Communication iron tower with intelligent inspection device
By integrating intelligent patrol devices on the communication tower, using feature extraction, status evaluation and strategy adjustment modules, the problems of poor real-time and low accuracy of data processing in the existing technology are solved, and accurate monitoring and efficient patrol of the tower operating status are achieved.
Patent Information
- Application Number
- CN202510172930.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-17
- Publication Date
- 2025-06-03
AI Technical Summary
The data processing of existing communication towers has poor real-time and low accuracy, resulting in low patrol efficiency and high cost.
A communication tower with intelligent patrol devices was designed, including feature extraction module, status evaluation module and strategy adjustment module. By performing feature extraction, data cleaning and hierarchical analysis model evaluation of tower operating status and environmental status data, the patrol strategy is dynamically adjusted.
Accurate monitoring and efficient inspection of the operating status of the communication tower has been achieved, inspection efficiency has been improved, labor costs have been reduced, and the safety and stability of the tower have been enhanced.
Smart Images
Figure CN120088879A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of intelligent inspection of communication towers, and particularly to a communication tower with an intelligent inspection device. Background Art
[0002] Today, with the rapid development of communication technology, communication towers, as an important part of the wireless communication network, their stability and security are directly related to the quality and reliability of communication services. Although intelligent inspection technology shows great potential in the field of communication tower maintenance, the existing technology still faces many challenges, such as poor real-time performance and low accuracy in processing the operation status data of communication towers. Summary of the Invention
[0003] Embodiments of the present disclosure provide a communication tower with an intelligent inspection device to solve the problems of poor real-time performance and low accuracy in existing data processing.
[0004] Embodiments of the present disclosure provide a communication tower with an intelligent inspection device, including: A feature extraction module, configured to extract features from the operation status data and environmental status data of the communication tower to obtain an initial feature data set, and perform data cleaning on the initial feature data set to obtain a target feature data set; A status evaluation module, configured to input the target feature data set into an analytic hierarchy process model for status evaluation to obtain a status evaluation result of the communication tower, where the analytic hierarchy process model is an algorithm model constructed based on the historical data of the communication tower; A strategy adjustment module, configured to update an initial inspection strategy based on the status evaluation result to obtain a target inspection strategy, and control a drone to inspect the communication tower based on the target inspection strategy.
[0005] In an exemplary embodiment of the present disclosure, the intelligent inspection device further includes a model construction module; The model construction module is configured to: Determine the number of hierarchical layers of the analytic hierarchy process model based on the quantity and type of the historical data of the communication tower, and construct a judgment matrix based on the number of hierarchical layers and the historical data; the historical data includes the historical operation status data and historical environmental status data of the communication tower; Calculate a consistency ratio based on the judgment matrix, and adjust the judgment matrix based on the comparison result between the consistency ratio and a preset threshold to obtain the analytic hierarchy process model.
[0006] In an exemplary embodiment of the present disclosure, calculating the consistency ratio based on the judgment matrix includes: Calculating a consistency index of each layer of the judgment matrix, and determining a random consistency index from a preset index mapping table based on the order of the judgment matrix; Calculate the consistency ratio based on the consistency index and its corresponding random consistency index.
[0007] In an exemplary embodiment of the present disclosure, the preset threshold includes a first preset threshold and a second preset threshold; Adjusting the judgment matrix based on the comparison result of the consistency ratio and the preset threshold to obtain an analytic hierarchy process model includes: If the consistency ratio is less than the first preset threshold, an analytic hierarchy process model is obtained based on the judgment matrix; If the consistency ratio is greater than or equal to the first preset threshold and less than the second preset threshold, adjust the assignment of the elements in the judgment matrix; when the consistency ratio is less than the first preset threshold, an analytic hierarchy process model is obtained based on the adjusted judgment matrix; If the consistency ratio is greater than or equal to the second preset threshold, adjust the hierarchy of the elements in the judgment matrix and adjust the assignment of the elements in the judgment matrix; when the consistency ratio is less than the first preset threshold, an analytic hierarchy process model is obtained based on the adjusted judgment matrix.
[0008] In an exemplary embodiment of the present disclosure, adjusting the hierarchy of the elements in the judgment matrix includes: Determine the abnormal elements in the judgment matrix, and determine the target hierarchy of the abnormal elements according to data characteristics and expert experience; If the current hierarchy of the abnormal element is less than the target hierarchy, adjust the abnormal element to the judgment matrix of the target hierarchy, and determine the adjusted weight of the abnormal element based on the first formula; If the current hierarchy of the abnormal element is greater than the target hierarchy, adjust the abnormal element to the judgment matrix of the target hierarchy, and determine the adjusted weight of the abnormal element based on the second formula.
