the tower-line system, judges the calculation results, and if the bearing capacity exceeds the member's ultimate bearing capacity, disaster inversion calculations are performed on this basis, and the calculation results are saved to the database;

[0098] Step 3: The intelligent evaluation and patrol positioning module for power transmission towers reads the component bearing capacity calculation results and line and tower information from the database, and uses the data to calculate the health status of the power transmission towers. Based on the calculation results, it performs an intelligent evaluation of the structural health status and compares the evaluation results with a threshold. If the threshold is exceeded, the weak parts of the structure are located.

[0099] This embodiment elaborates on the real-time monitoring of transmission tower status perception, real-time health evaluation, disaster process inversion, and weak link location of transmission towers. Relying on modern communication technology and intelligent sensing technology, and combining disaster information and power grid information, the integration and visualization of information are realized. The proposed real-time perception method for the structural health status of in-service transmission towers can realize the functions of intelligent evaluation and key point location of in-service transmission towers. A scoring standard for the health evaluation index of transmission towers is designed to facilitate the assessment of the overall operating status of transmission lines.

[0100] This invention facilitates the perception and assessment of the overall operational status of transmission lines, providing crucial theoretical support, technical assurance, and practical basis for enhancing the perception capabilities of critical transmission line corridors and constructing a robust power grid. It will be apparent to those skilled in the art that this invention is not limited to the details of the above exemplary embodiments, and that it can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within this invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0101] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A smart sensing and evaluation system for the structural health status of transmission lines, characterized in that, include: The system comprises a power transmission tower structural health status intelligent sensing module, a power transmission tower disaster inversion module, and a power transmission tower intelligent evaluation and patrol positioning module. The structural health status intelligent sensing module includes a line response detection unit, a data processing unit, a data storage unit, and a data transmission unit. The disaster inversion module includes a structural dynamics analysis unit, a tower mechanical performance calculation unit, and a disaster inversion calculation unit. The intelligent evaluation and patrol positioning module includes a health degree calculation unit, a health status evaluation unit, and a patrol positioning unit. The output terminal of the line response monitoring unit is unidirectionally electrically connected to the input terminal of the data processing unit, the output terminal of the data processing unit is unidirectionally electrically connected to the input terminal of the data storage unit, and the output terminal of the data storage unit is unidirectionally electrically connected to the input terminal of the data transmission unit. The output of the data transmission unit is unidirectionally electrically connected to the input of the tower mechanical performance calculation unit and the input of the structural dynamics analysis unit, respectively. The input of the disaster inversion calculation unit of the disaster inversion module is unidirectionally electrically connected to the output of the structural dynamics analysis unit. The tower mechanical performance calculation unit can calculate the tower bearing capacity, which serves as the basis for health calculation. The structural dynamics analysis unit has the function of using the finite element model of the tower-line system to solve and calculate the dynamic response of the transmission line, and the result data is transmitted to the disaster inversion calculation unit; The output of the tower mechanical performance calculation unit of the disaster inversion module is unidirectionally electrically connected to the input of the health calculation unit of the intelligent evaluation and patrol positioning modules, respectively. The output of the health calculation unit is unidirectionally electrically connected to the input of the health status evaluation unit, and the output of the health status evaluation unit is unidirectionally electrically connected to the input of the patrol positioning unit. The disaster inversion calculation unit has the functions of retrieving historical disaster information and disaster simulation. The sensing and evaluation method based on the intelligent sensing and evaluation system for the structural health status of transmission lines includes the following steps: Step 1: The system uses a line response detection unit composed of various pre-deployed sensors to collect data such as tower tilt monitoring, conductor tension monitoring, tower component stress monitoring, and meteorological information monitoring, and transmits the real-time sensing data to the database; Step 2: The system reads the structural model data and real-time sensing data of the transmission line and transmission tower from the database, then performs local wind field simulation calculations based on the geographical location of the transmission line, further performs structural dynamics simulation calculations and tower member bearing capacity calculations, and performs disaster inversion calculations based on this, saving the calculation results to the database; Step 3: The system reads the component bearing capacity calculation results and line and tower information from the database, uses the data to calculate the health status of the transmission tower, performs intelligent evaluation of the structural health status based on this, compares the evaluation results with a threshold, and if the threshold is exceeded, the weak parts of the structure are located.

2. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The line response monitoring unit has functions for monitoring the tilt angle of the entire tower, monitoring the conductor tension, monitoring the stress of tower components, and monitoring meteorological information.

3. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The data processing unit has an abnormal data removal function.

4. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The data storage unit has the function of temporarily storing monitoring data.

5. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The data transmission unit has the function of transmitting monitoring data over long distances.

6. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The health calculation unit has the function of calculating the health of components.

7. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The health status evaluation unit uses the proposed power transmission tower structure health evaluation system to evaluate the health status of the components.

8. The intelligent sensing and evaluation system for the structural health status of transmission lines according to claim 1, characterized in that, The patrol positioning unit has the function of locating and marking the weak points of the tower.

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