Communication tower monitoring method based on 5G network

Abstract

The invention discloses a communication iron tower monitoring method based on a 5G network, and the method comprises the steps: collecting the vibration, inclination angle, wind speed, temperature and humidity and other multi-mode data through installing an acceleration sensor, an inclination sensor and an environment sensor at the key positions (tower legs, a tower body and a tower top) of a communication iron tower. A modal parameter analysis technology is fused, and natural frequency and modal shape change are combined, so that fine deformation and abnormity of the iron tower can be accurately judged. In addition, an environment sensor is introduced to collect wind speed and temperature and humidity data, and environment correction is carried out on vibration signals and inclination angle data. The influence of external environment interference on the monitoring precision is effectively reduced, and high-reliability data can still be obtained under complex environment conditions.

Description

Technical Field

[0001] The present invention belongs to the field of communication tower monitoring, and specifically, relates to a communication tower monitoring method based on a 5G network. Background Art

[0002] Communication towers are important infrastructure in modern communication systems, and their safety and stability are directly related to the reliability of communication networks. However, since communication towers are often located in outdoor environments and are affected by natural factors such as strong winds, earthquakes, rain and snow, problems such as tilt, excessive vibration or structural damage may occur. Traditional communication tower monitoring technology has the following shortcomings. Traditional methods usually directly analyze vibration and tilt data, ignoring the interference of environmental factors such as wind speed, temperature and humidity, resulting in large data errors. In addition, most existing technologies lack modal analysis methods and cannot detect small deformations and potential structural problems of towers. In addition, existing methods mostly rely on static data monitoring and lack trend prediction capabilities based on time series, and cannot accurately evaluate the long-term health of communication towers or warn of potential safety hazards in the future.

[0003] In view of this, the present invention is proposed. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a communication tower monitoring method based on a 5G network, which solves the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is: A communication tower monitoring method based on a 5G network comprises the following steps: S1: Install a multimodal sensor network at key locations on the communication tower, and then upload the sensor data to the monitoring terminal via 5G communication; S2: De-noise and eliminate trend items on the collected sensor data at the monitoring terminal, and correct the signal deviation based on wind speed, temperature and humidity; S3: Calculate modal parameters through acceleration signals, extract natural frequencies using correlation function matrix and power spectrum density matrix, and correct natural frequencies in combination with tilt sensor data; S4: The modal parameters, tilt angle and environmental data are integrated to calculate the comprehensive deformation score. When the comprehensive deformation score exceeds the preset threshold, an early warning is triggered and the future health score is predicted through the trend model. S5: Data is uploaded to the monitoring center in real time via the 5G network. The user interface displays real-time changes in vibration, tilt angle, and environmental data, and provides early warnings.

[0006] Optionally, when installing the sensors in step S1, first, install an acceleration sensor and a tilt sensor at the connection point of each tower leg base 10 cm from the ground to monitor the vibration characteristics and tilt angle changes at the bottom of the iron tower; symmetrically install four acceleration sensors at 50% of the height from the ground in the middle of the tower body to monitor the vibration frequency of the middle section structure, and install a tilt sensor in the center of the middle section of the tower body to capture the overall tilt state; install an acceleration sensor in the center of the tower top to collect the top vibration signal, and install a tilt sensor at the end of each support arm at the top of the tower to monitor the top deformation. In addition, install a wind speed sensor and a temperature and humidity sensor in the middle of the tower body near the monitoring terminal to collect environmental parameters.

[0007] Optionally, the steps of performing denoising and trend elimination processing on the collected sensor data at the monitoring terminal and correcting the signal deviation based on wind speed, temperature and humidity are as follows: Vibration signal is filtered by filtering algorithm Filter high-frequency noise, retain effective signal features and use polynomial fitting method to calculate the trend term of vibration signal , and deducted from the original signal, the calculation formula is: ,in, Indicates a trend item.

[0008] According to wind speed , temperature and humidity The real-time data is used to correct the signal deviation. The correction formula is: ,in, , are the influence coefficients of wind speed and temperature, respectively. is the corrected vibration signal.