[0009] In an exemplary embodiment of the present disclosure, the first formula is:
[0010] Where e represents the abnormal element, represents the weight of the target hierarchy, represents the weight of the original hierarchy, n represents the total number of elements in the original hierarchy, m represents the total number of elements in the target hierarchy, W represents the total weight of the original hierarchy, V represents the total weight of the target hierarchy, and V = kW, k is an adjustment coefficient, and k is a constant greater than 1; is a regulation factor, 0 < < 1.
[0011] In an exemplary embodiment of the present disclosure, the second formula is:
[0012] Among them, e represents an abnormal element, represents the weight of the target level, represents the weight of the original level, n represents the total number of elements in the original level, m represents the total number of elements in the target level, W represents the total weight of the original level, V represents the total weight of the target level, and W = pV, where p is an adjustment coefficient and p is a constant greater than 1; is a regulation factor, 0 < < 1.
[0013] In an exemplary embodiment of the present disclosure, the state evaluation result includes a comprehensive evaluation score; Updating the initial inspection strategy based on the state evaluation result to obtain a target inspection strategy includes: If the comprehensive evaluation score is greater than or equal to a first value, the first inspection frequency and the first inspection technical means in the initial inspection strategy remain unchanged; If the comprehensive evaluation score is less than the first value and greater than or equal to a second value, the first inspection frequency in the initial inspection strategy is updated to a second inspection frequency; the first inspection frequency is less than the second inspection frequency; If the comprehensive evaluation score is less than the second value, the first inspection frequency in the initial inspection strategy is updated to a second inspection frequency, and the first inspection technical means is updated to a second inspection technical means; the number of monitoring devices included in the first inspection technical means is less than the number of monitoring devices included in the second inspection technical means.
[0014] In an exemplary embodiment of the present disclosure, the intelligent inspection device further includes a data acquisition module; The data acquisition module is connected to the feature extraction module, and the data acquisition module includes multiple sensors for collecting the operating state data and environmental state data of the communication tower.
[0015] In an exemplary embodiment of the present disclosure, the intelligent inspection device further includes a communication module; The communication module is used to connect to a remote monitoring center and send the state evaluation result, inspection data, and real-time position information of the unmanned aerial vehicle to the remote monitoring center; The communication module is further used to receive instructions from the remote monitoring center and control the working states of the respective sensors based on the instructions.
[0016] The beneficial effects of the communication tower with an intelligent inspection device provided by the embodiments of the present disclosure are: Through three major modules of feature extraction, status evaluation, and policy adjustment, the present disclosure realizes precise monitoring and efficient inspection of the operating status of communication towers. The intelligent inspection device in this embodiment can automatically collect and analyze the operating status and environmental data of the tower, accurately evaluate the tower status, and dynamically adjust the inspection policy according to the evaluation results to ensure the real-time nature of data processing, the pertinence and effectiveness of the inspection work. This not only improves the inspection efficiency, reduces the labor cost, but also enhances the safety and stability of the communication tower, providing a strong guarantee for the smooth operation of the communication network. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.
[0018] Figure 1 is a schematic structural diagram of the intelligent inspection device provided by the embodiment of the present disclosure; Figure 2 is a schematic structural diagram of another intelligent inspection device provided by the embodiment of the present disclosure. DETAILED IMPLEMENTATION MANNER
[0019] In order to enable those skilled in the art of this technology to better understand this solution, the following will clearly describe the technical solutions in the embodiments of this solution in conjunction with the drawings in the embodiments of this solution. Obviously, the described embodiments are some, rather than all, of the embodiments of this solution. Based on the embodiments in this solution, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this solution.
[0020] The term "including" in the specification, claims, and the above drawings of this solution, as well as any other deformation, means "including but not limited to", and is intended to cover non-exclusive inclusion, not limited to the examples listed in the text. In addition, terms such as "first" and "second" are used to distinguish different objects, rather than to describe a specific order.
[0021] The following will describe the implementation of the present disclosure in detail in conjunction with specific drawings: A communication tower is a communication device that provides support and fixation for equipment such as communication antennas and feeders, ensuring that the communication equipment can be at an appropriate height and position to achieve good signal coverage and transmission. By setting the communication antenna at a higher position, the propagation range of the signal can be expanded, signal occlusion and interference can be reduced, and the quality and stability of the communication signal can be improved. Currently, the fault inspection of communication towers is usually based on drone photography combined with manual judgment, which consumes manpower and material resources and cannot adjust the inspection strategy in a timely manner. Based on this, the present disclosure designs a communication tower with an intelligent inspection device.
[0022] Figure 1 It is a schematic structural diagram of the intelligent inspection device provided by an embodiment of the present disclosure. The intelligent inspection device includes: A feature extraction module 101, configured to extract features from the operation state data and environmental state data of the communication tower to obtain an initial feature data set, and perform data cleaning on the initial feature data set to obtain a target feature data set; A state evaluation module 102, configured to input the target feature data set into an analytic hierarchy process model for state evaluation to obtain a state evaluation result of the communication tower, and the analytic hierarchy process model is an algorithm model constructed based on the historical data of the communication tower; A strategy adjustment module 103, configured to update the initial inspection strategy based on the state evaluation result to obtain a target inspection strategy, and control the drone to inspect the communication tower based on the target inspection strategy.
[0023] In this embodiment, first, it is necessary to collect the operation state data and environmental state data of the communication tower. The operation state data of the communication tower includes structural stress and strain data, inclination data, tower vibration data, communication equipment operation data, etc.; the environmental state data includes meteorological data, electromagnetic environment data, and geological data, etc. The structural stress and strain data can be collected by installing strain gauges or stress sensors at key stressed components of the tower, such as main members and diagonal members. The inclination data can be collected by an inclination sensor installed at the top of the tower, the tower vibration data can be collected by an acceleration sensor installed on the tower, and the communication equipment operation data is obtained by connecting to a data acquisition device through an interface provided by the communication equipment itself, such as RS232, RS485, Ethernet interface, etc., using corresponding communication protocols, such as Modbus, SNMP, etc.
[0024] Install small weather stations in a certain area. Each weather station is equipped with sensors such as an anemometer, a wind vane, a temperature sensor, a humidity sensor, and a barometer. Each weather station can provide meteorological data for all communication towers in the area. The geological data can be collected by soil moisture sensors buried in the soil around the tower. The electromagnetic environment data can be collected by an electromagnetic radiation monitor installed on the communication tower.
[0025] The feature extraction module 101 can collect the operation status data of the communication tower (such as stress data of key parts of the tower, equipment operation parameters, etc.) and environmental status data, and select representative features from these complex data to form an initial feature data set. The initial feature data set may contain noise data, erroneous data or incomplete data, which affect the subsequent data analysis and therefore need to be preprocessed. This embodiment provides a method for removing these bad data, reasonably filling in missing values, and correcting or eliminating abnormal values through data cleaning, thereby obtaining a relatively accurate, complete and clean target feature data set to ensure the reliability of subsequent analysis and evaluation.
[0026] The status assessment module 102 can use the constructed hierarchical analysis model to analyze the processed target feature data set, obtain the status assessment result of the communication tower, and provide a basis for the adjustment of the inspection strategy. The hierarchical analysis model is constructed based on the historical data of the communication tower. The model decomposes the complex tower status assessment problem into multiple levels, such as the target level, the criterion level, and the indicator level. The target level represents the final result, the criterion level represents the factors affecting the final result, and the indicator level represents the specific influencing factors. The weight of each indicator is determined by quantitatively analyzing the relationship between each level. When the target feature data set is input into the model, the model comprehensively analyzes the indicator data according to the established weights and algorithms, and finally obtains the status assessment result of the communication tower. The evaluation result can intuitively reflect whether the current operating status of the tower is good and whether there are potential risks.
[0027] The strategy adjustment module 103 can update the initial inspection strategy in a targeted manner according to the status evaluation results, generate a target inspection strategy that is more in line with the actual status of the current tower, and control the drone to inspect the communication tower according to the target inspection strategy.
[0028] For example, if the status assessment results show that some parts of the tower or some operating parameters are abnormal or have potential risks, the strategy adjustment module 103 will correspondingly increase the frequency and accuracy requirements of the inspection items related to these areas or parameters, thereby optimizing the initial inspection strategy and generating a target inspection strategy. For example, if the assessment finds that the structural stress of a certain area of the tower is abnormal, the target inspection strategy can require the drone to use a high-definition camera to take more detailed photos and collect data for the area.