[0009] Optionally, the steps of calculating the modal parameters through the acceleration signal, extracting the natural frequency using the correlation function matrix and the power spectrum density matrix, and correcting the natural frequency in combination with the tilt sensor data are as follows: According to the collected acceleration signal and , calculate the correlation function matrix between each sensor: .in, is the time lag, is the total number of sampling points. The correlation function matrix is ​​used to describe the signal correlation between different sensor positions.

[0010] Correlation function matrix Perform Fourier transform to obtain the power spectrum density matrix, which is expressed as: ,in, represents the Fourier transform operation, and the power spectral density matrix is ​​used to identify the frequency characteristics of the vibration signal; The power spectral density matrix Perform singular value decomposition, the expression is: ,in, is the singular value matrix of natural frequencies, is the mode shape matrix, extract The natural frequency corresponding to the maximum value ; Combined with the tilt sensor data, the natural frequency is corrected , by calculating the change in the tilt angle (in is the initial tilt angle), the correction formula is: ,in, is the sensitivity coefficient of the influence of the tilt angle change on the natural frequency, is the corrected natural frequency.

[0011] Optionally, the steps of fusing the modal parameters, tilt angle and environmental data to calculate the comprehensive deformation score are: According to the corrected natural frequency With the reference natural frequency The relative change of modal parameter scores is calculated , whose expression is: ,in, To combine the natural frequency corrected by the tilt angle, is the base natural frequency when not deformed; Real-time tilt angle detected by the tilt sensor With initial tilt angle The absolute difference of , whose expression is: ; According to the wind speed collected by the environmental sensor , temperature and humidity , calculate the comprehensive impact score of the environment on deformation ,in, ,in, , , is the weight coefficient of wind speed, temperature and humidity; The modal parameter score, tilt angle score and environmental score are weighted and integrated to obtain the comprehensive deformation score. : ,in, , , They are the weights of modal parameters, tilt angle and environmental data, which comprehensively reflect the overall health status of the tower.

[0012] Optionally, when the comprehensive deformation score exceeds a preset threshold, the steps of triggering an early warning and predicting the future health score through a trend model are: When the comprehensive deformation score Exceeding the preset threshold When an abnormality occurs, an early warning is triggered and a health status report is generated, indicating the abnormal location and possible deformation cause, and pushed to the maintenance team; Based on long-term monitoring data, a time series trend model is constructed to predict future health scores , whose expression is: ,in, Score your current health. Score the current comprehensive deformation. is the comprehensive score of the current environmental data. , , is the weight parameter of the model.

[0013] Based on predicted future health scores and historical data trends to determine the long-term health of the tower. It indicates that there may be irreversible damage to the structure and it is recommended to implement comprehensive maintenance or replacement.

[0014] Optionally, the data is uploaded to the monitoring center in real time via the 5G network. The user interface displays the real-time changes of vibration, tilt angle and environmental data, and provides early warning steps as follows: The monitoring terminal encapsulates the modal parameters, tilt angle changes and environmental data processing results into standardized data packets. Then, the monitoring center decodes and classifies the received data packets, stores the vibration, tilt angle and environmental data in the cloud database, and archives them according to time sequence and sensor location. On the user interface developed by the monitoring center, the real-time changes of key parameters are displayed in visual graphics. When the comprehensive deformation score exceeds the preset threshold, an early warning message is generated on the user interface and pushed to the maintenance team via SMS, email or dedicated application.

[0015] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all the advantages described below at the same time: 1. The present invention installs acceleration sensors, tilt sensors and environmental sensors at key locations of the communication tower (tower legs, tower body and tower top) to collect multi-modal data such as vibration, tilt angle, wind speed, temperature and humidity. By integrating modal parameter analysis technology, combined with natural frequency and modal shape changes, the subtle deformation and abnormality of the tower can be accurately determined.

[0016] 2. The present invention introduces environmental sensors to collect wind speed, temperature and humidity data, and performs environmental correction on vibration signals and tilt angle data, effectively reducing the impact of external environmental interference on monitoring accuracy and ensuring that highly reliable data can still be obtained under complex environmental conditions.