[0029] As can be seen from the above, the embodiments of the present disclosure implement precise monitoring and efficient inspection of the operating status of communication towers through three major modules: feature extraction, status evaluation, and policy adjustment. The intelligent inspection device in this embodiment can automatically collect and analyze the operating status and environmental data of the tower, accurately evaluate the tower status, and dynamically adjust the inspection policy according to the evaluation results to ensure the real-time nature of data processing, the pertinence and effectiveness of the inspection work. This not only improves the inspection efficiency, reduces the labor cost, but also enhances the safety and stability of the communication tower, providing a strong guarantee for the smooth operation of the communication network.
[0030] In one embodiment of the present disclosure, referring to Figure 2 , the intelligent inspection device further includes a model construction module 104; The model construction module 104 is used for: Determining the number of hierarchical levels of the analytic hierarchy process model based on the quantity and type of the historical data of the communication tower, and constructing a judgment matrix based on the number of hierarchical levels and the historical data; the historical data includes the historical operating status data and historical environmental status data of the communication tower; Calculating the consistency ratio based on the judgment matrix, and adjusting the judgment matrix based on the comparison result between the consistency ratio and a preset threshold to obtain the analytic hierarchy process model.
[0031] In this embodiment, the intelligent inspection device further includes a model construction module 104. Since the status of the communication tower is affected by various factors, such as structural stress and strain, inclination, vibration, etc. in the operating status data, and meteorology, electromagnetic environment, geology, etc. in the environmental status data. The model construction module 104 can quantitatively analyze these complex factors and their mutual relationships by constructing an analytic hierarchy process model, determine the weights of the influence of each factor on the tower status, so as to more accurately evaluate the tower status. In addition, the operating environments and their own characteristics faced by communication towers in different regions and of different types are different. The model construction module 104 can construct a personalized analytic hierarchy process model suitable for the specific tower according to the historical data and actual situation of the tower, enabling the intelligent inspection device to adapt to various complex and diverse tower inspection requirements and improving the versatility and flexibility of the system.
[0032] In this embodiment, determining the number of hierarchical levels of the analytic hierarchy process model based on the quantity and type of the historical data of the communication tower includes: If the absolute value of the growth rate of the quantity of the historical data of the communication tower is less than a first value within the same time period, then determining the number of levels of the analytic hierarchy process model according to the type of the historical data of the communication tower; If the absolute value of the growth rate of the quantity of the historical data of the communication tower is greater than or equal to the first value within the same time period, then determining an adjustment ratio according to the growth rate of the quantity of the historical data of the communication tower, and determining the number of levels of the analytic hierarchy process model based on the adjustment ratio and the type of the historical data of the communication tower.
[0033] Exemplarily, if the absolute value of the growth rate of the historical data of the communication tower is less than the first value, it indicates that the data volume of the communication tower is in a relatively stable state and the data growth is relatively slow. At this time, the change in the data volume has little impact on the model layering. Therefore, the number of layers of the hierarchical analysis model can be determined according to the type of the historical data of the communication tower. For example, the operating state data (such as structural stress and strain, inclination, vibration, etc.) and the environmental state data (such as meteorology, electromagnetic environment, geology, etc.) can be used as different layers or indicators respectively. According to the complexity and mutual relationship of the data types, the layers can be reasonably divided, and various types of data can be placed in the index layer, and then the criterion layer and the target layer can be constructed based on their influence relationships on the overall state of the tower.
[0034] Construct a judgment matrix based on the number of layers and historical data. The judgment matrix is a key part of the hierarchical analysis model, which reflects the comparison of the relative importance among elements in the same layer. Taking the criterion layer as an example, assuming that there are multiple factors affecting the tower state in the criterion layer, such as structural stability, environmental adaptability, etc., by analyzing the historical data, determine the ratio of the relative importance between these factors in pairs, so as to construct a judgment matrix. For example, if it is found from the historical data that the influence degree of structural stability on the tower state is twice that of environmental adaptability, this relationship is reflected in the corresponding position of the judgment matrix. This judgment matrix constructed based on historical data can quantify the relationship among factors and provide a basis for subsequent calculation of weights and evaluation of consistency.
[0035] When constructing the judgment matrix, due to the possible inconsistency of human subjective judgment, for example, when comparing the relative importance of factor A and B, B and C, A and C, logical contradictions may occur. The consistency ratio calculates a value through a specific algorithm, comprehensively considering factors such as the eigenvalues of the judgment matrix, to reflect the degree of this inconsistency. The smaller this value is, the better the consistency of the judgment matrix.
[0036] Compare the calculated consistency ratio with the preset threshold. If the consistency ratio exceeds the preset threshold, it indicates that the consistency of the judgment matrix is poor and the judgment matrix needs to be adjusted; if it does not exceed, it is considered that the judgment matrix meets the requirements, and the model constructed with this judgment matrix is the hierarchical analysis model.
[0037] It can be concluded from the above that the intelligent inspection device in this embodiment constructs a hierarchical analysis model by using the historical data of the communication tower through the model construction module 104, realizing the quantitative evaluation of the tower state. This module flexibly determines the number of layers according to the change trend of the data quantity and the data type, and ensures the consistency of the model by constructing and adjusting the judgment matrix, improving the accuracy of the tower state evaluation.
[0038] In an embodiment of the present disclosure, calculating the consistency ratio based on the judgment matrix includes: Calculate the consistency index of each layer's judgment matrix, and determine the random consistency index from a preset index mapping table based on the order of the judgment matrix; Calculate the consistency ratio based on the consistency index and its corresponding random consistency index.
[0039] In this embodiment, the consistency index is used to measure the degree of logical consistency among the elements within the judgment matrix. The random consistency index is a standard value related to the order of the judgment matrix and is used as a reference for measuring the consistency of the judgment matrix. For judgment matrices of different orders, the randomly generated degree of inconsistency is different. Through the preset index mapping table, the corresponding random consistency index can be quickly found according to the order of the current judgment matrix. The consistency ratio is the ratio of the consistency index to the random consistency index.
[0040] It can be concluded from the above that this embodiment gives a detailed process for calculating the consistency ratio based on the judgment matrix, providing an important guarantee for the accuracy and reliability of the analytic hierarchy process model.
[0041] In an embodiment of the present disclosure, the preset thresholds include a first preset threshold and a second preset threshold; Adjust the judgment matrix based on the comparison result of the consistency ratio and the preset thresholds to obtain the analytic hierarchy process model, including: If the consistency ratio is less than the first preset threshold, obtain the analytic hierarchy process model based on the judgment matrix; If the consistency ratio is greater than or equal to the first preset threshold and less than the second preset threshold, adjust the assignment of the elements in the judgment matrix; when the consistency ratio is less than the first preset threshold, obtain the analytic hierarchy process model based on the adjusted judgment matrix; If the consistency ratio is greater than or equal to the second preset threshold, adjust the levels of the elements in the judgment matrix and adjust the assignment of the elements in the judgment matrix; when the consistency ratio is less than the first preset threshold, obtain the analytic hierarchy process model based on the adjusted judgment matrix.
[0042] In this embodiment, if the consistency ratio is less than the first preset threshold, it indicates that the inconsistency of the judgment matrix is within an acceptable range, the relative importance judgment of the elements within the matrix is relatively reasonable, and the logical consistency is relatively high. At this time, the analytic hierarchy process model can be directly constructed based on the current judgment matrix.
[0043] If the consistency ratio is greater than or equal to the first preset threshold and less than the second preset threshold, it indicates that there is a certain degree of inconsistency in the judgment matrix, but the problem is not particularly serious. The inconsistency may stem from small deviations in determining the relative importance ratios of elements. Only the assignments of elements in the judgment matrix need to be adjusted. For example, reexamine and correct the relative importance scores when comparing certain elements pairwise. During the adjustment process, continuously calculate the consistency ratio until it is less than the first preset threshold, and then construct an analytic hierarchy process model based on the adjusted judgment matrix.
[0044] If the consistency ratio is greater than or equal to the second preset threshold, it means that the inconsistency of the judgment matrix is very serious, which may be caused by unreasonable element hierarchy division or large deviations in the judgment of element relative importance. At this time, not only the assignments of elements in the judgment matrix need to be adjusted, but also the element hierarchy needs to be adjusted. For example, reevaluate whether some elements should be at the same level, or whether some elements need to be merged, split, etc. Similarly, continuously calculate the consistency ratio during the adjustment process. When the ratio is less than the first preset threshold, obtain the analytic hierarchy process model based on the adjusted judgment matrix.
[0045] It can be concluded from the above that by adopting different adjustment strategies according to the comparison results of the consistency ratio and different preset thresholds, the judgment matrix can be gradually optimized to reach an acceptable consistency level, and then an accurate and reliable analytic hierarchy process model can be constructed.
[0046] In an embodiment of the present disclosure, adjusting the hierarchy of elements in the judgment matrix includes: Determine the abnormal elements in the judgment matrix, and determine the target hierarchy of the abnormal elements according to data characteristics and expert experience; If the current hierarchy of the abnormal element is less than the target hierarchy, then adjust the abnormal element to the judgment matrix of the target hierarchy, and determine the adjusted weight of the abnormal element based on the first formula; If the current hierarchy of the abnormal element is greater than the target hierarchy, then adjust the abnormal element to the judgment matrix of the target hierarchy, and determine the adjusted weight of the abnormal element based on the second formula.