[0017] 3. The invention proposes a comprehensive deformation scoring method based on the fusion of modal parameters, tilt angle and environmental data, and accurately quantifies the health status of the tower through a weight model. When the score exceeds the threshold, an early warning is triggered and a detailed health report is provided. At the same time, combined with time series analysis technology, the future trend of the tower health score is predicted to detect potential risks in advance.

[0018] The specific implementation modes of the present invention are further described in detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 It is a flow chart of the communication tower monitoring method; It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but are intended to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0020] The present invention will now be described in further detail with reference to the accompanying drawings.

[0021] See also Figure 1 As shown, in this embodiment, a communication tower monitoring method based on a 5G network is provided, comprising the following steps: S1: Install a multimodal sensor network at key locations on the communication tower, and then upload the sensor data to the monitoring terminal via 5G communication; S2: De-noise and eliminate trend items on the collected sensor data at the monitoring terminal, and correct the signal deviation based on wind speed, temperature and humidity; S3: Calculate modal parameters through acceleration signals, extract natural frequencies using correlation function matrix and power spectrum density matrix, and correct natural frequencies in combination with tilt sensor data; S4: The modal parameters, tilt angle and environmental data are integrated to calculate the comprehensive deformation score. When the comprehensive deformation score exceeds the preset threshold, an early warning is triggered and the future health score is predicted through the trend model. S5: Data is uploaded to the monitoring center in real time via the 5G network. The user interface displays real-time changes in vibration, tilt angle, and environmental data, and provides early warnings.

[0022] In this embodiment, when installing the sensors in step S1, first, an acceleration sensor and a tilt sensor are installed at the connection point of each tower leg base 10 cm from the ground to monitor the vibration characteristics and tilt angle changes at the bottom of the iron tower; four acceleration sensors are symmetrically installed at 50% of the height of the tower body from the ground to monitor the vibration frequency of the middle section structure, and a tilt sensor is installed at the center of the middle section of the tower body to capture the overall tilt state; an acceleration sensor is installed at the center of the tower top to collect the top vibration signal, and a tilt sensor is installed at the end of each support arm of the tower top to monitor the top deformation. In addition, a wind speed sensor and a temperature and humidity sensor are installed at the middle of the tower body near the monitoring terminal to collect environmental parameters.

[0023] In this embodiment, the steps of performing denoising and trend item elimination processing on the collected sensor data at the monitoring terminal, and correcting the signal deviation based on wind speed, temperature and humidity are as follows: Vibration signal is filtered by filtering algorithm Filter high-frequency noise, retain effective signal features and use polynomial fitting method to calculate the trend term of vibration signal , and deducted from the original signal, the calculation formula is: ,in, represents the trend term, and t is the time variable, which is used to align the vibration signal and its trend term in time and is measured in seconds.

[0024] According to wind speed , temperature and humidity The real-time data is used to correct the signal deviation. The correction formula is: ,in, , are the influence coefficients of wind speed and temperature, respectively. is the corrected vibration signal.

[0025] In this embodiment, the steps of calculating modal parameters through acceleration signals, extracting natural frequencies using correlation function matrix and power spectrum density matrix, and correcting natural frequencies in combination with tilt sensor data are as follows: According to the collected acceleration signal and , calculate the correlation function matrix between each sensor: .in, is the time lag, is the total number of sampling points. The correlation function matrix is ​​used to describe the signal correlation between different sensor positions.

[0026] Correlation function matrix Perform Fourier transform to obtain the power spectrum density matrix, which is expressed as: ,in, represents the Fourier transform operation, and the power spectral density matrix is ​​used to identify the frequency characteristics of the vibration signal; The power spectral density matrix Perform singular value decomposition, the expression is: ,in, is the singular value matrix of natural frequencies, is the mode shape matrix, extract The natural frequency corresponding to the maximum value ; Combined with the tilt sensor data, the natural frequency is corrected , by calculating the change in the tilt angle (in is the initial tilt angle), the correction formula is: ,in, is the sensitivity coefficient of the influence of the tilt angle change on the natural frequency, is the corrected natural frequency.