[0047] The first formula is:
[0048] Where e represents the abnormal element, represents the weight of the target hierarchy, represents the weight of the original hierarchy, n represents the total number of elements in the original hierarchy, m represents the total number of elements in the target hierarchy, W represents the total weight of the original hierarchy, V represents the total weight of the target hierarchy, and V = kW, k is an adjustment coefficient, and k is a constant greater than 1; is a regulating factor, 0 < < 1.
[0049] The second formula is:
[0050] where e represents the abnormal element, represents the weight of the target level, represents the weight of the original level, n represents the total number of elements in the original level, m represents the total number of elements in the target level, W represents the total weight of the original level, V represents the total weight of the target level, and W = pV, where p is an adjustment coefficient and p is a constant greater than 1; is a regulation factor, 0 < < 1.
[0051] In this embodiment, assuming that an element is adjusted from a lower level to a higher level, from the first formula, it can be seen that is a regulation factor, 0 < < 1, and its value can be determined according to expert experience or historical data statistics. When an element is promoted from a lower level to a higher level, first, the weight of the element is preliminarily adjusted according to the adjustment ratio of the total weight between levels , then the ratio of the number of elements in the target level to the number of elements in the original level is considered for secondary adjustment, and finally, fine-tuning is performed according to the relative weight of the element in the original level and the regulation factor α to ensure the rationality and scientificity of the weight adjustment.
[0052] Assume that an element is adjusted from a higher level to a lower level, is a regulation factor, 0 < < 1, is a regulation factor, 0 < < 1. When an element is downgraded from a higher level to a lower level, first, the weight of the element is preliminarily adjusted according to the adjustment ratio of the total weight between levels , then the ratio of the number of elements in the target level to the number of elements in the original level is considered for secondary adjustment, and finally, fine-tuning is performed according to the relative weight of the element in the original level and the regulation factor β to make its weight in the target level more conform to the new hierarchical structure.
[0053] From the above, it can be concluded that this embodiment can reasonably adjust the levels of abnormal elements in the judgment matrix and accurately calculate their adjusted weights. This helps to improve the accuracy and rationality of the analytic hierarchy process model, enabling the model to more accurately reflect the relative importance between elements.
[0054] In an embodiment of the present disclosure, the state evaluation result includes a comprehensive evaluation score; Updating the initial inspection strategy based on the status evaluation result to obtain the target inspection strategy, including: If the comprehensive evaluation score is greater than or equal to the first value, keep the first inspection frequency and the first inspection technical means in the initial inspection strategy unchanged; If the comprehensive evaluation score is less than the first value and greater than or equal to the second value, update the first inspection frequency in the initial inspection strategy to the second inspection frequency; the first inspection frequency is less than the second inspection frequency; If the comprehensive evaluation score is less than the second value, update the first inspection frequency in the initial inspection strategy to the second inspection frequency, and update the first inspection technical means to the second inspection technical means; the number of monitoring devices included in the first inspection technical means is less than the number of monitoring devices included in the second inspection technical means.
[0055] In this embodiment, the comprehensive evaluation score is a quantitative reflection of the communication tower status, reflecting the current operating condition and potential risk degree of the tower. According to the different intervals where the score is located, adjusting the inspection strategy pertinently can make the inspection work more in line with the actual situation of the tower, ensuring both the inspection effect and reasonable resource allocation.
[0056] When the comprehensive evaluation score is greater than or equal to the first value, it indicates that the communication tower is in good operating condition and has low potential risks. At this time, there is no need to adjust the initial inspection strategy, and the original first inspection frequency and first inspection technical means are maintained, which can avoid waste of resources caused by excessive inspections.
[0057] When the comprehensive evaluation score is less than the first value and greater than or equal to the second value, it indicates that the status of the communication tower has declined and there are certain potential risks, but it has not reached a serious level. At this time, update the first inspection frequency in the initial inspection strategy to a higher second inspection frequency. Increasing the inspection frequency facilitates the staff to detect subtle changes in the tower status in a timely manner, facilitating the early discovery and handling of potential problems to prevent the problems from deteriorating.
[0058] When the comprehensive evaluation score is less than the first value and greater than or equal to the second value, it indicates that the status of the communication tower is poor and the potential risks are high, and a failure may occur at any time. At this time, not only the inspection frequency should be increased from the first inspection frequency to the second inspection frequency, but also the first inspection technical means should be updated to the second inspection technical means that includes more monitoring devices. More monitoring devices can provide more comprehensive and accurate tower status data, which helps to deeply analyze problems and take effective measures in a timely manner to ensure the safe and stable operation of the tower.
[0059] As can be seen from the above, this method of dynamically adjusting the inspection strategy according to the comprehensive evaluation score in this embodiment realizes the refined management of the inspection work. On the premise of ensuring the effective monitoring of communication towers, it avoids unnecessary resource investment, improves the inspection efficiency and effect, minimizes the risk of tower failures to the greatest extent, and ensures the stable operation of the communication network.
[0060] In one embodiment of the present disclosure, referring to Figure 2 , the intelligent inspection device further includes a data acquisition module 105; The data acquisition module 105 is connected to the feature extraction module 101. The data acquisition module 105 includes multiple sensors for collecting the operation status data and environmental status data of the communication tower.
[0061] In this embodiment, the data acquisition module 105 includes multiple sensors. Different types of sensors have different functions and can obtain relevant data of the communication tower from multiple dimensions. For example, in terms of operation status data, stress sensors can be installed on the key stress-bearing components of the tower to collect structural stress and strain data; tilt sensors are installed on the top of the tower to obtain tilt data; acceleration sensors are installed on the tower to collect vibration data of the tower; data acquisition devices connected through the interfaces of the communication equipment itself can collect the operation data of the communication equipment. In terms of environmental status data, anemometers, wind vanes, temperature sensors, humidity sensors, barometers, etc. equipped in the weather station can collect meteorological data; electromagnetic radiation monitors installed on the communication tower can collect electromagnetic environment data; soil moisture sensors buried in the soil around the tower can collect geological data.
[0062] As can be seen from the above, the main function of the data acquisition module 105 is to collect the operation status data and environmental status data of the communication tower. The operation status data can reflect the structure and equipment operation conditions of the tower itself, while the environmental status data reflects the external environmental conditions where the tower is located. These data are crucial for comprehensively understanding the working status of the communication tower, evaluating its safety and stability. By collecting data at intervals, the intelligent inspection device can grasp the dynamic changes of the tower in real time, providing a reliable basis for subsequent analysis and decision-making to achieve effective inspection and maintenance of the communication tower.
[0063] In one embodiment of the present disclosure, referring to Figure 2 , the intelligent inspection device further includes a communication module 106; The communication module 106 is used to connect to the remote monitoring center and send the status evaluation results, inspection data, and the real-time position information of the UAV to the remote monitoring center; The communication module 106 is also used to receive instructions from the remote monitoring center and control the working status of each sensor based on the instructions.
[0064] In this embodiment, the communication module 106 can send the communication tower status evaluation results obtained by the status evaluation module 102 to the remote monitoring center. These results include key information such as whether the current operating status of the tower is good and whether there are potential risks, enabling the management personnel in the monitoring center to quickly understand the overall condition of the tower and make decisions quickly, such as whether to arrange maintenance personnel to go to the site for inspection, whether to adjust the inspection strategy of the unmanned aerial vehicle, and whether to adjust the data acquisition frequency of the sensor.
[0065] It can be concluded from the above that the communication module 106 plays a crucial role in the intelligent inspection device. By realizing data interaction and remote control with the remote monitoring center, it greatly improves the management efficiency and intelligent level of the intelligent inspection device, providing a strong guarantee for the stable operation of the communication tower.
[0066] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the present disclosure.
Claims
1. A communication tower with an intelligent inspection device, characterized in that: The intelligent inspection device comprises: A feature extraction module is used to extract features from the operation status data and environmental status data of the communication tower to obtain an initial feature data set, and to clean the initial feature data set to obtain a target feature data set; A state assessment module, used for inputting the target feature data set into a hierarchical analysis model to perform state assessment to obtain a state assessment result of the communication tower, wherein the hierarchical analysis model is an algorithm model constructed based on historical data of the communication tower; The strategy adjustment module is used to update the initial inspection strategy based on the status evaluation result to obtain a target inspection strategy, and control the drone to inspect the communication tower based on the target inspection strategy.
2. A communication tower with an intelligent inspection device as claimed in claim 1, characterized in that: The intelligent inspection device also includes a model building module; The model building module is used to: Determine the number of hierarchical layers of the hierarchical analysis model based on the number and type of historical data of the communication tower, and construct a judgment matrix based on the number of hierarchical layers and the historical data; the historical data includes historical operation status data and historical environmental status data of the communication tower; The consistency ratio is calculated based on the judgment matrix, and the judgment matrix is adjusted based on the comparison result between the consistency ratio and a preset threshold value to obtain a hierarchical analysis model.