[0027] In this embodiment, the steps of fusing the modal parameters, the tilt angle and the environmental data to calculate the comprehensive deformation score are as follows: According to the corrected natural frequency With the reference natural frequency The relative change of modal parameter scores is calculated , whose expression is: ,in, To combine the natural frequency corrected by the tilt angle, is the base natural frequency when not deformed; Real-time tilt angle detected by the tilt sensor With initial tilt angle The absolute difference of , whose expression is: ;in, is the real-time tilt angle; According to the wind speed collected by the environmental sensor , temperature and humidity , calculate the comprehensive impact score of the environment on deformation ,in, ,in, , , is the weight coefficient of wind speed, temperature and humidity; The modal parameter score, tilt angle score and environmental score are weighted and integrated to obtain the comprehensive deformation score. : ,in, , , They are the weights of modal parameters, tilt angle and environmental data, which comprehensively reflect the overall health status of the tower.

[0028] In this embodiment, when the comprehensive deformation score exceeds the preset threshold, the steps of triggering an early warning and predicting the future health score through a trend model are: When the comprehensive deformation score Exceeding the preset threshold When an abnormality occurs, an early warning is triggered and a health status report is generated, indicating the abnormal location and possible deformation cause, and pushed to the maintenance team; Based on long-term monitoring data, a time series trend model is constructed to predict future health scores , whose expression is: ,in, Score your current health. Score the current comprehensive deformation. is the comprehensive score of the current environmental data. , , is the weight parameter of the model.

[0029] Based on predicted future health scores and historical data trends to determine the long-term health of the tower. It indicates that there may be irreversible damage to the structure and it is recommended to implement comprehensive maintenance or replacement.

[0030] In this embodiment, the data is uploaded to the monitoring center in real time through the 5G network, and the user interface displays the real-time changes of vibration, tilt angle and environmental data, and provides early warning steps as follows: The monitoring terminal encapsulates the modal parameters, tilt angle changes and environmental data processing results into standardized data packets. Then, the monitoring center decodes and classifies the received data packets, stores the vibration, tilt angle and environmental data in the cloud database, and archives them according to time sequence and sensor location. On the user interface developed by the monitoring center, the real-time changes of key parameters are displayed in visual graphics. When the comprehensive deformation score exceeds the preset threshold, an early warning message is generated on the user interface and pushed to the maintenance team via SMS and email.

[0031] In order to compare the beneficial effects of the present invention, we select the following two prior art solutions for comparison: Existing technology solution 1: Single-mode vibration monitoring solution Only the acceleration sensor is used to monitor the vibration signal of the tower without combining the tilt angle data and environmental parameter correction.

[0032] The natural frequency is directly calculated from the collected acceleration signal without correction for tilt angle and environmental influence.

[0033] The overall health score is based only on the natural frequency rate of change , without considering the tilt angle and environmental factors.

[0034] Prior art solution 2: monitoring solution based on tilt angle The tilt angle changes at key positions of the tower are monitored only by tilt sensors.

[0035] Without monitoring the modal parameters, it is not possible to detect vibration characteristics or natural frequency changes.

[0036] The change in tilt angle exceeding the threshold triggers an early warning, but the vibration characteristics and environmental impact are not comprehensively considered.

[0037] 2. The present invention The present invention combines multi-modal sensor data, including acceleration sensors, tilt sensors and environmental sensors; calculates a comprehensive deformation score through modal parameter extraction, tilt angle correction and environmental correction, and comprehensively quantifies the health status of the tower.

[0038] 3. Comparative Experimental Design Experimental objective: To verify the advantages of this invention in comprehensive health monitoring and early deformation detection.

[0039] Experimental conditions: Experimental scenario: A communication tower operates under different wind speed, temperature and humidity conditions, with sensors deployed on the tower legs, tower body and tower top.