3. A communication tower with an intelligent inspection device as claimed in claim 2, characterized in that: The calculating the consistency ratio based on the judgment matrix includes: Calculating the consistency index of each layer of the judgment matrix, and determining a random consistency index from a preset index mapping table based on the order of the judgment matrix; A consistency ratio is calculated based on the consistency indicator and its corresponding random consistency indicator.
4. A communication tower with an intelligent inspection device as claimed in claim 2, characterized in that: The preset threshold includes a first preset threshold and a second preset threshold; The step of adjusting the judgment matrix based on the comparison result between the consistency ratio and the preset threshold value to obtain a hierarchical analysis model includes: If the consistency ratio is less than a first preset threshold, obtaining a hierarchical analysis model based on the judgment matrix; If the consistency ratio is greater than or equal to the first preset threshold and less than the second preset threshold, the value of the element in the judgment matrix is adjusted; when the consistency ratio is less than the first preset threshold, a hierarchical analysis model is obtained based on the adjusted judgment matrix; If the consistency ratio is greater than or equal to the second preset threshold, the hierarchy of the elements in the judgment matrix and the value assignment of the elements in the judgment matrix are adjusted; when the consistency ratio is less than the first preset threshold, a hierarchical analysis model is obtained based on the adjusted judgment matrix.
5. A communication tower with an intelligent inspection device as claimed in claim 4, characterized in that: The adjusting the level of the elements in the judgment matrix includes: Determine the abnormal elements in the judgment matrix and determine the target level of the abnormal elements based on data characteristics and expert experience; If the current level of the abnormal element is less than the target level, the abnormal element is adjusted to the judgment matrix of the target level, and the adjusted weight of the abnormal element is determined based on the first formula; If the current level of the abnormal element is greater than the target level, the abnormal element is adjusted to the judgment matrix of the target level, and the adjusted weight of the abnormal element is determined based on the second formula.
6. A communication tower with an intelligent inspection device as claimed in claim 5, characterized in that: The first formula is: Among them, e represents an abnormal element, represents the weight of the target level, represents the weight of the original level, n represents the total number of elements in the original level, m represents the total number of elements in the target level, W represents the total weight of the original level, V represents the total weight of the target level, and V=kW, k is the adjustment coefficient, and k is a constant greater than 1; is the adjustment factor, 0< <1.
7. A communication tower with an intelligent inspection device as claimed in claim 5, characterized in that: The second formula is: Among them, e represents an abnormal element, represents the weight of the target level, represents the weight of the original level, n represents the total number of elements in the original level, m represents the total number of elements in the target level, W represents the total weight of the original level, V represents the total weight of the target level, and W=pV, p is the adjustment coefficient, and p is a constant greater than 1; is the adjustment factor, 0< <1.
8. A communication tower with an intelligent inspection device as claimed in claim 1, characterized in that: The status assessment results include a comprehensive assessment score; The initial inspection strategy is updated based on the status evaluation result to obtain a target inspection strategy, including: If the comprehensive evaluation score is greater than or equal to the first value, the first inspection frequency and the first inspection technical means in the initial inspection strategy are kept unchanged; If the comprehensive evaluation score is less than the first value and greater than or equal to the second value, the first inspection frequency in the initial inspection strategy is updated to the second inspection frequency; the first inspection frequency is less than the second inspection frequency; If the comprehensive evaluation score is less than the second value, the first inspection frequency in the initial inspection strategy is updated to the second inspection frequency, and the first inspection technical means is updated to the second inspection technical means; the number of monitoring devices included in the first inspection technical means is less than the number of monitoring devices included in the second inspection technical means.
9. A communication tower with an intelligent inspection device as claimed in claim 1, characterized in that: The intelligent inspection device also includes a data acquisition module; The data acquisition module is connected to the feature extraction module, and the data acquisition module includes a plurality of sensors for collecting operation status data and environmental status data of the communication tower.
10. A communication tower with an intelligent inspection device as claimed in claim 9, characterized in that: The intelligent inspection device also includes a communication module; The communication module is used to connect to the remote monitoring center and send the status assessment results, inspection data and real-time location information of the drone to the remote monitoring center; The communication module is also used to receive instructions from the remote monitoring center and control the working status of each sensor based on the instructions.