[0040] Data collection: All three schemes collected vibration signals, tilt angles and environmental data within 30 days.

[0041] Evaluation indicators: Anomaly detection sensitivity: The trigger rate of deformation detection (the correct detection rate when the deformation does not reach the danger threshold).

[0042] Warning accuracy: the proportion of actual deformation that occurs after the warning is triggered (reducing the false alarm rate).

[0043] Environmental adaptability: the extent to which the signal is interfered with by environmental factors (wind speed, temperature and humidity).

[0044] Completeness of data fusion: whether multi-dimensional changes can be reflected through comprehensive scoring.

[0045] 4. Experimental results analysis 1. Anomaly detection sensitivity Experimental data: comprehensive score and trigger rate of the simulated tower under different degrees of deformation.

[0046] Table 1: Anomaly detection sensitivity test results

[0047]

[0048] Result analysis: The present invention combines modal parameters and tilt angle correction to significantly improve the detection sensitivity under small deformation, with a trigger rate of 100%; while the existing schemes 1 and 2 have low trigger rates under small deformation conditions.

[0049] The single-mode vibration scheme is limited by the fact that it does not incorporate the tilt angle, and low-amplitude deformations are difficult to be identified.

[0050] 2. Early warning accuracy Experimental data: The proportion of actual deformation that occurs after the warning is triggered for different schemes (reducing the false alarm rate).

[0051] Table 2: Early warning accuracy results

[0052]

[0053] Result analysis: The present invention has the lowest false alarm rate (4%), high accuracy, and eliminates the interference of noise by combining multimodal data.

[0054] The single-mode vibration solution has a high false alarm rate because it does not consider the tilt angle and environmental impact.

[0055] 3. Environmental adaptability Table 2: Environmental adaptability results Experimental data: Signal deviation amplitude of different schemes under conditions of wind speed and temperature changes.

[0056] Result analysis: The present invention significantly reduces the influence of environmental interference through environmental correction, and the deviation amplitude is minimal.

[0057] The single-mode vibration scheme does not correct for environmental parameters and the signal deviation is large.

[0058] The present invention is not limited to the above-mentioned embodiments. Anyone should be aware that any structural changes made under the enlightenment of the present invention, and any technical solutions that are the same or similar to the present invention, fall within the protection scope of the present invention. The technology, shape, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A communication tower monitoring method based on 5G network, characterized in that: The following steps are involved: S1: Install a multimodal sensor network at key locations on the communication tower, and then upload the sensor data to the monitoring terminal via 5G communication; S2: De-noise and eliminate trend items on the collected sensor data at the monitoring terminal, and correct the signal deviation based on wind speed, temperature and humidity; S3: Calculate modal parameters through acceleration signals, extract natural frequencies using correlation function matrix and power spectrum density matrix, and correct natural frequencies in combination with tilt sensor data; S4: The modal parameters, tilt angle and environmental data are integrated to calculate the comprehensive deformation score. When the comprehensive deformation score exceeds the preset threshold, an early warning is triggered and the future health score is predicted through the trend model. S5: Data is uploaded to the monitoring center in real time via the 5G network. The user interface displays real-time changes in vibration, tilt angle, and environmental data, and provides early warnings.

2. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: When installing the sensors in step S1, first, an acceleration sensor and a tilt sensor are installed at the connection point of each tower leg base 10 cm from the ground to monitor the vibration characteristics and tilt angle changes of the bottom of the iron tower; four acceleration sensors are symmetrically installed at 50% of the height from the ground in the middle of the tower body to monitor the vibration frequency of the middle section structure, and a tilt sensor is installed in the center of the middle section of the tower body to capture the overall tilt state; an acceleration sensor is installed in the center of the tower top to collect the top vibration signal, and a tilt sensor is installed at the end of each support arm of the tower top to monitor the top deformation. In addition, a wind speed sensor and a temperature and humidity sensor are installed in the middle of the tower body near the monitoring terminal to collect environmental parameters.

3. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: The steps of denoising and trend elimination of the collected sensor data at the monitoring terminal and correcting the signal deviation based on wind speed, temperature and humidity are as follows: Vibration signal is filtered by filtering algorithm Filter high-frequency noise, retain effective signal features and use polynomial fitting method to calculate the trend term of vibration signal , and deducted from the original signal, the calculation formula is: ,in, represents the trend term, t is the time variable, which is used to align the vibration signal and its trend term in time, and is measured in seconds; According to wind speed , temperature and humidity The real-time data is used to correct the signal deviation. The correction formula is: ,in, , are the influence coefficients of wind speed and temperature, respectively. is the corrected vibration signal.

4. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: The steps of calculating the modal parameters through the acceleration signal, extracting the natural frequency using the correlation function matrix and the power spectrum density matrix, and correcting the natural frequency in combination with the tilt sensor data are as follows: According to the collected acceleration signal and , calculate the correlation function matrix between each sensor: .in, is the time lag, is the total number of sampling points, and the correlation function matrix is ​​used to describe the signal correlation between different sensor locations; Correlation function matrix Perform Fourier transform to obtain the power spectrum density matrix, which is expressed as: ,in, represents the Fourier transform operation, and the power spectral density matrix is ​​used to identify the frequency characteristics of the vibration signal; The power spectral density matrix Perform singular value decomposition, the expression is: ,in, is the singular value matrix of natural frequencies, is the mode shape matrix, extract The natural frequency corresponding to the maximum value ; Combined with the tilt sensor data, the natural frequency is corrected , by calculating the change in the tilt angle ,in is the initial tilt angle, and the correction formula is: ,in, is the sensitivity coefficient of the influence of the tilt angle change on the natural frequency, is the corrected natural frequency.

5. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: The steps to fuse the modal parameters, tilt angle and environmental data to calculate the comprehensive deformation score are as follows: According to the corrected natural frequency With the reference natural frequency The relative change of the modal parameter score is calculated , whose expression is: ,in, To combine the natural frequency corrected by the tilt angle, is the base natural frequency when not deformed; Real-time tilt angle detected by the tilt sensor With initial tilt angle The absolute difference of , whose expression is: ;in, is the real-time tilt angle; According to the wind speed collected by the environmental sensor , temperature and humidity , calculate the comprehensive impact score of the environment on deformation ,in, ,in, , , is the weight coefficient of wind speed, temperature and humidity; The modal parameter score, tilt angle score and environmental score are weighted and integrated to obtain the comprehensive deformation score. : ,in, , , They are the weights of modal parameters, tilt angle and environmental data, which comprehensively reflect the overall health status of the tower.

6. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: When the comprehensive deformation score exceeds the preset threshold, the steps to trigger the warning and predict the future health score through the trend model are as follows: When the comprehensive deformation score Exceeding the preset threshold When an abnormality occurs, an early warning is triggered and a health status report is generated, indicating the abnormal location and possible deformation cause, and pushed to the maintenance team; Based on long-term monitoring data, a time series trend model is constructed to predict future health scores , whose expression is: ,in, Score your current health. Score the current comprehensive deformation. is the comprehensive score of the current environmental data. , , is the weight parameter of the model; Based on predicted future health scores and historical data trends to determine the long-term health of the tower. It indicates that there may be irreversible damage to the structure and it is recommended to implement comprehensive maintenance or replacement.

7. A communication tower monitoring method based on 5G network according to claim 1, characterized in that: The data is uploaded to the monitoring center in real time through the 5G network. The user interface displays the real-time changes of vibration, tilt angle and environmental data, and provides early warning steps as follows: The monitoring terminal encapsulates the modal parameters, tilt angle changes and environmental data processing results into standardized data packets. Then, the monitoring center decodes and classifies the received data packets, stores the vibration, tilt angle and environmental data in the cloud database, and archives them according to time sequence and sensor location. On the user interface developed by the monitoring center, the real-time changes of key parameters are displayed in visual graphics. When the comprehensive deformation score exceeds the preset threshold, an early warning message is generated on the user interface and pushed to the maintenance team via SMS and email.

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